In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become m...DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become more sophisticated,there is an urgent need for Intrusion Detection Systems(IDS)capable of handling these challenges effectively.Traditional IDS models frequently have difficulties in detecting new or changing attack patterns since they heavily depend on existing characteristics.This paper presents a novel approach for detecting unknown Distributed Denial of Service(DDoS)attacks by integrating Sliced Iterative Normalizing Flows(SINF)into IDS.SINF utilizes the Sliced Wasserstein distance to repeatedly modify probability distributions,enabling better management of high-dimensional data when there are only a few samples available.The unique architecture of SINF ensures efficient density estimation and robust sample generation,enabling IDS to adapt dynamically to emerging threats without relying heavily on predefined signatures or extensive retraining.By incorporating Open-Set Recognition(OSR)techniques,this method improves the system’s ability to detect both known and unknown attacks while maintaining high detection performance.The experimental evaluation on CICIDS2017 and CICDDoS2019 datasets demonstrates that the proposed system achieves an accuracy of 99.85%for known attacks and an F1 score of 99.99%after incremental learning for unknown attacks.The results clearly demonstrate the system’s strong generalization capability across unseen attacks while maintaining the computational efficiency required for real-world deployment.展开更多
A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron micr...A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.展开更多
Sliced boiled chicken is a kind of Chinese food which has a history of more than two hundred years.At the very beginning,it was offered to customers as a kind of fast food.After two centuries’development,it has becom...Sliced boiled chicken is a kind of Chinese food which has a history of more than two hundred years.At the very beginning,it was offered to customers as a kind of fast food.After two centuries’development,it has become a cultural symbol of Guangdong region.In other words,the significance of sliced boiled chicken has transcended the food itself.It is an essential part of Cantonese life.Because it is a dish that is relatively easy to cook,we can see sliced boiled chicken everywhere in Guangdong Province,China.No matter in the city or in the countryside,in upscale restaurants or in fast food restaurants,if you want,you can easily find a place to enjoy the delicacy of sliced boiled chicken.However,most of the people just know to eat sliced boiled chicken.Only a small part of them will notice the history behind this dish.At the same time,though this dish is seen as a cultural symbol,most people just see it as a money making tool which greatly disturbs its development.展开更多
The study was conducted by researchers of the Research Center for Agricultural Energy and Machinery （CAEM） of the Ho Chi Minh City Nong Lam University （NLU） with the objectives of researching on drying ways for ca...The study was conducted by researchers of the Research Center for Agricultural Energy and Machinery （CAEM） of the Ho Chi Minh City Nong Lam University （NLU） with the objectives of researching on drying ways for cassava and of evaluating the adaptability of the reversible-airflow dryers in drying of cassava. The results obtained were as follows： done with thin-layer drying experiments, deep-layer drying experiments in the lab, and conducted drying experiments at the cassava dryer in actual production scale with two capacity sizes of 8 tons/batch and 16 tons/batch, that operates based on principle of reversible-airflow drying （SRA dryers）. By the means of drying experiments, the performance of the SRA dryers such as optimal drying temperature, drying time, drying airflow reversal timing, moisture content uniformity of the sliced cassava mass after finishing drying process, drying cost, etc. was defined, the optimal drying temperature was 70 ~C, the total actual drying time for finishing one batch was 25-28 hours, applicable time for drying airflow reversal was after drying 16 hours since startup, the deviation in moisture content of the cassava mass after drying was just 2%-3%, the drying costs （per one kg of dried cassava） calculated were in turns VND407/kg at the SRA-8 dryer （8 tons/batch）, and VND351/kg at the SRA-16 dryer （16 tons/batch）. Obviously, comparing with the sale price of dry cassava at present, these levels of drying cost are accounting for 7%-10%, which are suitable and acceptable. Thus, investment of the dryers for sliced cassava would be effective and contribute to bring more income for Vietnamese cassava farmers and dryer end-users.展开更多
In this study, the sliced functional time series (SFTS) model is applied to the Global, Northern and Southern temperature anomalies. We obtained the combined land-surface air and sea-surface water temperature from God...In this study, the sliced functional time series (SFTS) model is applied to the Global, Northern and Southern temperature anomalies. We obtained the combined land-surface air and sea-surface water temperature from Goddard Institute for Space Studies (GISS), NASA. The data are available for Global mean, Northern Hemisphere mean and Southern Hemisphere means (monthly, quarterly and annual) since 1880 to present (updated through March 2019). We analyze the global surface temperature change, compare alternative analyses, and address the questions about the reality of global warming. We detected the outliers during the last century not only in global temperature series but also in northern and southern hemisphere series. The forecasts for the next twenty years are obtained using SFTS models. These forecasts are compared with ARIMA, Random Walk with drift and Exponential Smoothing State Space (ETS) models. The comparison is made on the basis of root mean square error (RMSE), mean absolute percentage error (MAPE) and the length of prediction intervals.展开更多
Bamboo is a plant favored by Chinese people. Rigid, tall, straight and channing, it is honored along with cymbidium, plum blossom and chrysanthemum. Bamboo has a close relationship with people’s daily life. The poet ...Bamboo is a plant favored by Chinese people. Rigid, tall, straight and channing, it is honored along with cymbidium, plum blossom and chrysanthemum. Bamboo has a close relationship with people’s daily life. The poet Su Dongpo wrote the famous poem "Would rather have food without meats than live in a non-bamboo house" in the Song Dynasty. Earth Brand bamboo sliced展开更多
For functional data,the most popular dimension reduction methods are functional sliced inverse regression(FSIR)and functional sliced average variance estimation(FSAVE).Both FSIR and FSAVE methods are based on the slic...For functional data,the most popular dimension reduction methods are functional sliced inverse regression(FSIR)and functional sliced average variance estimation(FSAVE).Both FSIR and FSAVE methods are based on the slice approach to estimate the conditional expectation E[x(t)|y].While sliced-based methods are effective for scalar responses,they often perform poorly or even lead to failure for multivariate responses and small sample sizes as the so-called“curse of dimensionality”.To avoid this problem,this study proposes a projective resampling method that first projects the multivariate response into a scalar-response and then uses SDR method for the univariate response to estimate the effective dimension reduction space(e.d.r space).The proposed projective resampling method is insensitive to the number of slices and the dimensionality of the response variable.In theory,the proposed resampling method can fully recover the effective dimension reduction space.Furthermore,this study investigates the performance of the proposed method through simulation studies and one real data analysis and compares the proposed method with other methods.展开更多
Federated learning has become a popular tool in the big data era nowadays.It trains a centralized model based on data from different clients while keeping data decentralized.In this paper,we propose a federated sparse...Federated learning has become a popular tool in the big data era nowadays.It trains a centralized model based on data from different clients while keeping data decentralized.In this paper,we propose a federated sparse sliced inverse regression algorithm for the first time.Our method can simultaneously estimate the central dimension reduction subspace and perform variable selection in a federated setting.We transform this federated high-dimensional sparse sliced inverse regression problem into a convex optimization problem by constructing the covariance matrix safely and losslessly.We then use a linearized alternating direction method of multipliers algorithm to estimate the central subspace.We also give approaches of Bayesian information criterion and holdout validation to ascertain the dimension of the central subspace and the hyperparameter of the algorithm.We establish an upper bound of the statistical error rate of our estimator under the heterogeneous setting.We demonstrate the effectiveness of our method through simulations and real world applications.展开更多
Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in...Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment.This paper proposes a novel method for estimating target time delay using multi-bright spot echoes,assuming the target’s size and depth are known.Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise,the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes.Using the highlighting model theory and the target size information,an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles.Aiming to accurately estimate the target’s time delay,waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays.Simulation results show that,compared to the conventional matched filter,the proposed algorithm reduces the relative error by 65.9%-91.5%at a signal-to noise ratio of-25 dB,and by 66.7%-88.9%at a signal-to-reverberation ratio of−10 dB.This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.展开更多
Supercapacitor electrodes with porous structure based on renewable,eco-friendly and cost-effective materials have caused extensive concern in energy storage fields.Sliced bread,the common food ingredient,mainly contai...Supercapacitor electrodes with porous structure based on renewable,eco-friendly and cost-effective materials have caused extensive concern in energy storage fields.Sliced bread,the common food ingredient,mainly containing glucose polymers,can be a promising candidate to fabricate porous supercapacitor electrodes.Highly porous carbon aerogels by using sliced bread as the raw material were synthesized through a carefully controlled aerogel carbonization-activation process.Interestingly,the specific surface area and the pore size distribution of the porous carbon were controlled by the activation temperature,which result in the varied performance of the carbon aerogel as a supercapacitor.Electrochemical investigation measurements revealed that the hierarchical porous carbon aerogel shows an excellent capacitor behavior for construction of a symmetric supercapacitor,which demonstrated a high specific capacitance of 229 F·g-1 at discharge current of 0.2 A·g-1.In addition,the fabricated supercapacitor displayed excellent capacitance retention of 95.5% over 5000 cycles.展开更多
This paper concerns the dimension reduction in regression for large data set. The authors introduce a new method based on the sliced inverse regression approach, cMled cluster-based regularized sliced inverse regressi...This paper concerns the dimension reduction in regression for large data set. The authors introduce a new method based on the sliced inverse regression approach, cMled cluster-based regularized sliced inverse regression. The proposed method not only keeps the merit of considering both response and predictors＇ information, but also enhances the capability of handling highly correlated variables. It is justified under certain linearity conditions. An empirical application on a macroeconomic data set shows that the proposed method has outperformed the dynamic factor model and other shrinkage methods.展开更多
An experimental investigation on the fluidization and drying characteristics of sliced food products in a centrifugal fluidized bed dryer was carried out. The rotating speed ranges from 300 rpm to 500 rpm.Sliced potat...An experimental investigation on the fluidization and drying characteristics of sliced food products in a centrifugal fluidized bed dryer was carried out. The rotating speed ranges from 300 rpm to 500 rpm.Sliced potato and radish were used as the testing materials. The results show that the sliced materials can be fluidised well in the centrifugal fluidized bed. The fiuidized curve has a maximum value and the critical fiuidised velocities Vary with the type of the test material, its shape and dimension as well as operating parameters. The sliced food materials can be dried very well and fast in the ceotrifugal fiuidised bed with a large productivity. The factors that influence the drying process were examined and discussed. The final shape and inner structure of the dried products were observed.The water recovery characteristics of the dried products were also investigated.展开更多
A spectrally sliced heterodyne coherent receiver(SHCR)employing four balanced photodetectors and analog-to-digital converters with half of the signal bandwidth is proposed to complete the signal reception and field re...A spectrally sliced heterodyne coherent receiver(SHCR)employing four balanced photodetectors and analog-to-digital converters with half of the signal bandwidth is proposed to complete the signal reception and field recovery.We first numerically characterize the performance of SHCR compared with an intradyne coherent receiver and then validate the principle of the SHCR in a proof-of-concept single-polarization experiment.A 60 GBaud 16-quadrature amplitude modulation transmission is experimentally demonstrated over 80 km standard single-mode fiber with a bit-error-rate of 8.5×10^(-4) below the 7%hard-decision forward error correction threshold of 3.8×10^(-3).The SHCR offers a low-cost,hybrid-free,and channel-skew-tolerant candidate for data center interconnects.展开更多
The dimension reduction is helpful and often necessary in exploring the nonparametric regression structure.In this area,Sliced inverse regression (SIR) is a promising tool to estimate the central dimension reduction (...The dimension reduction is helpful and often necessary in exploring the nonparametric regression structure.In this area,Sliced inverse regression (SIR) is a promising tool to estimate the central dimension reduction (CDR) space.To estimate the kernel matrix of the SIR,we herein suggest the spline approximation using the least squares regression.The heteroscedasticity can be incorporated well by introducing an appropriate weight function.The root-n asymptotic normality can be achieved for a wide range choice of knots.This is essentially analogous to the kernel estimation.Moreover, we also propose a modified Bayes information criterion (BIC) based on the eigenvalues of the SIR matrix.This modified BIC can be applied to any form of the SIR and other related methods.The methodology and some of the practical issues are illustrated through the horse mussel data.Empirical studies evidence the performance of our proposed spline approximation by comparison of the existing estimators.展开更多
Tensor data have been widely used in many fields,e.g.,modern biomedical imaging,chemometrics,and economics,but often suffer from some common issues as in high dimensional statistics.How to find their low-dimensional l...Tensor data have been widely used in many fields,e.g.,modern biomedical imaging,chemometrics,and economics,but often suffer from some common issues as in high dimensional statistics.How to find their low-dimensional latent structure has been of great interest for statisticians.To this end,we develop two efficient tensor sufficient dimension reduction methods based on the sliced average variance estimation(SAVE)to estimate the corresponding dimension reduction subspaces.The first one,entitled tensor sliced average variance estimation(TSAVE),works well when the response is discrete or takes finite values,but is not■consistent for continuous response;the second one,named bias-correction tensor sliced average variance estimation(CTSAVE),is a de-biased version of the TSAVE method.The asymptotic properties of both methods are derived under mild conditions.Simulations and real data examples are also provided to show the superiority of the efficiency of the developed methods.展开更多
Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resou...Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures.Nonetheless,sustaining elevated Quality of Service(QoS)in dynamic,resource-limited systems poses significant hurdles.This study introduces an innovative packet-based proactive end-to-end(ETE)resource management system that facilitates network slicing with improved resilience and proactivity.To get around the drawbacks of conventional reactive systems,we develop a cost-efficient slice provisioning architecture that takes into account limits on radio,processing,and transmission resources.The optimization issue is non-convex,NP-hard,and requires online resolution in a dynamic setting.We offer a hybrid solution that integrates an advanced Deep Reinforcement Learning(DRL)methodology with an Improved Manta-Ray Foraging Optimization(ImpMRFO)algorithm.The ImpMRFO utilizes Chebyshev chaotic mapping for the formation of a varied starting population and incorporates Lévy flight-based stochastic movement to avert premature convergence,hence facilitating improved exploration-exploitation trade-offs.The DRL model perpetually acquires optimum provisioning strategies via agent-environment interactions,whereas the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.The DRL model perpetually acquires optimum provisioning methods via agent-environment interactions,while the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.Experimental findings reveal that the proactive ETE system outperforms DRL models and non-resilient provisioning techniques.Our technique increases PSSRr,decreases average latency,and optimizes resource use.These results demonstrate that the hybrid architecture for robust,real-time,and scalable slice management in future 6G networks is feasible.展开更多
A decellularized extracellular matrix(dECM)constitutes a pivotal biomaterial created by decellularizing the natural extracellular matrix(ECM).This material serves as a supportive medium for intricate cellular interact...A decellularized extracellular matrix(dECM)constitutes a pivotal biomaterial created by decellularizing the natural extracellular matrix(ECM).This material serves as a supportive medium for intricate cellular interactions,fostering cell growth,differentiation,and organization.However,challenges persist in decellularization,necessitating a balance between preserving the ECM structural integrity and achieving effective cellular removal.An approach to enhancing decellularization involves pre-eliminating unnecessary tissues and effectively reducing final DNA levels to lower than 50 ng/mg ECM on preprocessed tissues.Although this strategic step augments decellularization efficiency,the current manual execution method depends on the operator’s skill.To address this limitation,this study proposed an automated raw tissue slicing system that does not require tissue preparation for slicing.Through carefully controlled tissue applanation pressure and oscillatory incisions with optimized parameters,the system achieved a precision within±10µm in obtaining submillimeter-scale tissue slices of the porcine cornea while avoiding significant microscopic complications in the tissue structure,as observed by tissue histology.These findings suggested the system’s capability to streamline and automate preliminary tissue slicing operations.The efficacy of this approach for decellularization was validated by processing porcine corneas using the proposed system and subsequently decellularizing the processed tissues.DNA level analysis revealed that sliced,subdivided tissues created by this system could expedite DNA reduction even at the initial steps of decellularization,enhancing the overall decellularization procedure.展开更多
Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-toler...Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.展开更多
Fusarium graminearum(F.graminearum)is a severe phytopathogen threatening agriculture production and food security.Paeonol,serves as a plant-derived natural component,is a promising antifungal agent.At a concentration ...Fusarium graminearum(F.graminearum)is a severe phytopathogen threatening agriculture production and food security.Paeonol,serves as a plant-derived natural component,is a promising antifungal agent.At a concentration of 0.3125 mg/mL,paeonol was adequate to fully inhibit the growth of F.graminearum mycelia within 3 days.Fourier-Transform Infrared Spectroscopy(FT-IR)analysis showed that paeonol had no impact on the outer surface of F.graminearum cell walls.While propidium iodide staining,extracellular conductivity,and pH value measurements demonstrated that paeonol disrupted the cell membrane.Furthermore,lipid oxidation and osmotic stress responses were observed in F.graminearum treated with paeonol,resulting in a 47.23%rise in malondialdehyde(MDA)levels and a 515.43%increase in glycerol levels.Moreover,on the 7th day after exposure to paeonol treatment,the deoxynivalenol(DON)level was significantly reduced,measuring only onefifth of that in the control group.Finally,paeonol was shown to inhibit F.graminearum on wheat grains and steamed bread slices.These results,for the first time,revealed the inhibitory mode of action of paeonol against F.graminearum as reflected by disruption of cell membrane integrity,induction of lipid oxidation and osmotic pressure,as well as DON biosynthesis.Furthermore,this study provided scientific evidence for the potential applications of paeonol in agriculture and food industry.展开更多
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
基金supported by the National Science and Technology Council,Taiwan with grant numbers NSTC 112-2221-E-992-045,112-2221-E-992-057-MY3,and 112-2622-8-992-009-TD1.
文摘DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become more sophisticated,there is an urgent need for Intrusion Detection Systems(IDS)capable of handling these challenges effectively.Traditional IDS models frequently have difficulties in detecting new or changing attack patterns since they heavily depend on existing characteristics.This paper presents a novel approach for detecting unknown Distributed Denial of Service(DDoS)attacks by integrating Sliced Iterative Normalizing Flows(SINF)into IDS.SINF utilizes the Sliced Wasserstein distance to repeatedly modify probability distributions,enabling better management of high-dimensional data when there are only a few samples available.The unique architecture of SINF ensures efficient density estimation and robust sample generation,enabling IDS to adapt dynamically to emerging threats without relying heavily on predefined signatures or extensive retraining.By incorporating Open-Set Recognition(OSR)techniques,this method improves the system’s ability to detect both known and unknown attacks while maintaining high detection performance.The experimental evaluation on CICIDS2017 and CICDDoS2019 datasets demonstrates that the proposed system achieves an accuracy of 99.85%for known attacks and an F1 score of 99.99%after incremental learning for unknown attacks.The results clearly demonstrate the system’s strong generalization capability across unseen attacks while maintaining the computational efficiency required for real-world deployment.
文摘A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.
文摘Sliced boiled chicken is a kind of Chinese food which has a history of more than two hundred years.At the very beginning,it was offered to customers as a kind of fast food.After two centuries’development,it has become a cultural symbol of Guangdong region.In other words,the significance of sliced boiled chicken has transcended the food itself.It is an essential part of Cantonese life.Because it is a dish that is relatively easy to cook,we can see sliced boiled chicken everywhere in Guangdong Province,China.No matter in the city or in the countryside,in upscale restaurants or in fast food restaurants,if you want,you can easily find a place to enjoy the delicacy of sliced boiled chicken.However,most of the people just know to eat sliced boiled chicken.Only a small part of them will notice the history behind this dish.At the same time,though this dish is seen as a cultural symbol,most people just see it as a money making tool which greatly disturbs its development.
文摘The study was conducted by researchers of the Research Center for Agricultural Energy and Machinery （CAEM） of the Ho Chi Minh City Nong Lam University （NLU） with the objectives of researching on drying ways for cassava and of evaluating the adaptability of the reversible-airflow dryers in drying of cassava. The results obtained were as follows： done with thin-layer drying experiments, deep-layer drying experiments in the lab, and conducted drying experiments at the cassava dryer in actual production scale with two capacity sizes of 8 tons/batch and 16 tons/batch, that operates based on principle of reversible-airflow drying （SRA dryers）. By the means of drying experiments, the performance of the SRA dryers such as optimal drying temperature, drying time, drying airflow reversal timing, moisture content uniformity of the sliced cassava mass after finishing drying process, drying cost, etc. was defined, the optimal drying temperature was 70 ~C, the total actual drying time for finishing one batch was 25-28 hours, applicable time for drying airflow reversal was after drying 16 hours since startup, the deviation in moisture content of the cassava mass after drying was just 2%-3%, the drying costs （per one kg of dried cassava） calculated were in turns VND407/kg at the SRA-8 dryer （8 tons/batch）, and VND351/kg at the SRA-16 dryer （16 tons/batch）. Obviously, comparing with the sale price of dry cassava at present, these levels of drying cost are accounting for 7%-10%, which are suitable and acceptable. Thus, investment of the dryers for sliced cassava would be effective and contribute to bring more income for Vietnamese cassava farmers and dryer end-users.
文摘In this study, the sliced functional time series (SFTS) model is applied to the Global, Northern and Southern temperature anomalies. We obtained the combined land-surface air and sea-surface water temperature from Goddard Institute for Space Studies (GISS), NASA. The data are available for Global mean, Northern Hemisphere mean and Southern Hemisphere means (monthly, quarterly and annual) since 1880 to present (updated through March 2019). We analyze the global surface temperature change, compare alternative analyses, and address the questions about the reality of global warming. We detected the outliers during the last century not only in global temperature series but also in northern and southern hemisphere series. The forecasts for the next twenty years are obtained using SFTS models. These forecasts are compared with ARIMA, Random Walk with drift and Exponential Smoothing State Space (ETS) models. The comparison is made on the basis of root mean square error (RMSE), mean absolute percentage error (MAPE) and the length of prediction intervals.
文摘Bamboo is a plant favored by Chinese people. Rigid, tall, straight and channing, it is honored along with cymbidium, plum blossom and chrysanthemum. Bamboo has a close relationship with people’s daily life. The poet Su Dongpo wrote the famous poem "Would rather have food without meats than live in a non-bamboo house" in the Song Dynasty. Earth Brand bamboo sliced
基金supported by the National Social Science Foundation of China under Grant No.20BTJ041。
文摘For functional data,the most popular dimension reduction methods are functional sliced inverse regression(FSIR)and functional sliced average variance estimation(FSAVE).Both FSIR and FSAVE methods are based on the slice approach to estimate the conditional expectation E[x(t)|y].While sliced-based methods are effective for scalar responses,they often perform poorly or even lead to failure for multivariate responses and small sample sizes as the so-called“curse of dimensionality”.To avoid this problem,this study proposes a projective resampling method that first projects the multivariate response into a scalar-response and then uses SDR method for the univariate response to estimate the effective dimension reduction space(e.d.r space).The proposed projective resampling method is insensitive to the number of slices and the dimensionality of the response variable.In theory,the proposed resampling method can fully recover the effective dimension reduction space.Furthermore,this study investigates the performance of the proposed method through simulation studies and one real data analysis and compares the proposed method with other methods.
文摘Federated learning has become a popular tool in the big data era nowadays.It trains a centralized model based on data from different clients while keeping data decentralized.In this paper,we propose a federated sparse sliced inverse regression algorithm for the first time.Our method can simultaneously estimate the central dimension reduction subspace and perform variable selection in a federated setting.We transform this federated high-dimensional sparse sliced inverse regression problem into a convex optimization problem by constructing the covariance matrix safely and losslessly.We then use a linearized alternating direction method of multipliers algorithm to estimate the central subspace.We also give approaches of Bayesian information criterion and holdout validation to ascertain the dimension of the central subspace and the hyperparameter of the algorithm.We establish an upper bound of the statistical error rate of our estimator under the heterogeneous setting.We demonstrate the effectiveness of our method through simulations and real world applications.
基金Supported by the State Key Laboratory of Acoustics and Marine Information Chinese Academy of Sciences(SKL A202507).
文摘Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment.This paper proposes a novel method for estimating target time delay using multi-bright spot echoes,assuming the target’s size and depth are known.Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise,the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes.Using the highlighting model theory and the target size information,an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles.Aiming to accurately estimate the target’s time delay,waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays.Simulation results show that,compared to the conventional matched filter,the proposed algorithm reduces the relative error by 65.9%-91.5%at a signal-to noise ratio of-25 dB,and by 66.7%-88.9%at a signal-to-reverberation ratio of−10 dB.This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.
文摘Supercapacitor electrodes with porous structure based on renewable,eco-friendly and cost-effective materials have caused extensive concern in energy storage fields.Sliced bread,the common food ingredient,mainly containing glucose polymers,can be a promising candidate to fabricate porous supercapacitor electrodes.Highly porous carbon aerogels by using sliced bread as the raw material were synthesized through a carefully controlled aerogel carbonization-activation process.Interestingly,the specific surface area and the pore size distribution of the porous carbon were controlled by the activation temperature,which result in the varied performance of the carbon aerogel as a supercapacitor.Electrochemical investigation measurements revealed that the hierarchical porous carbon aerogel shows an excellent capacitor behavior for construction of a symmetric supercapacitor,which demonstrated a high specific capacitance of 229 F·g-1 at discharge current of 0.2 A·g-1.In addition,the fabricated supercapacitor displayed excellent capacitance retention of 95.5% over 5000 cycles.
基金supported by the National Science Foundation of China under Grant No.71101030the Program for Innovative Research Team in UIBE under Grant No.CXTD4-01
文摘This paper concerns the dimension reduction in regression for large data set. The authors introduce a new method based on the sliced inverse regression approach, cMled cluster-based regularized sliced inverse regression. The proposed method not only keeps the merit of considering both response and predictors＇ information, but also enhances the capability of handling highly correlated variables. It is justified under certain linearity conditions. An empirical application on a macroeconomic data set shows that the proposed method has outperformed the dynamic factor model and other shrinkage methods.
文摘An experimental investigation on the fluidization and drying characteristics of sliced food products in a centrifugal fluidized bed dryer was carried out. The rotating speed ranges from 300 rpm to 500 rpm.Sliced potato and radish were used as the testing materials. The results show that the sliced materials can be fluidised well in the centrifugal fluidized bed. The fiuidized curve has a maximum value and the critical fiuidised velocities Vary with the type of the test material, its shape and dimension as well as operating parameters. The sliced food materials can be dried very well and fast in the ceotrifugal fiuidised bed with a large productivity. The factors that influence the drying process were examined and discussed. The final shape and inner structure of the dried products were observed.The water recovery characteristics of the dried products were also investigated.
基金supported by the National Natural Science Foundation of China(No.62001287)National Key R&D Program of China(No.2018YFB1800904)。
文摘A spectrally sliced heterodyne coherent receiver(SHCR)employing four balanced photodetectors and analog-to-digital converters with half of the signal bandwidth is proposed to complete the signal reception and field recovery.We first numerically characterize the performance of SHCR compared with an intradyne coherent receiver and then validate the principle of the SHCR in a proof-of-concept single-polarization experiment.A 60 GBaud 16-quadrature amplitude modulation transmission is experimentally demonstrated over 80 km standard single-mode fiber with a bit-error-rate of 8.5×10^(-4) below the 7%hard-decision forward error correction threshold of 3.8×10^(-3).The SHCR offers a low-cost,hybrid-free,and channel-skew-tolerant candidate for data center interconnects.
基金This work was supported by the special fund (2006) for selecting and training young teachers of universities in Shanghai (Grant No.79001320)an FRG grant (FRG/06-07/I-06) from Hong Kong Baptist University,Chinaa grant (HKU 7058/05P) from the Research Grants Council of Hong Kong,China
文摘The dimension reduction is helpful and often necessary in exploring the nonparametric regression structure.In this area,Sliced inverse regression (SIR) is a promising tool to estimate the central dimension reduction (CDR) space.To estimate the kernel matrix of the SIR,we herein suggest the spline approximation using the least squares regression.The heteroscedasticity can be incorporated well by introducing an appropriate weight function.The root-n asymptotic normality can be achieved for a wide range choice of knots.This is essentially analogous to the kernel estimation.Moreover, we also propose a modified Bayes information criterion (BIC) based on the eigenvalues of the SIR matrix.This modified BIC can be applied to any form of the SIR and other related methods.The methodology and some of the practical issues are illustrated through the horse mussel data.Empirical studies evidence the performance of our proposed spline approximation by comparison of the existing estimators.
基金supported by the National Natural Science Foundation of China(Grant NO.12301377,11971208,92358303)the National Social Science Foundation of China(Grant NO.21&ZD152)+4 种基金the Outstanding Youth Fund Project of the Science and Technology Department of Jiangxi Province(Grant No.20224ACB211003)Jiangxi Provincial National Natural Science Foundation(Grant NO.20232BAB211014)the Science and technology research project of the Education Department of Jiangxi Province(Grant No.GJJ210535)the opening funding of Key Laboratory of Data Science in Finance and Economicsthe innovation team funding of Digital Economy and Industrial Development,Jiangxi University of Finance and Economics。
文摘Tensor data have been widely used in many fields,e.g.,modern biomedical imaging,chemometrics,and economics,but often suffer from some common issues as in high dimensional statistics.How to find their low-dimensional latent structure has been of great interest for statisticians.To this end,we develop two efficient tensor sufficient dimension reduction methods based on the sliced average variance estimation(SAVE)to estimate the corresponding dimension reduction subspaces.The first one,entitled tensor sliced average variance estimation(TSAVE),works well when the response is discrete or takes finite values,but is not■consistent for continuous response;the second one,named bias-correction tensor sliced average variance estimation(CTSAVE),is a de-biased version of the TSAVE method.The asymptotic properties of both methods are derived under mild conditions.Simulations and real data examples are also provided to show the superiority of the efficiency of the developed methods.
文摘Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures.Nonetheless,sustaining elevated Quality of Service(QoS)in dynamic,resource-limited systems poses significant hurdles.This study introduces an innovative packet-based proactive end-to-end(ETE)resource management system that facilitates network slicing with improved resilience and proactivity.To get around the drawbacks of conventional reactive systems,we develop a cost-efficient slice provisioning architecture that takes into account limits on radio,processing,and transmission resources.The optimization issue is non-convex,NP-hard,and requires online resolution in a dynamic setting.We offer a hybrid solution that integrates an advanced Deep Reinforcement Learning(DRL)methodology with an Improved Manta-Ray Foraging Optimization(ImpMRFO)algorithm.The ImpMRFO utilizes Chebyshev chaotic mapping for the formation of a varied starting population and incorporates Lévy flight-based stochastic movement to avert premature convergence,hence facilitating improved exploration-exploitation trade-offs.The DRL model perpetually acquires optimum provisioning strategies via agent-environment interactions,whereas the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.The DRL model perpetually acquires optimum provisioning methods via agent-environment interactions,while the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.Experimental findings reveal that the proactive ETE system outperforms DRL models and non-resilient provisioning techniques.Our technique increases PSSRr,decreases average latency,and optimizes resource use.These results demonstrate that the hybrid architecture for robust,real-time,and scalable slice management in future 6G networks is feasible.
基金supported by the Alchemist Project 1415180884(No.20012378,Development of Meta Soft Organ Module Manufacturing Technology without Immunity Rejection and Module Assembly Robot System)funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea)the Technology Development Program(No.S3318933)funded by the Ministry of SMEs and Startups(MSS,Republic of Korea).
文摘A decellularized extracellular matrix(dECM)constitutes a pivotal biomaterial created by decellularizing the natural extracellular matrix(ECM).This material serves as a supportive medium for intricate cellular interactions,fostering cell growth,differentiation,and organization.However,challenges persist in decellularization,necessitating a balance between preserving the ECM structural integrity and achieving effective cellular removal.An approach to enhancing decellularization involves pre-eliminating unnecessary tissues and effectively reducing final DNA levels to lower than 50 ng/mg ECM on preprocessed tissues.Although this strategic step augments decellularization efficiency,the current manual execution method depends on the operator’s skill.To address this limitation,this study proposed an automated raw tissue slicing system that does not require tissue preparation for slicing.Through carefully controlled tissue applanation pressure and oscillatory incisions with optimized parameters,the system achieved a precision within±10µm in obtaining submillimeter-scale tissue slices of the porcine cornea while avoiding significant microscopic complications in the tissue structure,as observed by tissue histology.These findings suggested the system’s capability to streamline and automate preliminary tissue slicing operations.The efficacy of this approach for decellularization was validated by processing porcine corneas using the proposed system and subsequently decellularizing the processed tissues.DNA level analysis revealed that sliced,subdivided tissues created by this system could expedite DNA reduction even at the initial steps of decellularization,enhancing the overall decellularization procedure.
基金supported by the Liaoning Revitalization Talents Program(XLYC2203148)
文摘Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.
基金support from the Grain,Oil,and Food Engineering Technology Research Center of the State Grain and Reserves Administration/Key Laboratory of Henan Province(GO202206)the Cultivation Program for Young Backbone Teachers at Henan University of Technology+3 种基金the Key R&D Projects in Henan Province(231111113300)Double First-Class Discipline Construction Program of Henan University of Technology(0517-24410014)National Key Research and Development Program of China(2023YFF1104600)Joint Research Fund for science and technology R&D Projects of Henan Province(225200810066).
文摘Fusarium graminearum(F.graminearum)is a severe phytopathogen threatening agriculture production and food security.Paeonol,serves as a plant-derived natural component,is a promising antifungal agent.At a concentration of 0.3125 mg/mL,paeonol was adequate to fully inhibit the growth of F.graminearum mycelia within 3 days.Fourier-Transform Infrared Spectroscopy(FT-IR)analysis showed that paeonol had no impact on the outer surface of F.graminearum cell walls.While propidium iodide staining,extracellular conductivity,and pH value measurements demonstrated that paeonol disrupted the cell membrane.Furthermore,lipid oxidation and osmotic stress responses were observed in F.graminearum treated with paeonol,resulting in a 47.23%rise in malondialdehyde(MDA)levels and a 515.43%increase in glycerol levels.Moreover,on the 7th day after exposure to paeonol treatment,the deoxynivalenol(DON)level was significantly reduced,measuring only onefifth of that in the control group.Finally,paeonol was shown to inhibit F.graminearum on wheat grains and steamed bread slices.These results,for the first time,revealed the inhibitory mode of action of paeonol against F.graminearum as reflected by disruption of cell membrane integrity,induction of lipid oxidation and osmotic pressure,as well as DON biosynthesis.Furthermore,this study provided scientific evidence for the potential applications of paeonol in agriculture and food industry.
