A CONCEPTUAL FRAMEWORK FOR MOBILE GROUP SUPPORT SYSTEMS

The rapid development of wireless communication and mobile devices has created a great opportunity to support mobile group coordination at a more efficient level than before. This article presents a framework for Mobile Group Support Systems (MGSS) that considers four dimensions: supporting whom, supporting what, where to support and how to support. A good MGSS design should take consideration with the characteristics of each dimension: the system should be able to support mobile users working jointly with members from multiple parties; using available and advanced mobile technology, the system should be able to support context freedom, context dependent, and ad hoc coordination under dynamic, uncertain, frequent disrupting, time and space stretched and fluid context. To meet these requirements, we discuss the issues related to three basic functions of MGSS: mobile communication, group coordination, and context awareness

Therapeutic effects of ulinastatin on postoperative complications and cognitive function in elderly patients with esophageal cancer after thoracic laparoscopic surgery

Purpose: To investigate the therapeutic effect of ulinastatin on postoperative complications and cognitive function in elderly patients with esophageal cancer after thoracic laparoscopic surgery. Methods: A total of 100 elderly in-patients with esophageal cancer who had undergone thoracic laparoscopic surgery from April 2019 to December 2020 were selected and randomly assigned to control and study groups. Patients in control group received conventional treatment, while those in the study group were administered ulinastatin. The two groups were compared with respect to response, incidence of postoperative complications, Mini-Mental State Examination (MMSE) cognitive function score, Barthel Index (BI) scores; preoperative, intraoperative, 12-h and 24-h post-surgery levels of IL-1β and IL-6; levels of CD3+, CD4+ and CD8+, as well as duration of surgery and waking time. Results: Response, MMSE score, BI index, and levels of CD3+, CD4+ and CD8+ in the study group were significantly higher than those in the control group (p < 0.05). Incidence of postoperative complications, and expression levels of IL-1β and IL-6 12 h and 24 h after surgery in the study group were lower than the corresponding control levels (p < 0.05). There were no significant differences in duration of operation and waking time between the two groups (p > 0.05). Conclusion: Ulinastatin significantly reduces postoperative complications, and also improves cognitive function in elderly patients with esophageal cancer after thoracic laparoscopic surgery. This finding is of great significance in the treatment of these patients

Honest Score Client Selection Scheme: Preventing Federated Learning Label Flipping Attacks in Non-IID Scenarios

Federated Learning (FL) is a promising technology that enables multiple actors to build a joint model without sharing their raw data. The distributed nature makes FL vulnerable to various poisoning attacks, including model poisoning attacks and data poisoning attacks. Today, many byzantine-resilient FL methods have been introduced to mitigate the model poisoning attack, while the effectiveness when defending against data poisoning attacks still remains unclear. In this paper, we focus on the most representative data poisoning attack - "label flipping attack" and monitor its effectiveness when attacking the existing FL methods. The results show that the existing FL methods perform similarly in Independent and identically distributed (IID) settings but fail to maintain the model robustness in Non-IID settings. To mitigate the weaknesses of existing FL methods in Non-IID scenarios, we introduce the Honest Score Client Selection (HSCS) scheme and the corresponding HSCSFL framework. In the HSCSFL, The server collects a clean dataset for evaluation. Under each iteration, the server collects the gradients from clients and then perform HSCS to select aggregation candidates. The server first evaluates the performance of each class of the global model and generates the corresponding risk vector to indicate which class could be potentially attacked. Similarly, the server evaluates the client's model and records the performance of each class as the accuracy vector. The dot product of each client's accuracy vector and global risk vector is generated as the client's host score; only the top p\% host score clients are included in the following aggregation. Finally, server aggregates the gradients and uses the outcome to update the global model. The comprehensive experimental results show our HSCSFL effectively enhances the FL robustness and defends against the "label flipping attack.

Semantic Change Driven Generative Semantic Communication Framework

The burgeoning generative artificial intelligence technology offers novel insights into the development of semantic communication (SemCom) frameworks. These frameworks hold the potential to address the challenges associated with the black-box nature inherent in existing end-to-end training manner for the existing SemCom framework, as well as deterioration of the user experience caused by the inevitable error floor in deep learning-based semantic communication. In this paper, we focus on the widespread remote monitoring scenario, and propose a semantic change driven generative SemCom framework. Therein, the semantic encoder and semantic decoder can be optimized independently. Specifically, we develop a modular semantic encoder with value of information based semantic sampling function. In addition, we propose a conditional denoising diffusion probabilistic mode-assisted semantic decoder that relies on received semantic information from the source, namely, the semantic map, and the local static scene information to remotely regenerate scenes. Moreover, we demonstrate the effectiveness of the proposed semantic encoder and decoder as well as the considerable potential in reducing energy consumption through simulation. The code is available at https://github.com/wty2011jl/SCDGSC.gi

Effect of microwave treatment on the physicochemical properties of potato starch granules

BACKGROUND: The degree of polymerization of amylose starch in potato was so large that the gel was hardness after gelatinization. Therefore, it is one of the most important ways that the microwave treatment was used to change the physicochemical properties of starch gel to make it suitable for the preparation of instant food. RESULTS: The effect of microwave treatment on the physicochemical properties including morphology, crystalline structure, molecular weight distribution and rheological properties of potato starch granules was evaluated by treating time of varying duration (0, 5, 10, 15, 20 s) at 2450 MHz and 750 W. Scanning electron micrographs (SEM) of potato starch granules showed flaws or fractures on the surface after 5 to 10s of microwaving and collapse after 15 to 20 s. Polarized light microscopy (PLM) indicated that microwave treating damaged the crystalline structure of potato starch, such that the birefringence of starch granules gradually decreased after 5 to 10s and even disappeared after microwaving from 15 to 20 s. The molecular weight (Mw) values of potato starch and the proportion of large M(W) fraction were considerably reduced with increasing the microwave treating time from 0 to 20s. The molecular weight slowly decreased over 5 ~ 15 s microwave treating but decreased abruptly at the time of 20s microwave treating. The apparent viscosity decreased as shear rate increased and presented shear-thinning behavior. The magnitudes of the storage modulus (G’) and loss modulus (G”) obtained at each shear rate increased with duration of microwave treating from 0 to 15 s but decreased from 15 to 20 s. CONCLUSIONS: These results demonstrated that the morphology and crystalline structure was damaged by microwave treatment. The high molecular weight of potato starch above 2 × 10(8) Da was so sensitive to the vibrational motion of the polar molecules due to the application microwave energy and broke easily for longer dextran chains. The fracture of starch granules, molecular chains leached from the starch granules and degradation of dextran chains contributing to the development of rheological properties

Survival and Stationary Distribution in a Stochastic SIS Model

The dynamics of a stochastic SIS epidemic model is investigated. First, we show that the system admits a unique positive global solution starting from the positive initial value. Then, the long-term asymptotic behavior of the model is studied: when 0 ≤ 1, we show how the solution spirals around the disease-free equilibrium of deterministic system under some conditions; when 0 > 1, we show that the stochastic model has a stationary distribution under certain parametric restrictions. In particular, we show that random effects may lead the disease to extinction in scenarios where the deterministic model predicts persistence. Finally, numerical simulations are carried out to illustrate the theoretical results