New Search

Advanced search

Results: 126,246,945

Save to Scifeed
Page of 12,624,695
Articles per Page
by
Show export options
  Select all
Sciprofile linkStefano Magistretti, Claudio Dell'era, Nicola Doppio
Published: 2 July 2020
Management Decision; doi:10.1108/md-10-2019-1501

The publisher has not yet granted permission to display this abstract.
Published: 1 July 2020
by MDPI
Abstract:
Attractiveness is perceived based on both facial physical features and prior experience for adults. Infants also prefer attractive or familiar faces, but it is unclear whether facial physical features and prior experience affect their preference. In this study, we investigated whether infants’ preference for faces was shaped by both facial physical features and facial looking experience. This experiment comprised two tasks, observation and preference looking. We manipulated fixation durations in the first task (observation experience) to differ between presented faces and measured the preference for faces in the second task right after the observation task. We conducted two experiments: the same faces in the same positions through both tasks in Experiment 1, and the same faces in different positions in Experiment 2, and analyzed the interaction between observation experience and attractiveness of face images in terms of preference. Observation experience and facial attractiveness only affected preference in Experiment 2: Infants generally looked longer at the flickered position but different face, but looked for the attractive face when the face in the flickered position changed from attractive to unattractive. We suggest that observation experience arouses spatial attention, and that facial attractiveness attracts infants’ attention only when they notice changes of faces.
Published: 1 July 2020
by MDPI
Abstract:
High-resolution real-time satellite-based precipitation estimation datasets can play a more essential role in flood forecasting and risk analysis of infrastructures. This is particularly true for extended deserts or mountainous areas with sparse rain gauges like Iran. However, there are discrepancies between these satellite-based estimations and ground measurements, and it is necessary to apply adjustment methods to reduce systematic bias in these products. In this study, we apply a quantile mapping method with gauge information to reduce the systematic error of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). Due to the availability and quality of the ground-based measurements, we divide Iran into seven climate regions to increase the sample size for generating cumulative probability distributions within each region. The cumulative distribution functions (CDFs) are then employed with a quantile mapping 0.6° × 0.6° filter to adjust the values of PERSIANN-CCS. We use eight years (2009–2016) of historical data to calibrate our method, generating nonparametric cumulative distribution functions of ground-based measurements and satellite estimations for each climate region, as well as two years (2017–2018) of additional data to validate our approach. The results show that the bias correction approach improves PERSIANN-CCS data at aggregated to monthly, seasonal and annual scales for both the calibration and validation periods. The areal average of the annual bias and annual root mean square errors are reduced by 98% and 56% during the calibration and validation periods, respectively. Furthermore, the averages of the bias and root mean square error of the monthly time series decrease by 96% and 26% during the calibration and validation periods, respectively. There are some limitations in bias correction in the Southern region of the Caspian Sea because of shortcomings of the satellite-based products in recognizing orographic clouds.
Published: 1 July 2020
by MDPI
Abstract:
Tomato and cucumber seedlings were grown in a growth chamber to evaluate the effects of different cycles of light–dark exposure conditions (T0 (control treatment) (1 cycle of 24 h distributed in 18 h of light exposure and six hours of dark), T1 (two cycles of 12 h distributed in nine hours of light exposure and three hours of dark) and T2 (three cycles of eight hours distributed in six hours of light exposure and two hours of dark) on growth, nutrient status, pigment concentration and physiological changes. Total dry weight showed different behaviors in both species, since in tomato the total dry weight remained unchanged under varying light–dark cycles, whereas in cucumber seedlings there was a clear decrease compared to the control treatment. In both species, plants grown under T2 showed the best water content. Nitrogen, P and K content—as well as partitioning in the different organs of the plants—displayed different patterns under varying cycles of light–dark conditions in both species. Chlorophyll (b and a + b) concentration decreased significantly in both species in T1 and T2 compared to the control treatment (T0). At physiological level, the concentration of total soluble sugars and proline in leaf showed the highest value in the control treatment with 18 h of light and six hours of dark.
Published: 1 July 2020
by MDPI
Abstract:
Background: This study aimed to evaluate and identify the specific CT findings by focusing on abnormalities in the main pancreatic duct (MPD) and pancreatic parenchyma in patients with small pancreatic cancer (PC) including carcinoma in situ (CIS). Methods: Nine CT findings indicating abnormalities of MPD and pancreatic parenchyma were selected as candidate findings for the presence of small PC ≤ 10 mm. The proportions of patients positive for each finding were compared between small PC and benign MPD stenosis groups. Interobserver agreement between two independent image reviewers was evaluated using kappa statistics. Results: The final analysis included 24 patients with small PC (including 11 CIS patients) and 28 patients with benign MPD stenosis. The proportion of patients exhibiting partial pancreatic parenchymal atrophy (PPA) corresponding to the distribution of MPD stenosis (45.8% vs. 7.1%, p < 0.01), upstream PPA arising from the site of MPD stenosis (33.3% vs. 3.6%, p = 0.01), and MPD abrupt stenosis (45.8% vs. 14.3%, p = 0.03) was significantly higher in the small PC group than in the benign MPD stenosis group. Conclusions: The presence of partial PPA, upstream PPA, and MPD abrupt stenosis on a CT image was highly suggestive of the presence of small PCs including CIS.
Published: 1 July 2020
by MDPI
Abstract:
This paper investigates an initial model for Zero Defect Manufacturing (ZDM) using a cost function where the operation and condition of a production process are reflected, and the quality of the output/product and the production process (as well as safety aspects) can be considered. The outset of the study is based on empirical data collected from five manufacturing companies, and proposes an initial model for ZDM with an Industry 4.0 perspective. The initial ZDM model has a generic setup for a real-life system and its replication as a digital twin using system models based on a representation of a generic production process with its connected control system, and potential interconnections between unit processes. It is based on concepts from system theory of dynamic systems and principles from condition monitoring and fault detection. In that way the model is deemed as highly generalizable for manufacturing and process industry companies as well as for some critical infrastructures with production and distribution systems. The proposed model with its cost function setup is analyzed and discussed in the context of ZDM. It is concluded that production processes in the manufacturing and process industry can be made more intelligent and interoperable using this approach. Improved sustainability, competitiveness, efficiency and profitability of companies are foreseen welcomed secondary effects. Finally, the proposed ZDM model further develops the ZDM by adding to it a systematic approach based on a solid mathematical foundation.
Published: 1 July 2020
by MDPI
Abstract:
Magnetic drug targeting (MDT) is a noninvasive method for the medical treatment of various diseases of the cardiovascular system. Biocompatible magnetic nanoparticles loaded with medicinal drugs are carried to a tissue target in the human body (in vivo) under the applied magnetic field. The present study examines the MDT technique in various microchannels geometries by adopting the principles of biofluid dynamics (BFD). The blood flow is considered as laminar, pulsatile and the blood as an incompressible and non-Newtonian fluid. A two-phase model is adopted to resolve the blood flow and the motion of magnetic nanoparticles (MNPs). The numerical results are obtained by utilizing a meshless point collocation method (MPCM) alongside with the moving least squares (MLS) approximation. The numerical results are verified by comparing with published numerical results. We investigate the effect of crucial parameters of MDT, including (1) the volume fraction of nanoparticles, (2) the location of the magnetic field, (3) the strength of the magnetic field and its gradient, (4) the way that MNPs approach the targeted area, and (5) the bifurcation angle of the vessel.
Published: 1 July 2020
by MDPI
Abstract:
The buzzword “smart home” promises an intelligent, helpful environment in which technology makes life easier, simpler or safer for its inhabitants. On a technical level, this is currently achieved by many networked devices interacting with each other, working on shared protocols and standards. From a user experience (UX) perspective, however, the interaction with such a collection of devices has become so complex that it currently rather stands in the way of widespread adoption and use. So far, it does not seem likely that a common user interface (UI) concept will emerge as a quasi-standard, as the desktop interface did for graphical UIs. Therefore, our research follows a different approach. Instead of many singular intelligent devices, we envision a UI concept for smart environments that integrates diverse pieces of technology in a coherent mental model of an embodied “room intelligence” (RI). RI will combine smart machinery, mobile robotic arms and mundane physical objects, thereby blurring the line between the physical and the digital world. The present paper describes our vision and emerging research questions and presents the initial steps of technical realization.
Published: 1 July 2020
by MDPI
Abstract:
During recent years, there has been great interest in exploring the potential for high-rate natural gas (NG) injection in North American blast furnaces (BFs) due to the fuel’s relatively low cost, operational advantages, and reduced carbon footprint. However, it is well documented that increasing NG injection rates results in declining raceway flame temperatures (a quenching effect on the furnace, so to speak), with the end result of a functional limit on the maximum injection rate that can be used while maintaining stable operation. Computational fluid dynamics (CFD) models of the BF raceway and shaft regions developed by Purdue University Northwest’s (PNW) Center for Innovation through Visualization and Simulation (CIVS) have been applied to simulate multi-phase reacting flow in industry blast furnaces with the aim of exploring the use of pre-heated NG as a method of widening the BF operating window. Simulations predicted that pre-heated NG injection could increase the flow of sensible heat into the BF and promote complete gas combustion through increased injection velocity and improved turbulent mixing. Modeling also indicated that the quenching effects of a 15% increase in NG injection rate could be countered by a 300K NG pre-heat. This scenario maintained furnace raceway flame temperatures and top gas temperatures at levels similar to those observed in baseline (stable) operation, while reducing coke rate by 6.3%.
Published: 1 July 2020
by MDPI
Abstract:
In everyday life, we are continually exposed to different lighting systems, from the home interior to car lights and from public lighting to displays. The basic emission principles on which they are based range from the old incandescent lamps to the well-established compact fluorescent lamps (CFL) and to the more modern Light Emitting Diode (LEDs) that are dominating the actual market and also promise greater development in the coming years. In the LED technology, the key point is the electroluminescence material, but the fundamental role of proper phosphors is sometimes underestimated even when it is essential for an ideal color rendering. In this review, we analyze the main solid-state techniques for lighting applications, paying attention to the fundamental properties of phosphors to be successfully applied. Currently, the most widely used materials are based on rare-earth elements (REEs) whereas Ce:YAG represents the benchmark for white LEDs. However, there are several drawbacks to the REEs’ supply chain and several concerns from an environmental point of view. We analyze these critical issues and review alternative materials that can overcome their use. New compounds with reduced or totally REE free, quantum dots, metal–organic framework, and organic phosphors will be examined with reference to the current state-of-the-art.
Page of 12,624,695
Articles per Page
by
Show export options
  Select all
Back to Top Top