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Alpine ecosystems are experiencing high rates of warming due to climate change which, is resulting in a significant upward shift of plant species in elevation as an attempt to track their thermal niches. The shift in the distribution of some species upwards sites of higher altitudes could imply broad changes ranging from the physiological response of individuals to alterations in the ecosystem functioning. In fact, plant species will be exposed to new environmental and geographical constraints together with the establishment of new biotic interactions. The objective of the present work is to elucidate the direct effects of low air pressure on the ecophysiology and performance of several plant species. For this purpose, three plant species (Trifolium pratensis, Hieracium pilosella and Arabidopsis thaliana) were grown in a controlled chambers with different air pressure conditions (100, 85, 75 and 60kPa). Diurnal variation of temperature, relative humidity, and light intensity were kept similar between chamber.The duration of the exp riment was one month after which, some ecophysiological parameters were determined and compared (growth, leaf gas exchange, chlorophyll fluorescence, C/N ratio and stable carbon isotope composition (δ13C)). Preliminary results showed that low air pressure decreases gas exchange rate, transpiration, stomatal conductance and growth parameters of the three species studied. Furthermore, low air pressure increases specific leaf area at 75kPa, whereas it decreases total carbon, C/N ratio and above plant biomass at 60kPa. We conclude that the upshift in the distribution of plant species in alpine environment could result in the appearance and development of new traits that will be of decisive importance in their adaptation process, distribution ranges and survival which, might have high evolutionary and ecological consequences.
My name is Bouchra El Omari, I am plant eco-physiologist, I did my Ph.D on the eco-physiological responses of holm oak after fire at the university of Barcelona. I worked as a postdoctoral researcher at the Smithsonian Tropical Research Institute and at the University of Barcelona. I have the experience working with plant species from both the tropical and Mediterranean areas. I studied the responses to excess light, drought and nitrogen deficiency and the susceptibility to the infection by several pathogens. I worked also as a Professor of Biology at the University of Sidi Mohamed ben Abdallah (Morocco). Actually, I am working as a senior researcher at the eurac Research (Italy). My research subject is the effect of low air pressure on the physiology of alpine plant species. My area of expertise is leaf gas exchange, resource storage and allocation, stable isotopes, plant hydraulics and chlorophyll fluorescence. Almost all my experimental results are published in international journals of high impact.
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In a recent paper, Oliveira et al. (2021) presented a large selection of video and personal camera footage of various earthquakes and tsunamis. As the use of video surveillance cameras is increasing in recent years due to the monitoring of spaces in either the urban setting, building´s interior, etc., and the number of occurrences is keeping its trend, if not increasing, much more information is getting available in the Internet or assembled in earthquake agencies. Video cameras are becoming essential tools to obtain real-time information on the mechanical performance of structures during seismic events, as well as on wave propagation properties causing tsunamis, landslides, water sloshing, etc. Their recorded images also provide essential clues on human behavior during shaking. It is like solving the inverse problem during its entire duration, not only by inspecting the final stage of its trajectory (animated versus fixed image). We will be looking at cases created by earthquakes but not described. In many instances, we could estimate motion associated with the movement in analysis, and we accompanied the presentation with analytical formulations to explain the real-time information qualitatively. For example, video images were a fundamental tool in investigating the collapse of two structures during the 2015 Nepal earthquake: the Dharahara Tower and the Tetrastyle Canopy. We can understand their time evolution from the onset of shaking to total collapse by accessing the video footage. Video footage does not replace laboratory static tests or tests on shaking table, pseudodynamic walls, etc., and instrumental networks to monitor Earth and buildings. Still, as long as well-used, the information collected over time is of great value as it shows the “reality” and complements other sources of information. They can serve as an "inspiration" and a random visual health monitoring system.
C.S. Oliveira got his PhD from the University of California, Berkeley, in 1975 and a Full Professor Position at Instituto Superior Tecnico, University of Lisbon, Portugal, in 1992, after 20 years of research at the National Civil Engineering Laboratory in Lisbon. He retired in 2016 and got Emeritus Tittle from Universidade de Lisboa in June 2022. His main field of interest is earthquake engineering, emphasizing engineering seismology, namely strong motion, seismic hazard and risk mitigations. His “scientific hobby” deals with in-situ/analytical vibrations of various types of civil engineering structures, and currently, he is preparing a book on his findings. He is an Associate Editor of the Bulletin of Earthquake Engineering and a Member of the Portuguese Academy of Sciences and the Academy of Engineering. He was awarded the “Nicholas Ambraseys Distinguished Lecture Award” by the “European Association of Earthquake Engineering” in 2021, recognizing his contribution to developing his area of expertise.
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An increasing resilience problem, even in the northern hemisphere, is the climate change driven colonization of cities by disease carrying mosquitoes. These tiny insects kill almost 1 million people every year and account for 17% of the estimated global burden of infectious diseases. In 2018 an outbreak of West Nile Virus affected 12 European countries, infecting more than 1,500 people and provoking almost 200 deaths. Now in 2023, Peru is facing an unprecedented outbreak of Dengue, with more than 110,000 probable cases and at least 121 deaths, only until the end of May. State-of-the art in mosquito surveillance consists on manual inspections of traps. We have developed an IoT sensor that automatically detects and counts mosquitoes, and identifies species, sex and age with Artificial Intelligence (all the data required by Public Health Authorities). The data is wirelessly sent to a cloud server, enabling for the first time remote and automated surveillance of mosquitoes. The same information can be used to enhance reactive actions such as the control and suppression of the vector of transmission, as well as to monitor the effectiveness of the actions to improve the resilience of citizens in effected areas. The technology has been tested by public health professional under real operational conditions, in different countries and urban settings. Traps and sensors were deployed and samples were collected periodically. The inspection of the samples was performed manually and compared with the estimations done by the sensor. A correlation analysis was done to examine the association between the real and estimated counts. Correlations were significant for all cases (p-value < 0.001) and Pearson’s coefficients were close to 1 which indicated a positive strong linear relationship between the estimations made by the sensor and the real values found in inspections of the traps.
CEO and co-founder of IRIDEON SL. Biotech Engineer, with PhD in Sensors and executive education in Business Administration and Marketing & Sales. Experience in analytics and sensor applications in Chemical Industry, Health, Environment and Agro-Food sectors.
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Knowledge of subsurface soil elemental content distribution over agricultural fields is important for optimizing modern agricultural practices and enhancing soil science knowledge. For example, soil carbon is a strong determinant of soil quality, crop productivity, and farm profitability. Thus, accurate field mapping of soil carbon can be beneficial in assessing modern agricultural practices and management decisions for enhancing carbon sequestration and has potential relevance to emerging carbon credit markets. Such soil carbon determinations are desirable since traditional chemical analysis of primary soil elements (particularly carbon) is laborious and time consuming due to the large sample numbers required (to account for landscape variability) and extensive laboratory processing. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This is a non-destructive method that requires no sample preparation a d can perform multi-elemental analyses of large soil volumes. Measurement results are negligibly impacted by local sharp changes in elemental contents. Neutron-gamma soil elemental analysis is based on registration of gamma rays issued from nuclei upon interaction with neutrons; gamma rays are issued due to different processes of neutron-nuclei interactions. For primary soil elements, characteristic gamma lines can be used for content determinations in soil. To attain suitable accuracy, elemental content measurements should continue for ~15 minutes per site. Paired with GPS, our developed scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. In this presentation, recent USDA-ARS NSDL developments concerning neutron gamma analysis applications will be discussed in more detail.
Graduate of the Institute of Technology (Leningrad, USSR) and majored in Radiation Chemistry and Nuclear Physics. Approximately 30 years of experience in Applied Radiation Chemistry and Applied Nuclear Physics. Beginning in 2013, worked at the National Soil Dynamics Laboratory (USDA-ARS, Auburn, AL, USA) on applying nuclear methods (primarily neutron-gamma analysis) for soil elemental analysis
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The purpose of the study was the identification of the presence of microplastics in the Agua Dulce Beach, city of Lima - Peru, therefore samples of sandy sediments were collected in order to evaluate the concentration of microplastic particles and identify their abundance, typology and possible sources of income. In order to obtain a representative sample, 20 sampling points (supra-coastal and high tide) were determined, from an area of 3.5 ha, in triangular transects. The result was the identification of 43 pieces per m2, it was also observed that the predominance of the type of microplastics found is of secondary origin (polystyrene and polypropylene); however, 20.9% correspond to primary microplastics (pellets). Despite the restrictions by COVID-19 with the closure of beaches to bathers between the period 2020 and 2021, there was an increase of 7.5% of microplastics on the beaches of the Peruvian coast. The identification of microplastics of primary (181 pieces) and secondary (683 pieces) origin in the sampled area confirms that we are facing a scenario with polluting agents that cause negative impacts on the environment and affect marine species by altering the food chain (including human health). The traceability analysis of the plastic found is: (1) Plastic processing plants located on the coast itself; (2) Artisanal fishing (buoys, fishing nets, waterproof suits, among others) where plastic waste is thrown into the sea, it erodes, fragments, and is deposited in the beach area, affecting the marine ecosystem; (3) Bathers, and (4) Drag by marine currents. In Peru, beach cleaning campaigns, as the main measure applied by the Peruvian government, however, preventive policies, regulation, education and the creation of alternative materials must constitute the system that allows reversing the adverse situation.
Doctor in Environmental Science - Master in Environmental Science, majoring in Management and Environmental Regulation of Land Use - Geographer engineer. Panellist at the ISWA World Solid Waste Congress: Singapore (2022), Athens – Greece (2021), Bilbao – Spain (2019), Kuala Lumpur – Malaysia (2018), Baltimore – USA (2017), Novi Sad – Serbia (2016), Antwerp – Belgium (2015), São Paulo – Brazil (2014), and Florence – Italy (2012). International speaker on solid waste representing Peru in: Turkey, Italy, Switzerland, Cuba, Paraguay, Ecuador, Costa Rica, El Salvador, Colombia and Argentina. Best Presentation Award, of the XVI. International Conference on Solid Waste Recycling Technologies, Estambul – Turquía (2022). Best Scientific Paper Award at the «World Resources Forum in 2016», San Jose – Costa Rica. Awarded Best Oral Paper at the «V Inter-American Solid Waste Congress in 2013», Lima – Peru. In 2023 he was recognized by the College of Engineers of Peru for «Outstanding professional work as a Geographical gineer». University teacher.
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With the evolution of the Internet of Things, our health-monitoring systems are advancing day by day. We explore this emerging technology and propose an advanced security framework that comprises a four-layer architecture health-monitoring system. We collect patient data using smart and intelligent devices. We categorize this collected information into different medical classes. Maintaining privacy and security while collecting this information from patient’s wearable smart and intelligent sensing devices is today’s major challenging task. Our main aim is to address this challenging task. So, We propose a lightweight and secure communication framework that is based on blockchain architecture for decentralized IoT networks. We use the concept of transfer learning for classification into different classes. We develop a model, which uses blockchain for security and takes an advantage of transfer learning that uses multiple pertained models. The presented routing methodology incorporates parameters viz. probability, credibility rating, node left energy to forward the data to its target station so that the network overhead and energy usage is minimized. For the classification of the collected patient information, we use 4 different pre-trained convolutional neural networks model: InceptionV3, ResNet50, SqueezeNet, and VGG19. After the simulation of the proposed routing protocol and we compare it with other benchmark protocols on different performance metrics. The experimental results give 92.24% classification accuracy better than earlier models.
Dr. Poonam Rani is an Associate Professor in the Computer Science and Engineering department at Netaji Subhas University of Technology (NSUT), formerly NSIT, Dwarka, New Delhi, India. She has done her Ph.D. in the Computer Engineering department at Delhi University, India, in Jan 2021. Her research interest includes Blockchain, IoT, Social networks Analysis, Soft Computing, and Machine learning. She has published several papers in reputed international journals including SCIE and international Scopus conferences and book chapters. She is invited as a Faculty Resource Person/Session Chair/Reviewer/TPC member in different FDP, conferences, and journals. She has reviewed several research articles in reputed international journals. Currently, she is a member of ISTE, IETE, and IEEE. She has worked in the timetable committee and admission committee. She is currently working as chairperson of DTCRC (CSE), Departmental NBA coordinator, Departmental Library coordinator, and member of AAI (Alumni Affairs Interim). She has guided several B.Tech. and M.Tech. students in their major projects. She is also teaching and guiding Ph.D. students in the CSE department of NSUT.
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Municipal solid waste (MSW) is a universal issue affecting all countries. The current MSW handling process by mainly disposing into open landfills has adverse environmental effects and is economically unfavorable. Due to the heterogeneous characteristics of MSW, a combination of different waste processing facilities with simultaneous cost and greenhouse gas (GHG) minimization needs to be performed for developing circular waste management. Taking Malaysia as a case study, a multi-objective MSW management model is established using the mixed-integer linear programming with augmented ε-constraint method version 2 to circumvent the limitation of the conventional weighting method. The model determines the optimum MSW allocation on seven waste processing facilities, including open landfills, material recycling facilities, sanitary landfills, anaerobic digestion, composting, incineration, and plasma gasification. Compared to the current scenario in Malaysia, the least-cost solution shows a 26% reduction for both cost and GHG emissions, while the least GHG emissions solution indicates a 159% reduction of GHG emissions with a 15% increase in cost. The sensitivity analysis demonstrates that plasma gasification is more favorable when electricity prices increase. A change in waste separation rate from 30% to 90% reduces total MSW management cost and the net GHG emissions by 18.24 MYR/tonne MSW and 0.30 tonne CO2-eq/tonne MSW, respectively. This study aligns with SDG 12 and SDG 13 and provides quantitative information to policymakers in developing a resilient and resource-efficient MSW management system in Malaysia. While the study takes Malaysia as a case study, the developed model can apply to other places facing a similar MSW disposal dilemma.
Dr Woon is an Associate Professor and Head of PhD Program of New Energy Science and Engineering at Xiamen University Malaysia, a Professional Technologist by the Malaysia Board of Technologists, and a Green Building Accredited Professional by REHDA Malaysia. He advocates achieving transformative resilience for climate and environmental sustainability in waste and wastewater management, green building, renewable energy, and green mobility. He is passionate about utilizing systems-analytical approaches such as life cycle assessment, multi-objective optimization, artificial intelligence, pinch analysis, material flow analysis, and P-graph analysis on issues related to the environment-economic-social well-being nexus. He has published 50 papers, with over half in WoS Q1/Q2 journals as the first/corresponding author. He serves as the editorial board member of Green and Low-Carbon Economy, and guest editor of several WoS/Scopus-indexed journals such as Cleaner Engineering and Technology, Frontiers in Sustainability, Sustainability, and Energies. He received his PhD in Environmental Engineering from the Hong Kong University of Science and Technology.
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The frequency and intensity of natural disasters have been increasing in recent decades, especially earthquakes are one of the causes of major natural disasters. Improving community adaptive response to disasters based on community capacity has gradually become an effective means of coping with disaster risks and improving residents' well-being and community participation in disaster planning and management. We integrate community resilience and disaster management to establish an evaluation framework for community-based earthquake disaster management (CEDM) based on community perspectives under the importance-performance analysis (IPA) method and identify the factors affecting community adaptive behavior. Features that affect the differentiation of community residents' adaptive behavior in the CEDM program are classified into risk perception, learning earthquake knowledge, the ability to earthquake prevention, and creating a platform on CEDM. The results identify that the CEDM has to integrate the higher community education plan, the stronger flexibility to disaster preparedness, the higher the residents' awareness of disaster prevention, the stronger the ability to adapt to disasters; the higher the ability of the government and non-profit organizations to cooperate with the community to deal with disasters, and the stronger the community's ability to manage disasters. These findings provide valuable insights into the construction of CEDM systems and related policymaking.
Education 202308 – NDHU, Ph.D. of Natural Resources and Environment Studies 2009 NCKU, Institute of Architecture, Ph.D. Candidate 2004 KSU, Master of Architecture Experience 2013-present Jingsi Temple & Tzu Chi Foundation, Architecture Designer 2010-2012, University Visiting Lecturer 2005-2009, CECI Engineering Division Publication 2022 International Journal of Natural Hazards (Springer) 2023 International Journal of Disaster Risk Reduction (Elsevier) will be published 2021 AAERE International Conference 2021 13th Annual Conference on Development Studies 2011 IEEE Published 2009 CIB Published Recent Research project 110-111 Hualien east coast ecosystem service function value evaluation research. 111 Research on social acceptance and economic impact assessment of ground-based photoelectric development on changes in land use patterns. Resilient urban and rural areas, disaster prevention and adjustment under extreme disasters Award 2021 13th Annual Conference on Development Studies won the Excellent 2002 International Competition Excellent Work 1998 Construction Award scholarship
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