The role of environmental stress on protein synthesis fidelity

Estudos recentes estabelecem uma ligação entre erros na tradução do mRNA e cancro, envelhecimento e neurodegeneração. RNAs de transferência mutantes que introduzem aminoácidos em locais errados nas proteínas aumentam a produção de espécies reactivas de oxigénio e a expressão de genes que regulam autofagia, ribofagia, degradação de proteínas não-funcionais e protecção contra o stress oxidativo. Erros na tradução do mRNA estão portanto relacionados com stress proteotóxico. Sabe-se agora que o mecanismo de toxicidade do crómio está associado à diminuição da fidelidade de tradução e à agregação de proteínas com malformações que destabilizam a sua estrutura terciária. Desta forma, é possível que os efeitos do stress ambiental ao nível da degeneração celular possam estar relacionados com a alteração da integridade da maquinaria da tradução. Neste estudo procedeu-se a uma avaliação alargada do impacto do stress ambiental na fidelidade da síntese de proteínas, utilizando S. cerevisiae como um sistema modelo. Para isso recorreu-se a repórteres policistrónicos de luciferase que permitiram quantificar especificamente a supressão de codões de terminação e o erro na leitura do codão AUG em células exposta a concentações não letais de metais pesados, etanol, cafeína e H2O2. Os resultados sugerem que a maquinaria de tradução é na generalidade muito resistente ao stress ambiental, devido a uma conjugação de mecanismos de homeostase que muito eficientemente antagonizam o impacto negativo dos erros de tradução. A nossa abordagem quantitativa permitiu-nos a identificar genes regulados por uma resposta programada ao stress ambiental que são também essenciais para mitigar a ocorrência de erros de tradução, nomeadamente, HSP12, HSP104 e RPN4. A exposição prolongada ao stress ambiental conduz à saturação dos mecanismos de homeostase, contribuindo para a acumulação de proteínas contendo erros de tradução e diminuindo a disponibilidade de proteínas funcionais directamente envolvidas na manutenção da fidelidade de tradução e integridade celular. Ao contrário de outras Hsps, a Hsp12p adopta normalmente uma localização membranar em condições de stress, que pode modular a fluidez e estabilidade membranar, sugerindo que a membrana plasmática é um alvo preferencial da perda de fidelidade da tradução. Para melhor compreender as respostas celulares aos erros de tradução, células contendo deleções em genes codificadores das Hsps foram transformadas com tRNAs mutantes que introduzem alterações no proteoma. Os nossos resultados demonstram que para além da resposta geral ao stress, estes tRNAs induzem alterações a nível do metabolismo celular e um aumento de aminoacilação com Metionina em vários tRNAs, sugerindo um mecanismo de protecção contra espécies reactivas de oxigénio. Em conclusão, este estudo sugere um papel para os erros de tradução na gestão de recursos energéticos e na adaptação das células a ambientes desfavoráveis.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Race-to-halt energy saving strategies

Energy consumption is one of the major issues for modern embedded systems. Early, power saving approaches mainly focused on dynamic power dissipation, while neglecting the static (leakage) energy consumption. However, technology improvements resulted in a case where static power dissipation increasingly dominates. Addressing this issue, hardware vendors have equipped modern processors with several sleep states. We propose a set of leakage-aware energy management approaches that reduce the energy consumption of embedded real-time systems while respecting the real-time constraints. Our algorithms are based on the race-to-halt strategy that tends to run the system at top speed with an aim to create long idle intervals, which are used to deploy a sleep state. The effectiveness of our algorithms is illustrated with an extensive set of simulations that show an improvement of up to 8% reduction in energy consumption over existing work at high utilization. The complexity of our algorithms is smaller when compared to state-of-the-art algorithms. We also eliminate assumptions made in the related work that restrict the practical application of the respective algorithms. Moreover, a novel study about the relation between the use of sleep intervals and the number of pre-emptions is also presented utilizing a large set of simulation results, where our algorithms reduce the experienced number of pre-emptions in all cases. Our results show that sleep states in general can save up to 30% of the overall number of pre-emptions when compared to the sleep-agnostic earliest-deadline-first algorithm.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

How does introducing love impact management?

Religion at work is nowadays a hot-topic for organizational researchers. Studies have been conducted in order to understand whether there is a possible connection between God and management. This study aims to understand what is the impact of managing through God’s Love. It was found that managing with Love contributes for a new organizational culture characterized by the way managers face work (Culture of Identification), the way they use their characteristics for the benefit of the organization (Culture of Integration), the way human relations are developed (Culture of Bonds) and that it creates sustainable value (Culture of Entrepreneurship) for organizations. Main implications of these results are presented below.

Integrated Management of Interface Power (IMIP) Framework

La présence importante de plusieurs réseaux sans-fils de différentes portées a encouragée le développement d’une nouvelle génération d’équipements portables sans-fils avec plusieurs interfaces radio. Ainsi, les utilisateurs peuvent bénéficier d’une large possibilité de connectivité aux réseaux sans-fils (e.g. Wi-Fi [1], WiMAX [2], 3G [3]) disponibles autour. Cependant, la batterie d’un nœud mobile à plusieurs interfaces sera rapidement épuisée et le temps d’utilisation de l’équipement sera réduit aussi. Pour prolonger l’utilisation du mobile les standards, des réseaux sans-fils, on définie (individuellement) plusieurs états (émission, réception, sleep, idle, etc.); quand une interface radio n’est pas en mode émission/réception il est en mode sleep/idle où la consommation est très faible, comparée aux modes émission/réception. Pourtant, en cas d’équipement portable à multi-interfaces radio, l’énergie totale consommée par les interfaces en mode idle est très importante. Autrement, un équipement portable équipé de plusieurs interfaces radio augmente sa capacité de connectivité mais réduit sa longévité d’utilisation. Pour surpasser cet inconvénient on propose une plate-forme, qu'on appelle IMIP (Integrated Management of Interface Power), basée sur l’extension du standard MIH (Media Independent Handover) IEEE 802.21 [4]. IMIP permet une meilleure gestion d’énergie des interfaces radio, d’un équipement mobile à multi-radio, lorsque celles-ci entrent en mode idle. Les expérimentations que nous avons exécutées montrent que l’utilisation de IMIP permet d'économiser jusqu'a 80% de l'énergie consommée en comparaison avec les standards existants. En effet, IMIP permet de prolonger la durée d'utilisation d'équipements à plusieurs interfaces grâce à sa gestion efficace de l'énergie.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Hyperresolution global land surface modeling: meeting a grand challenge for monitoring Earth's terrestrial water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Discerning policy and drivers for sustainable facilities management practice

Due to the changing nature of the facilities management (FM) profession, facilities managers are increasingly engaged with the evolving sustainability agenda in the UK and the development or uptake of sustainability policies within their organisations. This study investigates how facilities managers are engaging with the sustainability agenda and the drivers, policy issues and information they use to improve their sustainability performance management. A web based self-administered questionnaire survey of facilities managers in the UK was conducted to identify drivers and issues that influence and support good sustainable practices. A total of 268 facilities managers responded. The results indicate that legislation is the most important driver for the implementation of sustainable practices. Corporate image and Organisational ethos are also recognised. However demand for efficient monitoring, management and reporting on environmental impact is not highly rated even though the top three issues of sustainability managed by facilities managers are energy management, waste and recycling management and carbon footprint. In addition, facilities managers are expected to take ownership of activities assigned to the reduction of carbon emission. Government industries and organisation with high turnover are more likely to have a sustainability policy. Financial constraints are the main barriers while legislations are the main driver for implementing sustainability. For non-profit organisations and the charitable sector, financial constraints are no hindrance to implementing a sustainability policy. The conclusion drawn is that sustainability agendas continue to be influenced by regulated environmental issues rather than a balanced approach which takes into consideration the wider social and economic aspects of sustainability. While this scenario is far from ideal, the expectation is that the organisation will trust FM to take a vital role in delivering a comprehensive sustainability policy due to the rising tide of legislation, public scrutiny, as well as the needed business case for genuinely embracing sustainability. However, as the integration of sustainability with core business strategies is continuously evolving the emphasis on different drivers will vary from organisation to organisation as well as the responsibilities of facilities managers.

Domestic energy models: complexities in defining specific tools

The domestic (residential) sector accounts for 30% of the world’s energy consumption hence plays a substantial role in energy management and CO2 emissions reduction efforts. Energy models have been generally developed to mitigate the impact of climate change and for the sustainable management and planning of energy resources. Although there are different models and model categories, they are generally categorised into top down and bottom up. Significantly, top down models are based on aggregated data while bottom up models are based on disaggregated data. These approaches create fundamental differences which have been the centre of debate since the 1970’s. These differences have led to noticeable discrepancies in results which have led to authors arguing that the models are of a more complementary than a substituting nature. As a result developing methods suggest that there is the need to integrate either the two models (bottom up − top down) or aspects that combine two bottom up models or an upgrade of top down models to compensate for the documented limitations. Diverse schools of thought argue in favour of these integrations – currently known as hybrid models. In this paper complexities of identifying country specific and/or generic domestic energy models and their applications in different countries have been critically reviewed. Predominantly from the review it is evident that most of these methods have been adapted and used in the ‘western world’ with practically no such applications in Africa.

Service oriented approach to facility management using extended building information modelling

Facility management (FM), from a service oriented approach, addresses the functions and requirements of different services such as energy management, space planning and security service. Different service requires different information to meet the needs arising from the service. Object-based Building Information Modelling (BIM) is limited to support FM services; though this technology is able to generate 3D models that semantically represent facility’s information dynamically over the lifecycle of a building. This paper presents a semiotics-inspired framework to extend BIM from a service-oriented perspective. The extended BIM, which specifies FM services and required information, will be able to express building service information in the right format for the right purposes. The service oriented approach concerns pragmatic aspect of building’s information beyond semantic level. The pragmatics defines and provides context for utilisation of building’s information. Semiotics theory adopted in this paper is to address pragmatic issues of utilisation of BIM for FM services.