A Fuzzy Petri Nets Model for Computing With Words

Motivated by Zadeh's paradigm of computing with words rather than numbers, several formal models of computing with words have recently been proposed. These models are based on automata and thus are not well-suited for concurrent computing. In this paper, we incorporate the well-known model of concurrent computing, Petri nets, together with fuzzy set theory and thereby establish a concurrency model of computing with words--fuzzy Petri nets for computing with words (FPNCWs). The new feature of such fuzzy Petri nets is that the labels of transitions are some special words modeled by fuzzy sets. By employing the methodology of fuzzy reasoning, we give a faithful extension of an FPNCW which makes it possible for computing with more words. The language expressiveness of the two formal models of computing with words, fuzzy automata for computing with words and FPNCWs, is compared as well. A few small examples are provided to illustrate the theoretical development.Comment: double columns 14 pages, 8 figure

State-Based Control of Fuzzy Discrete Event Systems

To effectively represent possibility arising from states and dynamics of a system, fuzzy discrete event systems as a generalization of conventional discrete event systems have been introduced recently. Supervisory control theory based on event feedback has been well established for such systems. Noting that the system state description, from the viewpoint of specification, seems more convenient, we investigate the state-based control of fuzzy discrete event systems in this paper. We first present an approach to finding all fuzzy states that are reachable by controlling the system. After introducing the notion of controllability for fuzzy states, we then provide a necessary and sufficient condition for a set of fuzzy states to be controllable. We also find that event-based control and state-based control are not equivalent and further discuss the relationship between them. Finally, we examine the possibility of driving a fuzzy discrete event system under control from a given initial state to a prescribed set of fuzzy states and then keeping it there indefinitely.Comment: 14 double column pages; 4 figures; to be published in the IEEE Transactions on Systems, Man, and Cybernetics--Part B: Cybernetic

A Vector Matroid-Theoretic Approach in the Study of Structural Controllability Over F(z)

In this paper, the structural controllability of the systems over F(z) is studied using a new mathematical method-matroids. Firstly, a vector matroid is defined over F(z). Secondly, the full rank conditions of [sI-A|B] are derived in terms of the concept related to matroid theory, such as rank, base and union. Then the sufficient condition for the linear system and composite system over F(z) to be structurally controllable is obtained. Finally, this paper gives several examples to demonstrate that the married-theoretic approach is simpler than other existing approaches

THz ISAC: A Physical-Layer Perspective of Terahertz Integrated Sensing and Communication

The Terahertz (0.1-10 THz) band holds enormous potential for supporting unprecedented data rates and millimeter-level accurate sensing thanks to its ultra-broad bandwidth. Terahertz integrated sensing and communication (ISAC) is viewed as a game-changing technology to realize connected intelligence in 6G and beyond systems. In this article, challenges from THz channel and transceiver perspectives, as well as difficulties of ISAC are elaborated. Motivated by these challenges, THz ISAC channels are studied in terms of channel types, measurement and models. Moreover, four key signal processing techniques to unleash the full potential of THz ISAC are investigated, namely, waveform design, receiver processing, narrowbeam management, and localization. Quantitative studies demonstrate the benefits and performance of the state-of-the-art signal processing methods. Finally, open problems and potential solutions are discussed

Sensing Integrated DFT-Spread OFDM Waveform and Deep Learning-powered Receiver Design for Terahertz Integrated Sensing and Communication Systems

Terahertz (THz) communications are envisioned as a key technology of next-generation wireless systems due to its ultra-broad bandwidth. One step forward, THz integrated sensing and communication (ISAC) system can realize both unprecedented data rates and millimeter-level accurate sensing. However, THz ISAC meets stringent challenges on waveform and receiver design to fully exploit the peculiarities of THz channel and transceivers. In this work, a sensing integrated discrete Fourier transform spread orthogonal frequency division multiplexing (SI-DFT-s-OFDM) system is proposed for THz ISAC, which can provide lower peak-to-average power ratio than OFDM and is adaptive to flexible delay spread of the THz channel. Without compromising communication capabilities, the proposed SI-DFT-s-OFDM realizes millimeter-level range estimation and decimeter-per-second-level velocity estimation accuracy. In addition, the bit error rate (BER) performance is improved by 5 dB gain at the $10^{-3}$ BER level compared with OFDM. At the receiver, a deep learning based ISAC receiver with two neural networks is developed to recover transmitted data and estimate target range and velocity, while mitigating the imperfections and non-linearities of THz systems. Extensive simulation results demonstrate that the proposed deep learning methods can realize mutually enhanced performance for communication and sensing, and is robust against Doppler effects, phase noise, and multi-target estimation

Predicting Extreme Returns in Chinese Stock Market: An Application of Contextual Fundamental Analysis

Prior empirical works have illustrated the effectiveness of contextual fundamental analysis for predicting extreme returns in US stock market. This study employs a similar analysis framework to examine extreme returns in the largest emerging (Chinese) stock market. We find that Chinese extreme-performing stocks have many characteristics in common with but some other characteristics inconsistent with their US counterparts, suggesting that Chinese investors might hold their specific preferences to stocks. Furthermore, the likelihoods of predicting Chinese extreme and non-extreme returns are enhanced with the application of contextual fundamental analysis, particularly in identifying bottom-performing stocks

Lung Epithelial Cell Transcriptional Regulation as a Factor in COVID-19 Associated Coagulopathies

SARS-CoV-2 has rapidly become a global pandemic. In addition to the acute pulmonary symptoms of COVID-19 (the disease associated with SARS-CoV-2 infection), pulmonary and distal coagulopathies have caused morbidity and mortality in many patients. Currently, the molecular pathogenesis underlying COVID-19 associated coagulopathies are unknown. Identifying the molecular basis of how SARS-CoV-2 drives coagulation is essential to mitigating short and long term thrombotic risks of sick and recovered COVID-19 patients. We aimed to perform coagulation focused transcriptome analysis of in vitro infected primary respiratory epithelial cells, patient derived bronchial alveolar lavage (BALF) cells, and circulating immune cells during SARS-CoV-2 infection. Our objective was to identify transcription mediated signaling networks driving coagulopathies associated with COVID-19. We analyzed recently published experimentally and clinically derived bulk or single cell RNA sequencing datasets of SARS-CoV-2 infection to identify changes in transcriptional regulation of blood coagulation. We also confirmed that the transcriptional expression of a key coagulation regulator was recapitulated at the protein level. We specifically focused our analysis on lung tissue expressed genes regulating the extrinsic coagulation cascade and the plasminogen activation system. Analyzing transcriptomic data of in vitro infected normal human bronchial epithelial (NHBE) cells and patient derived BALF samples revealed that SARS-CoV-2 infection induces the extrinsic blood coagulation cascade and suppresses the plasminogen activation system. We also performed in vitro SARS-CoV-2 infection experiments on primary human lung epithelial cells to confirm that transcriptional upregulation of Tissue Factor, the extrinsic coagulation cascade master regulator, manifested at the protein level. Further, infection of NHBEs with influenza A virus (IAV) did not drive key regulators of blood coagulation in a similar manner as SARS-CoV-2. Additionally, peripheral blood mononuclear cells (PBMCs) did not differentially express genes regulating the extrinsic coagulation cascade or plasminogen activation system during SARS-CoV-2 infection, suggesting that they are not directly inducing coagulopathy through these pathways. The hyper-activation of the extrinsic blood coagulation cascade and the suppression of the plasminogen activation system in SARS-CoV-2 infected epithelial cells may drive diverse coagulopathies in the lung and distal organ systems. Understanding how hosts drive such transcriptional changes with SARS-CoV-2 infection may enable the design of host-directed therapeutic strategies to treat COVID-19 and other coronaviruses inducing hyper-coagulation

Low Skeletal Muscle Mass Is Associated With Inferior Preoperative and Postoperative Shoulder Function in Elderly Rotator Cuff Tear Patients

BACKGROUND: The age-related loss of skeletal muscle mass is an important characteristic of sarcopenia, an increasingly recognized condition with systemic implications. However, its association with shoulder function in elderly patients with rotator cuff tears (RCT) remains unknown. This study aimed to investigate the relationship between low skeletal muscle mass and shoulder function in elderly RCT patients. METHODS: A retrospective analysis was conducted on RCT patients who underwent chest computed tomography (CT) scans for clinical evaluation. Preoperative CT scan images of the chest were used to calculate the cross-sectional area (CSA) of thoracic muscle at the T4 level. The medical records were reviewed. Shoulder function was assessed using the ASES score and CMS score both preoperatively and at the final follow-up. Data on the preoperative range of motion (ROM) for the affected shoulder, were collected for analysis. Subgroup analyses by sex were also performed. RESULTS: A total of 283 RCT patients, consisting of 95 males and 188 females, with a mean age of 66.22 ± 4.89(range, 60-95 years) years were included in this retrospective study. The low muscle mass group showed significantly higher level of c-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) compared to the normal group(3.75 ± 6.64 mg/L vs. 2.17 ± 2.30 mg/L, p = 0.021; 19.08 ± 12.86 mm/H vs.15.95 ± 10.76 mm/H, p = 0.038; respectively). In the normal group, pre-operative passive ROM, including forward elevation, abduction, lateral rotation, and abductive external rotation, was significantly better than that in the low muscle mass group (127.18 ± 34.87° vs. 89.76 ± 50.61°; 119.83 ± 45.76° vs. 87.16 ± 53.32°; 37.96 ± 28.33° vs. 25.82 ± 27.82°; 47.71 ± 23.56° vs. 30.87 ± 27.76°, all p \u3c 0.01, respectively). Similar results were found in the active ROM of the shoulder. The female low muscle mass group exhibited significantly poorer passive and active ROM (p \u3c 0.05). The post-operative ASES scores and CMS scores of the female low muscle mass group were also statistically worse than those of the female normal group (p \u3c 0.05). CONCLUSIONS: The results of present study revealed that the low skeletal muscle mass is associated with inferior ROM of the shoulder and per- and post-operative shoulder function, especially for elderly female patients