Coupling of Josephson flux-flow oscillators to an external RC load

We investigate by numerical simulations the behavior of the power dissipated in a resistive load capacitively coupled to a Josephson flux flow oscillator and compare the results to those obtained for a d.c. coupled purely resistive load. Assuming realistic values for the parameters R and C, both in the high- and in the low-Tc case the power is large enough to allow the operation of such a device in applications.Comment: uuencoded, gzipped tar archive containing 11 pages of REVTeX text + 4 PostScript figures. To appear in Supercond. Sci. Techno

Prediction of Poly-methyl-methacrylate Laser Milling Process Characteristics Based on Neural Networks and Fuzzy Data☆

Abstract Laser milling is a recent technology adopted in rapid prototyping to produce tool, mould and polymer-based microfluidic devices. In this process, a laser beam is used to machine a solid bulk, filling the area to be machined with a number of closely spaced parallel lines. Compared to traditional machining, this method has some advantages, such as: greater flexibility of use, no mechanical contact with the surface, a reduction in industrial effluents, a fine accuracy of machining, even with complex forms, and the possibility to work different kind of materials. While it is relatively easy to predict the depth of the area worked, the surface roughness is more difficult to predict due to the materials behaviors at microscopic level. This is truer when polymer processing is considered due to the local thermal effects. The paper addresses the application of an artificial neural network computing technique to predict the depth and the surface roughness in laser milling tests of poly-methyl-methacrylate. The tests were carried out adopting a CO 2 laser working in continuous and pulsed wave mode. The obtained results showed a good agreement between the model and the experimental data. As a matter of fact, despite the thermal degradation that occurs on the PMMA surface, neural network processing offers an effective method for the prevision of roughness parameters as a function of the adopted process parameters

Does cultural distance affect online review ratings? Measuring international customers’ satisfaction with services leveraging digital platforms and big data

The advent and development of digital platforms has helped enhance the international visibility of brands, products and services, and has also introduced a proliferation of online reviews. This study develops a big data analysis of customer online reviews of hospitality services to gauge the extent to which the cultural distance among service providers and their customers influences online review ratings. By examining almost 715,000 online reviews written by hotel customers from more than 100 different nationalities, the effect of national cultural differences among service customers and providers (namely cultural distance) on online review ratings is innovatively scrutinized. The paper, by considering reviewers’ behavioral features, demographics, and trip-related factors, reveals that the effect of national cultural distance on online review ratings is negative. Several implications for practitioners are also discussed

Military Working Dogs Operating in Afghanistan Theater: Comparison between Pre-and Post-Mission Blood Analyses to Monitor Physical Fitness and Training

The intergovernmental organization known as the United Nations (UN) was born “to maintain international peace and security” through different operations and tasks, including “mine action” and “explosive detection”. Explosives are the most frequent cause of injuries in military personnel and an enormous danger for civilians. The role of explosive detection dogs (EDDs) and mine detection dogs has gained great consideration over time, leading to their intense use in military operations. Literature regarding working injuries reported by EDDs during missions is limited. The aim of the present study is to investigate the hematological changes that occurred between pre-and post-mission blood analyses in military working dogs deployed to Afghanistan in order to evaluate signs of health problems or physical adjustments. Examining the clinical records, only three dogs reported a medical issue, one with gastric dilatation-volvulus (GDV), and two with lameness episodes. Lack of health issues occurring during the missions was reflected by the absence of significant differences between pre-and post-mission blood analyses. Blood results were also examined by dividing the EDDs into groups considering age at departure, sex, breed and mission length. A few categories demonstrated significant changes in some parameters; however, the mean values were always included in the ranges of normality, indicating that their physical fitness and training were adequate for the required tasks

Cognitive Decision-making Systems for Scraps Control in Aerospace Turbine Blade Casting☆

Abstract The competitiveness of a casting system in modern lost wax production of superalloy turbine blades strongly depends on the reduction of scraps, which commonly affect superalloy cast parts. In order to achieve a focused goal of competitiveness, some key and vital parameters (Key Process Variables) have to be continuously taken under control to make very accurate predictions of Target Variables, which represent, as mapped KPVs domain, the ultimate performance of the entire production link. Such an approach is based on the development of robust control monitoring of the ceramic shell manufacture, which is specifically conceived to foster a possible reduction of scraps in the production if superalloy components. The concerned control will take into consideration data coming from both sensors and measured values in laboratory. The sensor data, which is originated from both new adopted inline and offline equipments at Europea Microfusioni Aerospaziali S.p.A. (EMA) and data measured in the EMA laboratories, will be merged into a sensor pattern vector which represents the basis to develop the EMA demonstrator within the Intelligent Fault Correction and self Optimizing manufacturing systems EU project funded in FP7. The sensor pattern vector will be used to feed an automatic system for the prediction of the process vital parameters. An automated system, based on artificial intelligence paradigms, in particular neural networks, will be fed with the data coming from the sensor pattern vector in order to produce an optimal multi-object output

Effects of exercise on urinary biochemical parameters and proteins in a group of well-trained military working dogs

Exercise-induced proteinuria has been widely investigated in humans, also in relation to intensity and duration of activity. Instead, there are only limited publications regarding urinary biochemical parameters and urinary proteins before and after physical activity in dogs. This paper aimed to investigate the effects of exercise on urinary biochemistry and proteins in military dogs. Twenty-four dogs were enrolled in this study. All the dogs were clinically sound, and they were examined before and after activity. Pulse rates (PR) and respiratory rate (RR) were monitored. Urine was sampled before and after a training session of search activity. Standard urinalysis was carried out, urine total proteins and creatinine were measured and the urinary protein:creatinine ratio was calculated; finally, the urinary proteins were separated using sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). Clinical examination before and after activity did not reveal any pathological finding. After activity, the PR was slightly increased, while the RR was notably increased (p < 0.05). Total proteins, albumin, and their ratio with creatinine were significantly higher after exercise when considering all the dogs included or only the females while, when considering only the males no significant difference was detected. The clinical relevance of this study was related to the possibility of using urine as a non-invasive sample for monitoring health status after training activity and exercise in dogs. An increase in microalbuminuria after search activity, measured using SDS-PAGE could be considered an early biomarker of renal function during training sessions

Environmental assessment of vegetable crops towards the water-energy-food nexus: A combination of precision agriculture and life cycle assessment

The increase in world population and the resulting demand for food, water and energy are exerting increasing pressure on soil, water resources and ecosystems. Identification of tools to minimise the related environmental impacts within the food–energy–water nexus is, therefore, crucial. The purpose of the study is to carry out an analysis of the agri-food sector in order to improve the energy-environmental performance of four vegetable crops (beans, peas, sweet corn, tomato) through a combination of precision agriculture (PA) and life cycle assessment (LCA). Thus, PA strategies were identified and a full LCA was performed on actual and future scenarios for all crops in order to evaluate the benefits of a potential combination of these two tools. In the case study analysed, a life cycle approach was able to target water consumption as a key parameter for the reduced water availability of future climate scenarios and to set a multi-objective function combining also such environmental aspects to the original goal of yield maximisation. As a result, the combination of PA with the LCA perspective potentially allowed the path for an optimal trade-off of all the parameters involved and an overall reduction of the expected environmental impacts in future climate scenarios

Neural Networks Tool Condition Monitoring in Single-point Dressing Operations

Abstract Cognitive modeling of tool wear progress is employed to obtain a dependable trend of tool wear curves for optimal utilization of tool life and productivity improvement, while preserving the surface integrity of the ground parts. This paper describes a method to characterize the dresser wear condition utilizing vibration signals by applying a cognitive paradigm, such as Artificial Neural Networks (ANNs). Dressing tests with a single-point dresser were performed in a surface grinding machine and tool wear measurements taken along the experiments. The results show that ANN processing offers an effective method for the monitoring of grinding wheel wear based on vibration signal analysis

Tri-Lab data models and format (DMF) project: parallel I/O and data exchange

A central goal of the ASCI program is to push simulation and modeling for Science-based Stockpile Stewardship to unprecedented levels. ASCI applications will use extremely high-fidelity models, on the order of one billion cells, to generate terabytes of raw data. Such vast amounts of data produced by these supercomputing applications will overwhelm scientists, whose efforts to understand their results are hindered by inadequate visualization and data management tools. Much of the Scientific Data Management (SDM) effort concerns managing the large and complex data emerging from these simulation codes. One particular area for which commercial and scalable solutions do not exist is in Parallel I/O and data exchange between simulations. To address these needs, the Tri-lab Data Models and Formats effort of the SDM project is developing capabilities to enable the capturing and sharing of simulation data

The Endocannabinoid System: A Putative Role in Neurodegenerative Diseases

BACKGROUND: Following the characterization of the chemical structure of D9-tetrahydrocannabinol (THC), the main psychoactive constituent of marijuana, researchers have moved on with scientific valuable explorations. OBJECTIVES: The aim of this review is to highlight the role of endocannabinoid system in neurodegenerative diseases. MATERIALS AND METHODS: The article is a critical analysis of the most recent data currently present in scientific literature on the subject; a qualitative synthesis of only the most significant articles has been performed. RESULTS: In central nervous system, endocannabinoids show a neuromodulatory function, often of retrograde type. This way, they play an important role in synaptic plasticity and in cognitive, motor, sensory and affective processes. In addition, in some acute or chronic pathologies of central nervous system, such as neurodegenerative and neuroinflammatory diseases, endocannabinoids can perform a pro-homeostatic and neuroprotective function, through the activation of CB1 and CB2 receptors. Scientific evidence shows that an hypofunction or a dysregulation of the endocannabinoid system may be responsible for some of the symptoms of diseases such as multiple sclerosis, amyotrophic lateral sclerosis, Huntington’s, Parkinson’s and Alzheimer’s diseases. CONCLUSIONS: The important role played by endocannabinoid system promises interesting developments, in particular to evaluate the effectiveness of new drugs in both psychiatry and neurology