Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial...Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures.Nonetheless,they also form a major source of prediction error in structure-activity relationship(SAR)models.To date,several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs.In this paper,we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet,tailored for ACs.Through extensive comparison with multiple baseline models on 30 benchmark datasets,the results showed that ACtriplet was significantly better than those deep learning(DL)models without pretraining.In addition,we explored the effect of pre-training on data representation.Finally,the case study demonstrated that our model's interpretability module could explain the prediction results reasonably.In the dilemma that the amount of data could not be increased rapidly,this innovative framework would better make use of the existing data,which would propel the potential of DL in the early stage of drug discovery and optimization.展开更多
Localized surface plasmon resonance(LSPR)effects in gold nanoparticles(AuNPs)significantly influence the excited states of nearby molecules,offering unique opportunities for enhancing molecular triplet states.Herein,w...Localized surface plasmon resonance(LSPR)effects in gold nanoparticles(AuNPs)significantly influence the excited states of nearby molecules,offering unique opportunities for enhancing molecular triplet states.Herein,we report the synthesis of DNA-templated gold nanostars(AuNF_A15)and gold nanospheres(AuNS_T15)via a seed-mediated growth method and their ability to enhance the triplet state of coralyne,a small molecule with promising applications in photodynamic therapy(PDT).DNA single strands(A15 or T15)were employed as templates to regulate the morphology of AuNPs,resulting in nanostars and nanospheres.The nanostars exhibited a superior LSPR effect due to their“lightning rod effect",significantly enhancing coralyne’s triplet signal by 15-fold compared to a 10-fold enhancement observed with nanospheres.This enhancement was confirmed via steady-state and nanosecond transient absorption spectroscopy.These findings demonstrate that DNA-assembled gold nanostars hold exceptional potential for enhancing molecular triplet states,particularly for PDT applications involving DNA-targeting small molecules.展开更多
The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibratio...The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibration signals induced by external events and to effectively provide early warnings of potential intrusion activities.Due to the complexity and diversity of external intrusion events,traditional deep learning methods can achieve event recognition with an average accuracy exceeding 90%.However,these methods rely on large-scale datasets,leading to significant time and labor costs during the data collection process.Additionally,traditional methods perform poorly when faced with the scarcity of low-frequency event samples,making it challenging to address these rare occurrences.To address this issue,this paper proposes a small-sample learning model based on triplet learning for intrusion event recognition.The model employs a 6-way 20-shot support set configuration and utilizes the KNN clustering algorithm to assess the model's performance.Experimental results indicate that the model achieves an average accuracy of 91.6%,further validating the superior performance of the triplet learning model in classifying external intrusion events.Compared to traditional methods,this approach not only effectively reduces the dependence on large-scale datasets but also better addresses the classification of low-frequency event samples,demonstrating significant application potential.展开更多
Image-based similar trademark retrieval is a time-consuming and labor-intensive task in the trademark examination process.This paper aims to support trademark examiners by training Deep Convolutional Neural Network(DC...Image-based similar trademark retrieval is a time-consuming and labor-intensive task in the trademark examination process.This paper aims to support trademark examiners by training Deep Convolutional Neural Network(DCNN)models for effective Trademark Image Retrieval(TIR).To achieve this goal,we first develop a novel labeling method that automatically generates hundreds of thousands of labeled similar and dissimilar trademark image pairs using accompanying data fields such as citation lists,Vienna classification(VC)codes,and trademark ownership information.This approach eliminates the need for manual labeling and provides a large-scale dataset suitable for training deep learning models.We then train DCNN models based on Siamese and Triplet architectures,evaluating various feature extractors to determine the most effective configuration.Furthermore,we present an Adapted Contrastive Loss Function(ACLF)for the trademark retrieval task,specifically engineered to mitigate the influence of noisy labels found in automatically created datasets.Experimental results indicate that our proposed model(Efficient-Net_v21_Siamese)performs best at both True Negative Rate(TNR)threshold levels,TNR 0.9 and TNR 0.95,with==respective True Positive Rates(TPRs)of 77.7%and 70.8%and accuracies of 83.9%and 80.4%.Additionally,when testing on the public trademark dataset METU_v2,our model achieves a normalized average rank(NAR)of 0.0169,outperforming the current state-of-the-art(SOTA)model.Based on these findings,we estimate that considering only approximately 10%of the returned trademarks would be sufficient,significantly reducing the review time.Therefore,the paper highlights the potential of utilizing national trademark data to enhance the accuracy and efficiency of trademark retrieval systems,ultimately supporting trademark examiners in their evaluation tasks.展开更多
Heterostructures of organic semi-conductors and transition metal dichalcogenides(TMDs)are viable candidates for superior optoelec-tronic devices.Photoinduced inter-facial charge transfer is crucial for the performance...Heterostructures of organic semi-conductors and transition metal dichalcogenides(TMDs)are viable candidates for superior optoelec-tronic devices.Photoinduced inter-facial charge transfer is crucial for the performance efficiency of such devices,yet the underlying mecha-nism,especially the roles of optical-ly dark triplets and spatially sepa-rated charge transfer states,is poorly understood.In the present work,we obtain the struc-tures of distinct excited states and investigate how they are involved in the charge transfer process at the Pd-octaethylporphyrin(PdOEP)and WS_(2) interface in terms of their energies and couplings.The results show that electron transfer from the triplet PdOEP formed via intersystem crossing prevails over direct electron transfer from the singlet(two orders of magnitude faster).Further analysis reveals that the relatively higher rate of triplet electron transfer compared to singlet electron transfer is mainly attributed to a smaller reorganization energy,which is dominated by the out-of-plane vibrations of the organic component.The work emphasizes the important roles of the optically dark triplets in the electron transfer of the PdOEP@WS_(2) heterostructure,and provides valuable theoretical insights for further improv-ing the optoelectronic performance of TMD-based devices.展开更多
Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third...Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a designed multi-attention mechanism focuses on important local features during the feature extraction stage. Moreover, a triplet loss function is utilized to learn discriminative hash codes to construct a compact and efficient triplet deep hashing. Finally, upsampling is used to restore the original resolution of the images during retrieval, thereby enabling more accurate matching. To ensure the security of medical image data, a lightweight image encryption method based on frequency domain encryption is designed to encrypt the chest X-ray images. The findings of the experiment indicate that, in comparison to various advanced image retrieval techniques, the suggested approach improves the precision of feature extraction and retrieval using the COVIDx dataset. Additionally, it offers enhanced protection for the confidentiality of medical images stored in cloud settings and demonstrates strong practicality.展开更多
A new cyclometalated iridium（IlI） complex Ir（DPP）3 （DPP=2,3-diphenylpyrazine） was prepared by reaction of DPP with iridium trichloride hydrate under microwave irradiation. The structure of the complex was confir...A new cyclometalated iridium（IlI） complex Ir（DPP）3 （DPP=2,3-diphenylpyrazine） was prepared by reaction of DPP with iridium trichloride hydrate under microwave irradiation. The structure of the complex was confirmed by elemental analysis, ^1H NMR, and mass spectroscopy. The UV-Vis absorption and photoluminescent properties of the complex were investigated. The complex shows strong ^1MLCT （singlet metal to ligand charge-transfer） and aMLCT （triplet metal to ligand charge-transfer） absorption at 382 and 504 nm, respectively. The complex also shows strong photoluminescence at 573 nm at room temperature. These results suggest the complex to be a promising phosphorescent material.展开更多
Analysis of the secondary structures of mRNAs which encode mature peptides shows that the location of each codon in mRNA secondary structure has a trend, which appears to be in agreement with the conformational proper...Analysis of the secondary structures of mRNAs which encode mature peptides shows that the location of each codon in mRNA secondary structure has a trend, which appears to be in agreement with the conformational property of the corresponding amino acid to some extent. Most of the codons that encode hydrophobic amino acids are located in stable stem regions of mRNA secondary structures, and vice versa, most of the codons that encode hydrophilic amino acids are located in flexible loop regions. This result supports the recent conclusion that there may be the information transfer between the three dimensional structures of mRNA and the encoded protein.展开更多
The formation of triplet chlorophyll and carotenoid by radical pair recombination have been observed in the reaction centers of photosystems of bacteria and higher plants. This is an important process for the photopro...The formation of triplet chlorophyll and carotenoid by radical pair recombination have been observed in the reaction centers of photosystems of bacteria and higher plants. This is an important process for the photoprotection of the reaction centers, for the dissipation of excessive energy by non_radiative decay of carotenoid triplet. Triplet generation by the same mechanism in an artificial system has rarely been observed, only a few cases were reported in donor_acceptor triad supermolecules. This is probably the first time report of the simulation of the generation of triplet by back electron transfer using dye_sensitized TiO 2 solar cell reaction. Triplet states have been observed in all_ trans _retinoic acid sensitized TiO 2 colloid during the recombination of the trapped electron with the retinoic acid radical cation after photoexcitation. The intermediates were characterized by ns time_resolved spectroscopy.展开更多
The development of fluorescent materials capable of harvesting triplet excitons efficiently is of great importance in achieving high-performance low-cost organic light-emitting diodes（OLEDs）.Among the three mechanis...The development of fluorescent materials capable of harvesting triplet excitons efficiently is of great importance in achieving high-performance low-cost organic light-emitting diodes（OLEDs）.Among the three mechanisms converting triplet to singlet excitons,triplet fusion delayed fluorescence（TFDF） plays a key role in the demonstration of highly efficient and reliable OLEDs,especially blue devices,for practice applications.This review focuses on the recent development of TFDF materials and their applications in OLEDs.Fundamental TFDF mechanism,molecular design principles,and the structure-property relationship of TFDF materials with a particular emphasis on their different excited state characters,are presented and discussed.Moreover,the future perspectives and ongoing challenges of TFDF materials are also highlighted.展开更多
A new approach to the research of the distribution of prime-triplets is developed. It differs from the usual methods (involving the sieve method) for this kind of research, and basing on Chebyshev inequality and on th...A new approach to the research of the distribution of prime-triplets is developed. It differs from the usual methods (involving the sieve method) for this kind of research, and basing on Chebyshev inequality and on the computation of average concentration of all the related subset. It leads to the proofs of following Lemma 2 and Theorem 2 (Lemma 1 and Theorem 1 in Reference 1 had been proved by means of this new method): Lemma 2 Among all the prime-triplet-subsets there exists at least one such subset which is an infinite set. Theorem 2 All the prime-triplet-subsets or infinitely many such subsets are infinite sets.Formulas for estimating the amount of such infinite sets are provided in this paper.展开更多
Photosensitizers constitute a crucial element in the process of triplet-triplet annihilation upconversion,necessitating robust absorption of visible or near-infrared light,high intersystem crossing efficiency,prolonge...Photosensitizers constitute a crucial element in the process of triplet-triplet annihilation upconversion,necessitating robust absorption of visible or near-infrared light,high intersystem crossing efficiency,prolonged triplet state lifetime,and minimal energy dissipation during intersystem crossing and vibrational relaxation.Nonetheless,conventional monomeric photosensitizers frequently fail to simultaneously meet these requirements.In recent years,researchers,including our group,have fabricated photosensitizers that incorporate multiple covalent linkages,such as dyads and triads,which are regarded more likely to achieve comprehensive performance optimization.This review article explores the design and characteristics of recently synthesized dyads and triads photosensitizers that operate on the principles of intramolecular singlet energy transfer and intramolecular triplet energy transfer,demonstrating their outstanding efficacy in high-efficiency triplet-triplet annihilation upconversion.We provide an exhaustive explanation of the design rationales,photophysical,and photochemical properties of these photosensitizers,along with suggestions for the creation of photosensitizers with enhanced performance.Moreover,we discuss potential avenues and opportunities for the future development of triplet-triplet annihilation upconversion technology.展开更多
Triplet-triplet energy transfer in fluorene dimer with electronic structure calculations. The two is investigated by combining rate theories key parameters for the control of energy transfer, electronic coupling and r...Triplet-triplet energy transfer in fluorene dimer with electronic structure calculations. The two is investigated by combining rate theories key parameters for the control of energy transfer, electronic coupling and reorganization energy, are calculated based on the diabatic states constructed by the constrained density functional theory. The fluctuation of the electronic coupling is further revealed by molecular dynamics simulation. Succeedingly, the diagonal and off-diagonal fluctuations of the Hamiltonian are mapped from the correlation functions of those parameters, and the rate is then estimated both from the perturbation theory and wavepacket diffusion method. The results manifest that both the static and dynamic fluctuations enhance the rate significantly, but the rate from the dynamic fluctuation is smaller than that from the static fluctuation.展开更多
Based upon seven superconducting gravimeter （SG） records of 20 000 h length after the 2004 Sumatra earthquake, four methods, namely the ensemble empirical mode decomposition （EEMD）, the multi-station experiment （...Based upon seven superconducting gravimeter （SG） records of 20 000 h length after the 2004 Sumatra earthquake, four methods, namely the ensemble empirical mode decomposition （EEMD）, the multi-station experiment （MSE） technique, the autoregressive （AR） method and the product spec- trum analysis （PSA） method, are chosen jointly together to detect the inner core translational modes （1S1）. After the conventional pretreatment, each of the seven simultaneous residual gravity series is di- vided into five segments with an 80% overlap, and then EEMD is applied to all the 35 residual SG se- ries as a dyadic filter bank to get 35 filtered series. After then, according to different stations and dif- ferent time windows, five new simultaneous gravity datasets are obtained. After using MSE for each of the five new datasets, the AR method is used to demodulate some known harmonic signals from the new sequences that obtained by using MSE, and three demodulated product spectra are obtained. Then, according to two criterions, two clear spectral peaks at periods of 4.548 9±2.3×10^-5 and 3.802 3±3.2×10^-5 h corresponding respectively to the singlets m=-1 and m=＋l are identified from various spectral peaks, and they are close to the predictions of the 1066A model given by Rieutord （2002）, but no spectral peak corresponding to the singlet m=0 is found. We conclude that the selected two peaks might be the ob- served singlets of the Slichter triplet.展开更多
This work aimed at investigating the crucial factor in building and maintaining the combustion front during in-situ combustion(ISC),oxidized coke and pyrolyzed coke.The surface morphologies,elemental contents,and non-...This work aimed at investigating the crucial factor in building and maintaining the combustion front during in-situ combustion(ISC),oxidized coke and pyrolyzed coke.The surface morphologies,elemental contents,and non-isothermal mass losses of the oxidized and pyrolyzed cokes were thoroughly examined.The results indicated that the oxidized coke could be combusted at a lower temperature compared to the pyrolyzed coke due primarily to their differences in the molecular polarity and microstructure.Kinetic triplets of coke combustion were determined using iso-conversional models and one advanced integral master plots method.The activation energy values of the oxidized and pyrolyzed cokes varied in the range of 130-153 k J/mol and 95-120 kJ/mol,respectively.The most appropriate reaction model of combustion of the oxidized and pyrolyzed cokes followed three-dimensional diffusion model(D_(3)) and random nucleation and subsequent growth model(F_(1)),respectively.These observations assisted in building the numerical model of these two types of cokes to simulate the ISC process.展开更多
Tunneling conductance in normal metal/insulator/triplet superconductor junctions is studied theoretically as a function of the bias voltage at zero temperature and finite temperature. The results show there are zero-b...Tunneling conductance in normal metal/insulator/triplet superconductor junctions is studied theoretically as a function of the bias voltage at zero temperature and finite temperature. The results show there are zero-bias conductance peak, zero-bias conductance dip and double-minimum structures in the spectra for p-wave superconductor junctions. The existence of such structures in the conductance spectrum can be taken as evidence that the pairing symmetry of Sr2RuO4 is p-wave symmetry.展开更多
BACKGROUND Peritoneal metastasis from colorectal cancer(CRC)carries a poor prognosis in most studies.The majority of those studies used either a single-agent or doublet chemotherapy regimen in the first-line setting.A...BACKGROUND Peritoneal metastasis from colorectal cancer(CRC)carries a poor prognosis in most studies.The majority of those studies used either a single-agent or doublet chemotherapy regimen in the first-line setting.AIM To investigate the prognostic significance of peritoneal metastasis in a cohort of patients treated with triplet chemotherapy in the first-line setting.METHODS We retrospectively evaluated progression-free survival(PFS)and overall survival(OS)in 51 patients with metastatic CRC treated in a prospective clinical trial with capecitabine,oxaliplatin,irinotecan,and bevacizumab in the first-line setting according to the presence and absence of peritoneal metastasis.Furthermore,univariate and multivariate analyses for PFS and OS were performed to assess the prognostic significance of peritoneal metastasis at the multivariate level.RESULTS Fifty-one patients were treated with the above triplet therapy.Fifteen had peritoneal metastasis.The patient characteristics of both groups showed a significant difference in the sidedness of the primary tumor(left-sided primary tumor in 60%of the peritoneal group vs 86%in the nonperitoneal group,P=0.03)and the presence of liver metastasis(40%for the peritoneal group vs 75%for the nonperitoneal group,P=0.01).Univariate analysis for PFS showed a statistically significant difference for age less than 65 years(P=0.034),presence of liver metastasis(P=0.046),lung metastasis(P=0.011),and those who underwent metastasectomy(P=0.001).Only liver metastasis and metastasectomy were statistically significant for OS,with P values of 0.001 and 0.002,respectively.Multivariate analysis showed that age(less than 65 years)and metastasectomy were statistically significant for PFS,with P values of 0.002 and 0.001,respectively.On the other hand,the absence of liver metastasis and metastasectomy were statistically significant for OS,with P values of 0.003 and 0.005,respectively.CONCLUSION Peritoneal metastasis in patients with metastatic CRC treated with first-line triple chemotherapy does not carry prognostic significance at univariate and multivariate levels.Confirmatory larger studies are warranted.展开更多
Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from ima...Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.:U23A20530,82273858,and 82173746)the National Key Research and Development Programof China(Grant No.:2023YFF1204904)Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism(Shanghai Municipal Education Commission,China).
文摘Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures.Nonetheless,they also form a major source of prediction error in structure-activity relationship(SAR)models.To date,several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs.In this paper,we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet,tailored for ACs.Through extensive comparison with multiple baseline models on 30 benchmark datasets,the results showed that ACtriplet was significantly better than those deep learning(DL)models without pretraining.In addition,we explored the effect of pre-training on data representation.Finally,the case study demonstrated that our model's interpretability module could explain the prediction results reasonably.In the dilemma that the amount of data could not be increased rapidly,this innovative framework would better make use of the existing data,which would propel the potential of DL in the early stage of drug discovery and optimization.
基金supported by the National Natural Science Foundation of China(Nos.21933005,22473014,and 22273007)the National Key R&D Program of China(No.2022YFA1505400).
文摘Localized surface plasmon resonance(LSPR)effects in gold nanoparticles(AuNPs)significantly influence the excited states of nearby molecules,offering unique opportunities for enhancing molecular triplet states.Herein,we report the synthesis of DNA-templated gold nanostars(AuNF_A15)and gold nanospheres(AuNS_T15)via a seed-mediated growth method and their ability to enhance the triplet state of coralyne,a small molecule with promising applications in photodynamic therapy(PDT).DNA single strands(A15 or T15)were employed as templates to regulate the morphology of AuNPs,resulting in nanostars and nanospheres.The nanostars exhibited a superior LSPR effect due to their“lightning rod effect",significantly enhancing coralyne’s triplet signal by 15-fold compared to a 10-fold enhancement observed with nanospheres.This enhancement was confirmed via steady-state and nanosecond transient absorption spectroscopy.These findings demonstrate that DNA-assembled gold nanostars hold exceptional potential for enhancing molecular triplet states,particularly for PDT applications involving DNA-targeting small molecules.
基金Supported by the Scientific Research and Technology Development Project of Petrochina Southwest Oil and Gas Field Company(20230307-02)。
文摘The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibration signals induced by external events and to effectively provide early warnings of potential intrusion activities.Due to the complexity and diversity of external intrusion events,traditional deep learning methods can achieve event recognition with an average accuracy exceeding 90%.However,these methods rely on large-scale datasets,leading to significant time and labor costs during the data collection process.Additionally,traditional methods perform poorly when faced with the scarcity of low-frequency event samples,making it challenging to address these rare occurrences.To address this issue,this paper proposes a small-sample learning model based on triplet learning for intrusion event recognition.The model employs a 6-way 20-shot support set configuration and utilizes the KNN clustering algorithm to assess the model's performance.Experimental results indicate that the model achieves an average accuracy of 91.6%,further validating the superior performance of the triplet learning model in classifying external intrusion events.Compared to traditional methods,this approach not only effectively reduces the dependence on large-scale datasets but also better addresses the classification of low-frequency event samples,demonstrating significant application potential.
基金funded by the Institute of InformationTechnology,VietnamAcademy of Science and Technology(project number CSCL02.02/22-23)“Research and Development of Methods for Searching Similar Trademark Images Using Machine Learning to Support Trademark Examination in Vietnam”.
文摘Image-based similar trademark retrieval is a time-consuming and labor-intensive task in the trademark examination process.This paper aims to support trademark examiners by training Deep Convolutional Neural Network(DCNN)models for effective Trademark Image Retrieval(TIR).To achieve this goal,we first develop a novel labeling method that automatically generates hundreds of thousands of labeled similar and dissimilar trademark image pairs using accompanying data fields such as citation lists,Vienna classification(VC)codes,and trademark ownership information.This approach eliminates the need for manual labeling and provides a large-scale dataset suitable for training deep learning models.We then train DCNN models based on Siamese and Triplet architectures,evaluating various feature extractors to determine the most effective configuration.Furthermore,we present an Adapted Contrastive Loss Function(ACLF)for the trademark retrieval task,specifically engineered to mitigate the influence of noisy labels found in automatically created datasets.Experimental results indicate that our proposed model(Efficient-Net_v21_Siamese)performs best at both True Negative Rate(TNR)threshold levels,TNR 0.9 and TNR 0.95,with==respective True Positive Rates(TPRs)of 77.7%and 70.8%and accuracies of 83.9%and 80.4%.Additionally,when testing on the public trademark dataset METU_v2,our model achieves a normalized average rank(NAR)of 0.0169,outperforming the current state-of-the-art(SOTA)model.Based on these findings,we estimate that considering only approximately 10%of the returned trademarks would be sufficient,significantly reducing the review time.Therefore,the paper highlights the potential of utilizing national trademark data to enhance the accuracy and efficiency of trademark retrieval systems,ultimately supporting trademark examiners in their evaluation tasks.
基金supported by the Fundamental Re-search Funds for the Central Universities(Ganglong Cui)and National Key Research and Development Pro-gram of China(No.2021YFA1500703 to Ganglong Cui)National Natural Science Foundation of China(No.22103067 to Xiao-Ying Xie)and Natural Science Foundation of Shandong Province(No.ZR2021QB105 to Xiao-Ying Xie).
文摘Heterostructures of organic semi-conductors and transition metal dichalcogenides(TMDs)are viable candidates for superior optoelec-tronic devices.Photoinduced inter-facial charge transfer is crucial for the performance efficiency of such devices,yet the underlying mecha-nism,especially the roles of optical-ly dark triplets and spatially sepa-rated charge transfer states,is poorly understood.In the present work,we obtain the struc-tures of distinct excited states and investigate how they are involved in the charge transfer process at the Pd-octaethylporphyrin(PdOEP)and WS_(2) interface in terms of their energies and couplings.The results show that electron transfer from the triplet PdOEP formed via intersystem crossing prevails over direct electron transfer from the singlet(two orders of magnitude faster).Further analysis reveals that the relatively higher rate of triplet electron transfer compared to singlet electron transfer is mainly attributed to a smaller reorganization energy,which is dominated by the out-of-plane vibrations of the organic component.The work emphasizes the important roles of the optically dark triplets in the electron transfer of the PdOEP@WS_(2) heterostructure,and provides valuable theoretical insights for further improv-ing the optoelectronic performance of TMD-based devices.
基金supported by the NationalNatural Science Foundation of China(No.61862041).
文摘Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a designed multi-attention mechanism focuses on important local features during the feature extraction stage. Moreover, a triplet loss function is utilized to learn discriminative hash codes to construct a compact and efficient triplet deep hashing. Finally, upsampling is used to restore the original resolution of the images during retrieval, thereby enabling more accurate matching. To ensure the security of medical image data, a lightweight image encryption method based on frequency domain encryption is designed to encrypt the chest X-ray images. The findings of the experiment indicate that, in comparison to various advanced image retrieval techniques, the suggested approach improves the precision of feature extraction and retrieval using the COVIDx dataset. Additionally, it offers enhanced protection for the confidentiality of medical images stored in cloud settings and demonstrates strong practicality.
文摘A new cyclometalated iridium（IlI） complex Ir（DPP）3 （DPP=2,3-diphenylpyrazine） was prepared by reaction of DPP with iridium trichloride hydrate under microwave irradiation. The structure of the complex was confirmed by elemental analysis, ^1H NMR, and mass spectroscopy. The UV-Vis absorption and photoluminescent properties of the complex were investigated. The complex shows strong ^1MLCT （singlet metal to ligand charge-transfer） and aMLCT （triplet metal to ligand charge-transfer） absorption at 382 and 504 nm, respectively. The complex also shows strong photoluminescence at 573 nm at room temperature. These results suggest the complex to be a promising phosphorescent material.
文摘Analysis of the secondary structures of mRNAs which encode mature peptides shows that the location of each codon in mRNA secondary structure has a trend, which appears to be in agreement with the conformational property of the corresponding amino acid to some extent. Most of the codons that encode hydrophobic amino acids are located in stable stem regions of mRNA secondary structures, and vice versa, most of the codons that encode hydrophilic amino acids are located in flexible loop regions. This result supports the recent conclusion that there may be the information transfer between the three dimensional structures of mRNA and the encoded protein.
基金The Fund of"Hundred Talents Program"the National Key Basic Research and Development(973)Plan(G1998010102).
文摘The formation of triplet chlorophyll and carotenoid by radical pair recombination have been observed in the reaction centers of photosystems of bacteria and higher plants. This is an important process for the photoprotection of the reaction centers, for the dissipation of excessive energy by non_radiative decay of carotenoid triplet. Triplet generation by the same mechanism in an artificial system has rarely been observed, only a few cases were reported in donor_acceptor triad supermolecules. This is probably the first time report of the simulation of the generation of triplet by back electron transfer using dye_sensitized TiO 2 solar cell reaction. Triplet states have been observed in all_ trans _retinoic acid sensitized TiO 2 colloid during the recombination of the trapped electron with the retinoic acid radical cation after photoexcitation. The intermediates were characterized by ns time_resolved spectroscopy.
基金supported by National Natural Science Foundation of China(No.21372168)
文摘The development of fluorescent materials capable of harvesting triplet excitons efficiently is of great importance in achieving high-performance low-cost organic light-emitting diodes（OLEDs）.Among the three mechanisms converting triplet to singlet excitons,triplet fusion delayed fluorescence（TFDF） plays a key role in the demonstration of highly efficient and reliable OLEDs,especially blue devices,for practice applications.This review focuses on the recent development of TFDF materials and their applications in OLEDs.Fundamental TFDF mechanism,molecular design principles,and the structure-property relationship of TFDF materials with a particular emphasis on their different excited state characters,are presented and discussed.Moreover,the future perspectives and ongoing challenges of TFDF materials are also highlighted.
文摘A new approach to the research of the distribution of prime-triplets is developed. It differs from the usual methods (involving the sieve method) for this kind of research, and basing on Chebyshev inequality and on the computation of average concentration of all the related subset. It leads to the proofs of following Lemma 2 and Theorem 2 (Lemma 1 and Theorem 1 in Reference 1 had been proved by means of this new method): Lemma 2 Among all the prime-triplet-subsets there exists at least one such subset which is an infinite set. Theorem 2 All the prime-triplet-subsets or infinitely many such subsets are infinite sets.Formulas for estimating the amount of such infinite sets are provided in this paper.
基金supported by the National Natural Science Foundation of China(No.22203004 and No.21927814)the Anhui Normal University 2023 Scholarship and Supplementary Discipline Construction Project(No.2023GFXK160).
文摘Photosensitizers constitute a crucial element in the process of triplet-triplet annihilation upconversion,necessitating robust absorption of visible or near-infrared light,high intersystem crossing efficiency,prolonged triplet state lifetime,and minimal energy dissipation during intersystem crossing and vibrational relaxation.Nonetheless,conventional monomeric photosensitizers frequently fail to simultaneously meet these requirements.In recent years,researchers,including our group,have fabricated photosensitizers that incorporate multiple covalent linkages,such as dyads and triads,which are regarded more likely to achieve comprehensive performance optimization.This review article explores the design and characteristics of recently synthesized dyads and triads photosensitizers that operate on the principles of intramolecular singlet energy transfer and intramolecular triplet energy transfer,demonstrating their outstanding efficacy in high-efficiency triplet-triplet annihilation upconversion.We provide an exhaustive explanation of the design rationales,photophysical,and photochemical properties of these photosensitizers,along with suggestions for the creation of photosensitizers with enhanced performance.Moreover,we discuss potential avenues and opportunities for the future development of triplet-triplet annihilation upconversion technology.
基金This work was supported by the National Natural Science Foundation of China （No.20833004 and No.21073146） and the Research Fund for the Doctoral Program of Higher Education of China （No.200803840009）.
文摘Triplet-triplet energy transfer in fluorene dimer with electronic structure calculations. The two is investigated by combining rate theories key parameters for the control of energy transfer, electronic coupling and reorganization energy, are calculated based on the diabatic states constructed by the constrained density functional theory. The fluctuation of the electronic coupling is further revealed by molecular dynamics simulation. Succeedingly, the diagonal and off-diagonal fluctuations of the Hamiltonian are mapped from the correlation functions of those parameters, and the rate is then estimated both from the perturbation theory and wavepacket diffusion method. The results manifest that both the static and dynamic fluctuations enhance the rate significantly, but the rate from the dynamic fluctuation is smaller than that from the static fluctuation.
基金supported by the National Natural Science Foundation of China(No.41174011)the National Natural Science Foundation of China(Nos.41128003,41021061,40974015)+2 种基金the National 973 Project of China(No.2013CB733305)the Fundamental Research Funds for the Central Universities(No.2012214020203)the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,China(Nos.12-02-04,12-02-02)
文摘Based upon seven superconducting gravimeter （SG） records of 20 000 h length after the 2004 Sumatra earthquake, four methods, namely the ensemble empirical mode decomposition （EEMD）, the multi-station experiment （MSE） technique, the autoregressive （AR） method and the product spec- trum analysis （PSA） method, are chosen jointly together to detect the inner core translational modes （1S1）. After the conventional pretreatment, each of the seven simultaneous residual gravity series is di- vided into five segments with an 80% overlap, and then EEMD is applied to all the 35 residual SG se- ries as a dyadic filter bank to get 35 filtered series. After then, according to different stations and dif- ferent time windows, five new simultaneous gravity datasets are obtained. After using MSE for each of the five new datasets, the AR method is used to demodulate some known harmonic signals from the new sequences that obtained by using MSE, and three demodulated product spectra are obtained. Then, according to two criterions, two clear spectral peaks at periods of 4.548 9±2.3×10^-5 and 3.802 3±3.2×10^-5 h corresponding respectively to the singlets m=-1 and m=＋l are identified from various spectral peaks, and they are close to the predictions of the 1066A model given by Rieutord （2002）, but no spectral peak corresponding to the singlet m=0 is found. We conclude that the selected two peaks might be the ob- served singlets of the Slichter triplet.
基金supported by Chinese Postdoctoral Science Foundation (2021M692696)the National Science and Technology Project (2016ZX05058-003-017)Sichuan Science and Technology Program (2021YFH0081)。
文摘This work aimed at investigating the crucial factor in building and maintaining the combustion front during in-situ combustion(ISC),oxidized coke and pyrolyzed coke.The surface morphologies,elemental contents,and non-isothermal mass losses of the oxidized and pyrolyzed cokes were thoroughly examined.The results indicated that the oxidized coke could be combusted at a lower temperature compared to the pyrolyzed coke due primarily to their differences in the molecular polarity and microstructure.Kinetic triplets of coke combustion were determined using iso-conversional models and one advanced integral master plots method.The activation energy values of the oxidized and pyrolyzed cokes varied in the range of 130-153 k J/mol and 95-120 kJ/mol,respectively.The most appropriate reaction model of combustion of the oxidized and pyrolyzed cokes followed three-dimensional diffusion model(D_(3)) and random nucleation and subsequent growth model(F_(1)),respectively.These observations assisted in building the numerical model of these two types of cokes to simulate the ISC process.
文摘Tunneling conductance in normal metal/insulator/triplet superconductor junctions is studied theoretically as a function of the bias voltage at zero temperature and finite temperature. The results show there are zero-bias conductance peak, zero-bias conductance dip and double-minimum structures in the spectra for p-wave superconductor junctions. The existence of such structures in the conductance spectrum can be taken as evidence that the pairing symmetry of Sr2RuO4 is p-wave symmetry.
文摘BACKGROUND Peritoneal metastasis from colorectal cancer(CRC)carries a poor prognosis in most studies.The majority of those studies used either a single-agent or doublet chemotherapy regimen in the first-line setting.AIM To investigate the prognostic significance of peritoneal metastasis in a cohort of patients treated with triplet chemotherapy in the first-line setting.METHODS We retrospectively evaluated progression-free survival(PFS)and overall survival(OS)in 51 patients with metastatic CRC treated in a prospective clinical trial with capecitabine,oxaliplatin,irinotecan,and bevacizumab in the first-line setting according to the presence and absence of peritoneal metastasis.Furthermore,univariate and multivariate analyses for PFS and OS were performed to assess the prognostic significance of peritoneal metastasis at the multivariate level.RESULTS Fifty-one patients were treated with the above triplet therapy.Fifteen had peritoneal metastasis.The patient characteristics of both groups showed a significant difference in the sidedness of the primary tumor(left-sided primary tumor in 60%of the peritoneal group vs 86%in the nonperitoneal group,P=0.03)and the presence of liver metastasis(40%for the peritoneal group vs 75%for the nonperitoneal group,P=0.01).Univariate analysis for PFS showed a statistically significant difference for age less than 65 years(P=0.034),presence of liver metastasis(P=0.046),lung metastasis(P=0.011),and those who underwent metastasectomy(P=0.001).Only liver metastasis and metastasectomy were statistically significant for OS,with P values of 0.001 and 0.002,respectively.Multivariate analysis showed that age(less than 65 years)and metastasectomy were statistically significant for PFS,with P values of 0.002 and 0.001,respectively.On the other hand,the absence of liver metastasis and metastasectomy were statistically significant for OS,with P values of 0.003 and 0.005,respectively.CONCLUSION Peritoneal metastasis in patients with metastatic CRC treated with first-line triple chemotherapy does not carry prognostic significance at univariate and multivariate levels.Confirmatory larger studies are warranted.
基金supported in part by the General Program Hunan Provincial Natural Science Foundation of 2022,China(2022JJ31022)the Undergraduate Education Reform Project of Hunan Province,China(HNJG-20210532)the National Natural Science Foundation of China(62276276)。
文摘Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.
