A knowledge based machine tool maintenance planning system Using case-based reasoning techniques

In advanced manufacturing systems, Computer Numerical Control (CNC) machine tools are important equipment to manufacture product components of high precision, whilst from equipment maintenance point of view, they are regarded as the ‘products’ provided by machine tool manufacturers. Therefore, the reliability of CNC machine tools affects not only the quality of the components they manufacture, but also the reputation and profits of equipment suppliers. This paper presents a novel knowledge-based maintenance planning system to facilitate information and knowledge sharing between all stakeholders including machine tool manufacturers, users (manufacturing systems), maintenance service providers and part suppliers (for machine tools), in the emerging ‘Product-Service’ business model. Case Based Reasoning principles have been implemented to improve the efficiency of maintenance planning. Ontologies were adopted to represent field knowledge using adaptation guided retrievals based on semantic similarity and correlation. The adaption algorithm has been developed based on the Casual Theory and the dependence relationship to generate the solution for required maintenance problems. The proposed system was implemented using Content Management technologies, which proved to have advantages over traditional database systems in managing engineering knowledge, and has been verified using an example CNC machine tool. The results were commented by industrial collaborators as very promising and further exploitation in industry was recommended

Knowledge management for maintenance, repair and service of manufacturing

Manufacturing equipment, such as numerical controlled machines and assembly cranes, requires constant maintenance and service in their operating lifecycle. Equipment maintenance plays an important role in avoiding unexpected failures and ensuring production efficiency. During maintenance operations, much data is generated and stored in databases. It is essential for manufacturing companies to develop a system to integrate equipment condition monitoring, fault prediction and knowledge base to support maintenance decisions. A case study, carried out within a power generator manufacturing organisation, was conducted to understand what the maintenance process is and how maintenance knowledge is currently managed. It was concluded that maintenance process is less efficient, and maintenance records, stored within internal databases, are not consistent, which makes knowledge hard to share, learn from and reuse. This paper proposes a Knowledge Management System for Maintenance, Repair and Service in Manufacturing Systems to support better maintenance decision and improve maintenance efficiency

Advances in the Application of Chromatographic Techniques in Forensic Toxicology Fund

With the gradual advancement of knowledge and civilization, forensic science and technology is steadily developing and evolving. Chromatography, as an important analytical technique with the advantages of simplicity, rapidity and high sensitivity, has been widely used by researchers in various countries in the process of detecting toxic substances and drugs in forensic science. This paper presents a comprehensive analysis and exploration of chromatographic techniques from three perspectives: the development of chromatography, its classification according to the two-phase state, chromatographic separation mechanism and the nature of the stationary phase, and the applications of chromatographic techniques. The future development trend of chromatographic analysis technology is also prospected in order to provide new ideas for the development and research2o2f other technologies in thefield of forensic science

Enhanced hydrogen storage properties of LiAlH4 catalyzed by CoFe2O4 nanoparticles

The catalytic effects of CoFe2O4 nanoparticles on the hydrogen storage properties of LiAlH4 prepared by ball milling were investigated. The onset desorption temperature of the LiAlH4 + 2 mol% CoFe2O4 sample is 65 °C, which is 90 °C lower that of the as-received LiAlH4, with approximately 7.2 wt% hydrogen released at 250 °C. The isothermal desorption results show that for the 2 mol% CoFe2O4 doped sample dehydrogenated at 120 °C, 6.8 wt% of hydrogen can be released within 160 min, which is 6.1 wt% higher than that of the as-received LiAlH4 under the same conditions. Through the differential scanning calorimetry (DSC) and the Kissinger desorption kinetics analyses, the apparent activation energy, Ea, of the 2 mol% CoFe2O4 doped sample is calculated as 52.4 kJ mol -1 H2 and 86.5 kJ mol-1 H2 for the first two decomposition processes. This is 42.4 kJ mol-1 H 2 and 86.1 kJ mol-1 H2 lower compared with the pristine LiAlH4, respectively, indicating considerably improved dehydrogenation kinetics by doping the CoFe2O4 catalyst in the LiAlH4 matrix. From the Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyses, a series of finely dispersed Fe and Co species with a range of valence states, produced from the reactions between LiAlH4 and CoFe2O4, play a synergistic role in remarkably improving LiAlH4 dehydrogenation properties. The rehydrogenation properties of the LiAlH4 + 2 mol% CoFe 2O4 sample have also been investigated at 140 °C under 6.5 MPa pressure held for 2.5 hPeer ReviewedPostprint (published version

Safety, tolerability, and pharmacokinetics of TG-1000, a new molecular entity against influenza virus: first-in-human study

Background: The cap-snatching mechanism of influenza virus mRNA transcription is strongly suppressed by TG-1000, a prodrug rapidly metabolized into TG-0527, is a potent cap-dependent nucleic acid endonuclease inhibitor. Herein, we aimed to assess the safety, tolerability, and pharmacokinetics of TG-1000 in healthy participants and the effect of food on the pharmacokinetics and safety of TG-1000.Method: The study was divided into 2 parts: Part A [Single Ascending-Dose (SAD) study, 10–160 mg] and Part B [Food-Effect (FE) study, 40 mg] were launched sequentially. The study included 66 participants for both investigations. We administered different TG-1000 capsules or placebo doses per the study protocol and collected blood samples for pharmacokinetic assessments at specific times. In plasma, TG-1000 and its active metabolite TG-0527 were assayed, and PK parameters were determined.Results: In SAD, the increase in AUC was less than the proportional increase in dose over the 20–160 mg dose range, while the increase in Cmax was proportional to the increase in dose. In the 10–160 mg dose range, T1/2, λz and Tmax of TG-0527 were dose-independent; and T1/2 and Tmax were within 33.8–39.4 h and 3.02–6 h, respectively. In FE, the AUC0-inf, AUC0-last, and Cmax of TG-0527 decreased by approximately 17.52%, 18.76%, and 41.35%, respectively, and the Tmax delay was around 1.50 h. No serious adverse events occurred during the studies.Conclusion: Overall, TG-1000 was well tolerated and exhibited an acceptable safety and PK profile, supporting further clinical investigation of TG-1000 for the treatment of influenza

Phase Control on Surface for the Stabilization of High Energy Cathode Materials of Lithium Ion Batteries.

The development of high energy electrode materials for lithium ion batteries is challenged by their inherent instabilities, which become more aggravated as the energy densities continue to climb, accordingly causing increasing concerns on battery safety and reliability. Here, taking the high voltage cathode of LiNi0.5Mn1.5O4 as an example, we demonstrate a protocol to stabilize this cathode through a systematic phase modulating on its particle surface. We are able to transfer the spinel surface into a 30 nm shell composed of two functional phases including a rock-salt one and a layered one. The former is electrochemically inert for surface stabilization while the latter is designated to provide necessary electrochemical activity. The precise synthesis control enables us to tune the ratio of these two phases, and achieve an optimized balance between improved stability against structural degradation without sacrificing its capacity. This study highlights the critical importance of well-tailored surface phase property for the cathode stabilization of high energy lithium ion batteries

Polarization-based probabilistic discriminative model for quantitative characterization of cancer cells

We propose a polarization-based probabilistic discriminative model for deriving a set of new sigmoid-transformed polarimetry feature parameters, which not only enables accurate and quantitative characterization of cancer cells at pixel level, but also accomplish the task with a simple and stable model. By taking advantages of polarization imaging techniques, these parameters enable a low-magnification and wide-field imaging system to separate the types of cells into more specific categories that previously were distinctive under high magnification. Instead of blindly choosing the model, the L0 regularization method is used to obtain the simplified and stable polarimetry feature parameter. We demonstrate the model viability by using the pathological tissues of breast cancer and liver cancer, in each of which there are two derived parameters that can characterize the cells and cancer cells respectively with satisfactory accuracy and sensitivity. The stability of the final model opens the possibility for physical interpretation and analysis. This technique may bypass the typically labor-intensive and subjective tumor evaluating system, and could be used as a blueprint for an objective and automated procedure for cancer cell screening

The Role of Pre-Existing Diabetes Mellitus on Hepatocellular Carcinoma Occurrence and Prognosis: A Meta-Analysis of Prospective Cohort Studies

The impact of pre-existing diabetes mellitus (DM) on hepatocellular carcinoma (HCC) occurrence and prognosis is complex and unclear. The aim of this meta-analysis is to evaluate the association between pre-existing diabetes mellitus and hepatocellular carcinoma occurrence and prognosis.We searched PubMed, Embase and the Cochrane Library from their inception to January, 2011 for prospective epidemiological studies assessing the effect of pre-existing diabetes mellitus on hepatocellular carcinoma occurrence, mortality outcomes, cancer recurrence, and treatment-related complications. Study-specific risk estimates were combined by using fixed effect or random effect models.The database search generated a total of 28 prospective studies that met the inclusion criteria. Among these studies, 14 reported the risk of HCC incidence and 6 studies reported risk of HCC specific mortality. Six studies provided a total of 8 results for all-cause mortality in HCC patients. Four studies documented HCC recurrence risks and 2 studies reported risks for hepatic decomposition occurrence in HCC patients. Meta-analysis indicated that pre-existing diabetes mellitus (DM) was significantly associated with increased risk of HCC incidence [meta-relative risk (RR) = 1.87, 95% confidence interval (CI): 1.15-2.27] and HCC-specific mortality (meta-RR = 1.88, 95%CI: 1.39-2.55) compared with their non-DM counterparts. HCC patients with pre-existing DM had a 38% increased (95% CI: 1.13-1.48) risk of death from all-causes and 91% increased (95%CI: 1.41-2.57) risk of hepatic decomposition occurrence compared to those without DM. In DM patients, the meta-RR for HCC recurrence-free survival was 1.93(95%CI: 1.12-3.33) compared with non-diabetic patients.The findings from the current meta-analysis suggest that DM may be both associated with elevated risks of both HCC incidence and mortality. Furthermore, HCC patients with pre-existing diabetes have a poorer prognosis relative to their non-diabetic counterparts