For practical implementation of massive multiple-input multiple-output (MIMO) systems, the hybrid processing (precoding/combining) structure is promising to reduce the high implementation cost and ...power consumption rendered by large number of radio frequency (RF) chains of the traditional processing structure. The hybrid processing is realized through low-dimensional digital baseband processing combined with analog RF processing enabled by phase shifters. We propose to design hybrid RF and baseband precoders/combiners for multistream transmission in massive MIMO systems, by directly decomposing the predesigned unconstrained digital precoder/combiner of a large dimension. This approach is fundamental and general in the sense that any conventional full RF chain precoding solution of a MIMO system configuration can be converted to a hybrid processing structure by matrix decomposition. The constant amplitude constraint of analog RF processing results in the matrix decomposition problem nonconvex. Based on an alternate optimization technique, the nonconvex matrix decomposition problem can be decoupled into a series of convex subproblems and effectively solved by restricting the phase increment of each entry in the RF precoder/combiner within a small vicinity of its preceding iterate. A singular value decomposition-based technique is proposed to secure an initial point sufficiently close to the global solution of the original nonconvex problem. Through simulation, the convergence of the alternate optimization for such a matrix decomposition-based hybrid processing (MD-HP) scheme is examined, and the performance of the MD-HP scheme is demonstrated to be near-optimal.
A review of the salinity measurement technology based on the optical fiber sensor is presented. The principles of optical fiber measurement, the structures of probes and the characteristics of ...various sensing structures are concerned. Firstly, this paper discusses the relationship between the salinity and refractive index, and the effect of ion pairs on the refractive index. Secondly, four methods of direct or non-direct measurements of salinity are summarized, including optical refraction method, optical fiber grating, optical interference and surface plasmon effect. Subsequently, the article compares performances of various sensing structures and analyses the advantages and disadvantages of different sensors. Finally, a prospect of salinity measurement requirement and the development direction of fiber-optic sensors in this area are addressed.
Inflammatory bowel disease (IBD), which mainly includes ulcerative colitis (UC) and Crohn's disease (CD), is a group of chronic bowel diseases that are characterized by abdominal pain, diarrhea, and ...bloody stools. IBD is strongly associated with depression, and its patients have a higher incidence of depression than the general population. Depression also adversely affects the quality of life and disease prognosis of patients with IBD. The tryptophan-kynurenine metabolic pathway degrades more than 90% of tryptophan (TRP) throughout the body, with indoleamine 2,3-dioxygenase (IDO), the key metabolic enzyme, being activated in the inflammatory environment. A series of metabolites of the pathway are neurologically active, among which kynerunic acid (KYNA) and quinolinic acid (QUIN) are molecules of great interest in recent studies on the mechanisms of inflammation-induced depression. In this review, the relationship between depression in IBD and the tryptophan-kynurenine metabolic pathway is overviewed in the light of recent publications.
In this work, a simple and rapid approach was developed for separation and detection of chiral compounds based on a magnetic molecularly imprinted polymer modified poly(dimethylsiloxane) (PDMS) ...microchip coupled with electrochemical detection. Molecularly imprinted polymers were prepared employing Fe3O4 nanoparticles (NPs) as the supporting substrate and norepinephrine as the functional monomer in the presence of template molecule in a weak alkaline solution. After extracting the embedded template molecules, Fe3O4@polynorepinephrine NPs (MIP–Fe3O4@PNE NPs) showed specific molecular recognition selectivity and high affinity towards the template molecule, which were then used as stationary phase of microchip capillary electrochromatography for chiral compounds separation. Mandelic acid and histidine enantiomers were used as model compounds to test the chiral stationary phase. By using R‐mandelic acid as the template molecule, mandelic acid enantiomer was effectively separated and detected on the MIP‐Fe3O4@PNE NPs modified PDMS microchip. Moreover, the successful separation of histidine enantiomers on the MIP–Fe3O4@PNE NPs modified microchip using L‐histidine as template molecule was also achieved.
Defects on product surfaces affect quality of the product. Machine vision provides an efficient tool for the surface defect detection. Threshold is commonly used to separate objects from the image ...background in the vision-based inspection method. The Otsu method is one of the most used approaches to decide the threshold for a satisfied result when the image histogram is bimodal, but it fails when the histogram of an image is unimodal or close to unimodal. Defects in product surfaces can range from small to large sizes, which results in distributions of the image histogram change from unimodal to bimodal. An improved Otsu method, named the weighted object variance (WOV), is proposed in this research to detect defects on product surfaces. A parameter that equals the cumulative probability of defects occurrence is weighted on the object variance of between-class variance. The weight ensures that the threshold always be a value that locates at the valley of two peaks or at the left bottom rim of a single peak histogram. It is essential to have a high detection rate and low false alarm rate for the defect detection. Experimental results demonstrate the effectiveness of the improved Otsu method in the defect detection of various surfaces. Compared to other thresholding methods such as maximum entropy, Otsu, valley-emphasis, and modified valley-emphasis methods, the WOV method provides better segmentation results.
An unprecedented Rauhut–Currier‐type 1,6‐conjugate addition has been developed. With chiral cyclohexane‐based phosphine‐amide catalyst 3 h, the 1,6‐conjugate reaction has been achieved to produce ...chiral diarylmethine compounds in excellent yields (91–99 %) and enantioselectivities (92–98 % ee).
Addition methide‐ology: The first enantioselective Rauhut–Currier‐type 1,6‐conjugate addition of para‐quinone methides has been developed. Chiral multifunctional diarylmethine compounds were achieved in excellent yields and enantioselectivities.
Abstract
The broadband emission of numerous pulsar wind nebula (PWNe) in our Galaxy can be well described by synchrotron radiation and inverse Compton scattering from relativistic particles, ...specifically electrons and positrons. However, the particle transport mechanism is still under debate. We use here a time-dependent model to investigate the particle transport process of the young PWN, while the particle cooling processes are also analyzed. Following applications of the model to six young PWNe, our results show that (1) the particle cooling process is dominated by adiabatic loss in the low-energy band but by synchrotron loss in the high-energy band; (2) the advection dominates the particle transport process in the low-energy band, whereas the advection and diffusion codominate in the high-energy band, indicating that both advection and diffusion play an important role in particle transport; and (3) the diffusion coefficient is (2–360) × 10
24
cm
2
s
−1
at the electron energy of 1 TeV, i.e., about 3 orders of magnitude smaller than the value considered to be the average in the Galaxy. We conclude that a slow-diffusion mechanism may explain the multiband observation of the sample of six young PWNe considered in this study.
Summary
Background and Aims
We aimed to define gender‐specific, optimal alanine aminotransferase (ALT) cut‐off values for the prediction of significant liver histological changes (SLHC) in Chinese ...patients with grey zone (GZ) chronic hepatitis B (CHB) and normal ALT.
Methods
In a retrospective study, we included 1101 consecutive patients with GZ CHB and normal ALT assigned to training or internal validation cohorts. We included an independent cohort of 842 patients for external validation. We performed receiver operating characteristic (ROC) curve, smoothed curve fitting, and threshold effect analyses to determine optimal ALT cut‐off values. Area under the curve (AUC) values were calculated to assess their predictive performance.
Results
A proportion of 79.3% of patients with GZ CHB and normal ALT (≤40 U/L) had SLHC. ROC curve analysis initially identified optimal ALT cut‐off values of 29 U/L (male) and 22 U/L (female). After smoothed curve fitting and threshold effect analyses, new optimal cut‐off values were 27 U/L for males and 24 U/L for females. AUCs for these values were 0.836 (male) and 0.833 (female) in the internal validation cohort, and 0.849 (male) and 0.844 (female) in the external validation cohort. The accuracy and discriminative ability of the newly defined ALT cut‐off values were greater than those of the current recommendations.
Conclusion
This study established novel optimal ALT cut‐off values for more precise prediction of SLHC among Chinese patients with GZ CHB and normal ALT levels. This may help identify individuals who will benefit from timely antiviral therapy.
1101 antiviral treatment naïve CHB patients in the grey zone (GZ) with normal ALT 1.60.1%‐79.3% in GZ CHB patient groups with different upper limits of normal (ULNs) for ALT have SLHC 2. The new optimal ALT cut‐offs to predict SLHC were 27U/L (male) and 24U/L (female).
We present a unified approach to the design of two well-known classes of computationally efficient digital filters, namely the interpolated and frequency-response-masking (FRM) FIR filters, that are ...optimized in minimax sense. The highly nonconvex minimax designs of these filters are carried out by jointly optimizing the subfilters involved using a convex-concave procedure (CCP) that yields an iterative and converging process where each iteration involves a convex problem of minimizing a linear function subject to convex quadratic constraints. We present an analysis to explain why CCP is well-suited for the design problems at hand. We also show that the CCP-based design framework is flexible to allow extension to the design of FRM filters that simultaneously promotes sparsity of the filter coefficients to reduce implementation complexity. Design examples with comparisons are presented to demonstrate the performance of the proposed design methods.
In the rapidly advancing ubiquitous intelligence society, the role of data as a valuable resource has become paramount. As a result, there is a growing need for the development of autonomous economic ...agents (AEAs) capable of intelligently and autonomously trading data. These AEAs are responsible for acquiring, processing, and selling data to entities such as software companies. To ensure optimal profitability, an intelligent AEA must carefully allocate its portfolio, relying on accurate return estimation and well-designed models. However, a significant challenge arises due to the sensitive and confidential nature of data trading. Each AEA possesses only limited local information, which may not be sufficient for training a robust and effective portfolio allocation model. To address this limitation, we propose a novel data trading market where AEAs exclusively possess local market information. To overcome the information constraint, AEAs employ federated learning (FL) that allows multiple AEAs to jointly train a model capable of generating promising portfolio allocations for multiple data products. To account for the dynamic and ever-changing revenue returns, we introduce an integration of the histogram of oriented gradients (HoGs) with the discrete wavelet transformation (DWT). This innovative combination serves to redefine the representation of local market information to effectively handle the inherent nonstationarity of revenue patterns associated with data products. Furthermore, we leverage the transform domain of local model drifts in the global model update process, effectively reducing the communication burden and significantly improving training efficiency. Through simulations, we provide compelling evidence that our proposed schemes deliver superior performance across multiple evaluation metrics, including test loss, cumulative return, portfolio risk, and Sharpe ratio.
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