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Brain tumor is a severe cancer disease caused by uncontrollable and abnormal partitioning of cells. Recent progress in the field of deep learning has helped the health industry in Medical Imaging for Medical Diagnostic of many diseases. For Visual learning and Image Recognition, task CNN is the most prevalent and commonly used machine learning algorithm. Similarly, in our paper, we introduce the convolutional neural network (CNN) approach along with Data Augmentation and Image Processing to categorize brain MRI scan images into cancerous and non-cancerous. Using the transfer learning approach we compared the performance of our scratched CNN model with pre-trained VGG-16, ResNet-50, and Inception-v3 models. As the experiment is tested on a very small dataset but the experimental result shows that our model accuracy result is very effective and have very low complexity rate by achieving 100% accuracy, while VGG-16 achieved 96%, ResNet-50 achieved 89% and Inception-V3 achieved 75% accuracy. Our model requires very less computational power and has much better accuracy results as compared to other pre-trained models.

Cation-disordered Li-excess cathodes with oxygen redox reactions are promising candidates for high-energy-density Li ion batteries. Nevertheless, the oxygen redox process that is required for the high capacity often comes with the oxygen loss, which leads to severe capacity degradation and voltage decay. In this work, we have successfully synthesized a series of Li-excess cation-disordered cathodes (Li1.2Mn0.4+xTi0.4-xO2-xFx) (0 ​≤ ​x ​≤ ​0.2) with different fluorine (F) contents. The electrochemical performance results show that the Li1.2Mn0.55Ti0.25O1.85F0.15 (LMTOF0.15) exhibits the highest reversible capacity (275 mAh g-1, under 30 ​mA ​g-1), cyclability, and voltage retentions. The mapping of resonant inelastic X-ray scattering (mRIXS) and differential electrochemical mass spectroscopy (DEMS) results reveal that the fluorination enhances the reversible lattice oxygen redox reaction while suppressing irreversible gas release and surface reactions. The X-ray Absorption Spectroscopy (XAS) during the initial two cycles shows that F-substitution alleviates the reduction of the Mn valence state during the whole (dis)charge processes in the bulk and at the surface of the material, results in higher average discharge voltage. In addition, the introduction of F improves the structural stability and suppresses local lattice distortion of the material. Therefore, LMTOF0.15 is able to cycle with smaller polarization, less interfacial side reaction and Mn dissolution, and therefore results in enhanced cyclability. This work provides a comprehensive understanding of the fluorination effect on the cationic and anionic redox activities in cation-disordered Li-excess cathodes.

Voltage decay,i.e., the voltage decrease during electrochemical cycling, has been a decade-long challenge for lithium-ion batteries. This issue not only leads to a substantial loss of energy density, but also raises challenges for the battery management system, hindering the commercial application of high capacity lithium-rich oxide. Here, we show that through a combination of electrochemical conditioning and thermal treatment, Li2MnO3, the parent compound of lithium-rich oxide, which typically displays severe voltage and capacity decay, could be converted into a new phase that essentially suppresses the voltage decay with improved capacity retention and rate performance. By combining atomic-sensitive nuclear magnetic resonance, differential electrochemical mass spectrometry and synchrotron-based resonant inelastic X-ray scattering, we disclose that treatment triggers the formation of three-coexisting phases,i.e., the lithium-rich layered, spinel and defect spinel phases, which enables improved reversibility of the oxygen redox activity and enhanced manganese redox reactions in the initial cycle. Our findings suggest the key role of the local structure in the voltage decay problem and provide insights for material optimizations towards lithium- and manganese-rich cathodes without the voltage decay.

As a parent compound of Li-rich electrodes, Li2MnO3 exhibits high capacity during the initial charge; however, it suffers notoriously low Coulombic efficiency due to oxygen and surface activities. Here, we successfully optimize the oxygen activities toward reversible oxygen redox reactions by intentionally introducing protons into lithium octahedral vacancies in the Li2MnO3 system with its original structural integrity maintained. Combining structural probes, theoretical calculations, and resonant inelastic X-ray scattering results, a moderate coupling between the introduced protons and lattice oxygen at the oxidized state is revealed, which stabilizes the oxygen activities during charging. Such a coupling leads to an unprecedented initial Coulombic efficiency (99.2%) with a greatly improved discharge capacity of 302 mAh g-1 in the protonated Li2MnO3 electrodes. These findings directly demonstrate an effective concept for controlling oxygen activities in Li-rich systems, which is critical for developing high-energy cathodes in batteries.

Macrostate and microstate characteristics of interregional nonlinear interdependence of brain dynamics are investigated for Zen-meditation and normal resting EEG. Evaluation of nonlinear interdependence based on nonlinear dynamic theory and phase space reconstruction is employed in the 30-channel electroencephalographic (EEG) signals to characterize the functioning interactions among different local neuronal networks. This paper presents a new scheme for exploring the microstate and macrostate of interregional brain neural network interactivity. Nonlinear interdependence quantified by similarity index is applied to the phase trajectory reconstructed from multi-channel EEG. The microstate similarity-index matrix (miSIM) is evaluated every 5 millisecond. The miSIMs are classified by K-means clustering. The cluster center corresponds to the macrostate SIM (maSIM) evaluated by conventional scheme. Zen-meditation EEG exhibits rather stationary and stronger interconnectivity among frontal midline regional neural oscillators, whereas resting EEG appears to drift away more often from the midline and extend to the inferior brain regions.

Bayesian network has been used extensively in data mining. The Privacy-Preserving data mining algorithm based on quantum ant colony optimization is proposed in this paper. The algorithm is based on distributed database. The algorithm is divided into two steps. In the first step, the modified quantum ant colony optimization algorithm is used to get the local Bayesian network structure. The purpose of the second step is getting the global Bayesian network structure by using local ones. In order to protect the privacy, the secure sum is used in the algorithm. The algorithm is proved to be convergent on theory. Some experiments have been done on the algorithm, and the results proved that the algorithm is feasible.

(1) Background: This research is aimed to develop new methods to investigate the cardiorespiratory interaction of Zen-meditation practitioners (Zen-meditation group) and healthy ordinary young people (control group) by quantitatively evaluating the respiratory sinus arrhythmia (RSA) behavior. (2) Methods: Twenty-five voluntary controls and seven Zen-meditation practitioners were recruited. Experimental protocol involves five sessions of different mental-stress levels (control group) and five sessions of Zen-meditation practice (experimental group). Forty-minute (thirty-minute) ECG and respiratory signals were recorded for each control (experimental) subject. By detecting R peaks, heart-rate sequence is constructed. Two methods are proposed to evaluate RSA behavior based on cycle-to-cycle synchronization between heart-rate and respiratory sequence. (3) Results: Based on the proposed method of computing RSA coefficient, control group average for each session is 0.70 (Rest I), 0.65 (CAT I), 0.75 (BC), 0.63 (CAT II) and 0.70 (Rest II); whereas Zen-meditation group average is 0.81 (S1), 0.84 (S2), 0.84 (S3), 0.86 (S4) and 0.81 (S5), all superior to which of the control group. Average RSA normal rate in Zen-meditation group (91.03%) remarkably surpasses which in the control group (80.48%) in the Rest sessions. (4) Conclusions: Using the time-domain HRV (heart-rate variability) as a reference, our methods, RSA coefficient and RSA normal rate, provide more reliable and direct estimate of RSA behavior than conventional peak-valley method computing the inspiratory–expiratory difference in R-to-R interval of ECG. Moreover, results of the proposed methods are confined in a specified range (RSA coefficient between 0 and 1, RSA normal rate between 0% and 100%) facilitates the interpretation of the quantitative RSA behavior. In the RSA analysis, breathing-control session using anthropic interventions induces more prominent RSA activity in control group. Nevertheless, HHIS Zen meditation, with excellent qi circulation activated by ten-mailuns system, naturally (in the way of do-nothing) elicits superior RSA performance better than sophisticated way of breathing control.

Mutations in the Aristaless-Related Homeobox (ARX) gene cause structural anomalies of the brain, epilepsy, and neurocognitive deficits in children. During forebrain development, Arx is expressed in both pallial and subpallial progenitor cells. We previously demonstrated that elimination of Arx from subpallial-derived cortical interneurons generates an epilepsy phenotype with features overlapping those seen in patients with ARX mutations. In this report, we have selectively removed Arx from pallial progenitor cells that give rise to the cerebral cortical projection neurons. While no discernable seizure activity was recorded, these mice exhibited a peculiar constellation of behaviors. They are less anxious, less social, and more active when compared with their wild-type littermates. The overall cortical thickness was reduced, and the corpus callosum and anterior commissure were hypoplastic, consistent with a perturbation in cortical connectivity. Taken together, these data suggest that some of the structural and behavioral anomalies, common in patients with ARX mutations, are specifically due to alterations in pallial progenitor function. Furthermore, our data demonstrate that some of the neurobehavioral features found in patients with ARX mutations may not be due to on-going seizures, as is often postulated, given that epilepsy was eliminated as a confounding variable in these behavior analyses.

Innovatively new behaviors of heart rate variability caused by special heart-transition process were observed in the long-term, well-experienced Zen practitioners while practicing the heart-to-heart imprint sealing (HHIS) Zen meditation. HHIS Zen practice involves specific neurocardiac-cardiorespiratory interaction while on the way of realizing the heart-dominant, detached brain. Results of analyzing the electrocardiogram and respiratory signals of 10 experienced practitioners reveal several distinctive characteristics: (1) remarkably linear correlation between standard deviation of the normal R-to-R intervals, SDNN, and total power in very-low-frequency (VLF, 0.0033–0.04[Formula: see text]Hz) band of power spectrum of the heart-rate sequence, (2) time-varying VLF power dominating over the low-frequency and high-frequency power in heart rate variability (HRV) variations, (3) intermittent transition into slowly, deeply abdominal respiration inducing a boost of heart rates, (4) heart-rate baseline slowly fluctuating at 0.005–0.0067[Formula: see text]Hz, about 1.5–2 cycles in 5-min period, and (5) remarkable respiratory sinus arrhythmia (RSA) synchrony between heart rate and respiration rhythm. This paper proposes a rational scientific hypothesis for the neurocardiac-cardiorespiratory mechanism. The unique scheme of HHIS Zen meditation involves the spiritual-qi concentration and refinement for pinpointing into the particular energy centers, mailuns. Ignition by a subtle, deepest abdominal respiration, electrical impulses rapidly transmit from solar plexus to branchial plexuses to activate unique heart-transition process. Simultaneously, another branch streams upward the spinal cord to cervical plexus and brainstem that effectively harmonizes neurocardiac interactions. To investigate the underlying behaviors, time-domain and frequency-domain HRV based on continuous wavelet transform were employed.

The connotation and extension of furniture design, which aims to enhance the quality of people's lives, is constantly expanding and improving. The innovation of furniture design also demands us to take the users' prospective, focus on people's lifestyle, seek the designing elements and seize the designing inspiration so as to complete the design.

Micro mobility gives a basic the support of intra-domain roaming. Most recent micro-mobility researches have focused on providing routing service without considering security. In this paper, we employ the hop-by-hop routing authenticated protocol for authentication verification . We create a lightweight cryptography via one-way hash chains. Furthermore, we analyze the security properties.

With the development of wireless sensor networks (WSNs), many applications require for the privacy preserving. Providing an efficient privacy-preserving data aggregation in WSNs is becoming more and more important. The secure data aggregation in WSNs has been studied in recent years, but most of the algorithms are suffering from the high computation overhead and high communication overhead, and some of the algorithms do not supply the data integrity checking. To resolve these problems, a modified private-preserving data aggregation based on complex number algorithm for WSN is proposed in this paper. An efficient key distribution scheme is used in the algorithm to improve the security of the key. The complex number is used in the algorithm to protect the privacy and check the data integrity. According to the analysis in the paper, the algorithm is efficient in terms of communication, computation and integrity checking.

In this work, Li-rich Li1.2Mn0.43+Mnx4+Ti0.4-xO2 (LMMxTO, 0