A Two-Phase Maximum-Likelihood Sequence Estimation for Receivers with Partial CSI

The optimality of the conventional maximum likelihood sequence estimation (MLSE), also known as the Viterbi Algorithm (VA), relies on the assumption that the receiver has perfect knowledge of the channel coefficients or channel state information (CSI). However, in practical situations that fail the assumption, the MLSE method becomes suboptimal and then exhaustive checking is the only way to obtain the ML sequence. At this background, considering directly the ML criterion for partial CSI, we propose a two-phase low-complexity MLSE algorithm, in which the first phase performs the conventional MLSE algorithm in order to retain necessary information for the backward VA performed in the second phase. Simulations show that when the training sequence is moderately long in comparison with the entire data block such as 1/3 of the block, the proposed two-phase MLSE can approach the performance of the optimal exhaustive checking. In a normal case, where the training sequence consumes only 0.14 of the bandwidth, our proposed method still outperforms evidently the conventional MLSE.Comment: 5 pages and 4 figure

The Selection Strategy for Circulating Tumor Cells (CTCs) Isolation and Enumeration: Technical Features, Methods, and Clinical Applications

The key aim of the proposed chapter is to provide readers a brief description for the most important parts of the field of circulating tumor cells (CTCs): the core techniques, including negative and positive selection‐based CTC isolation, and the differences between them. Most importantly, we will also review the clinical applications and important findings in clinical trials. The evidence‐based review will not only help clinicians use CTCs to predict recurrence and foresee the disease‐related outcomes but also to inspire the researchers in this field to conduct further investigations

Low Polarization Voltage and High Sensitivity CMOS Condenser Microphone Using Stress Relaxation Design

AbstractIn this paper, a CMOS condenser microphone with high sensitivity and low polarization voltage was designed, simulated and fabricated. Due to CMOS process temperature variant and lattice defects, the poly-membrane would be invoked normal stress and gradient stress. These two residual stresses would deform the membrane and increase the membrane's rigidity. For these concerns, an interlace slots design is utilized to reduce the normal stress up to 90%, and the annealing process is applied to decrease the gradient stress. The acoustical sensitivity was increased considerably to -45dBV at 2.7V bias voltage, and, the noise level is -85dBV at 1KHz

Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms

A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete

Disordered Fe vacancies and superconductivity in potassium-intercalated iron selenide (K2-xFe4+ySe5)

The parent compound of an unconventional superconductor must contain unusual correlated electronic and magnetic properties of its own. In the high-Tc potassium intercalated FeSe, there has been significant debate regarding what the exact parent compound is. Our studies unambiguously show that the Fe-vacancy ordered K2Fe4Se5 is the magnetic, Mott insulating parent compound of the superconducting state. Non-superconducting K2Fe4Se5 becomes a superconductor after high temperature annealing, and the overall picture indicates that superconductivity in K2-xFe4+ySe5 originates from the Fe-vacancy order to disorder transition. Thus, the long pending question whether magnetic and superconducting state are competing or cooperating for cuprate superconductors may also apply to the Fe-chalcogenide superconductors. It is believed that the iron selenides and related compounds will provide essential information to understand the origin of superconductivity in the iron-based superconductors, and possibly to the superconducting cuprates