Co-optimization Learning Network for MRI Segmentation of Ischemic Penumbra Tissues

Convolutional neural networks (CNNs) have brought hope for the medical image auxiliary diagnosis. However, the shortfall of labeled medical image data is the bottleneck that limits the performance improvement of supervised CNN methods. In addition, annotating a large number of labeled medical image data is often expensive and time-consuming. In this study, we propose a co-optimization learning network (COL-Net) for Magnetic Resonance Imaging (MRI) segmentation of ischemic penumbra tissues. COL-Net base on the limited labeled samples and consists of an unsupervised reconstruction network (R), a supervised segmentation network (S), and a transfer block (T). The reconstruction network extracts the robust features from reconstructing pseudo unlabeled samples, which is the auxiliary branch of the segmentation network. The segmentation network is used to segment the target lesions under the limited labeled samples and the auxiliary of the reconstruction network. The transfer block is used to co-optimization the feature maps between the bottlenecks of the reconstruction network and segmentation network. We propose a mix loss function to optimize COL-Net. COL-Net is verified on the public ischemic penumbra segmentation challenge (SPES) with two dozen labeled samples. Results demonstrate that COL-Net has high predictive accuracy and generalization with the Dice coefficient of 0.79. The extended experiment also shows COL-Net outperforms most supervised segmentation methods. COL-Net is a meaningful attempt to alleviate the limited labeled sample problem in medical image segmentation.

Rethinking the Image Fusion: A Fast Unified Image Fusion Network based on Proportional Maintenance of Gradient and Intensity

In this paper, we propose a fast unified image fusion network based on proportional maintenance of gradient and intensity (PMGI), which can end-to-end realize a variety of image fusion tasks, including infrared and visible image fusion, multi-exposure image fusion, medical image fusion, multi-focus image fusion and pan-sharpening. We unify the image fusion problem into the texture and intensity proportional maintenance problem of the source images. On the one hand, the network is divided into gradient path and intensity path for information extraction. We perform feature reuse in the same path to avoid loss of information due to convolution. At the same time, we introduce the pathwise transfer block to exchange information between different paths, which can not only pre-fuse the gradient information and intensity information, but also enhance the information to be processed later. On the other hand, we define a uniform form of loss function based on these two kinds of information, which can adapt to different fusion tasks. Experiments on publicly available datasets demonstrate the superiority of our PMGI over the state-of-the-art in terms of both visual effect and quantitative metric in a variety of fusion tasks. In addition, our method is faster compared with the state-of-the-art.

12. Licensing Agreements and Other Agreements Involving Intellectual Property Rights

This chapter examines some of the different types of intellectual property rights (IPRs) before outlining the relationship between intellectual property and both EU competition law and the EU free movement rules. It focuses, however, on IP licensing agreements and their treatment under Article 101. The chapter traces the development of EU competition policy to IP licensing agreements and examine the current Technology Transfer Block Exemption and the Guidelines in detail. It also examines patent settlement agreements (including pay for delay agreements), patnet pools, trade mark licences, trade mark delimitation agreements, and copyright (other than software) licences not covered by the TTBER and Guidelines.

Rayleigh Wave Calibration of Acoustic Emission Sensors and Ultrasonic Transducers

Acoustic emission (AE) sensors and ultrasonic transducers were characterized for the detection of Rayleigh waves (RW). Small aperture reference sensors were characterized first using the fracture of glass capillary tubes in combination with a theoretical displacement calculation, which utilized finite element method (FEM) and was verified by laser interferometer. For the calibration of 18 commercial sensors and two piezoceramic disks, a 90° angle beam transducer was used to generate RW pulses on an aluminum transfer block. By a substitution method, RW receiving sensitivity of a sensor under test was determined over the range of frequency from 22 kHz to 2 MHz. Results were compared to the sensitivities to normally incident waves (NW) and to other guided waves (GW). It was found that (1) NW sensitivities are always higher than RW sensitivities, (2) differences between NW and RW receiving sensitivities are dependent on frequency and sensor size, (3) most sensors show comparable RW and GW receiving sensitivities, especially those of commonly used AE sensors, and (4) the receiving sensitivities of small aperture (1 mm diameter) sensors behave differently from larger sensors.

Intermanual transfer of visuomotor adaptation is related to awareness

Previous studies compared the effects of gradual and sudden adaptation on intermanual transfer to find out whether transfer depends on awareness of the perturbation. Results from different groups were contradictory. Since results of our own study suggest that awareness depends on perturbation size, we hypothesize that awareness-related intermanual transfer will only appear after adaptation to a large, sudden perturbation but not after adaptation to a small sudden perturbation or a gradual perturbation, large or small. To confirm this, four groups (S30, G30, S75, G75) of subjects performed out-and-back reaching movements with their right arm. In a baseline block, they received veridical visual feedback of hand position. In the subsequent adaptation block, feedback was rotated by 30 deg (S30, G30) or 75 deg (S75, G75). This rotation was either introduced suddenly (S30, S75) or gradually in steps of 3 deg (G30, G75). After the adaptation block, subjects did an awareness test comprising exclusion and inclusion conditions. The experiment concluded with an intermanual transfer block, in which movements were performed with the left arm under rotated feedback, and a washout block again under veridical feedback. We used a hierarchical Bayesian model to estimate individual movement directions and group averages. The movement directions in different conditions were then used to calculate group and individual indexes of adaptation, awareness, unawareness, transfer and washout. Both awareness and transfer were larger in S75 than in other groups, while unawareness and washout were smaller in S75 than in other groups. Furthermore, the size of awareness indices correlated to intermanual transfer across subjects, even when transfer was normalized to final adaptation level. Thus, we show for the first time that the amount of intermanual transfer directly relates to the extent of awareness of the learned perturbation.

Pengaruh Nilai Wettability pada Pool Boiling Heat Transfer Studi Kasus Hydrophobic, Hydrophilic dan Superhydrophilic

Telah dilakukan penelitian tentang efek dari berbagai nilai wettability dari permukaan pada pool boiling heat transfer. Percobaan dilakukan dengan menggunakan air murni sebagai fluida kerja dan subcooling 0K. Heat transfer block yang digunakan adalah mirror surafce (dipoles tembaga) / hidrofilik, superhydrophilic / copper berlapis TiO2 and permukaan hidrofobik / PTFE. Hasil penelitian menunjukkan bahwa kinerja perpindahan panas dari permukaan dengan lapisan PTFE lebih baik di fluks panas rendah. Sedangkan untuk fluks panas menengah, permukaan superhydrophilic (TiO2) lebih unggul dibandingkan dengan permukaan hidrofilik dan hidrofobik

12. Licensing Agreements and other Agreements Involving Intellectual Property Rights

All books in this flagship series contain carefully selected substantial extracts from key cases, legislation, and academic debate, providing able students with a stand-alone resource. This chapter examines some of the different types of intellectual property rights (IPRs) before outlining the relationship between intellectual property and both EU competition law and the EU free movement rules. It focuses, however, on IP licensing agreements and their treatment under Article 101. The chapter is organized as follows. Section 3 traces the development of EU competition policy to IP licensing agreements. Sections 4 and 5 examine the current Technology Transfer Block Exemption, Regulation 772/2004 (TTBER) and the Guidelines in detail (noting where significant changes might occur in 2014). Sections 6, 7, and 8 deal with trade mark licences, trade mark delimitation agreements, and copyright (other than software) licences not covered by the TTBER and Guidelines. Section 9 outlines issues arising in cases involving IPRs under Article 102, while Section 10 concludes.

Signal Processing based on Stable radix-2 DCT I-IV Algorithms having Orthogonal Factors

This paper presents stable, radix-2, completely recursive discrete cosine transform algorithms DCT-I and DCT-III solely based on DCT-I, DCT-II, DCT-III, and DCT-IV having sparse and orthogonal factors. Error bounds for computing the completely recursive DCT-I, DCT-II, DCT-III, and DCT-IV algorithms having sparse and orthogonal factors are addressed. Signal flow graphs are demonstrated based on the completely recursive DCT-I, DCT-II, DCT-III, and DCT-IV algorithms having orthogonal factors. Finally image compression results are presented based on the recursive 2D DCT-II and DCT-IV algorithms for image size 512 by 512 pixels with transfer block sizes 8 by 8, 16 by 16, and 32 by 32 with 93.75% absence of coefficients in each transfer block.