Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering

As the common clustering algorithms use vector space model (VSM) to represent document, the conceptual relationships between related terms which do not co-occur literally are ignored. A genetic algorithm-based clustering technique, named GA clustering, in conjunction with ontology is proposed in this article to overcome this problem. In general, the ontology measures can be partitioned into two categories: thesaurus-based methods and corpus-based methods. We take advantage of the hierarchical structure and the broad coverage taxonomy of Wordnet as the thesaurus-based ontology. However, the corpus-based method is rather complicated to handle in practical application. We propose a transformed latent semantic analysis (LSA) model as the corpus-based method in this paper. Moreover, two hybrid strategies, the combinations of the various similarity measures, are implemented in the clustering experiments. The results show that our GA clustering algorithm, in conjunction with the thesaurus-based and the LSA-based method, apparently outperforms that with other similarity measures. Moreover, the superiority of the GA clustering algorithm proposed over the commonly used k-means algorithm and the standard GA is demonstrated by the improvements of the clustering performance

Exploiting Quorum Sensing Interfering Strategies in Gram-Negative Bacteria for the Enhancement of Environmental Applications

Quorum sensing (QS) is a widespread intercellular form of communication to coordinate physiological processes and cooperative activities of bacteria at the population level, and it depends on the production, secretion, and detection of small diffusible autoinducers, such as acyl-homoserine lactones (AHLs), auto-inducing oligo-peptides (AIPs) and autoinducer 2. In this review, the function of QS autoinducers of gram-negative bacteria in different aspects of wastewater treatment systems is examined. Based on research primarily performed over the past ten years, QS involvement in the formation of biofilm and aerobic granules and changes of the microbial community and degradation/transformation pathways is discussed. In particular, the QS pathway in the role of bacterial infections and disease prevention in aquaculture is addressed. Interference of QS autoinducer-regulated pathways is considered potential treatment for a variety of environmentally related problems. This review is expected to serve as a stepping stone for further study and development strategies based on the mediation of QS-regulated pathways to enhance applications in both wastewater treatment systems and aquaculture

Indole contributes to tetracycline resistance via the outer membrane protein OmpN in Vibrio splendidus

As an interspecies and interkingdom signaling molecule, indole has recently received attention for its diverse effects on the physiology of both bacteria and hosts. In this study, indole increased the tetracycline resistance of Vibrio splendidus. The minimal inhibitory concentration of tetracycline was 10 mu g/mL, and the OD600 of V. splendidus decreased by 94.5% in the presence of 20 mu g/mL tetracycline; however, the OD600 of V. splendidus with a mixture of 20 mu g/mL tetracycline and 125 mu M indole was 10- or 4.5-fold higher than that with only 20 mu g/mL tetracycline at different time points. The percentage of cells resistant to 10 mu g/mL tetracycline was 600-fold higher in the culture with an OD600 of approximately 2.0 (higher level of indole) than that in the culture with an OD600 of 0.5, which also meant that the level of indole was correlated to the tetracycline resistance of V. splendidus. Furthermore, one differentially expressed protein, which was identified as the outer membrane porin OmpN using SDS-PAGE combined with MALDI-TOF/TOF MS, was upregulated. Consequently, the expression of the ompN gene in the presence of either tetracycline or indole and simultaneously in the presence of indole and tetracycline was upregulated by 1.8-, 2.54-, and 6.01-fold, respectively, compared to the control samples. The combined results demonstrated that indole enhanced the tetracycline resistance of V. splendidus, and this resistance was probably due to upregulation of the outer membrane porin OmpN

Unscented Particle Filtering Algorithm for Optical-fiber Sensing Intrusion Localization Based on Particle Swarm Optimization

To improve the convergence and precision of intrusion localization in optical-fiber sensing perimeter protection applications, we present an algorithm based on an unscented particle filter (UPF). The algorithm employs particle swarm optimization (PSO) to mitigate the sample degeneracy and impoverishment problem of the particle filter. By comparing the present fitness value of particles with the optimum fitness value of the objective function, PSO moves particles with insignificant UPF weights towards the higher likelihood region and determines the optimal positions for particles with larger weights. The particles with larger weights results in a new sample set with a more balanced distribution between the priors and the likelihood. Simulations demonstrate that the algorithm speeds up convergence and improves the precision of intrusion localization

Peer-to-peer energy trading in electrical distribution networks

In response to the challenges posed by the increasing penetration of distributed generation from renewable energy sources and the increasing electricity retail prices with decreasing Feed-In Tariff rates, a new energy trading arrangement, “peer-to-peer (P2P) energy trading” has been proposed. It refers to the direct energy trading among consumers and prosumers in distribution networks, which is developed based on the “P2P economy” concept (also known as sharing economy). A hierarchical system architecture model has been proposed in order to identify and categorise the key elements and technologies involved in P2P energy trading. A P2P energy trading platform called “Elecbay” is designed. The P2P bidding is simulated using game theory. Test results in a grid-connected LV Microgrid with distributed generators and flexible demands show that P2P energy trading is able to improve the local balance of energy generation and consumption, and the enhanced variety of peers is able to further facilitate the balance. Two necessary control systems are proposed for the Microgrid with “Elecbay”. A voltage control system which combines droop control and on-load-tap-changer (OLTC) control is designed and simulated. Simulation results show that the proposed voltage control system is sufficient for supporting the P2P energy trading in the Microgrid. The total number of operation times of the OLTC is reduced with P2P energy trading compared to the reference scenario. The information and communication technology (ICT) infrastructures for the P2P bidding platform and the voltage control system are investigated. The information exchange among peers and other parties (Elecbay, distribution system operators, etc.) is designed based on TCP/IP protocol. Existing and private communication networks with different communication medium, bandwidths, etc., are modelled. Simulation results show that the existing ICT infrastructures are sufficient for supporting both the P2P energy trading platform and the voltage control system. Therefore, no large amount of additional investments are required

Review of existing peer-to-peer energy trading projects

Peer-to-Peer (P2P) energy trading is a novel paradigm of power system operation, where people can generate their own energy from Renewable Energy Sources (RESs) in dwellings, offices and factories, and share it with each other locally. The number of projects and trails in this area has significantly increased recently all around the world. This paper elaborates main focuses and outcomes of those projects, and compares their similarities and differences. The results show that although many of the trails focus on the business models acting similarly to a supplier's role in the electricity sector, it is also necessary to design the necessary communication and control networks that could enable P2P energy trading in or among local Microgrids

Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering

As the common clustering algorithms use vector space model (VSM) to represent document, the conceptual relationships between related terms which do not co-occur literally are ignored. A genetic algorithm-based clustering technique, named GA clustering, in conjunction with ontology is proposed in this article to overcome this problem. In general, the ontology measures can be partitioned into two categories: thesaurus-based methods and corpus-based methods. We take advantage of the hierarchical structure and the broad coverage taxonomy of Wordnet as the thesaurus-based ontology. However, the corpus-based method is rather complicated to handle in practical application. We propose a transformed latent semantic analysis (LSA) model as the corpus-based method in this paper. Moreover, two hybrid strategies, the combinations of the various similarity measures, are implemented in the clustering experiments. The results show that our GA clustering algorithm, in conjunction with the thesaurus-based and the LSA-based method, apparently outperforms that with other similarity measures. Moreover, the superiority of the GA clustering algorithm proposed over the commonly used k-means algorithm and the standard GA is demonstrated by the improvements of the clustering performance

Spinal column shortening versus revision detethering for recurrent adult tethered cord syndrome: a preliminary comparison of perioperative and clinical outcomes.

OBJECTIVE:Recurrent tethered cord syndrome (TCS), believed to result from tension on the distal portion of the spinal cord, causes a constellation of neurological symptoms. Detethering surgery has been the traditional treatment for TCS. However, in cases of recurrent TCS, there is a risk of new neurological deficits developing, and subsequent retethering is difficult to prevent. Spinal column shortening has been proposed as an alternative technique to reduce the tension on the spinal cord without incurring the morbidity of revision surgery on the spinal cord. The authors compared the perioperative outcomes and morbidity of patients who were treated with one or the other procedure. METHODS:The medical records of 16 adult patients with recurrent TCS who were treated between 2005 and 2018 were reviewed. Eight patients underwent spinal column shortening, and 8 patients underwent revision detethering surgery. Patient demographics, clinical outcomes, and perioperative factors were analyzed. The authors include a video to illustrate their technique of spinal column shortening. RESULTS:Within the spinal column shortening group, no patients experienced any complications, and all 8 patients either improved or stabilized with regard to lower-extremity and bowel and bladder function. Within the revision detethering group, 2 patients had worsening of lower-extremity strength, 3 patients had worsening of bowel and bladder function, and 1 patient had improvement in bladder function. Also, 3 patients had wound-related complications. The median estimated blood loss was 731 ml in the shortening group and 163 ml in the revision detethering group. The median operative time was 358 minutes in the shortening group and 226 minutes in the revision detethering group. CONCLUSIONS:Clinical outcomes were comparable between the groups, but none of the spinal column shortening patients experienced worsening, whereas 3 of the revision detethering patients did and also had wound-related complications. Although the operative times and blood loss were higher in the spinal column shortening group, this procedure may be an alternative to revision detethering in extremely scarred or complex wound revision cases

A bidding system for peer-to-peer energy trading in a grid-connected microgrid

Peer-to-Peer (P2P) energy trading is a novel paradigm of power system operation, where people can generate their own energy from Renewable Energy Sources (RESs) in dwellings, offices and factories, and share it with each other locally. An architecture model was proposed to present the design and interoperability aspects of components for P2P energy trading in a microgrid. A specific Customer-to-Customer business model was introduced in a benchmark grid-connected microgrid based on the architecture model. The core component of a bidding system, called Elecbay, was also proposed and simulated using game theory. Test results show that P2P energy trading is able to balance local generation and demand, therefore, has a potential to enable a large penetration of RESs in the power grid

Terminology-aware Medical Dialogue Generation

Medical dialogue generation aims to generate responses according to a history of dialogue turns between doctors and patients. Unlike open-domain dialogue generation, this requires background knowledge specific to the medical domain. Existing generative frameworks for medical dialogue generation fall short of incorporating domain-specific knowledge, especially with regard to medical terminology. In this paper, we propose a novel framework to improve medical dialogue generation by considering features centered on domain-specific terminology. We leverage an attention mechanism to incorporate terminologically centred features, and fill in the semantic gap between medical background knowledge and common utterances by enforcing language models to learn terminology representations with an auxiliary terminology recognition task. Experimental results demonstrate the effectiveness of our approach, in which our proposed framework outperforms SOTA language models. Additionally, we provide a new dataset with medical terminology annotations to support the research on medical dialogue generation. Our dataset and code are available at https://github.com/tangg555/meddialog.Comment: Submitted to ICASSP 202