Superior Thermoelectric Performance of Textured Ca3Co4−xO9+δ Ceramic Nanoribbons

Calcium cobaltite Ca₃Co_4−xO_9+δ (CCO) is a promising p-type thermoelectric (TE) material for high-temperature applications in air. The grains of the material exhibit strong anisotropic properties, making texturing and nanostructuring mostly favored to improve thermoelectric performance. On the one hand multitude of interfaces are needed within the bulk material to create reflecting surfaces that can lower the thermal conductivity. On the other hand, low residual porosity is needed to improve the contact between grains and raise the electrical conductivity. In this study, CCO fibers with 100% flat cross sections in a stacked, compact form are electrospun. Then the grains within the nanoribbons in the plane of the fibers are grown. Finally, the nanoribbons are electrospun into a textured ceramic that features simultaneously a high electrical conductivity of 177 S cm⁻¹ and an immensely enhanced Seebeck coefficient of 200 µV K⁻¹ at 1073 K are assembled. The power factor of 4.68 µW cm⁻¹ K⁻² at 1073 K in air surpasses all previous CCO TE performances of nanofiber ceramics by a factor of two. Given the relatively high power factor combined with low thermal conductivity, a relatively large figure-of-merit of 0.3 at 873 K in the air for the textured nanoribbon ceramic is obtained.     

Learning headway estimation in driving

OBJECTIVE: The main purpose of the present study was to examine to what extent the ability to attain a required headway of 1 or 2 s can be improved through practical driving instruction under real traffic conditions and whether the learning is sustained after a period during which there has been no controlled training. BACKGROUND: The failure of drivers to estimate headways correctly has been demonstrated in previous studies. METHODS: Two methods of training were used: time based (in seconds) and distance based (in a combination of meters and car lengths). For each method, learning curves were examined for 18 participants at speeds of 50, 80, and 100 km/hr. RESULTS: The results indicated that drivers were weak in estimating headway prior to training using both methods. The learning process was rapid for both methods and similar for all speeds; thus, after one trial with feedback, there was already a significant improvement. The learning was retained over time, for at least the 1 month examined in this study. CONCLUSION: Both the time and distance training of headway improved drivers' ability to attain required headways, with the learning being maintained over a retention interval. The learning process was based on perceptual cues from the driving scene and feedback from the experimenter, regardless of the formal training method. APPLICATION: The implications of these results are that all drivers should be trained in headway estimation using an objective distance measuring device, which can be installed on driver instruction vehicles.     

Temporal Reasoning for a Collaborative Planning Agent in a Dynamic Environment

We present a temporal reasoning mechanism for an individual agent situated in a dynamic environment such as the web and collaborating with other agents while interleaving planning and acting. Building a collaborative agent that can flexibly achieve its goals in changing environments requires a blending of real-time computing and AI technologies. Therefore, our mechanism consists of an Artificial Intelligence (AI) planning subsystem and a Real-Time (RT) scheduling subsystem. The AI planning subsystem is based on a model for collaborative planning. The AI planning subsystem generates a partial order plan dynamically. During the planning it sends the RT scheduling subsystem basic actions and time constraints. The RT scheduling subsystem receives the dynamic basic actions set with associated temporal constraints and inserts these actions into the agent's schedule of activities in such a way that the resulting schedule is feasible and satisfies the temporal constraints. Our mechanism allows the agent to construct its individual schedule independently. The mechanism handles various types of temporal constraints arising from individual activities and its collaborators. In contrast to other works on scheduling in planning systems which are either not appropriate for uncertain and dynamic environments or cannot be expanded for use in multi-agent systems, our mechanism enables the individual agent to determine the time of its activities in uncertain situations and to easily integrate its activities with the activities of other agents. We have proved that under certain conditions temporal reasoning mechanism of the AI planning subsystem is sound and complete. We show the results of several experiments on the system. The results demonstrate that interleave planning and acting in our environment is crucial.     

All-GaAs/AlGaAs readout circuit for quantum-well infrared detectorfocal plane array

We report the fabrication and testing of an all-GaAs/AlGaAs hybrid readout circuit operating at 77 K designated for use with an GaAs/AlGaAs background-limited quantum-well infrared photodetector focal plane array (QWIP FPA). The circuit is based on a direct injection scheme, using specially designed cryogenic GaAs/AlGaAs MODFET's and a novel n⁺ -GaAs/AlGaAs/n⁺-GaAs semiconductor capacitor, which is able to store more than 15 000 electrons/μm² in a voltage range of ±0.7 V. The semiconductor capacitor shows little voltage dependence, small frequency dispersion, and no hysteresis. We have eliminated the problem of low-temperature degradation of the MODFET I-V characteristics and achieved very low gate leakage current of about 100 fA in the subthreshold regime. The MODFET electrical properties including input-referred noise voltage and subthreshold transconductance were thoroughly tested. Input-referred noise voltage as low as 0.5 μV/√Hz at 10 Hz was measured for a 2×30 μm² gate MODFET. We discuss further possibilities for monolithic integration of the developed devices     

Accelerator mass spectrometry at the rehovot pelletron tandem: Measurements of abundances of cosmogenic radioisotopes and future prospects

The accelerator mass spectrometry system developed at the Rehovot 14UD Pelletron tandem laboratory has been used in measurements of abundances of cosmogenic nuclei. Measurements of ³⁶Cl concentrations in natural water samples from the Jordan River and Dead Sea Basin are presented in the framework of a ³⁶Cl budget analysis of the Dead Sea. The feasibility of ⁴¹Ca detection at concentrations ranging down to 1 × 10^?13 by tandem accelerator mass spectrometry has been demonstrated.     

The effectiveness of a training method using self-modeling webcam photos for reducing musculoskeletal risk among office workers using computers

An intervention study was conducted to examine the effectiveness of an innovative self-modeling photo-training method for reducing musculoskeletal risk among office workers using computers. Sixty workers were randomly assigned to either: 1) a control group; 2) an office training group that received personal, ergonomic training and workstation adjustments or 3) a photo-training group that received both office training and an automatic frequent-feedback system that displayed on the computer screen a photo of the worker's current sitting posture together with the correct posture photo taken earlier during office training. Musculoskeletal risk was evaluated using the Rapid Upper Limb Assessment (RULA) method before, during and after the six weeks intervention. Both training methods provided effective short-term posture improvement; however, sustained improvement was only attained with the photo-training method. Both interventions had a greater effect on older workers and on workers suffering more musculoskeletal pain. The photo-training method had a greater positive effect on women than on men.     

Increasing Recognition of Wrong-Patient Errors through Improved Interface Design of a Computerized Provider Order Entry System

Wrong-patient errors from inadvertent menu selections while using computerized provider order entry (CPOE) systems could have fatal consequences. This study investigated whether the manipulation of CPOE interface design could improve healthcare providers’ ability to recognize patient selection errors and also decrease the time to error recognition. Using a 2 × 2 design, 120 participants were randomly assigned to one of four groups, interacting with different versions of a simulated CPOE: (1) control – standard version; (2) highlighted selection – the selected patient row was highlighted for 2 s, by blanking the rest of the screen; (3) photo – photographs of patients’ faces were displayed in all screens; (4) combined – with photo and highlighted selection. Each participant navigated through five order scenarios. On the last scenario, an error was simulated by directing the participant to a wrong patient. Recognition rates of the wrong-patient error and times to error recognition were significantly improved for the highlighted selection, photo, and combined groups, relative to the control group. These results suggest that the addition of patient photos and highlighted selection could substantially reduce errors in CPOE systems and other applications.