Efficient Spectrum Sharing Between Coexisting OFDM Radar and Downlink Multiuser Communication Systems

This paper investigates the problem of joint subcarrier and power allocation in the coexistence of radar and multi-user communication systems. Specifically, in our research scenario, the base station (BS) provides information transmission services for multiple users while ensuring that its interference to a separate radar system will not affect the radar's normal function. To this end, we propose a subcarrier and power allocation scheme based on orthogonal frequency division multiple access (OFDM). The original problem consisting involving multivariate fractional programming and binary variables is highly non-convex. Due to its complexity, we relax the binary constraint by introducing a penalty term, provided that the optimal solution is not affected. Then, by integrating multiple power variables into one matrix, the original problem is reformulated as a multi-ratio fractional programming (FP) problem, and finally a quadratic transform is employed to make the non-convex problem a sequence of convex problems. The numerical results indicate the performance trade-off between the multi-user communication system and the radar system, and notably that the performance of the communication system is not improved with power increase in the presence of radar interference beyond a certain threshold. This provides a useful insight for the energy-efficient design of the system.Comment: 6 pages, 5 figure

Characterization of anti-leukemia components from Indigo naturalis using comprehensive two-dimensional K562/cell membrane chromatography and in silico target identification.

Traditional Chinese Medicine (TCM) has been developed for thousands of years and has formed an integrated theoretical system based on a large amount of clinical practice. However, essential ingredients in TCM herbs have not been fully identified, and their precise mechanisms and targets are not elucidated. In this study, a new strategy combining comprehensive two-dimensional K562/cell membrane chromatographic system and in silico target identification was established to characterize active components from Indigo naturalis, a famous TCM herb that has been widely used for the treatment of leukemia in China, and their targets. Three active components, indirubin, tryptanthrin and isorhamnetin, were successfully characterized and their anti-leukemia effects were validated by cell viability and cell apoptosis assays. Isorhamnetin, with undefined cancer related targets, was selected for in silico target identification. Proto-oncogene tyrosine-protein kinase (Src) was identified as its membrane target and the dissociation constant (Kd) between Src and isorhamnetin was 3.81 μM. Furthermore, anti-leukemia effects of isorhamnetin were mediated by Src through inducing G2/M cell cycle arrest. The results demonstrated that the integrated strategy could efficiently characterize active components in TCM and their targets, which may bring a new light for a better understanding of the complex mechanism of herbal medicines

Development of high throughput microscope mode secondary ion mass spectrometry imaging

This paper describes the development and initial results from a secondary ion mass spectrometer coupled with microscope mode detection. Stigmatic ion microscope imaging enables us to decouple the primary ion (PI) beam focus from spatial resolution and is a promising route to attaining higher throughput for mass spectrometry imaging (MSI). Using a commercial C60+ PI beam source, we can defocus the PI beam to give uniform intensity across a 2.5 mm2 area. By coupling the beam with a position-sensitive spatial detector, we can achieve mass spectral imaging of positive and negative secondary ions (SIs), which we demonstrate using samples comprising metals and dyes. Our approach involves simultaneous desorption of ions across a large field of view, enabling mass spectral images to be recorded over an area of 2.5 mm2 in a matter of seconds. Our instrument can distinguish spatial features with a resolution of better than 20 μm, and has a mass resolution of >500 at 500 u. There is considerable scope to improve this, and through simulations we estimate the future performance of the instrument

Integrated Sensing and Communications: Recent Advances and Ten Open Challenges

It is anticipated that integrated sensing and communications (ISAC) would be one of the key enablers of next-generation wireless networks (such as beyond 5G (B5G) and 6G) for supporting a variety of emerging applications. In this paper, we provide a comprehensive review of the recent advances in ISAC systems, with a particular focus on their foundations, system design, networking aspects and ISAC applications. Furthermore, we discuss the corresponding open questions of the above that emerged in each issue. Hence, we commence with the information theory of sensing and communications (S$\&$C), followed by the information-theoretic limits of ISAC systems by shedding light on the fundamental performance metrics. Next, we discuss their clock synchronization and phase offset problems, the associated Pareto-optimal signaling strategies, as well as the associated super-resolution ISAC system design. Moreover, we envision that ISAC ushers in a paradigm shift for the future cellular networks relying on network sensing, transforming the classic cellular architecture, cross-layer resource management methods, and transmission protocols. In ISAC applications, we further highlight the security and privacy issues of wireless sensing. Finally, we close by studying the recent advances in a representative ISAC use case, namely the multi-object multi-task (MOMT) recognition problem using wireless signals.Comment: 26 pages, 22 figures, resubmitted to IEEE Journal. Appreciation for the outstanding contributions of coauthors in the paper

The Case-Only Test for Gene-Environment Interaction is Not Uniformly Powerful: An Empirical Example: Gene-Environment Interaction

The case-only test has been proposed as a more powerful approach to detect gene-environment (G×E) interactions. This approach assumes that the genetic and environmental factors are independent. While it is well known that Type I error rate will increase if this assumption is violated, it is less widely appreciated that gene-environment correlation can also lead to power loss. We illustrate this phenomenon by comparing the performance of the case-only test to other approaches to detect G×E interactions in a genome-wide association study of esophageal squamous carcinoma (ESCC) in Chinese populations. Some of these approaches do not use information on the correlation between exposure and genotype (standard logistic regression), while others seek to use this information in a robust fashion to boost power without increasing Type I error (two-step, empirical Bayes and cocktail methods). G×E interactions were identified involving drinking status and two regions containing genes in the alcohol metabolism pathway, 4q23 and 12q24. Although the case-only test yielded the most significant tests of G×E interaction in the 4q23 region, the case-only test failed to identify significant interactions in the 12q24 region which were readily identified using other approaches. The low power of the case-only test in the 12q24 region is likely due to the strong inverse association between the SNPs in this region and drinking status. This example underscores the need to consider multiple approaches to detect gene-environment interactions, as different tests are more or less sensitive to different alternative hypotheses and violations of the gene-environment independence assumption

Lack of Trehalose Accelerates H2O2-Induced Candida albicans Apoptosis through Regulating Ca2+ Signaling Pathway and Caspase Activity

Trehalose is a non-reducing disaccharide and can be accumulated in response to heat or oxidative stresses in Candida albicans. Here we showed that a C. albicans tps1Δ mutant, which is deficient in trehalose synthesis, exhibited increased apoptosis rate upon H2O2 treatment together with an increase of intracellular Ca2+ level and caspase activity. When the intracellular Ca2+ level was stimulated by adding CaCl2 or A23187, both the apoptosis rate and caspase activity were increased. In contrast, the presence of two calcium chelators, EGTA and BAPTA, could attenuate these effects. Moreover, we investigated the role of Ca2+ pathway in C. albicans apoptosis and found that both calcineurin and the calcineurin-dependent transcription factor, Crz1p, mutants showed decreased apoptosis and caspase activity upon H2O2 treatment compared to the wild-type cells. Expression of CaMCA1, the only gene found encoding a C. albicans metacaspase, in calcineurin-deleted or Crz1p-deleted cells restored the cell sensitivity to H2O2. Our results suggest that Ca2+ and its downstream calcineurin/Crz1p/CaMCA1 pathway are involved in H2O2 -induced C. albicans apoptosis. Inhibition of this pathway might be the mechanism for the protective role of trehalose in C. albicans

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable