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Cancer-associated cachexia (CAC) is a critical contributor to pancreatic ductal adenocarcinoma (PDAC) mortality. Thus, there is an urgent need for new strategies to mitigate PDAC-associated cachexia; and the exploration of dietary interventions is a critical component. We previously observed that a ketogenic diet (KD) combined with gemcitabine enhances overall survival in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. In this study, we investigated the effect and cellular mechanisms of a KD in combination with gemcitabine on the maintenance of skeletal muscle mass in KPC mice. For this purpose, male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD), a KD, a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. We observed that a KD or a KG-mitigated muscle strength declined over time and presented higher gastrocnemius weights compared CD-fed mice. Mechanistically, we observed sex-dependent effects of KG treatment, including the inhibition of autophagy, and increased phosphorylation levels of eIF2α in KG-treated KPC mice when compared to CG-treated mice. Our data suggest that a KG results in preservation of skeletal muscle mass. Additional research is warranted to explore whether this diet-treatment combination can be clinically effective in combating CAC in PDAC patients.

Supplementary Table S1. Experimental diets composition. Supplementary Figure S1. A ketogenic diet plus gemcitabine extends median overall survival in KPC mice. Supplementary Figure S2. Histopathological analysis of necrosis (C) in pancreatic tumor isolated from female and male KPC mice treated with CD, KD, CG or KD. Supplementary Figure S3. Histopathological analysis of fibrosis in pancreatic tumor isolated from female and male KPC mice treated with CD, KD, CG or KD. Supplementary Figure S4. IL-10, IFN-γ and MCP-1 levels were measured in serum obtained from female and male KPC mice fed a CD, KD, CG or KG at euthanasia. Supplementary Figure S5. Effect of a ketogenic diet plus gemcitabine on AKT and ERK activation at endpoint. Supplementary Figure S6. Effect of a ketogenic diet plus gemcitabine on glycolytic pathway in pancreatic tumors. Supplementary Figure S7. A ketogenic diet plus gemcitabine affects the gut microbiota. Supplementary Figure S8. A ketogenic diet affects the gut microbiota.

Pancreatic ductal adenocarcinoma (PDAC) continues to be a major health problem. A ketogenic diet (KD), characterized by a very low carbohydrate and high fat composition, has gained attention for its antitumor potential. We evaluated the effect and mechanisms of feeding a strict KD alone or in combination with gemcitabine in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. For this purpose, both male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD; %kcal: 65% carb, 15% protein, 20% fat), a KD (%kcal: 1% carb, 15% protein, 84% fat), a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. Mice fed a KD alone or in combination with gemcitabine showed significantly increased blood β-hydroxybutyrate levels compared with mice fed a CD or CG. KPC mice fed a KG had a significant increase in overall median survival compared with KPC mice fed a CD (increased overall median survival by 42%). Interestingly, when the data were disaggregated by sex, the effect of a KG was significant in female KPC mice (60% increase in median overall survival), but not in male KPC mice (28% increase in median overall survival). Mechanistically, the enhanced survival response to a KD combined with gemcitabine was multifactorial, including inhibition of ERK and AKT pathways, regulation of fatty acid metabolism and the modulation of the gut microbiota. In summary, a KD in combination with gemcitabine appears beneficial as a treatment strategy in PDAC in KPC mice, deserving further clinical evaluation.Significance:This article is the first preclinical study to comprehensively evaluate the effect of a KD alongside chemotherapy using a standard autochthonous genetically modified mouse model (in both male and female KPC mice).

Pancreatic ductal adenocarcinoma (PDAC) continues to be a major health problem. A ketogenic diet (KD), characterized by a very low carbohydrate and high fat composition, has gained attention for its antitumor potential. We evaluated the effect and mechanisms of feeding a strict KD alone or in combination with gemcitabine in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. For this purpose, both male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD; %kcal: 65% carb, 15% protein, 20% fat), a KD (%kcal: 1% carb, 15% protein, 84% fat), a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. Mice fed a KD alone or in combination with gemcitabine showed significantly increased blood β-hydroxybutyrate levels compared with mice fed a CD or CG. KPC mice fed a KG had a significant increase in overall median survival compared with KPC mice fed a CD (increased overall median survival by 42%). Interestingly, when the data were disaggregated by sex, the effect of a KG was significant in female KPC mice (60% increase in median overall survival), but not in male KPC mice (28% increase in median overall survival). Mechanistically, the enhanced survival response to a KD combined with gemcitabine was multifactorial, including inhibition of ERK and AKT pathways, regulation of fatty acid metabolism and the modulation of the gut microbiota. In summary, a KD in combination with gemcitabine appears beneficial as a treatment strategy in PDAC in KPC mice, deserving further clinical evaluation. Significance: This article is the first preclinical study to comprehensively evaluate the effect of a KD alongside chemotherapy using a standard autochthonous genetically modified mouse model (in both male and female KPC mice).

Temperate phages (active prophages induced from bacteria) help control pathogenicity, modulate community structure, and maintain gut homeostasis. Complete phage genome sequences are indispensable for understanding phage biology. Traditional plaque techniques are inapplicable to temperate phages due to their lysogenicity, curbing their identification and characterization. Existing bioinformatics tools for prophage prediction usually fail to detect accurate and complete temperate phage genomes. This study proposes a novel computational temperate phage detection method (TemPhD) mining both the integrated active prophages and their spontaneously induced forms (temperate phages) from next-generation sequencing raw data. Applying the method to the available dataset resulted in 192 326 complete temperate phage genomes with different host species, expanding the existing number of complete temperate phage genomes by more than 100-fold. The wet-lab experiments demonstrated that TemPhD can accurately determine the complete genome sequences of the temperate phages, with exact flanking sites, outperforming other state-of-the-art prophage prediction methods. Our analysis indicates that temperate phages are likely to function in the microbial evolution by (i) cross-infecting different bacterial host species; (ii) transferring antibiotic resistance and virulence genes and (iii) interacting with hosts through restriction-modification and CRISPR/anti-CRISPR systems. This work provides a comprehensively complete temperate phage genome database and relevant information, which can serve as a valuable resource for phage research.

Laser-induced breakdown spectroscopy (LIBS) experiments were carried out with an ammonium dinitramide (ADN)-based propellant to measure its distribution, that is the mixture ratio, in an inert atmosphere. A heating sampler was developed to produce a premixed sample with a known mixture ratio and this was connected to a chamber that had been designed to simulate the space propulsion environment. Determining the time window for the acquisition and saturation threshold of LIBS were the main motivations to investigate the effective lifetimes of atomic spectral lines and the effect of laser energy on the emission ratio. From the spectroscopic analysis, it was found that the ratio of the intensities of H (656.3 nm), O (777 nm) and N (746.8 nm) over Ar (738.4 nm) increased monotonically with the mixture ratio in the range of 0–0.06. A series of propellant/Ar mixtures with a pressure in the region of 40–100 kPa were used to obtain a linear correlation between the intensity ratio of LIBS spectra and the local mixture ratio. It was observed that the logarithm of the slope of the lines also showed a linear correlation with the pressure. Considering that the current method was applied by necessity with the given pressure, the local pressure was studied based on its dependence on the full width at half maximum (FWHM) of H and Ar spectral lines. Consequently, the emission ratios of H/Ar, O/Ar and N/Ar were utilized as a diagnostic tool to obtain the distribution of the propellant in the inert atmosphere. The LIBS-based results not only provide fundamental data for the on-line measurements of ADN-based thrusters, but also hold promise for promoting the application of LIBS in the field of energetic ionic liquids.

(1) Background: Macrosomia is prevalent in China and worldwide. The current method of predicting macrosomia is ultrasonography. We aimed to develop new predictive models for recognizing macrosomia using a random forest model to improve the sensitivity and specificity of macrosomia prediction; (2) Methods: Based on the Shandong Multi-Center Healthcare Big Data Platform, we collected the prenatal examination and delivery data from June 2017 to May 2018 in Jinan, including the macrosomia and normal-weight newborns. We constructed a random forest model and a logistic regression model for predicting macrosomia. We compared the validity and predictive value of these two methods and the traditional method; (3) Results: 405 macrosomia cases and 3855 normal-weight newborns fit the selection criteria and 405 pairs of macrosomia and control cases were brought into the random forest model and logistic regression model. On the basis of the average decrease of the Gini coefficient, the order of influencing factors was: interspinal diameter, transverse outlet, intercristal diameter, sacral external diameter, pre-pregnancy body mass index, age, the number of pregnancies, and the parity. The sensitivity, specificity, and area under curve were 91.7%, 91.7%, and 95.3% for the random forest model, and 56.2%, 82.6%, and 72.0% for logistic regression model, respectively; the sensitivity and specificity were 29.6% and 97.5% for the ultrasound; (4) Conclusions: A random forest model based on the maternal information can be used to predict macrosomia accurately during pregnancy, which provides a scientific basis for developing rapid screening and diagnosis tools for macrosomia.

This study aims to explore the impact of isolation measures implemented during the COVID-19 pandemic on childbirth outcomes in pregnant women. The design was a retrospective cohort study. The pregnant women during the outbreak lockdown and isolation from February 1 to April 30, 2020, were defined as the exposed population, and the pregnant women in the same time frame in 2019 as the non-exposed population. All data for the study were obtained from the National Health Care Data Platform of Shandong University. Generalized linear regression models were used to analyze the differences in pregnancy outcomes between the two study groups. A total of 34,698 pregnant women from Shandong Province, China in the data platform met the criteria and were included in the study. The proportions were 11.53% and 8.93% for macrosomia in the exposed and the non-exposed groups and were 3.47% and 4.37% for low birth weight infants, respectively, which were significantly different. They were 22.55% and 25.94% attributed to average exposed effect for macrosomia and low birth weight infants. Meanwhile, the mean weight and standard deviation of full-term infants in the exposure group were 3414.80 ± 507.43 g, which were significantly higher than in the non-exposed group (3347.22 ± 502.57 g, P 0.001). The effect of exposure was significant in the third trimester. In conclusion, the isolation during the COVID-19 pandemic increases the birth weight of infants and the probability of macrosomia, regardless of which trimester in isolation a pregnant woman was, while the third trimester is the sensitive window of exposure. Our findings provide a basis for health care and policy development during pregnancy in COVID-19, due to COVID-19 still showing a pandemic trend around the world in 2022.

Community correction refers to the correction on the five types of objects. Community correction work is to correct the community correction objects’ psychology and behavioral habits by taking proper correction measures for corresponding correction objects, promote them to return to society. Selection of correction measures is a key component in community correction work. However, this work is still at the manual stage in China, which consumes much manpower and resources. To this end, we propose an algorithm namely FFM-FTRL which is the first time that machine learning is applied to addressing the recommendation of community correction measures, improving the efficiency of community correction work. Our method is specifically designed to solve sparse data, and reduce model training time. To evaluate its effectiveness, we select FM and FFM-SGD as our baselines. Experimental results show that F1 score is improved by 4% and 0.5%, and the training time is shortened.

Microplastics (MPS) are widespread in our environment and have a potential impact on the reproductive development of humans and mammals. In this study, we evaluated the effect of 5 µm polystyrene microplastics(PS-MPS) on spermatogenesis in mice. The damage by PS-MPS to epididymal sperm was studied using blood cell counts. The results showed that the number of viable epididymis sperm after PS-MPS exposure was significantly reduced. Using Duff-Quik staining, we found that the PS-MPS exposure increased the rate of sperm deformity. The testis is an important organ responsible for normal spermatogenesis. HE and TUNEL staining showed atrophy, shedding, and apoptosis of sperm cells at all levels of the testis after exposure to PS-MPS. Western blot and qPCR analysis were used to detect Nrf2/HO-1 and NF-κB. The results showed that after PS-MPS exposure, the expression of the pro-inflammatory molecule NF-κB and that of the inflammatory factors interleukin (IL)-1β and IL-6 increased significantly, whereas that of the anti-inflammatory molecule Nrf2/HO-1 decreased. These results indicate that the abnormal sperm quality in ICR mice caused by PS-MPS exposure is closely related to the Nrf2/HO-1/NF-κB pathway.

Biodiversity loss is a social and ecological emergency, and calls have been made for the global expansion of protected areas (PAs) to tackle this crisis. It is unclear, however, where best to locate new PAs to protect biodiversity cost-effectively. To answer this question, we conducted a spatial meta-analysis by overlaying seven global biodiversity templates to identify conservation priority zones. These are then combined with low human impact areas to identify cost-effective zones (CEZs) for PA designation. CEZs cover around 38% of global terrestrial area, of which only 24% is currently covered by existing PAs. To protect more CEZs, we propose three scenarios with conservative, moderate, and ambitious targets, which aim to protect 19, 26, and 43% of global terrestrial area, respectively. These three targets are set for each Convention on Biological Diversity party with spatially explicit CEZs identified, providing valuable decision support for the post-2020 global biodiversity framework.

Biodiversity is declining at an unprecedented rate, and conservation is needed in many places including human-dominated landscapes. Evaluation of conflict risk between biodiversity conservation and human activities is a prerequisite for countries to develop strategies to achieve better conservation outcomes. However, quantitative methods to measure the conflict risk in large-scale areas are still lacking. Here we put forward a quantitative model in large-scale areas and produce the first continuum map of conflict risk in China. Our results show that conflict risk hotspots take up 32.86 % of China's terrestrial area, which may affect 42.98 % of China's population and more than 98 % of threaten vertebrates. Although species richness is high in these hotspot regions, only 10.69 % of them are covered by protected areas. Therefore, alternative conservation measures and proactive spatial planning are needed, especially in regions along the coastlines and around the Sichuan Basin. Especially, extraordinary attentions should be paid to urban agglomerations such as the Pearl River Delta and Yangtze River Delta. Compared to previous studies, our study quantifies the conflict risk of every gird cell, enabling the comparison among any locations. The analysis of 500 times generations shows a low sensitivity of the model as the maximum standard deviation is only 0.017. Furthermore, our model can be applied in other countries or at global scale to provide strategies for conflict governance and biodiversity conservation.

This study verifies the effectiveness of a dynamic resonant frequency control system for transducers. This system enables the resonant frequency of the transducer to match the driving frequency. In general, the resonant frequency of an ultrasonic transducer is fixed based on its design and material properties. Therefore, it is difficult to actively control the frequency when driving the transducer. However, for high-power piezoelectric actuators, it is important to control the ratio of the fundamental and higher-order resonant frequency of the longitudinal vibration precisely at 1:2. A high-power and high mechanical quality factor (high-Q) ultrasonic transducer requires precise control of its resonant frequency. However, the resonant frequency may shift due to changes in boundary conditions or non-linear phenomena in piezoelectric vibration while driving the ultrasonic transducer. To maintain the resonant frequency ratio of the ultrasonic transducer at 1:2, we propose to dynamically control the resonant frequency ratio constant. In this study, we made two main proposals to our dynamic resonant frequency control system. One is the stepped structure of the transducer, and the other is the completely automatic control. In the stepped structure, a Langevin transducer was designed to have a resonant frequency ratio of almost 1:2 for the first and third longitudinal mode in the initial condition. Additionally, this structure could achieve control of only one of two resonant frequencies of the transducer. For the utterly automatic control system, piezoelectric elements were introduced for controlling the resonant frequency ratio precisely. For this propose, switching the electrical boundary conditions of these piezoelectric elements was carried out by MOSFETs connected to the ultrasonic transducer and control its optimum duty ratio automatically by our feedback system. This system realized dynamic control of the resonant frequency. As a result, the resonant frequency of the transducer matched the driving frequency in the frequency band from 23.23 kHz to 23.93 kHz. It was also confirmed that the shape of the excited non-sinusoidal waveform could be controlled by using resonant frequency control.

Multivariate pattern analysis (MVPA) approach applied to neuroimaging data, such as functional magnetic resonance imaging (fMRI) data, has received a great deal of attention because of its sensitivity to distinguishing patterns of neural activities associated with different stimuli or cognitive states. Generally, when using MVPA approach to decode the mental states or stimuli, a set of discriminative variables (e.g., voxels) is first selected. However, in most of existing MVPA methods, the selected variables do not contain all informative variables, since these selected variables are sufficient for decoding. In this paper, we propose a multivariate pattern analysis method based on sparse representation for decoding the brain states and localizing category-specific brain activation areas corresponding to two experimental conditions/tasks at the same time. Unlike traditional MVPA approaches, this method is designed to find informative variables as many as possible. We applied the proposed method to two judgement experiments: a gender discrimination and an emotion discrimination task, data analysis results demonstrate its effectiveness and potential applications.

Swirl-stabilized flame is commonly used in gas turbine combustor. Under the operation conditions of interests, such flame is in turbulent regime, exhibiting quasi-periodic dynamic characteristics with one or multiple oscillation modes. We have reported a strategy to investigate the dynamics of the flame. The measurement of the swirling flame in a gas turbine model combustor is carried out by simultaneous planar laser-induced fluorescence (PLIF) and high-speed chemiluminescence (CL) imaging of OH radical, as the former technique is capable of providing highly resolved transient structure of the reaction zone of the flame while the latter is a perfect indicator of the dynamic motion of the flame. The proper orthogonal decomposition (POD) method was applied to both sets of data to unveil the main dynamics mode of both observations. The evolution of the OH* CL mode coefficients provided the information of the oscillation frequency and the momentum of the flame when the PLIF image is taken. Furthermore, the connection of the OH PLIF and OH* CL measurements were investigated by extended proper orthogonal decomposition (EPOD) method. The EPOD analysis showed a strong correlation between the reaction zone at the PLIF plane and the total OH* CL of the flame, enabling the reconstruction of the evolution of the reaction zone. By the application of the strategy above, combustor was tested under different equivalent ratio, and the dynamics of the flame were compared.

A dual-dye-laser Laser-induced Fluorescence (LIF) system is established for flow field investigations in JF-10, a H 2 /O 2 -detonation-driven shock tunnel. The shock tunnel generates 400 mm-wide hypersonic flow with total enthalpy of 16.1 MJ/kg and static pressure at only105Pa, where LIF measurement is extremely challenging. In this LIF system, the laser sheet of a conventional planar LIF is rotated 90 degrees along its propagation direction, so that the fluorescence signal collected by the camera concentrates on a sharp line. The S/N ratio is increased, thus single-shot measurements are achievable. The rotational temperature of the flow measured by two-line thermometry (TLT) with simultaneous excitation of two $\gamma$ (0,0) transitions of NO at distinct rotational levels. Compared with single-dye-laser set-up, the current system is less affected by the fluctuation of the flow field from each facility operation, thus capable of reflect the dramatic temperature change across the shock layer. With precise control of the proper of the laser, and through evaluation of the error of the data, the temperature measurement and numerical simulation in the flow is consistent. Meanwhile, the velocity of the flow is measured by molecular tagging velocimetry (MTV) with a long-life fluorescence excitation, and the result agrees with the expected value. The UV LIF technique is proven useful in flow diagnostics in high-enthalpy regime.

In order to make it possible to control the plasma state and predict the regime transitions via coupling optical and electrical diagnosis in aerospace engineering, we have experimentally investigated the regime transitions under 0.1–15 kPa with an input discharge power of 0–25 W in a parallel-plate electrode configuration. An abnormal glow discharge (AGD), filamentary discharge (FD), and arc discharge (AD) are distinguished using the voltage–current characteristics under different gas pressures. The electron excitation temperature ( T e ), electron density ( N e ), spatial resolutions of T e and N e , and ionization degree are obtained via optical emission spectroscopy to reveal the transition mechanisms. Thermal instability, characterized by T e , plays a dominant role during the transition from an AGD to an FD. The conclusions are supported by analysis of ionization degree, whereas electronic instability becomes the dominant mechanism in the transition from an FD to an AD. This is related to collision kinetics because of an observed drop in N e , which is verified by the spatial resolution as well. Moreover, planar laser-induced fluorescence provides further insight into the instantaneous location and relative number variation of Ar 1 s 5 metastable atoms, which agrees well with the plasma properties mentioned above. In addition, a pressure of 1 kPa with a maximum input power of 17.5 W are specified as suitable working parameters for further study when applied to microthrusters due to its higher N e and better stability.

To recognize individuals, the brain often integrates audiovisual information from familiar or unfamiliar faces, voices, and auditory names. To date, the effects of the semantic familiarity of stimuli on audiovisual integration remain unknown. In this functional magnetic resonance imaging (fMRI) study, we used familiar/unfamiliar facial images, auditory names, and audiovisual face-name pairs as stimuli to determine the influence of semantic familiarity on audiovisual integration. First, we performed a general linear model analysis using fMRI data and found that audiovisual integration occurred for familiar congruent and unfamiliar face-name pairs but not for familiar incongruent pairs. Second, we decoded the familiarity categories of the stimuli (familiar vs. unfamiliar) from the fMRI data and calculated the reproducibility indices of the brain patterns that corresponded to familiar and unfamiliar stimuli. The decoding accuracy rate was significantly higher for familiar congruent versus unfamiliar face-name pairs (83.2%) than for familiar versus unfamiliar faces (63.9%) and for familiar versus unfamiliar names (60.4%). This increase in decoding accuracy was not observed for familiar incongruent versus unfamiliar pairs. Furthermore, compared with the brain patterns associated with facial images or auditory names, the reproducibility index was significantly improved for the brain patterns of familiar congruent face-name pairs but not those of familiar incongruent or unfamiliar pairs. Our results indicate the modulatory effect that semantic familiarity has on audiovisual integration. Specifically, neural representations were enhanced for familiar congruent face-name pairs compared with visual-only faces and auditory-only names, whereas this enhancement effect was not observed for familiar incongruent or unfamiliar pairs. Hum Brain Mapp 37:4333-4348, 2016. © 2016 Wiley Periodicals, Inc.

The numerical manifold method (NMM), a Galerkin-type numerical method, has been successful in the solution of problems with finite definition domains, yet it has never been applied to problems with unbounded domains, or exterior problems. This study aims to fill the big gap by constructing infinite patches, together with the finite patches, to cover the unbounded domain. The local approximations of infinite patches can take the asymptotic estimations of the solutions at infinity, which are available for all those well-established boundary value problems. Compared with the infinite element methods in the finite element method (FEM), the construction of the trial functions by NMM is more elegant in theory and more systematical in methodology, resulting in more accurate solutions. Some typical examples in potential and half-space elasticity problems are investigated to illustrate the applicability and accuracy of the proposed method.

At cocktail parties, our brains often simultaneously receive visual and auditory information. Although the cocktail party problem has been widely investigated under auditory-only settings, the effects of audiovisual inputs have not. This study explored the effects of audiovisual inputs in a simulated cocktail party. In our fMRI experiment, each congruent audiovisual stimulus was a synthesis of 2 facial movie clips, each of which could be classified into 1 of 2 emotion categories (crying and laughing). Visual-only (faces) and auditory-only stimuli (voices) were created by extracting the visual and auditory contents from the synthesized audiovisual stimuli. Subjects were instructed to selectively attend to 1 of the 2 objects contained in each stimulus and to judge its emotion category in the visual-only, auditory-only, and audiovisual conditions. The neural representations of the emotion features were assessed by calculating decoding accuracy and brain pattern-related reproducibility index based on the fMRI data. We compared the audiovisual condition with the visual-only and auditory-only conditions and found that audiovisual inputs enhanced the neural representations of emotion features of the attended objects instead of the unattended objects. This enhancement might partially explain the benefits of audiovisual inputs for the brain to solve the cocktail party problem.

Goal : Motor imagery-related mu/beta rhythms, which can be voluntarily modulated by subjects, have been widely used in EEG-based brain computer interfaces (BCIs). Moreover, it has been suggested that motor imagery-specific EEG differences can be enhanced by feedback training. However, the differences observed in the EEGs of naive subjects are typically not sufficient to provide reliable EEG control and thus result in unintended feedback. Such feedback can frustrate subjects and impede training. In this study, a hybrid BCI paradigm combining motor imagery and steady-state visually evoked potentials (SSVEPs) has been proposed to provide effective continuous feedback for motor imagery training. Methods : During the initial training sessions, subjects must focus on flickering buttons to evoke SSVEPs as they perform motor imagery tasks. The output/feedback of the hybrid BCI is based on hybrid features consisting of motor imagery- and SSVEP-related brain signals. In this context, the SSVEP plays a more important role than motor imagery in generating feedback. As the training progresses, the subjects can gradually decrease their visual attention to the flickering buttons, provided that the feedback is still effective. In this case, the feedback is mainly based on motor imagery. Results : Our experimental results demonstrate that subjects generate distinguishable brain patterns of hand motor imagery after only five training sessions lasting approximately 1.5 h each. Conclusion : The proposed hybrid feedback paradigm can be used to enhance motor imagery training. Significance : This hybrid BCI system with feedback can effectively identify the intentions of the subjects.

Compressive sensing (CS) is a radical new way of sampling signal at a sub-Nyquist rate, acquires a signal of interest indirectly by correcting a very limited number of its “projections”, and the signal can be exactly reconstructed from these “projections”, this new signal acquisition paradigm has revolutionized the way digital data are traditionally acquired. Generally, researchers always use orthogonal wavelet as sparse basis, but it fails to provide an optimal sparse representation for images that contain texture details. In this paper, we use shearlet which is a new directional multiresolution transform, can efficiently represent the directional information of images, meanwhile, using the RecPF of [4] as the reconstruction algorithm. The experimental results indicate that the quality of reconstructed image is improved and obtain better performance of PSNR.

Association rules are the main technique for data mining. Apriori algorithm is a classical algorithm of association rule mining. Lots of algorithms for mining association rules and their mutations are proposed on basis of apriori algorithm, but traditional algorithms are not efficient. For the two bottlenecks of frequent itemsets mining: the large multitude of candidate 2-itemsets, the poor efficiency of couting their support, this paper proposes a novel algorithm so called reduced apriori algorithm with tag (RAAT), which reduces one redundant pruning operations of C2. If the number of frequent 1-itemsets is n, then the number of connected candidate 2-itemsets is Cn 2, while pruning operations Cn 2. The novel algorithm decreases pruning operations of candidate 2-itemsets, thereby saving time and increasing efficiency.For the bottleneck:poor efficiency of couting support, RAAT optimizes subset operation, through the transaction tag to speed up support calculations. The experimental results obtained from tests show that RAAT outperforms original one efficiency.