Dynamic Development Contests

Public, private, and not-for-profit organizations find advanced technology and product development projects challenging to manage due to the time and budget pressures, and turn to their development partners and suppliers to address their development needs. We study how dynamic development contests with enriched rank-based incentives and carefully-tailored information design can help these organizations outsource their development projects at the minimum project lead time by stimulating competition among suppliers. We show that an organization can use dynamically adjusted flexible rewards to achieve the absolute minimum expected project lead time at a significantly lower cost than a fixed-reward policy. Importantly, our flexible-reward policy pays the absolute minimum expected reward (i.e., achieves the first best). We further study the case where the organization does not have sufficient budget to offer a reward that attains the absolute minimum expected lead time. We propose that in this case, the organization can dynamically increase the contest reward until its budget constraint binds and then use information sharing as a strategic tool to incentivize suppliers. Specifically, we propose an easy-to-implement random-update policy where the organization periodically monitors the status of suppliers at random times and immediately discloses any partial progress. We show that such a random-update policy outperforms other canonical information disclosure strategies. Our results indicate that dynamic rewards and strategic information disclosure are powerful tools to help organizations outsource their development needs swiftly and cost effectively

Investigating the Effect of Increasing Nano Cellulose to Diesel Fuel on Emission and Performance of Internal Combustion Engine

IntroductionToday, the number of diesel engines is increasing due to their high efficiency and low greenhouse gases. In the present study, the effect of adding nano cellulose as nanoparticles to diesel fuel on the performance parameters and emissions of diesel engine was investigated. Nano cellulose was provided by the Nano Novin Company in Sari. Nano cellulose values were considered at 3 levels of zero, 25 ppm and 75 ppm. Also, the tests were performed at 3 engine speed of 1600, 2000 and 2400 rpm in full load mode.Materials and MethodsIn this study, nanocellulose was used as nanoparticles to add to diesel and to evaluate the performance and emission parameters of the engine. To prevent the deposition of nano cellulose in diesel fuel, jelly type nano cellulose was used. The samples were named after adding different amounts of nano cellulose, abbreviated D100N0, D100N25 and D100N75. D100 means 100% pure diesel and N means different amounts of nano cellulose with different amounts. Ultrasound was used to obtain homogeneous samples. About 3 liters were prepared from each sample so that it could be used for at least 3 repetitions. The required tests were performed at three different speeds of 1600, 2000 and 2400 rpm in full load mode. The necessary equipment was used to measure the performance parameters and air emissions, including diesel engine connected to the dynamometer, emissions measuring device, fuel system and control room (to apply the load and provide conditions for each treatment and data collection). The air-cooled, four-stroke, compression-ignition single-cylinder engine made by the Italian company Lombardini was used. The D400 eddy current dynamometer made in Germany was used. The ability to measure power by this dynamometer is a maximum of 21 hp, a maximum speed of 10,000 rpm and a maximum torque of 80 N.m. To measure of emissions, the MAHA MGT5 emissions meter was used. This device is able to measure the values of CO, CO2, NOX, O2 and UHC.Results and DiscussionThe results showed that increasing engine speed in all fuel combinations increased engine power, specific fuel consumption, carbon monoxide and unburned hydrocarbons and decreased torque. Also, increasing the amount of nano cellulose per engine speed increased the amount of power and torque, but reduced the specific fuel consumption, carbon monoxide and unburned hydrocarbons. The amount of NOX increased with increasing engine speed, but at each engine speed the addition of 25 ppm nanocellulose to pure diesel significantly increased the amount of NOX. But at low speed, increasing 75 ppm nanocellulose to pure diesel reduced the amount of NOX.ConclusionThe results of this study showed that the addition of nano cellulose as nanoparticles can improve the performance of diesel engines and also reduce the amount of emissions gases emitted from the engine. The results also showed that increasing 25ppm nanocellulose had a greater effect on engine performance. But to reduce the amount of emissions, 75 ppm nanocellulose was better

The requirements and challenges in preventing of road traffic injury in Iran. A qualitative study

<p>Abstract</p> <p>Background</p> <p>Road traffic injuries (RTIs) are a major public health problem, especially in low- and middle-income countries. Among middle-income countries, Iran has one of the highest mortality rates from RTIs. Action is critical to combat this major public health problem. Stakeholders involved in RTI control are of key importance and their perceptions of barriers and facilitators are a vital source of knowledge. The aim of this study was to explore barriers to the prevention of RTIs and provide appropriate suggestions for prevention, based on the perceptions of stakeholders, victims and road-users as regards RTIs.</p> <p>Methods</p> <p>Thirty-eight semi-structured interviews were conducted with informants in the field of RTI prevention including: police officers; public health professionals; experts from the road administrators; representatives from the General Governor, the car industry, firefighters; experts from Emergency Medical Service and the Red Crescent; and some motorcyclists and car drivers as well as victims of RTIs. A qualitative approach using grounded theory method was employed to analyze the material gathered.</p> <p>Results</p> <p>The core variable was identified as "The lack of a system approach to road-user safety". The following barriers in relation to RTI prevention were identified as: human factors; transportation system; and organizational coordination. Suggestions for improvement included education (for the general public and targeted group training), more effective legislation, more rigorous law enforcement, improved engineering in road infrastructure, and an integrated organization to supervise and coordinate preventive activities.</p> <p>Conclusion</p> <p>The major barriers identified in this study were human factors and efforts to change human behaviour were suggested by means of public education campaigns and stricter law enforcement. However, the lack of a system approach to RTI prevention was also an important concern. There is an urgent need for both an integrated system to coordinate RTI activities and prevention and a major change in stakeholders' attitudes towards RTI prevention. The focus of all activities should take place on road users' safety.</p

Exciton-photon interaction in a quantum dot embedded in a photonic microcavity

We present a detailed analysis of exciton-photon interaction in a microcavity made out of a photonic crystal slab. Here we have analyzed a disk-like quantum dot where an exciton is formed. Excitonic eigen-functions in addition to their eigen-energies are found through direct matrix diagonalization, while wave functions corresponding to unbound electron and hole are chosen as the basis set for this procedure. In order to evaluate these wave functions precisely, we have used Luttinger Hamiltonian in the case of hole while ignoring bands adjacent to conduction band for electron states. After analyzing Excitonic states, a photonic crystal based microcavity with a relatively high quality factor mode has been proposed and its lattice constant has been adjusted to obtain the prescribed resonant frequency. We use finite-difference time-domain method in order to simulate our cavity with sufficient precision. Finally, we formulate the coupling constants for exciton-photon interaction both where intra-band and inter-band transitions occur. By evaluating a sample coupling constant, it has been shown that the system can be in strong coupling regime and Rabi oscillations can occur for Excitonic state population.Comment: Journal of Physics B: Atomic and Molecular Physics (to appear

Barriers and facilitators to provide effective pre-hospital trauma care for road traffic injury victims in Iran: a grounded theory approach

BACKGROUND: Road traffic injuries are a major global public health problem. Improvements in pre-hospital trauma care can help minimize mortality and morbidity from road traffic injuries (RTIs) worldwide, particularly in low- and middle-income countries (LMICs) with a high rate of RTIs such as Iran. The current study aimed to explore pre-hospital trauma care process for RTI victims in Iran and to identify potential areas for improvements based on the experience and perception of pre-hospital trauma care professionals. METHODS: A qualitative study design using a grounded theory approach was selected. The data, collected via in-depth interviews with 15 pre-hospital trauma care professionals, were analyzed using the constant comparative method. RESULTS: Seven categories emerged to describe the factors that hinder or facilitate an effective pre-hospital trauma care process: (1) administration and organization, (2) staff qualifications and competences, (3) availability and distribution of resources, (4) communication and transportation, (5) involved organizations, (6) laypeople and (7) infrastructure. The core category that emerged from the other categories was defined as "interaction and common understanding". Moreover, a conceptual model was developed based on the categories. CONCLUSIONS: Improving the interaction within the current pre-hospital trauma care system and building a common understanding of the role of the Emergency Medical Services (EMS) emerged as key issues in the development of an effective pre-hospital trauma care process

Discerning Tumor Status from Unstructured MRI Reports—Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing

Information in electronic medical records is often in an unstructured free-text format. This format presents challenges for expedient data retrieval and may fail to convey important findings. Natural language processing (NLP) is an emerging technique for rapid and efficient clinical data retrieval. While proven in disease detection, the utility of NLP in discerning disease progression from free-text reports is untested. We aimed to (1) assess whether unstructured radiology reports contained sufficient information for tumor status classification; (2) develop an NLP-based data extraction tool to determine tumor status from unstructured reports; and (3) compare NLP and human tumor status classification outcomes. Consecutive follow-up brain tumor magnetic resonance imaging reports (2000–­2007) from a tertiary center were manually annotated using consensus guidelines on tumor status. Reports were randomized to NLP training (70%) or testing (30%) groups. The NLP tool utilized a support vector machines model with statistical and rule-based outcomes. Most reports had sufficient information for tumor status classification, although 0.8% did not describe status despite reference to prior examinations. Tumor size was unreported in 68.7% of documents, while 50.3% lacked data on change magnitude when there was detectable progression or regression. Using retrospective human classification as the gold standard, NLP achieved 80.6% sensitivity and 91.6% specificity for tumor status determination (mean positive predictive value, 82.4%; negative predictive value, 92.0%). In conclusion, most reports contained sufficient information for tumor status determination, though variable features were used to describe status. NLP demonstrated good accuracy for tumor status classification and may have novel application for automated disease status classification from electronic databases