6G is desired to support more intelligence networks and this trend attaches importance to the self-healing capability if degradation emerges in the cellular networks.As a primary component of selfhealing networks,faul...6G is desired to support more intelligence networks and this trend attaches importance to the self-healing capability if degradation emerges in the cellular networks.As a primary component of selfhealing networks,fault detection is investigated in this paper.Considering the fast response and low timeand-computational consumption,it is the first time that the Online Broad Learning System(OBLS)is applied to identify outages in cellular networks.In addition,the Automatic-constructed Online Broad Learning System(AOBLS)is put forward to rationalize its structure and consequently avoid over-fitting and under-fitting.Furthermore,a multi-layer classification structure is proposed to further improve the classification performance.To face the challenges caused by imbalanced data in fault detection problems,a novel weighting strategy is derived to achieve the Multilayer Automatic-constructed Weighted Online Broad Learning System(MAWOBLS)and ensemble learning with retrained Support Vector Machine(SVM),denoted as EMAWOBLS,for superior treatment with this imbalance issue.Simulation results show that the proposed algorithm has excellent performance in detecting faults with satisfactory time usage.展开更多
BACKGROUND Leiomyomas or fibroids commonly originate from the uterus;extrauterine leiomyomas are rare and most often arise from the broad ligament.Diagnosing broad ligament leiomyomas becomes particularly challenging ...BACKGROUND Leiomyomas or fibroids commonly originate from the uterus;extrauterine leiomyomas are rare and most often arise from the broad ligament.Diagnosing broad ligament leiomyomas becomes particularly challenging when they undergo degenerative changes because their clinical and radiological features often mimic those of ovarian tumors.We report a rare case of a giant broad ligament fibroid with cystic degeneration,which was initially mistaken for an ovarian mass.CASE SUMMARY A 49-year-old woman presented with mild abdominal distension and pain as the only symptoms.Upon abdominal examination,a large mass measuring approximately 30 cm and extending from the pelvic cavity to just below the xiphoid process was identified.Both transvaginal ultrasound and contrast-enhanced computed tomography suggested an ovarian origin of the mass.However,laparotomy confirmed that the mass originated from the right broad ligament.The mass was separated from the uterus and bilateral ovaries,with no involvement of the uterus or ovaries.The mass was completely resected with respecting the patient’s desire to retain her uterus and adnexa.Postoperative histopathological examination confirmed leiomyoma with cystic degeneration.CONCLUSION Broad ligament myomas mimic ovarian tumors;accurate diagnosis and careful operation are critical to avoid complications and ensure safety.展开更多
Wheat leaf rust,caused by Puccinia triticina(Pt),is one of the most devastating diseases in common wheat(Triticum aestivum L.)and can lead to heavy yield loss(Chai et al.2020).Leaf rust can result in 50%yield loss dur...Wheat leaf rust,caused by Puccinia triticina(Pt),is one of the most devastating diseases in common wheat(Triticum aestivum L.)and can lead to heavy yield loss(Chai et al.2020).Leaf rust can result in 50%yield loss during epidemic years(Huerta-Espino et al.2011;Gebrewahid et al.2020;Kolomiets et al.2021).Breeding varieties resistant to leaf rust have been recognized as the most effective and economical method to mitigate wheat losses caused by Pt.The narrow genetic basis of wheat constrains the number of cultivars resistant to leaf rust(Jin et al.2021).展开更多
In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to t...In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.展开更多
Bi_(2)YbO_(4)Cl with a fluorite layer structure belongs to the family of the bismuth rare-earth oxyhalides Bi_(2)REO_(4)X(X=Cl,B r,I).However,the synthesis and photoelectric properties of Bi_(2)YbO_(4)Cl have almost n...Bi_(2)YbO_(4)Cl with a fluorite layer structure belongs to the family of the bismuth rare-earth oxyhalides Bi_(2)REO_(4)X(X=Cl,B r,I).However,the synthesis and photoelectric properties of Bi_(2)YbO_(4)Cl have almost not been reported.In this work,Bi_(2)YbO_(4)Cl was synthesized using the solid-state method and the solvothermal method.Yb3+ions show a strong characteristic absorption peak at 980 nm,which was measured by ultraviolet-visible-near-infrared absorption spectra.The transient photoconductivity of Bi_(2)YbO_(4)Cl was obtained by time-resolved terahertz spectroscopy system under 400 and 800 nm laser excitations,respectively.The frequency-dependent transient photoconductivity analysis reveals the Drude-Smith behavior in Bi_(2)YbO_(4)Cl.Under photoexcitation,the hot charge carriers with a long relaxation lifetime and a carrier mobility of 48 cm^(2)/(V·s) are obtained.The synthesis of Bi_(2)YbO_(4)Cl is of great significance for the development of novel photocatalytic and photo harvesting materials with broad spectral response.展开更多
Coronaviruses are single-stranded,positive-sense RNA enveloped viruses that have posed a significant threat to human health over the past few decades,particularly severe acute respiratory syndrome coronavirus(SARS-CoV...Coronaviruses are single-stranded,positive-sense RNA enveloped viruses that have posed a significant threat to human health over the past few decades,particularly severe acute respiratory syndrome coronavirus(SARS-CoV),Middle East respiratory syndrome coronavirus(MERS-CoV),and SARS-CoV-2.These viruses have caused widespread infections and fatalities,with profound impacts on global economies,social life,and public health systems.Due to their broad host range in natural settings and the consequent high potential for zoonotic spillover events,a thorough investigation of the common viral mechanisms and the identification of druggable targets for pan-coronavirus antiviral development are of utmost importance.展开更多
Ingenious microstructure design and rational composition collocation have been proved to be an effective strategy for developing efficient electromagnetic wave(EMW)absorbers.It would be promising to fabricate a hollow...Ingenious microstructure design and rational composition collocation have been proved to be an effective strategy for developing efficient electromagnetic wave(EMW)absorbers.It would be promising to fabricate a hollow structured composite integrating multiple loss mechanisms(conduction,magnetic,and polarization losses)for excellent EMW absorption.Herein,a novel dielectric-magnetic compound of ZnO/Ni@C hollow microsphere was prepared through hydrothermal reactions followed by an in-situ chemical vapor deposition(CVD).In this ternary composite,abundant ZnO/Ni heterostructures formed the hollow microsphere skeletons and provided unique Schottky junctions,which endowed the composite with improved impedance matching and strong polarization loss.Meanwhile,the amorphouspolycrystalline carbon layer deposited on the surface of each microsphere enhanced the conduction and interfacial polarization losses.In addition,the magnetic Ni nanoparticles induced magnetic loss.Benefiting from the synergistic effect of the hollow structure and multiple loss mechanisms,the ternary composite exhibits an effective absorption bandwidth as wide as 6.55 GHz at a thickness of only 1.85 mm,accompanied by a minimum reflection loss of–39.8 dB.Besides,the radar cross-section and the electromagnetic field simulation further verify the superior EMW absorption performance of the composites.Our work provides a new reference for the fabrication of dielectric-magnetic ternary hollow microspheres as EMW absorbers with thin thickness and broad bandwidth.展开更多
The popularity of the Internet of Things(IoT)has enabled a large number of vulnerable devices to connect to the Internet,bringing huge security risks.As a network-level security authentication method,device fingerprin...The popularity of the Internet of Things(IoT)has enabled a large number of vulnerable devices to connect to the Internet,bringing huge security risks.As a network-level security authentication method,device fingerprint based on machine learning has attracted considerable attention because it can detect vulnerable devices in complex and heterogeneous access phases.However,flexible and diversified IoT devices with limited resources increase dif-ficulty of the device fingerprint authentication method executed in IoT,because it needs to retrain the model network to deal with incremental features or types.To address this problem,a device fingerprinting mechanism based on a Broad Learning System(BLS)is proposed in this paper.The mechanism firstly characterizes IoT devices by traffic analysis based on the identifiable differences of the traffic data of IoT devices,and extracts feature parameters of the traffic packets.A hierarchical hybrid sampling method is designed at the preprocessing phase to improve the imbalanced data distribution and reconstruct the fingerprint dataset.The complexity of the dataset is reduced using Principal Component Analysis(PCA)and the device type is identified by training weights using BLS.The experimental results show that the proposed method can achieve state-of-the-art accuracy and spend less training time than other existing methods.展开更多
High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency...High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.展开更多
Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone...Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone to serious intra-class and inter-class imbalance problems, which can significantly degrade the classification performance. To address the above issues, we propose the multi-label weighted broad learning system(MLW-BLS) from the perspective of label imbalance weighting and label correlation mining. Further, we propose the multi-label adaptive weighted broad learning system(MLAW-BLS) to adaptively adjust the specific weights and values of labels of MLW-BLS and construct an efficient imbalanced classifier set. Extensive experiments are conducted on various datasets to evaluate the effectiveness of the proposed model, and the results demonstrate its superiority over other advanced approaches.展开更多
Broad ligament hematoma is typically seen during cesarean section due to rupture of branches of uterine and vaginal vessels and it’s rare to be seen post-normal vaginal delivery. Addressing puerperal hematomas postpa...Broad ligament hematoma is typically seen during cesarean section due to rupture of branches of uterine and vaginal vessels and it’s rare to be seen post-normal vaginal delivery. Addressing puerperal hematomas postpartum presents considerable challenges for obstetric care providers. While hematomas such as those affecting the vulva, vulvovaginal region, or paravaginal area are frequently encountered, retroperitoneal hematomas are rare and notably pose a greater risk to the life of the patient. The medical literature contains scant case reports on retroperitoneal hematomas, with no consensus on a definitive treatment approach. Pelvic arterial embolization has emerged as both a sensible and increasingly preferred method for treating these hematomas recently, but its application is contingent upon the patient maintaining hemodynamic stability and the availability of a specialized interventional embolization unit. In our case, we are presenting a very rare case of a 31-year-old primigravida female with a history of in vitro fertilization pregnancy. She delivered a normal vaginal delivery at 31 weeks gestation. Unfortunately, she experienced multiple complications intrapartum, including preeclampsia and placental abruption. These complications increased her risk of developing a broad ligament hematoma.展开更多
With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation security.Although X-ray baggage monitoring is...With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation security.Although X-ray baggage monitoring is now standard,manual screening has several limitations,including the propensity for errors,and raises concerns about passenger privacy.To address these drawbacks,researchers have leveraged recent advances in deep learning to design threatsegmentation frameworks.However,these models require extensive training data and labour-intensive dense pixelwise annotations and are finetuned separately for each dataset to account for inter-dataset discrepancies.Hence,this study proposes a semi-supervised contour-driven broad learning system(BLS)for X-ray baggage security threat instance segmentation referred to as C-BLX.The research methodology involved enhancing representation learning and achieving faster training capability to tackle severe occlusion and class imbalance using a single training routine with limited baggage scans.The proposed framework was trained with minimal supervision using resource-efficient image-level labels to localize illegal items in multi-vendor baggage scans.More specifically,the framework generated candidate region segments from the input X-ray scans based on local intensity transition cues,effectively identifying concealed prohibited items without entire baggage scans.The multi-convolutional BLS exploits the rich complementary features extracted from these region segments to predict object categories,including threat and benign classes.The contours corresponding to the region segments predicted as threats were then utilized to yield the segmentation results.The proposed C-BLX system was thoroughly evaluated on three highly imbalanced public datasets and surpassed other competitive approaches in baggage-threat segmentation,yielding 90.04%,78.92%,and 59.44%in terms of mIoU on GDXray,SIXray,and Compass-XP,respectively.Furthermore,the limitations of the proposed system in extracting precise region segments in intricate noisy settings and potential strategies for overcoming them through post-processing techniques were explored(source code will be available at https://github.com/Divs1159/CNN_BLS.)展开更多
This paper introduced the definition and importance of combination of sta-ple food. With broad bean nutrition flour as a sample, the preparation of the combi-nation of staple food was also described. In addition, the ...This paper introduced the definition and importance of combination of sta-ple food. With broad bean nutrition flour as a sample, the preparation of the combi-nation of staple food was also described. In addition, the main nutritional value of broad bean nutrition flour was introduced. Compared with those of other single flours, the nutritional value of broad bean nutrition flour was improved. Moreover, the nutrients in the broad bean nutrition flour would not be destroyed during the processing and preparation of staple food, and the processed steamed bread and raw noodle are more characteristic. The application value and prospects of broad bean nutrition flour, as a combination of staple food, were further discussed.展开更多
[Objective] The aim was to indentify diseased leaves of broad bean by vibra- tional spectroscopy. [Method] In this paper, broad bean rust, fusarium rhizome rot, broad bean zonate spot, yellow leaf curl virus and norma...[Objective] The aim was to indentify diseased leaves of broad bean by vibra- tional spectroscopy. [Method] In this paper, broad bean rust, fusarium rhizome rot, broad bean zonate spot, yellow leaf curl virus and normal leaves were studied using Fourier transform infrared spectroscopy combined with chemometrics. [Result] The spectra of the samples were similar, only with minor differences in absorption inten- sity of several peaks. Second derivative analyses show that the significant difference of all samples was in the range of 1 200-700 cm2. The data in the range of 1 200- 700 cm＇ were selected to evaluate correlation coefficients, hierarchical cluster analy- sis （HCA） and principal component analysis （PCA）. Results showed that the correla- tion coefficients are larger than 0.928 not only between the healthy leaves, but also between the same diseased leaves. The values between healthy and diseased leaves, and among diseased leaves, are all declined. HCA and PCA yielded about 73.3% and 82.2% accuracy, respectively. [Conclusion] This study demonstrated that FTIR techniques might be used to detect crop diseases.展开更多
Using Tongxian No.2 as material, the effects of different film-covering time, different sowing time and different planting density on the occurrence of freeze injury and yield of fresh broad beans were investigated. T...Using Tongxian No.2 as material, the effects of different film-covering time, different sowing time and different planting density on the occurrence of freeze injury and yield of fresh broad beans were investigated. The randomized block design was adopted. The results showed that with the delayed film covering, the incidence of mild freeze injury and number of headless seedlings were increased correspondingly, but the yield was increased; with the delayed sowing, the branch number per plant, effective branch number per plant, incidence of mild freeze injury and number of headless seedlings were all reduced, and the broad beans, sowed on September 30 th, obtained the highest yield; planting density showed on effect on the occurrence of freeze injury, and the yield was increased with the increase of planting density. Under the same film-covering time, the incidence of freeze injury was reduced with the delayed sowing time and it showed no changes when planting density was changed, but the yield was increased with the increase of planting density and it was highest when broad bean seeds were sowed on September 30th;under the same sowing time, the incidence of freeze injury was increased with the delayed film-covering time and it showed no changes when planting density was changed, and the yield was increased with the delayed film-covering time and increased planting density; under the same planting density, the incidence of freeze injury was increased with the delayed film-covering time but was reduced with the delayed sowing time, and the yield was increased with the delayed film-covering time and it was highest when the broad bean seeds were sowed on September30 th. Under same film-covering time and sowing time, the total branch number per plant and effective branch number per plant were reduced, but the yield was increased with the increase of planting density; under same film-covering time and planting density, the incidence of freeze injury was reduced with the delayed sowing time, and the yield was highest when broad bean seeds were sowed on September30th; under same sowing time and planting density, the incidence of freeze injury and the yield were all increased with the delayed film-covering time.展开更多
Fourier transform infrared （FTIR） spectroscopy was used to study diseased leaves in broad bean. Results showed that the infrared spectra of different broad bean diseased leaves were similar, which were mainly made u...Fourier transform infrared （FTIR） spectroscopy was used to study diseased leaves in broad bean. Results showed that the infrared spectra of different broad bean diseased leaves were similar, which were mainly made up of the vibrational absorption bands of protein,lipid and polysaccharide.There were minor differences in-cluding the spectral peak position, peak shape and the absorption intensity in the range of 1 800-1 300 cm-1. There were obvious differences among their second derivative spectra in the range of 1 800-1 300 cm-1. After the procedure of the Fourier self-deconvolution and curve fitting of health bean leaves and broad bean diseased leaves in the range of 1 700-1 500 cm-1, three sub-peaks were obtained at 1 550 cm-1 （protein amide Ⅱ band）, 1 605 cm-1 （lignin） and 1 650 cm-1 （protein amide I band）.The ratios of relative areas of the bands of amide Ⅱ, lignin, and amide I were 38.86%, 28.68% and 32.47% in the spectra of healthy leaves, respec-tively. It was distinguished from the diseased leaves （chocolate spot leaf： 15.42%, 42.98% and 41.61%, ring spot leaf：32.39%, 35.63% and 31.98%, rust leaf： 13.97%, 46.40% and 39.65%, yel owing leaf curl disease leaf： 24.01%,36.55% and 39.44%）. For sub-peak area ratios （A1 563/A1 605, A1 650/A1 605 and A1 563/A1 654）, those of four kinds of diseased leaves were smal er than that of healthy leaves, and there were also differences among four kinds of diseased leaves. The results proved that FTIR combining with curve fitting might be a potential y useful tool for detecting different kinds of broad bean diseases.展开更多
[Objective] This study aimed to investigate the influence of Pb2＋ on the growth and development of broad bean roots. [Method] The effects of Pb2＋ solution of different concentrations on root length, color, bending a...[Objective] This study aimed to investigate the influence of Pb2＋ on the growth and development of broad bean roots. [Method] The effects of Pb2＋ solution of different concentrations on root length, color, bending and mitotic index frequency of root tip cells of broad bean were measured and observed. [Result] Pb2＋ at concentration lower than 20 mg/L promoted the growth and development of roots, increased the cell mitotic indexes, but had little influence on root color and bending. When the Pb2＋ concentration was higher than 20 mg/L, the root growth was inhibited; the root color gradually turned deeper; the roots bended, but the cell mitotic index was decreased. [Conclusion] Pb2＋ promoted the growth of broad bean at low concentration but inhibited the growth at high concentration, and the influence was related to Pb2＋ concentration and time.展开更多
Perovskite LaCoO_(3)is of great potential in electromagnetic wave absorption considering its outstanding dielectric loss as well as the existing magnetic response with the magnetic doping.However,the dissipation mecha...Perovskite LaCoO_(3)is of great potential in electromagnetic wave absorption considering its outstanding dielectric loss as well as the existing magnetic response with the magnetic doping.However,the dissipation mechanism of the magnetic doping on the microwave absorption is lack of sufficient investigated.In this paper,LaCo_(1-x)Fe_(x)O_(3)(x=0,0.05,0.1,0.15,0.2,0.25,0.3,LCFOs)perovskites with different Fe doping amounts were prepared successfully by the sol-gel method and subsequent heat treatment in the air atmosphere.The structure characterization carried out by the frst-principles calculations shows the effect of Fe doping on the dielectric and magnetic properties of LCFOs and the strong hybridization of Co/Fe-3d with O-2p in the LCFOs system was successfully demonstrated.Particularly,when x=0.1 and the thickness is only 1.95 mm,the LaCo_(0.9)Fe_(0.1)O_(3)exhibits the best microwave absorption performance with the minimum reflection loss(RL)value of about-41 dB.The typical samples achieve a broad effective absorption bandwidth(EAB)of 5.16 GHz(7.92-13.08 GHz),which covers the total X band(8-12 GHz).Considering that,the especial Fe doping perovskite is promising to be a candidate as efficient microwave absorbers.展开更多
Data sharing in Internet of Vehicles(IoV)makes it possible to provide personalized services for users by service providers in Intelligent Transportation Systems(ITS).As IoV is a multi-user mobile scenario,the reliabil...Data sharing in Internet of Vehicles(IoV)makes it possible to provide personalized services for users by service providers in Intelligent Transportation Systems(ITS).As IoV is a multi-user mobile scenario,the reliability and efficiency of data sharing need to be further enhanced.Federated learning allows the server to exchange parameters without obtaining private data from clients so that the privacy is protected.Broad learning system is a novel artificial intelligence technology that can improve training efficiency of data set.Thus,we propose a federated bidirectional connection broad learning scheme(FeBBLS)to solve the data sharing issues.Firstly,we adopt the bidirectional connection broad learning system(BiBLS)model to train data set in vehicular nodes.The server aggregates the collected parameters of BiBLS from vehicular nodes through the federated broad learning system(FedBLS)algorithm.Moreover,we propose a clustering FedBLS algorithm to offload the data sharing into clusters for improving the aggregation capability of the model.Some simulation results show our scheme can improve the efficiency and prediction accuracy of data sharing and protect the privacy of data sharing.展开更多
基金supported in part by the National Key Research and Development Project under Grant 2020YFB1806805partially funded through a grant from Qualcomm。
文摘6G is desired to support more intelligence networks and this trend attaches importance to the self-healing capability if degradation emerges in the cellular networks.As a primary component of selfhealing networks,fault detection is investigated in this paper.Considering the fast response and low timeand-computational consumption,it is the first time that the Online Broad Learning System(OBLS)is applied to identify outages in cellular networks.In addition,the Automatic-constructed Online Broad Learning System(AOBLS)is put forward to rationalize its structure and consequently avoid over-fitting and under-fitting.Furthermore,a multi-layer classification structure is proposed to further improve the classification performance.To face the challenges caused by imbalanced data in fault detection problems,a novel weighting strategy is derived to achieve the Multilayer Automatic-constructed Weighted Online Broad Learning System(MAWOBLS)and ensemble learning with retrained Support Vector Machine(SVM),denoted as EMAWOBLS,for superior treatment with this imbalance issue.Simulation results show that the proposed algorithm has excellent performance in detecting faults with satisfactory time usage.
文摘BACKGROUND Leiomyomas or fibroids commonly originate from the uterus;extrauterine leiomyomas are rare and most often arise from the broad ligament.Diagnosing broad ligament leiomyomas becomes particularly challenging when they undergo degenerative changes because their clinical and radiological features often mimic those of ovarian tumors.We report a rare case of a giant broad ligament fibroid with cystic degeneration,which was initially mistaken for an ovarian mass.CASE SUMMARY A 49-year-old woman presented with mild abdominal distension and pain as the only symptoms.Upon abdominal examination,a large mass measuring approximately 30 cm and extending from the pelvic cavity to just below the xiphoid process was identified.Both transvaginal ultrasound and contrast-enhanced computed tomography suggested an ovarian origin of the mass.However,laparotomy confirmed that the mass originated from the right broad ligament.The mass was separated from the uterus and bilateral ovaries,with no involvement of the uterus or ovaries.The mass was completely resected with respecting the patient’s desire to retain her uterus and adnexa.Postoperative histopathological examination confirmed leiomyoma with cystic degeneration.CONCLUSION Broad ligament myomas mimic ovarian tumors;accurate diagnosis and careful operation are critical to avoid complications and ensure safety.
基金funded by the National Natural Science Foundation of China(32272083)。
文摘Wheat leaf rust,caused by Puccinia triticina(Pt),is one of the most devastating diseases in common wheat(Triticum aestivum L.)and can lead to heavy yield loss(Chai et al.2020).Leaf rust can result in 50%yield loss during epidemic years(Huerta-Espino et al.2011;Gebrewahid et al.2020;Kolomiets et al.2021).Breeding varieties resistant to leaf rust have been recognized as the most effective and economical method to mitigate wheat losses caused by Pt.The narrow genetic basis of wheat constrains the number of cultivars resistant to leaf rust(Jin et al.2021).
基金supported in part by the National Natural Science Foundation of China(62403396,62433018,62373113)the Guangdong Basic and Applied Basic Research Foundation(2023A1515011527,2023B1515120010)the Postdoctoral Fellowship Program of CPSF(GZB20240621)
文摘In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.
基金Project supported by the National Natural Science Foundation of China (61988102)the Key-Area Research and Development Program of Guangdong Province(2019B090917007)the Science and Technology Planning Project of Guangdong Province (2019B090909011)。
文摘Bi_(2)YbO_(4)Cl with a fluorite layer structure belongs to the family of the bismuth rare-earth oxyhalides Bi_(2)REO_(4)X(X=Cl,B r,I).However,the synthesis and photoelectric properties of Bi_(2)YbO_(4)Cl have almost not been reported.In this work,Bi_(2)YbO_(4)Cl was synthesized using the solid-state method and the solvothermal method.Yb3+ions show a strong characteristic absorption peak at 980 nm,which was measured by ultraviolet-visible-near-infrared absorption spectra.The transient photoconductivity of Bi_(2)YbO_(4)Cl was obtained by time-resolved terahertz spectroscopy system under 400 and 800 nm laser excitations,respectively.The frequency-dependent transient photoconductivity analysis reveals the Drude-Smith behavior in Bi_(2)YbO_(4)Cl.Under photoexcitation,the hot charge carriers with a long relaxation lifetime and a carrier mobility of 48 cm^(2)/(V·s) are obtained.The synthesis of Bi_(2)YbO_(4)Cl is of great significance for the development of novel photocatalytic and photo harvesting materials with broad spectral response.
基金supported by the Key Research and Development Program,Ministry of Science and Technology of the People’s Republic of China(Nos.2023YFC2606500,2023YFE0206500).
文摘Coronaviruses are single-stranded,positive-sense RNA enveloped viruses that have posed a significant threat to human health over the past few decades,particularly severe acute respiratory syndrome coronavirus(SARS-CoV),Middle East respiratory syndrome coronavirus(MERS-CoV),and SARS-CoV-2.These viruses have caused widespread infections and fatalities,with profound impacts on global economies,social life,and public health systems.Due to their broad host range in natural settings and the consequent high potential for zoonotic spillover events,a thorough investigation of the common viral mechanisms and the identification of druggable targets for pan-coronavirus antiviral development are of utmost importance.
基金supported by the National Natural Science Foundation of China(Nos.52272288 and 51972039)the China Postdoctoral Science Foundation(No.2021M700658).
文摘Ingenious microstructure design and rational composition collocation have been proved to be an effective strategy for developing efficient electromagnetic wave(EMW)absorbers.It would be promising to fabricate a hollow structured composite integrating multiple loss mechanisms(conduction,magnetic,and polarization losses)for excellent EMW absorption.Herein,a novel dielectric-magnetic compound of ZnO/Ni@C hollow microsphere was prepared through hydrothermal reactions followed by an in-situ chemical vapor deposition(CVD).In this ternary composite,abundant ZnO/Ni heterostructures formed the hollow microsphere skeletons and provided unique Schottky junctions,which endowed the composite with improved impedance matching and strong polarization loss.Meanwhile,the amorphouspolycrystalline carbon layer deposited on the surface of each microsphere enhanced the conduction and interfacial polarization losses.In addition,the magnetic Ni nanoparticles induced magnetic loss.Benefiting from the synergistic effect of the hollow structure and multiple loss mechanisms,the ternary composite exhibits an effective absorption bandwidth as wide as 6.55 GHz at a thickness of only 1.85 mm,accompanied by a minimum reflection loss of–39.8 dB.Besides,the radar cross-section and the electromagnetic field simulation further verify the superior EMW absorption performance of the composites.Our work provides a new reference for the fabrication of dielectric-magnetic ternary hollow microspheres as EMW absorbers with thin thickness and broad bandwidth.
基金supported by National Key R&D Program of China(2019YFB2102303)National Natural Science Foundation of China(NSFC61971014,NSFC11675199)Young Backbone Teacher Training Program of Henan Colleges and Universities(2021GGJS170).
文摘The popularity of the Internet of Things(IoT)has enabled a large number of vulnerable devices to connect to the Internet,bringing huge security risks.As a network-level security authentication method,device fingerprint based on machine learning has attracted considerable attention because it can detect vulnerable devices in complex and heterogeneous access phases.However,flexible and diversified IoT devices with limited resources increase dif-ficulty of the device fingerprint authentication method executed in IoT,because it needs to retrain the model network to deal with incremental features or types.To address this problem,a device fingerprinting mechanism based on a Broad Learning System(BLS)is proposed in this paper.The mechanism firstly characterizes IoT devices by traffic analysis based on the identifiable differences of the traffic data of IoT devices,and extracts feature parameters of the traffic packets.A hierarchical hybrid sampling method is designed at the preprocessing phase to improve the imbalanced data distribution and reconstruct the fingerprint dataset.The complexity of the dataset is reduced using Principal Component Analysis(PCA)and the device type is identified by training weights using BLS.The experimental results show that the proposed method can achieve state-of-the-art accuracy and spend less training time than other existing methods.
基金supported in part by the National Natural Science Foundation of China(62371116 and 62231020)in part by the Science and Technology Project of Hebei Province Education Department(ZD2022164)+2 种基金in part by the Fundamental Research Funds for the Central Universities(N2223031)in part by the Open Research Project of Xidian University(ISN24-08)Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education(Guilin University of Electronic Technology,China,CRKL210203)。
文摘High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.
基金supported in part by the National Key R&D Program of China (2023YFA1011601)the Major Key Project of PCL, China (PCL2023AS7-1)+3 种基金in part by the National Natural Science Foundation of China (U21A20478, 62106224, 92267203)in part by the Science and Technology Major Project of Guangzhou (202007030006)in part by the Major Key Project of PCL (PCL2021A09)in part by the Guangzhou Science and Technology Plan Project (2024A04J3749)。
文摘Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone to serious intra-class and inter-class imbalance problems, which can significantly degrade the classification performance. To address the above issues, we propose the multi-label weighted broad learning system(MLW-BLS) from the perspective of label imbalance weighting and label correlation mining. Further, we propose the multi-label adaptive weighted broad learning system(MLAW-BLS) to adaptively adjust the specific weights and values of labels of MLW-BLS and construct an efficient imbalanced classifier set. Extensive experiments are conducted on various datasets to evaluate the effectiveness of the proposed model, and the results demonstrate its superiority over other advanced approaches.
文摘Broad ligament hematoma is typically seen during cesarean section due to rupture of branches of uterine and vaginal vessels and it’s rare to be seen post-normal vaginal delivery. Addressing puerperal hematomas postpartum presents considerable challenges for obstetric care providers. While hematomas such as those affecting the vulva, vulvovaginal region, or paravaginal area are frequently encountered, retroperitoneal hematomas are rare and notably pose a greater risk to the life of the patient. The medical literature contains scant case reports on retroperitoneal hematomas, with no consensus on a definitive treatment approach. Pelvic arterial embolization has emerged as both a sensible and increasingly preferred method for treating these hematomas recently, but its application is contingent upon the patient maintaining hemodynamic stability and the availability of a specialized interventional embolization unit. In our case, we are presenting a very rare case of a 31-year-old primigravida female with a history of in vitro fertilization pregnancy. She delivered a normal vaginal delivery at 31 weeks gestation. Unfortunately, she experienced multiple complications intrapartum, including preeclampsia and placental abruption. These complications increased her risk of developing a broad ligament hematoma.
基金supported by research funds from Khalifa University,No.CIRA-2021-052the Advanced Technology Research Center Program(ASPIRE),No.AARE20-279.
文摘With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation security.Although X-ray baggage monitoring is now standard,manual screening has several limitations,including the propensity for errors,and raises concerns about passenger privacy.To address these drawbacks,researchers have leveraged recent advances in deep learning to design threatsegmentation frameworks.However,these models require extensive training data and labour-intensive dense pixelwise annotations and are finetuned separately for each dataset to account for inter-dataset discrepancies.Hence,this study proposes a semi-supervised contour-driven broad learning system(BLS)for X-ray baggage security threat instance segmentation referred to as C-BLX.The research methodology involved enhancing representation learning and achieving faster training capability to tackle severe occlusion and class imbalance using a single training routine with limited baggage scans.The proposed framework was trained with minimal supervision using resource-efficient image-level labels to localize illegal items in multi-vendor baggage scans.More specifically,the framework generated candidate region segments from the input X-ray scans based on local intensity transition cues,effectively identifying concealed prohibited items without entire baggage scans.The multi-convolutional BLS exploits the rich complementary features extracted from these region segments to predict object categories,including threat and benign classes.The contours corresponding to the region segments predicted as threats were then utilized to yield the segmentation results.The proposed C-BLX system was thoroughly evaluated on three highly imbalanced public datasets and surpassed other competitive approaches in baggage-threat segmentation,yielding 90.04%,78.92%,and 59.44%in terms of mIoU on GDXray,SIXray,and Compass-XP,respectively.Furthermore,the limitations of the proposed system in extracting precise region segments in intricate noisy settings and potential strategies for overcoming them through post-processing techniques were explored(source code will be available at https://github.com/Divs1159/CNN_BLS.)
基金Supported by Jiangsu Agricultural Science and Technology Innovation Fund[CX(13)3084]Jiangsu Province Science and Technology Support Program,China(BE2013352)~~
文摘This paper introduced the definition and importance of combination of sta-ple food. With broad bean nutrition flour as a sample, the preparation of the combi-nation of staple food was also described. In addition, the main nutritional value of broad bean nutrition flour was introduced. Compared with those of other single flours, the nutritional value of broad bean nutrition flour was improved. Moreover, the nutrients in the broad bean nutrition flour would not be destroyed during the processing and preparation of staple food, and the processed steamed bread and raw noodle are more characteristic. The application value and prospects of broad bean nutrition flour, as a combination of staple food, were further discussed.
基金Supported by National Natural Science Foundation of China(30960179)Natural Science Foundation of Yunnan Province(2007A048M)~~
文摘[Objective] The aim was to indentify diseased leaves of broad bean by vibra- tional spectroscopy. [Method] In this paper, broad bean rust, fusarium rhizome rot, broad bean zonate spot, yellow leaf curl virus and normal leaves were studied using Fourier transform infrared spectroscopy combined with chemometrics. [Result] The spectra of the samples were similar, only with minor differences in absorption inten- sity of several peaks. Second derivative analyses show that the significant difference of all samples was in the range of 1 200-700 cm2. The data in the range of 1 200- 700 cm＇ were selected to evaluate correlation coefficients, hierarchical cluster analy- sis （HCA） and principal component analysis （PCA）. Results showed that the correla- tion coefficients are larger than 0.928 not only between the healthy leaves, but also between the same diseased leaves. The values between healthy and diseased leaves, and among diseased leaves, are all declined. HCA and PCA yielded about 73.3% and 82.2% accuracy, respectively. [Conclusion] This study demonstrated that FTIR techniques might be used to detect crop diseases.
基金Supported by Jiangsu Agricultural Science and Technology Innovation Fund[CX(12)3006]Jiangsu Province Science and Technology Support Program,China(BE2013352)Study on Saving the Cost Facility Cultivation Techniques of High-quality,Safe and Efficient in Fresh Faba Bean(HL2014029)~~
文摘Using Tongxian No.2 as material, the effects of different film-covering time, different sowing time and different planting density on the occurrence of freeze injury and yield of fresh broad beans were investigated. The randomized block design was adopted. The results showed that with the delayed film covering, the incidence of mild freeze injury and number of headless seedlings were increased correspondingly, but the yield was increased; with the delayed sowing, the branch number per plant, effective branch number per plant, incidence of mild freeze injury and number of headless seedlings were all reduced, and the broad beans, sowed on September 30 th, obtained the highest yield; planting density showed on effect on the occurrence of freeze injury, and the yield was increased with the increase of planting density. Under the same film-covering time, the incidence of freeze injury was reduced with the delayed sowing time and it showed no changes when planting density was changed, but the yield was increased with the increase of planting density and it was highest when broad bean seeds were sowed on September 30th;under the same sowing time, the incidence of freeze injury was increased with the delayed film-covering time and it showed no changes when planting density was changed, and the yield was increased with the delayed film-covering time and increased planting density; under the same planting density, the incidence of freeze injury was increased with the delayed film-covering time but was reduced with the delayed sowing time, and the yield was increased with the delayed film-covering time and it was highest when the broad bean seeds were sowed on September30 th. Under same film-covering time and sowing time, the total branch number per plant and effective branch number per plant were reduced, but the yield was increased with the increase of planting density; under same film-covering time and planting density, the incidence of freeze injury was reduced with the delayed sowing time, and the yield was highest when broad bean seeds were sowed on September30th; under same sowing time and planting density, the incidence of freeze injury and the yield were all increased with the delayed film-covering time.
基金Supported by National Natural Science Foundation of China(30960179)Program for Innovative Research Team in Science and Technology in University of Yunnan Province~~
文摘Fourier transform infrared （FTIR） spectroscopy was used to study diseased leaves in broad bean. Results showed that the infrared spectra of different broad bean diseased leaves were similar, which were mainly made up of the vibrational absorption bands of protein,lipid and polysaccharide.There were minor differences in-cluding the spectral peak position, peak shape and the absorption intensity in the range of 1 800-1 300 cm-1. There were obvious differences among their second derivative spectra in the range of 1 800-1 300 cm-1. After the procedure of the Fourier self-deconvolution and curve fitting of health bean leaves and broad bean diseased leaves in the range of 1 700-1 500 cm-1, three sub-peaks were obtained at 1 550 cm-1 （protein amide Ⅱ band）, 1 605 cm-1 （lignin） and 1 650 cm-1 （protein amide I band）.The ratios of relative areas of the bands of amide Ⅱ, lignin, and amide I were 38.86%, 28.68% and 32.47% in the spectra of healthy leaves, respec-tively. It was distinguished from the diseased leaves （chocolate spot leaf： 15.42%, 42.98% and 41.61%, ring spot leaf：32.39%, 35.63% and 31.98%, rust leaf： 13.97%, 46.40% and 39.65%, yel owing leaf curl disease leaf： 24.01%,36.55% and 39.44%）. For sub-peak area ratios （A1 563/A1 605, A1 650/A1 605 and A1 563/A1 654）, those of four kinds of diseased leaves were smal er than that of healthy leaves, and there were also differences among four kinds of diseased leaves. The results proved that FTIR combining with curve fitting might be a potential y useful tool for detecting different kinds of broad bean diseases.
文摘[Objective] This study aimed to investigate the influence of Pb2＋ on the growth and development of broad bean roots. [Method] The effects of Pb2＋ solution of different concentrations on root length, color, bending and mitotic index frequency of root tip cells of broad bean were measured and observed. [Result] Pb2＋ at concentration lower than 20 mg/L promoted the growth and development of roots, increased the cell mitotic indexes, but had little influence on root color and bending. When the Pb2＋ concentration was higher than 20 mg/L, the root growth was inhibited; the root color gradually turned deeper; the roots bended, but the cell mitotic index was decreased. [Conclusion] Pb2＋ promoted the growth of broad bean at low concentration but inhibited the growth at high concentration, and the influence was related to Pb2＋ concentration and time.
基金fnancial support from the National Natural Science Foundation of China(No.51971111)。
文摘Perovskite LaCoO_(3)is of great potential in electromagnetic wave absorption considering its outstanding dielectric loss as well as the existing magnetic response with the magnetic doping.However,the dissipation mechanism of the magnetic doping on the microwave absorption is lack of sufficient investigated.In this paper,LaCo_(1-x)Fe_(x)O_(3)(x=0,0.05,0.1,0.15,0.2,0.25,0.3,LCFOs)perovskites with different Fe doping amounts were prepared successfully by the sol-gel method and subsequent heat treatment in the air atmosphere.The structure characterization carried out by the frst-principles calculations shows the effect of Fe doping on the dielectric and magnetic properties of LCFOs and the strong hybridization of Co/Fe-3d with O-2p in the LCFOs system was successfully demonstrated.Particularly,when x=0.1 and the thickness is only 1.95 mm,the LaCo_(0.9)Fe_(0.1)O_(3)exhibits the best microwave absorption performance with the minimum reflection loss(RL)value of about-41 dB.The typical samples achieve a broad effective absorption bandwidth(EAB)of 5.16 GHz(7.92-13.08 GHz),which covers the total X band(8-12 GHz).Considering that,the especial Fe doping perovskite is promising to be a candidate as efficient microwave absorbers.
基金supported by the National Natural Science Foundation of China under Grant No.61901099, 61972076, 61973069 and 62061006the Natural Science Foundation of Hebei Province under Grant No.F2020501037the Natural Science Foundation of Guangxi under Grant No.2018JJA170167
文摘Data sharing in Internet of Vehicles(IoV)makes it possible to provide personalized services for users by service providers in Intelligent Transportation Systems(ITS).As IoV is a multi-user mobile scenario,the reliability and efficiency of data sharing need to be further enhanced.Federated learning allows the server to exchange parameters without obtaining private data from clients so that the privacy is protected.Broad learning system is a novel artificial intelligence technology that can improve training efficiency of data set.Thus,we propose a federated bidirectional connection broad learning scheme(FeBBLS)to solve the data sharing issues.Firstly,we adopt the bidirectional connection broad learning system(BiBLS)model to train data set in vehicular nodes.The server aggregates the collected parameters of BiBLS from vehicular nodes through the federated broad learning system(FedBLS)algorithm.Moreover,we propose a clustering FedBLS algorithm to offload the data sharing into clusters for improving the aggregation capability of the model.Some simulation results show our scheme can improve the efficiency and prediction accuracy of data sharing and protect the privacy of data sharing.
