A new method for complexity determination by using fractals and its applications in material surface characteristics

In this article, a new method for complexity determination by using fractals in combination with an artificial intelligent approach is proposed and its application in laser hardening technology is detailed. In particular, nanoindentation tests were applied as a way to investigate the hardness properties of tool steel alloys with respect to both marginal and relevant changes in laser hardening parameters. Specifically, process duration and temperature were considered, together with nanoindentation, later related to surface characteristics by image analysis and Hurst exponent determination. Three different Machine Learning algorithms (Random Forest, Support Vector Machine and k-Nearest Neighbors) were used and predictions compared with measures in terms of mean, variability and linear correlation. Evidences confirmed the general applicability of this method, based on integrating fractals for microstructure analysis and machine learning for their deep understanding, in material science and process engineering

MACHINE LEARNING TOOLS IN THE ANALYZE OF A BIKE SHARING SYSTEM

Advanced models, based on artificial intelligence and machine learning, are used here to analyze a bike-sharing system. The specific target was to predict the number of rented bikes in the Nova Mesto (Slovenia) public bike share scheme. For this purpose, the topological properties of the transport network were determined and related to the weather conditions. Pajek software was used and the system behavior during a 30-week period was investigated. Open questions were, for instance: how many bikes are shared in different weather conditions? How the network topology impacts the bike sharing system? By providing a reasonable answer to these and similar questions, several accurate ways of modeling the bike sharing system which account for both topological properties and weather conditions, were developed and used for its optimization

Modelling the Surface Roughness of Steel after Laser hardening by using 2D Visibility Network, Convolutional neural Networks and Genetic Programming

The surface characterization of materials after Robot Laser Hardening (RLH) is a technically demanding procedure. RLH is commonly used to harden parts, especially when subject to wear. By changing their surface properties, this treatment can offer several benefits such as lower costs for additional machining, no use of cooling agents or chemicals, high flexibility, local hardening, minimal deformation, high accuracy, and automated and integrated process in the production process. However, the surface roughness strongly depends on the heat treatment and parameters used in the process. This article used a network theory approach (i.e., the visibility network in 2D space) to analyze the surface roughness of tool steel EN100083-1 upon RLH. Specifically, two intelligent methods were merged in this investigation. Firstly, a genetic algorithm was applied to derive a relationship between the parameters of the robot laser cell and topological surface properties. Furthermore, convolutional neural networks allowed the assessment of surface roughness based on 2D photographic image

Distributed/virtual manufacturing system cell: an experimental installation

The main objectives of the “Distributed/Virtual Manufacturing System (D/V MS) Cell” project are: (1) The development of Tele-services technologies and organisation for the production planning and control functions; (2) The development of permanent high performance laboratory facilities that enable development and demonstration of D/V MS design and control, i.e., global distribution of production planning and control functions; (3) The development of an abstract environment, i.e., a virtual environment for design and real time control of manufacturing systems, or one of its elements, independent of the physical implementations. The D/V MS Cell satisfies the defined hierarchical distributed control model The Hardware System of the D/V MS Cell is composed by: (1) Machine tool cell: CNC milling machine, external sensors and actuators, interface computer with communications links, (2) Machine cell: Two machine simulators, PLC, sensors and actuators, computer based local controller, (3) Robot cell: Robot SCORBOT ER-VII, artificial vision system, conveyor system, computer based local controller, (4) Control centre: Video projector, computer based remote controller, computer based real time video and audio system. The Software System of the D/V MS Cell is composed by: (1) Applications for Human-Computer Interface (HMI): Interfaces for machine tool and robot programming and control, interface for production planning and control, (2) Computer-Machine Interface, via RS-232C, (3) Computer-Computer Interface, for communications via Internet. The hardware structure of the (D/V MS) Cell is already implemented and interfaces for machine tool programming and control are developed (software system). The operation of the complete system is planned for the year 1999

Antibiotics Residues as Limiting Factor of Honey Quality

Residues of veterinary drugs represent a significant risk to the health of honey consumers. Antibiotics can get into honey by using the antibiotics for treatment and prevention of bees diseases but also through the plant nectar and pollen. In Serbia, the use of antibiotics in beekeeping for bacterial diseases treatment is prohibited and accordingly there is no prescribed maximum permissible concentration for them in honey. The aim of this paper is to monitor the presence of antibiotic residues in honey which necessarily indicate their illegal and uncontrolled use. The presence of antibiotic residues in honey was screened for microbiological method "Modified method 4 plates" (EUR 15127-EN). The total of 135 samples of different honey types has been examined. Five of them (3.7%) were positive to antibiotic residues. The presence of antibiotic residues was found in the acacia honey (0.31%), linden honey (0.33%), sunflower honey (0.19%), mixed honey (0.17%) and honeydew honey (0.10%). Such unprofessional, unconscionable and unlawful use of antibiotics leads to their presence in honey and other bee products, as well as in the highly desirable and valuable products making them unusable

Plasma inflammatory cytokines and survival of pancreatic cancer patients.

OBJECTIVES: Inflammation and inflammatory conditions have been associated with pancreatic cancer risk and progression in a number of clinical, epidemiological, and animal model studies. The goal of the present study is to identify plasma markers of inflammation associated with survival of pancreatic cancer patients, and assess their joint contribution to patient outcome. METHODS: We measured circulating levels of four established markers of inflammation (C-reactive protein (CRP), interleukin-6 (IL-6), soluble tumor necrosis factor receptor type II (sTNF-RII), and macrophage inhibitory cytokine-1 (MIC-1)) in 446 patients enrolled in an ongoing prospective clinic-based study. Hazard ratios (HRs) and 95% confidence intervals (CI) for death were estimated using multivariate Cox proportional hazards models. RESULTS: Overall mortality was significantly increased in patients in the top quartile of CRP (HR = 2.52, 95% CI: 1.82-3.49), IL-6 (HR = 2.78, 95% CI: 2.03-3.81), sTNF-RII (HR = 2.00, 95% CI: 1.46-2.72), and MIC-1 (HR = 2.53, 95% CI: 1.83-3.50), compared to those in the bottom quartile (P-trend CONCLUSION: Individual elevated plasma inflammatory cytokines are associated with significant and dramatic reductions in pancreatic cancer patient survival. Furthermore, we observed an independent combined effect of those cytokines on patient survival, suggesting that multiple inflammatory pathways are likely involved in PDAC progression. Future research efforts to target the inflammatory state using combination strategies in pancreatic cancer patients are warranted

An Investigation into the Measurement and Prediction of Mechanical Stiffness of Lower-limb Prostheses used for Running

Two energy return prosthesis are subjected to three different statically applied loading methods. This initial study proposes that statically applied loading to a sport prosthesis using several controlled methods were statistically robust enough to derive a mechanical stiffness value. However, any predicted stiffness is drawn into question when allowing any movement of the distal end. This uncertainty will make any evaluation or prescription of lower-limb prosthesis technology based upon their stiffness incorrect. In addition, the peak calculated stiffness at the expected bodyweight induced ground impact load of a runner is judged the most representative assessment method. This study attempts to build on previous research advocating the need to monitor the performance of prosthesis lower-limb technology in disability sport. Practitioner Summary: This paper extends previous research regarding the fairness of prosthetics technology used in running with a lower-limb amputation. It pilots a quantitative assessment of high activity prosthetics technology and ultimately demonstrates how incorrect assessment can lead to incorrect specification of running prosthesis for elite level spor

Tsunami-Related Data: A Review of Available Repositories Used in Scientific Literature

Various organizations and institutions store large volumes of tsunami-related data, whose availability and quality should benefit society, as it improves decision making before the tsunami occurrence, during the tsunami impact, and when coping with the aftermath. However, the existing digital ecosystem surrounding tsunami research prevents us from extracting the maximum benefit from our research investments. The main objective of this study is to explore the field of data repositories providing secondary data associated with tsunami research and analyze the current situation. We analyze the mutual interconnections of references in scientific studies published in the Web of Science database, governmental bodies, commercial organizations, and research agencies. A set of criteria was used to evaluate content and searchability. We identified 60 data repositories with records used in tsunami research. The heterogeneity of data formats, deactivated or nonfunctional web pages, the generality of data repositories, or poor dataset arrangement represent the most significant weak points. We outline the potential contribution of ontology engineering as an example of computer science methods that enable improvements in tsunami-related data management

NON-INVASIVE BLOOD PRESSURE AND OTHER PHYSIOLOGICAL DATA IN CHEMICALLY IMMOBILIZED BROWN BEARS (URSUS ARCTOS)

Free-ranging brown bears (Ursus arctos) were snared and subsequently darted with a combination of xylazine-ketamine in Croatia (n = 5) or darted from a helicopter with a combination of medetomidine-tiletamine-zolazepam in Scandinavia (n = 20). Three adults and one yearling (1 year old) bear were captured in Croatia, with one adult being captured twice. The Scandinavian bears were divided into Group A (yearlings, n = 7) and Group B (subadults, n = 2 and adults, n = 11). The exertion time (time from activation of the trap or from the start of the helicopter chase to recumbency) and the induction time (time from darting to recumbency) were recorded. The rectal temperature (Tr) was measured as soon as possible after induction and then monitored at frequent intervals (varied between individuals) in immobilized bears. Blood pressure (BP) was measured with a non-invasive method (Korotkoff's technique) every 5 minutes. The heart rate (HR), respiratory rate (RR), and arterial haemoglobin oxygen saturation (SpO2) were recorded every 5 minutes. Reliability of the BP monitoring technique, trends of variation of the physiological variables, and the factors related to the capture were assessed. Both exertion and induction times were longer in Croatian bears than in Scandinavian bears. In Croatian bears, the Tr was either constant or slightly decreasing, with hyperthermia recorded in two individuals (Tr > 39.0° C). In Scandinavian bears, 17 of 20 individuals developed an initial hyperthermia. Four of five bears in Croatia and 17 of 20 bears in Scandinavia showed a decreasing trend in systolic and mean BP over time. According to the Korotkoff method, all bears were hypertensive (mean BP > 130 mmHg) with varying severity, and the systolic pressure was significantly lower in yearlings when compared to subadults and adults. Yearlings had significantly (p < 0.05) higher HR than subadults and adults, however there was no significant differences in RR, SpO2, and Tr between the age groups. All Croatian bears and 13 of 20 Scandinavian bears were moderately to severely hypoxemic (SpO2 < 90%). Further studies with simultaneous invasive and non-invasive (Korotkoff) BP monitoring techniques are required to confirm the accuracy of methods used in this study. The data presented here provides evidence of the physiological impact of different capture methods and chemical immobilization of brown bears in Croatia and Scandinavia

Matrix-assisted laser desorption/ionization time of flight mass spectrometry identification of Vibrio (Listonella) anguillarum isolated from sea bass and sea bream

Vibrio (Listonella) anguillarum is a pathogenic bacterium causing septicaemia in a wide range of marine organisms and inducing severe mortalities, thus it is crucial to conduct its accurate and rapid identification. The aim of this study was to assess MALDI-TOF MS as a method of choice for identification of clinical V. anguillarum isolates from affected marine fish. Since the method accuracy might be influenced by the type of the medium used, as well as by the incubation conditions, we tested V. anguillarum isolates grown on standard media with and without the addition of NaCl, cultured at three incubation temperatures, and at three incubation periods. The best scores were retrieved for V. anguillarum strains grown on NaCl-supplemented tryptone soy agar (TSA) at 22°C and incubated for 48h (100% identification to species level; overall score 2.232), followed by incubation at 37°C and 48h (100% to species level; score 2.192). The strains grown on non-supplemented TSA gave the best readings when incubated at 22°C for 72h (100% identification to species level; overall score 2.182), followed by incubation at 15°C for 72h (100% to species level; score 2.160). Unreliable identifications and no-identifications were growing with the incubation duration at 37°C, on both media, amounting to 88.89% for 7d incubation on supplemented TSA, and 92.60% for 7d incubation on non-supplemented TSA. The age of the cultured strains and use of media significantly impacted the mass spectra, demonstrating that for reliable identification, MALDI-TOF MS protein fingerprinting with the on-target extraction should be performed on strains grown on a NaCl-supplemented medium at temperatures between 15 and 22°C, incubated for 48-72 hours