In2O3:Ga and In2O3:P-based one-electrode gas sensors: Comparative study

Gas sensing characteristics of one-electrode sensors based on the In₂O₃ ceramics doped by gallium and phosphorus have been discussed. In₂O₃-based ceramic was prepared by sol–gel technology. Ozone, CO, CH₄ and H₂ were used as tested gases. The doping concentration effect on the sensor parameters such as magnitude of response, operating temperature, response and recovery times, sensitivity to the air humidity, and selectivity have been analyzed. It was shown that In₂O₃ doping by Ga and P could be used for the sensor performance optimization. It was assumed that the appearance of the second phase (InPO₄ and Ga₂O₃) and the change of structural parameters, taking place during doping process, were the main factors controlling the change of operating characteristics in In₂O₃:P and In₂O₃:Ga-based sensors.     

An investigation into the cause of loss of containment from the supply of mini-bulk lubricants

An Intermediate Bulk Container (IBC) was punctured during its handling, releasing oil onto soil at an environmentally-sensitive region of Australia. The telehandler did not pierce the plastic of the IBC directly (as was expected) but rather one of the tynes had caught on the underside of the metal base plate, despite numerous controls being in place at time of spill, revealing a previously unreported mechanism for a fluid spill from handling of petroleum hydrocarbons. The diverse investigation team used a root cause analysis (RCA) technique to identify the underlying cause: the inspection process was inadequate with contributing factors of not using a spotter and design of IBC did not anticipate conditions. Engineering controls were put in place as part of the change management process to help prevent spills from occurring from piercing from telehandler tynes on the current project site.     

A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

Synthesis and in vitro bioactivity assessment of injectable bioglass−organic pastes for bone tissue repair

The aim of this work was to study the bioactivity of systems based on a clinically tested bioactive glass (BG) particulates (mol%: 4.33 Na₂O−30.30 CaO−12.99 MgO−45.45 SiO₂−2.60 P₂O₅−4.33 CaF₂) and organic carriers. The cohesiveness of injectable bone graft products is of high relevance when filling complex volumetric bone defects. With this motivation behind, BG particulates with mean sizes within 11−14 μm were mixed in different proportions with glycerol (G) and polyethylene glycol (PEG) as organic carriers and the mixtures were fully injectable exhibiting Newtonian flow behaviors. The apatite forming ability was investigated using X-ray diffraction and field emission scanning electron microscopy under secondary electron mode after immersion of samples in simulated body fluid (SBF) for time durations varying between 12 h and 7 days. The results obtained revealed that in spite of the good adhesion of glycerol and PEG carriers to glass particles during preparation stage, they did not hinder the exposure of bioactive glass particulates to the direct contact with SBF solution. The results confirmed the excellent bioactivity in vitro for all compositions expressed by high biomineralization rates with the formation of crystalline hydroxyapatite being identified by XRD after 12 h of immersion in SBF solution.     

Strain engineering for thermal conductivity of single-walled carbon nanotube forests

We perform classical molecular dynamics simulations to investigate the mechanical compression effect on the thermal conductivity of the single-walled carbon nanotube (SWCNT) forest, in which SWCNTs are closely aligned and parallel with each other. We find that the thermal conductivity can be linearly enhanced by increasing compression before the buckling of SWCNT forests, but the thermal conductivity decreases quickly with further increasing compression after the forest is buckled. Our phonon mode analysis reveals that, before buckling, the smoothness of the inter-tube interface is maintained during compression, and the inter-tube van der Waals interaction is strengthened by the compression. Consequently, the twisting-like mode (good heat carrier) is well preserved and its group velocity is increased by increasing compression, resulting in the enhancement of the thermal conductivity. The buckling phenomenon changes the circular cross section of the SWCNT into ellipse, which causes effective roughness at the inter-tube interface for the twisting motion. As a result, in ellipse SWCNTs, the radial breathing mode (poor heat carrier) becomes the most favorable motion instead of the twisting-like mode and the group velocity of the twisting-like mode drops considerably, both of which lead to the quick decrease of the thermal conductivity with further increasing compression after buckling.     

Effects of visual and linguistic anthropomorphic cues on social perception,self-awareness,and information disclosure in a health website

Acknowledging the lack of studies examining both visual and linguistic anthropomorphic cues and the underlying mechanisms of their effects, we investigated how the different modalities of anthropomorphic cues in a health website influenced information disclosure. In a 2 (visual cues: human vs. non-human image) × 2 (linguistic cues: conversational vs. impersonal language) × 2 (question type: less vs. more sensitive questions) between-subjects experiment (N = 254), participants registered with a mock-up health website. We assessed a behavioral outcome of not disclosing personal information and psychological outcomes of social perception and self-awareness as potential mediators. Results revealed distinctive effects of the two modalities of the anthropomorphic cues. Anthropomorphic images, on one hand, increased public and private self-awareness, and public self-awareness in turn led to less information disclosure. Anthropomorphic language, on the other hand, heightened social perception and promoted information disclosure, but social perception did not predict the disclosure. These results indicate unique underlying mechanisms of the effects of anthropomorphism: priming effect of visual cues, and communicative effects of linguistic cues.     

A novel intelligent approach for yaw position forecasting in wind energy systems

Yaw control systems orientate the rotor of a wind turbine into the wind direction, optimize the wind power generated by wind turbines and alleviate the mechanical stresses on a wind turbine. Regarding the advantages of yaw control systems, a k-nearest neighbor classifier (k-NN) has been developed in order to forecast the yaw position parameter at 10-min intervals in this study. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters are used in 2, 3, 4, 5 and 6-dimensional input spaces. The forecasting model using Manhattan distance metric for k = 3 uncovered the most accurate performance for atmosphere pressure, wind direction, wind speed and rotor speed inputs. However, the forecasting model using Euclidean distance metric for k = 1 brought out the most inconsistent results for atmosphere pressure and wind speed inputs. As a result of multi-tupled analyses, many feasible inferences were achieved for yaw position control systems. In addition, the yaw position forecasting model developed was compared with the persistence model and it surpassed the persistence model significantly in terms of the improvement percent.     

Energy-optimal base station density in cellular access networks with sleep modes

Sleep modes are widely accepted as an effective technique for energy-efficient networking: by adequately putting to sleep and waking up network resources according to traffic demands, a proportionality between energy consumption and network utilization can be approached, with important reductions in energy consumption. Previous studies have investigated and evaluated sleep modes for wireless access networks, computing variable percentages of energy savings. In this paper we characterize the maximum energy saving that can be achieved in a cellular wireless access network under a given performance constraint. In particular, our approach allows the derivation of realistic estimates of the energy-optimal density of base stations corresponding to a given user density, under a fixed performance constraint. Our results allow different sleep mode proposals to be measured against the maximum theoretically achievable improvement. We show, through numerical evaluation, the possible energy savings in today’s networks, and we further demonstrate that even with the development of highly energy-efficient hardware, a holistic approach incorporating system level techniques is essential to achieving maximum energy efficiency.     

The relationship between centrality and land use patterns: Empirical evidence from five Chinese metropolises

The relationship between location and land use patterns is one of the classic theoretical issues in urban studies. Classic models based on the monocentricity hypothesis have limitations in the interpretation of modern urban structure. China has experienced institutional transformation in recent decades, and the interaction of national government policy, market forces and the natural environment has influenced urban planning in Chinese metropolises, resulting in urban structures with special characteristics. This paper examines the distribution of location and land use intensity, and tested the Alonso model by the relationship between them in five Chinese metropolises using Point of Interest data, space syntax methodology, the grid weighted statistical method and the Geographically Weighted Regression (GWR) model. Universal patterns about the scaling relation between intensity of land use types and the centrality of location are revealed. The elasticity of land use types to location, from high to low sensitivity, is commercial, residential then industrial land in most of the five metropolises studied. The sensitivity sequence of land use studied suggests that the hypothetical model based on the classical Alonso model can explain the spatial structure of modern metropolises in China to some extent, especially for the commercial land. But the order of sensitivity of residential land and industrial land to location does not conform to the model. The spatial heterogeneity in land use intensity and centrality were explored and the factors embedded were discussed. It can be found that the relation between centrality and land use intensity conforms to power law. In most of the metropolises studied, when the scaling relation between land use intensity and centrality is super linear, the sequence of the frequency value from high to low are commercial, residential and industrial land; when the scaling relation is sublinear, the sequence of the frequency value is industrial, residential and commercial land.