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Systems of cogeneration of cooling, heating and electric power with renewable energy sources are a very suitable solution for the independency of fossil fuels and reducing the emission of environmental pollutants. In this research, an internal combustion engine with a boiler and a linear parabolic concentrating collector has been used to realize the production of electrical and thermal energy. That the internal combustion engine is responsible for the production of electric power, which is responsible for the thermal energy by the concentrated linear collector with the boiler and the heat exchanger. Due to the need for thermal energy at different times, a thermal storage tank has been used in such a way that the thermal energy produced by the solar collector and boiler is stored in the tank to supply the load at the required times. The results show that the total cost of final products for one day of the hottest month of summer in the proposed thermal power plant with fossil fuel will be $69.3 and $63.5, respectively, and for 1 day of the coldest month of winter, the total cost of producing final products in the proposed and fossil system will be $31.6 and $28.5, respectively.

Uncovered solar collectors using perforated absorbent plates are a variety of reception collectors that are used for solar heating of air for consumption in air conditioning systems and dryers. The thermal performance of these collectors is subject to various factors including diameter and step holes, air suction velocity and solar radiation. Using modeling, a proper evaluation of the effect of each of these parameters on the thermal performance of the collector can be obtained. In this paper, by using heat transfer and energy balance modeling in different components of the sample collector, the effect of each of these parameters is estimated by using the preheatment of building air, thermal efficiency and output temperature of the collector according to the parameters of solar radiation, air suction velocity, diameter and step of the holes of the absorbent plate. Also, the efficiency of heat exchange of perforated plates is estimated for air suction velocity, diameter and step of holes. The results show that increasing the suction rate of air and solar radiation increases the thermal efficiency of the collector. Also, efficiency of the heat exchange (εHX), which decreases with increasing suction speed, is due to the decrease in the output temperature of the collector because of the increase in the amount of inlet air to it, increasing the suction rate from 60 m/h to 160 m/h reduces the efficiency of the heat exchange by 30%.

Additional file 1. Table S1. PRISMA Checklist; Table S2. Search strategies and the number of records according to different electronic database.

Evaluation processes must be conceived in line with learner-centered emphasis though instruction in English for Academic Purposes (EAP) is grounded on learner-centered approaches, EAP- English for Academic Purpose, which is considered as a major important functional feature of the language. Formative evaluation is major evaluation approach that provides various advantages for EAP students. This study examined (n=50) the perception of lecturers in three Thai universities, including Walailak, of including the inclusion of formative assessments in EAP instruction. The findings showed that, despite several obstacles to its implementation, lecturers have adapted optimistic attitudes to the use of formative evaluation in EAP education through studies and interviews. In addition, the instructors knew the merits of EAP training assessment. However, the expertise and the knowledge required for the formational assessment of EAP instructions were not available to them. The main evaluation in the form of the final examination was summative. This study suggests that formative evaluation should be taken into account in the EAP curriculum. Â Â Â

One of the factors limiting busiest airport’s runway throughput capacity is the spacing to be applied between landing aircraft to ensure that the runway is vacated when the follower aircraft reaches the runway threshold. Today, because the Controller is not able to always anticipate the runway occupancy time (ROT) of the leader aircraft, significant spacing buffers are added to the minimum required spacing in order to cover all possible cases, which negatively affects the resulting arrival throughput. The present paper shows how a Machine Learning (ML) analysis can support the development of accurate, yet operational, models for ROT prediction depending on all impact parameters. Based on Gradient Boosting Regressors, those ML models make use of flight information (such as aircraft type, airline, flight data) and weather information to model the ROT. This paper shows how it can be used operationally to increase runway capacity while maintaining or reducing the risk of delivery of separations below runway occupancy time. The methodology and related benefits are assessed using three years of field measurements gathered at Zurich airport.

The present study explores teachers of English as a foreign language (EFL) in Asia, their attitudes toward teaching English, the roles of teaching the English language, motivations, benefits, implications, and the reason they are highly recognized in non-English speaking countries. The researcher applied the qualitative method through semi-structured interviews with (n=4) Ghanaian teachers working in three countries in Asia as EFL instructors; their strengths and weaknesses were investigated. The result of semi-structured interviews revealed that Ghanaian teachers' primary role in Asia is to teach English and literacy skills. Moreover, the reasons they chose to work in Asia are higher salaries and better working conditions. Their inability to speak the local language and culture diversity were their weaknesses. Native and Non-native English teachers' preferences, which directly/indirectly affect English teaching, are discussed. The respondents' positive attitude toward English teaching overseas is also investigated and presented. This empirical study revealed the globalization of English in the 21st century.

A flight may be late departing or arriving from an airport because of the delays that occurred earlier on that day. From a small amount of initial delay, it can propagate and compromise on-time performance of the overall operations of the same aircraft. It can propagate on the next legs and compromise other flights as well which causes disruption in the network. A lot of research has been done in the area of flight delay propagation and many models were created to help airlines and operators reduce that very same effect. The Time Based Separation (TBS) project has brought new methods for separation of arrivals by time instead of distance. It’s a promising method for reducing flight delays. In this paper, by collecting flight records data from the Central Office for Delay Analysis in EUROCONTROL, we’ve observed a significant decrease in delays in case of strong headwinds, which proves the very point of TBS’s effectiveness in optimizing runway throughput and network operations. The dataset consisted of around 60’000 flights at London Heathrow airport. By using that data, a few analyses are executed which show us the overall effect on the network.

Tungsten is considered by the European Union as a critical raw material for future development due to its expected demand and scarcity of resource within Europe. It is therefore, critical to optimize European tungsten operations and maximise recoveries. The role of enhanced gravity/centrifugal concentrators in recovering tungsten from ultra-fine fractions should form an important part of this aim. Reported herein are the results of investigations to improve efficiency of Wolf Minerals’ Draklends mine, a major European tungsten mine, by recovering saleable material from a magnetic waste stream of a low-intensity magnetic separator using an enhanced gravity concentrator. The mine hosts wolframite and ferberite as the main tungsten bearing mineral species. A Mozley multi-gravity separator (MGS) C-900 was selected as it is suited to exploiting small variations in mineral density to affect a separation. Working with a current manufacturer, a novel scraping blade system was tested. To assess the MGS in a statistically valid manner, a response surface methodology was followed to determine optimal test conditions. The test programme showed that the most important parameters were drum speed and wash water rate. Under optimal conditions the model predicted that 40% of the tungsten could be recovered above the required grade of 43% WO3.

Wake turbulence can be experienced by aircraft when encountering the wake vortex of another aircraft. The aim of this study is to improve the understanding of the risk posed by en route wake-vortex encounters in the en route flight phase. To quantify this risk, a simulation framework has been conceived that makes use of recorded historical surveillance data and computes the wake-vortex trajectory and decay for each aircraft based on a wake-vortex model. The simulation has been validated and subsequently used to determine the probability of encountering a wake vortex in upper European airspace. The simulation results bear out that a severe wake-vortex encounter can be expected approximately once every 38 days. Three factors have been identified that contribute to the risk of encountering a wake vortex during the en route phase of flight, viz., the characteristics of the exposed or generating aircraft, the encounter geometry, and the prevailing tropopause height in the atmosphere. The combined time evolutio...

Accidents on the runway triggered the development and implementation of mitigation strategies. Therefore, the airline industry is moving toward proactive risk management, which aims to identify and predict risk percursors and to mitigate risks before accidents occur. For certain predictions Machine Learning techniques can be used. Although many studies have explored and applied novel Machine Learning techniques on different aircraft Radar and operational Taxi data, the identification and prediction of abnormal Runway Occupancy Times and the observation of related percursors are not well developed. In our previous papers, three feasible methods were introduced: Lasso, Multi-Layer Perceptiona and Neural Networks to predict the Taxi-Out Time on the taxiway and the time to Fly and True Airspeed profile on final approach. This paper presents a new Machine Learing method, where we merge these feasible Machine Learning techniques for prediction the abnormal Runway Occupancy times of unique radar data patterns. Additionally we use in this study the Regression Tree method to observe key related precursors extracted from the top 10 features. Compared with existing methods, the new method no longer requires predefined criteria or domain knowledge. Tests were conductioned using runway and final approach aircraft radar data consisting of 78,321 Charles de Gaulle flights and were benchmarked against 500,000 Vienna flights.

currently, at many airports, the runway throughput is the limiting factor for the overall capacity. Among the most important constraining parameters is the separation minima expressed in distance. On the top of these minima, the difference of the leader and follower aircraft speed profiles imposes to consider buffer to cope with compression effect. Currently, Air Traffic Control Officers (ATCO’s) take these buffers on the basis of their training and experience. However, this experience will not be sufficient to safety deploy advanced concepts, like pair-wise separations, that increase variability in the separations to be delivered and therefore in the compression buffer to be considered. Systematic analysis of years of radar tracks has allowed to better predict the buffers to apply by characterising the time to fly (T2F) given a separation distance and True Airspeed (TAS) profile as a function of meteorological parameters.This paper presents how Machine Learning (ML) techniques may be used for predicting the T2F and TAS profile on final approach. Different ML techniques will be assessed on their forecast performance, computational time and amount of data needed for delivering a reliable prediction. The techniques will be applied on 2 different major European airports traffic and will be benchmarked against Optimized Runway Delivery (ORD) study using a Model Based Approach (MBA) for deriving the T2F and TAS. As a result the most efficient ML techniques will be applied on two case studies for predicting the T2F and TAS.

It is generally assumed that during sprayforming the amount of micro- and macro-segregation in the sprayforms will be limited or absent because of low liquid fractions, small grain size and high cooling rate. This paper shows that macro-segregation can occur in sprayforms of Al, even when small liquid fractions are present during growth of the sprayform. This segregation occurs by an inverse mechanism, with solute-rich liquid sucked back through a solid network by solidification shrinkage. Liquid flow outwards is further enhanced by the centrifugal force produced by sprayform rotation. The liquid sucked outwards is enriched in solute (with partition coefficients

Objective To evaluate the sociological effect on indigenous biological event signature recognition and community resilience due to the operational activities of an infectious disease forecast station. Introduction The nation’s first operational infectious disease forecast station, modeled after warning protocols developed in the meteorology community, was activated in 2011. The approach was originally pioneered in Haiti following the 2010 earthquake. Methods We assembled global event signature and forecast libraries that reflected locally diagnosed infectious disease activity and infrastructure impact in a rural community from a public health, veterinary, and human clinical medicine perspective. The deployment site is home to a variety of infectious disease including hantavirus, plague, tularemia, and West Nile in the context of high wildlife-livestock-human interfacing. Information derived from the issuance of forecasts coupled to situational awareness was shared with the public, local officials, public health officers, veterinarians, healthcare providers, and patients through various social media methods. Results Provision of 30-60-90 day forecasts for routine and non-routine endemic infectious disease activity and impact facilitated better coordination of public health messaging and daily conversation with patients in the inpatient and outpatient settings. The signature of an unusual, infrastructure-disruptive outbreak of metapneumovirus and respiratory syncytial virus was recognized and communicated with enough time to activate effective clinical mitigation protocols. Cost estimates demonstrated financial benefit at a local level to anticipating surges of infectious disease activity with enough time to mitigate patient demand. Community-wide engagement with infectious disease forecasts and live event advisories included the promotion of proactive infection control and public health surveillance and response, healthcare provider recognition of non-routine infectious disease, clinical sampling and diagnostic testing protocols, clinician and patient education, and synchronization of proactive disease reporting both in the routine daily clinical setting and in times of crisis. Collateral benefit of consistent messaging delivered to the public by the participating entities was noted. Community awareness of the repertoire of indigenous infectious disease activity was expanded beyond the official public health notification list. Neither issuance of infectious disease forecasts nor advisories issued during crises triggered an influx of anxious well phone calls or visits to the medical system that was deemed operationally relevant. Conclusions Activation of a local infectious disease forecast station modeled after a local weather station promotes routine communication of a broader array of infectious disease activity than that monitored by public health; facilitates proactive, cost effective healthcare; and enabled recognition of unusual, disruptive infectious activity with enough time to enable mitigation of clinical, infrastructure, and financial impact to the community. Routine communication of comprehensive infectious disease forecast and situational awareness information promotes community adaptive fitness to a wide variety of infectious hazards. The results suggest it is possible to transform the traditional public health model of data collection and analysis to one of transparent and open data availability to support innovative reduction in morbidity and mortality.

EURFORUM's Strategic Research Agenda addresses research issues in the particular field of urban transport considering all transport modes and focusing on intermodality for both passenger and freight transport. Technology-oriented as well as policy-oriented research is considered. The focus is directed on urban issues, including the transport between an agglomeration and its surroundings. EURFORUM's SRA relies on the conviction that holistic and interdisciplinary research is the most adequate approach to solve the problems identified in the area of urban transport. Additionally, special attention is paid to urban mobility changes in newly associated States (EU-12). The overall objectives of EURFORUM are to better structure and to better coordinate European research on urban mobility for passengers and goods, by involving all relevant urban mobility stakeholders in the discussion.