Search results for: temporal lobe epilepsy

Authors: Bikash Ranjan Mishra, Lopamudra D. Satpathy

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In the wake of the phenomenal surge in international business in the last decades or more, both the developed and developing economies around the world are in massive competition to attract more and more FDI flows. While the developed countries have marched ahead in the race, the developing countries, especially those of Asian economies, have followed them at a rapid pace. While most of the previous studies have analysed the role of institutional quality in the promotion of FDI flows in developing countries, very few studies have taken an integrated approach of examining the comprehensive impact of institutional quality, globalization pattern and domestic financial development on FDI flows. In this context, the paper contributes to the literature in two important ways. Firstly, two composite indices of institutional quality and domestic financial development for the Asian countries are constructed in comparison to earlier studies that resort to a single variable for indicating the institutional quality and domestic financial development. Secondly, the impact of these variables on FDI flows through their interaction with geographical region is investigated. The study uses panel data covering the time period of 1996 to 2012 by selecting twenty Asian developing countries by emphasizing the quality of institutions from the geographical regions of eastern, south-eastern, southern and western Asia. Control of corruption, better rule of law, regulatory quality, effectiveness of the government, political stability and voice and accountability are used as indicators of institutional quality. Besides these, the study takes into account the domestic credits in the hands of public, private sectors and in stock markets as domestic financial indicators. First in the specification of model, a factor analysis is performed to reduce the vast determinants, which are highly correlated with each other, to a manageable size. Afterwards, a reduced version of the model is estimated with the extracted factors in the form of index as independent variables along with a set of control variables. It is found that the institutional quality index and index of globalization exert a significant effect on FDI inflows of the host countries; in contrast, the domestic financial index does not seem to play much worthy role. Finally, some robustness tests are performed to make sure that the results are not sensitive to temporal and spatial unobserved heterogeneity. On the basis of the above study, one general inference can be drawn from the policy prescription point of view that the government of these developing countries should strengthen their domestic institution, both financial and non-financial. In addition to these, welfare policies should also target for rapid globalization. If the financial and non-financial institutions of these developing countries become sound and grow more globalized in the economic, social and political domain, then they can appeal to more amounts of FDI inflows that will subsequently result in advancement of these economies.

Keywords: Asian developing economies, FDI, institutional quality, panel data

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Authors: A. Onur Kutlu, H. Tolga Bolukbasi

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Since the 1990s, governments, international organizations and scholars have drawn increasing attention to the significance of women in the labour force. While advanced industrial countries in North Western Europe and North America have managed to increase female labour force participation (FLFP) in the early post world war two period, emerging economies of the 1970s have only been able to increase FLFP only a decade later. Among these areas, Southern Europe features a wave of remarkable bounce backs in FLFP. However, despite striking similarities between the features in Southern Europe and those in Turkey, Turkey has not been able to pull women into the labour force. Despite a host of institutional similarities, Turkey has failed to reach to the level of her Southern European neighbours. This paper addresses the puzzle why Turkey lag behind in FLFP in comparison to her Southern European neighbours. There are signs showing that FLFP is currently reaching a critical threshold at a time when structural factors may allow a trend. It is not known, however, the constellation of conditions which may bring rising FLFP in Turkey. In order to gain analytical leverage from similar transitions in countries that share similar labour market and welfare state regime characteristics, this paper identifies the conditions in Southern Europe that brought rising FLFP to be able to explore the prospects for Turkey. Second, this paper takes these variables in the fuzzy set Qualitative Comparative Analysis (fsQCA) as conditions which can potentially explain the outcome of rising FLFP in Portugal, Spain, Italy, Greece and Turkey. The purpose here is to identify any causal pathway there may exist that lead to rising FLFP in Southern Europe. In order to do so, this study analyses two time periods in all cases, which represent different periods for different countries. The first period is identified on the basis of low FLFP and the second period on the basis of the transition to significantly higher FLFP. Third, the conditions are treated following the standard procedures in fsQCA, which provide equifinal: two distinct paths to higher levels of FLFP in Southern Europe, each of which may potentially increase FLFP in Turkey. Based on this analysis, this paper proposes that there exist two distinct paths leading to higher levels of FLFP in Southern Europe. Among these paths, salience of left parties emerges as a sufficient condition. In cases where this condition was not present, a second path combining enlarging service sector employment, increased tertiary education among women and increased childcare enrolment rates led to increasing FLFP.

Keywords: female labour force participation, fsQCA, Southern Europe, Turkey

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Shi-Bo Feng, Sheng-Jie Zhang, Jin Zhou

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The relationship between microbial diversity and algal bloom has received considerable attention for decades. Microbes undoubtedly affect annual bloom events and impact the physiology of both partners, as well as shape ecosystem diversity. However, knowledge about interactions and network correlations among broader-spectrum microbes that lead to the dynamics in a complete bloom cycle are limited. In this study, pyrosequencing and network approaches simultaneously assessed the associate patterns among bacteria, archaea, and microeukaryotes in surface water and sediments in response to a natural dinoflagellate (Alexandrium sp.) bloom. In surface water, among the bacterial community, Gamma-Proteobacteria and Bacteroidetes dominated in the initial bloom stage, while Alpha-Proteobacteria, Cyanobacteria, and Actinobacteria become the most abundant taxa during the post-stage. In the archaea biosphere, it clustered predominantly with Methanogenic members in the early pre-bloom period while the majority of species identified in the later-bloom stage were ammonia-oxidizing archaea and Halobacteriales. In eukaryotes, dinoflagellate (Alexandrium sp.) was dominated in the onset stage, whereas multiply species (such as microzooplankton, diatom, green algae, and rotifera) coexistence in bloom collapse stag. In sediments, the microbial species biomass and richness are much higher than the water body. Only Flavobacteriales and Rhodobacterales showed a slight response to bloom stages. Unlike the bacteria, there are small fluctuations of archaeal and eukaryotic structure in the sediment. The network analyses among the inter-specific associations show that bacteria (Alteromonadaceae, Oceanospirillaceae, Cryomorphaceae, and Piscirickettsiaceae) and some zooplankton (Mediophyceae, Mamiellophyceae, Dictyochophyceae and Trebouxiophyceae) have a stronger impact on the structuring of phytoplankton communities than archaeal effects. The changes in population were also significantly shaped by water temperature and substrate availability (N & P resources). The results suggest that clades are specialized at different time-periods and that the pre-bloom succession was mainly a bottom-up controlled, and late-bloom period was controlled by top-down patterns. Additionally, phytoplankton and prokaryotic communities correlated better with each other, which indicate interactions among microorganisms are critical in controlling plankton dynamics and fates. Our results supplied a wider view (temporal and spatial scales) to understand the microbial ecological responses and their network association during algal blooming. It gives us a potential multidisciplinary explanation for algal-microbe interaction and helps us beyond the traditional view linked to patterns of algal bloom initiation, development, decline, and biogeochemistry.

Keywords: microbial community, harmful algal bloom, ecological process, network

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Authors: Nur Fareza Mustapha

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Solutions to policy problems need to be curated to the local context, taking into account the trajectory of the local development path to ensure its efficacy. For Kuala Lumpur, rapid urbanization and migration into the city for the past few decades have increased the demand for housing to accommodate a growing urban population. As a critical factor affecting housing affordability, land supply constraints have been attributed to intensifying market pressures, which grew in tandem with the demands of urban development, along with existing institutional constraints in the governance of land. While demand-side pressures are inevitable given the fixed supply of land, supply-side constraints in regulations distort markets and if addressed inappropriately, may lead to mistargeted policy interventions. Given Malaysia’s historical development, regulatory barriers for land may originate from the British colonial period, when many aspects of the current laws governing tenure were introduced and formalized, and henceforth, became engrained in the system. This research undertakes a postcolonial institutional analysis approach to uncover the causal mechanism driving the evolution of land tenure systems in post-colonial Kuala Lumpur. It seeks to determine the sources of these shifts, focusing on the incentives and bargaining positions of actors during periods of institutional flux/change. It aims to construct a conceptual framework to further this understanding and to elucidate how this historical trajectory affects current access to urban land markets for housing. Archival analysis is used to outline and analyse the evolution of land tenure systems in Kuala Lumpur while stakeholder interviews are used to analyse its impact on the current urban land market, with a particular focus on the provision of and access to affordable housing in the city. Preliminary findings indicate that many aspects of the laws governing tenure that were introduced and formalized during the British colonial period have endured until the present day. Customary rules of tenure were displaced by rules following a European tradition, which found legitimacy through a misguided interpretation of local laws regarding the ownership of land. Colonial notions of race and its binary view of native vs. non-natives have also persisted in the construction and implementation of current legislation regarding land tenure. More concrete findings from this study will generate a more nuanced understanding of the regulatory land supply constraints in Kuala Lumpur, taking into account both the long and short term spatial and temporal processes that affect how these rules are created, implemented and enforced.

Keywords: colonial discourse, historical institutionalism, housing, land policy, post-colonial city

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Authors: Evans V. Mauda, Stefan H. Foord, Thinandavha C. Munyai

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The greatest threat to biodiversity is a loss of habitat through landscape fragmentation and attrition. Land use changes are therefore among the most immediate drivers of species diversity. Urbanization and agriculture are the main drivers of habitat loss and transformation in the Savanna biomes of South Africa. Agricultural expansion and the intensification in particular, take place at the expense of biodiversity and will probably be the primary driver of biodiversity loss in this century. Arthropods show measurable behavioural responses to changing land mosaics at the smallest scale and heterogeneous environments are therefore predicted to support more complex and diverse biological assemblages. Ants are premier soil turners, channelers of energy and dominate insect fauna, while spiders are a mega-diverse group that can regulate other invertebrate populations. This study aims to quantify the response of these two taxa in a rural-urban mosaic of a rapidly developing communal area. The study took place in and around two villages in the north-eastern corner of South Africa. Two replicates for each of the dominant land use categories, viz. urban settlements, dryland cultivation and cattle rangelands, were set out in each of the villages and sampled during the dry and wet seasons for a total of 2 villages × 3 land use categories × 2 seasons = 24 assemblages. Local scale variables measured included vertical and horizontal habitat structure as well as structural and chemical composition of the soil. Ant richness was not affected by land use but local scale variables such as vertical vegetation structure (+) and leaf litter cover (+), although vegetation complexity at lower levels was negatively associated with ant richness. However, ant richness was largely shaped by regional and temporal processes invoking the importance of dispersal and historical processes. Spider species richness was mostly affected by land use and local conditions highlighting their landscape elements. Spider richness did not vary much between villages and across seasons and seems to be less dependent on context or history. There was a considerable amount of variation in spider richness that was not explained and this could be related to factors which were not measured in this study such as temperature and competition. For both ant and spider assemblages the constrained ordination explained 18 % of variation in these taxa. Three environmental variables (leaf litter cover, active carbon and rock cover) were important in explaining ant assemblage structure, while two (sand and leaf litter cover) were important for spider assemblage structure. This study highlights the importance of disturbance (land use activities) and leaf litter with the associated effects on ant and spider assemblages across the study area.

Keywords: ants, assemblages, biosphere, diversity, land use, spiders, urbanization

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Authors: Juan Peña Aguilar, Lilia Villasana, Rodrigo Valencia, Alberto Pastrana, Martin Vivanco, Juan Peña C

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Each year a growing number of companies entering Mexico in search of the domestic market share. These activities, including stores, telephone long distance and local raw materials and energy, and particularly the financial sector, have managed to significantly increase its weight in the flows of FDI in Mexico , however, you should consider whether these trends FDI are positive for the Mexican economy and these activities increase Mexican exports in the medium term , and its share in GDP , gross fixed capital formation and employment. In general stresses that these activities, by far, have been unable to significantly generate linkages with the rest of the economy, a process that has not favored with competitiveness policies and activities aimed at these neutral or horizontal. Since the nineties foreign direct investment (FDI) has shown a remarkable dynamism, both internationally and in Latin America and in Mexico. Only in Mexico the first recipient of FDI in importance in Latin America during 1990-1995 and was displaced by Brazil since FDI increased from levels below 1 % of GDP during the eighties to around 3 % of GDP during the nineties. Its impact has been significant not only from a macroeconomic perspective , it has also allowed the generation of a new industrial production structure and organization, parallel to a significant modernization of a segment of the economy. The case of Mexico also is particularly interesting and relevant because the destination of FDI until 1993 had focused on the purchase of state assets during privatization process. This paper aims to present FDI flows in Mexico and analyze the different business strategies that have been touched and encouraged by the FDI. On the one hand, looking briefly discuss regulatory issues and source and recipient of FDI sectors. Furthermore, the paper presents in more detail the impacts and changes that generated the FDI contribution of FDI in the Mexican economy , besides the macroeconomic context and later legislative changes that resulted in the current regulations is examined around FDI in Mexico, including aspects of the Free Trade Agreement (NAFTA). It is worth noting that foreign investment can not only be considered from the perspective of the receiving economic units. Instead, these flows also reflect the strategic interests of transnational corporations (TNCs) and other companies seeking access to markets and increased competitiveness of their production networks and global distribution, among other reasons. Similarly it is important to note that foreign investment in its various forms is critically dependent on historical and temporal aspects. Thus, the same functionality can vary significantly depending on the specific characteristics of both receptor units as sources of FDI, including macroeconomic, institutional, industrial organization, and social aspects, among others.

Keywords: foreign direct investment (FDI), competitiveness, neoliberal regime, globalization, gross domestic product (GDP), NAFTA, macroeconomic

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Authors: Justin Durham, Chanda Rooney, Robert Mather, Mickie Vanhoy

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The psychological construct of empathy is to understand a person’s cognitive perspective and experience the other person’s emotional state. Deciphering emotional states is conducive for interpreting vicarious pain. Observing others' physical pain activates neural networks related to the actual experience of pain itself. The study addresses empathy as a nonlinear dynamic process of simulation for individuals to understand the mental states of others and experience vicarious pain, exhibiting self-organized criticality. Such criticality follows from a combination of neural networks with an excitatory feedback loop generating bistability to resonate permutated empathy. Cortical networks exhibit diverse patterns of activity, including oscillations, synchrony and waves, however, the temporal dynamics of neurophysiological activities underlying empathic processes remain poorly understood. Mu rhythms are EEG oscillations with dominant frequencies of 8-13 Hz becoming synchronized when the body is relaxed with eyes open and when the sensorimotor system is in idle, thus, mu rhythm synchrony is expected to be highest in baseline conditions. When the sensorimotor system is activated either by performing or simulating action, mu rhythms become suppressed or desynchronize, thus, should be suppressed while observing video clips of painful injuries if previous research on mirror system activation holds. Twelve undergraduates contributed EEG data and survey responses to empathy and psychopathy scales in addition to watching consecutive video clips of sports injuries. Participants watched a blank, black image on a computer monitor before and after observing a video of consecutive sports injuries incidents. Each video condition lasted five-minutes long. A BIOPAC MP150 recorded EEG signals from sensorimotor and thalamocortical regions related to a complex neural network called the ‘pain matrix’. Physical and social pain are activated in this network to resonate vicarious pain responses to processing empathy. Five EEG single electrode locations were applied to regions measuring sensorimotor electrical activity in microvolts (μV) to monitor mu rhythms. EEG signals were sampled at a rate of 200 Hz. Mu rhythm desynchronization was measured via 8-13 Hz at electrode sites (F3 & F4). Data for each participant’s mu rhythms were analyzed via Fast Fourier Transformation (FFT) and multifractal time series analysis.

Keywords: desynchronization, dynamical systems theory, electroencephalography (EEG), empathy, multifractal time series analysis, mu waveform, neurophysiology, pain simulation, social cognition

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Authors: Tatiana N. Astakhova, Alexander E. Saprygin, Tatyana A. Golovko, Alexander N. Savostyanov, Mikhail S. Vlasov, Natalia V. Borisova, Alexandera G. Karpova, Urana N. Kavai-ool, Elena D. Mokur-ool, Nikolay A. Kolchanov, Lubomir I. Aftanas

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The aim of the study is to compare behaviorally and EEG reactions in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians during the recognition of syntax errors in native and foreign languages. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All participants completed a linguistic task, in which they had to find a syntax error in the written sentences. Russian participants completed the task in Russian and in English. Tuvinian and Yakut participants completed the task in Russian, English, and Tuvinian or Yakut, respectively. EEG’s were recorded during the solving of tasks. For Russian participants, EEG's were recorded using 128-channels. The electrodes were placed according to the extended International 10-10 system, and the signals were amplified using ‘Neuroscan (USA)’ amplifiers. For Tuvinians and Yakuts EEG's were recorded using 64-channels and amplifiers Brain Products, Germany. In all groups 0.3-100 Hz analog filtering, sampling rate 1000 Hz were used. Response speed and the accuracy of recognition error were used as parameters of behavioral reactions. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The accuracy of solving tasks and response speed in Russians were higher for Russian than for English. The P300 amplitudes in Russians were higher for English; the P600 amplitudes in the left temporal cortex were higher for the Russian language. Both Tuvinians and Yakuts have no difference in accuracy of solving tasks in Russian and in their respective national languages (Tuvinian and Yakut). However, the response speed was faster for tasks in Russian than for tasks in their national language. Tuvinians and Yakuts showed bad accuracy in English, but the response speed was higher for English than for Russian and the national languages. With Tuvinians, there were no differences in the P300 and P600 amplitudes and in cortical topology for Russian and Tuvinian, but there was a difference for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference and were reflected foreign language comprehension -while the Russian language comprehension was reflected native language comprehension. We found out that the Tuvinians recognized both Russian and Tuvinian as native languages, and English as a foreign language. The Yakuts recognized both English and Yakut as a foreign language, only Russian as a native language. According to the inquirer, both Tuvinians and Yakuts use the national language as a spoken language, whereas they don’t use it for writing. It can well be a reason that Yakuts perceive the Yakut writing language as a foreign language while writing Russian as their native.

Keywords: EEG, language comprehension, native and foreign languages, Siberian inhabitants

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Authors: Shotiros Protong

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The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

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Authors: Prabhat Kashyap, Krishan Kumar

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Delhi, the capital of India, is one of the most populated and polluted city among the world. In terms of air quality, Delhi’s air is degrading day by day & becomes worst of any major city in the world. The role of biogenic volatile organic compounds (BVOCs) is not much studied in cities like Delhi as a culprit for degraded air quality. They not only play a critical role in rural areas but also determine the atmospheric chemistry of urban areas as well. Particularly, Isoprene (2-methyl 1,3-butadiene, C5H8) is the single largest emitted compound among other BVOCs globally, that influence the tropospheric ozone chemistry in urban environment as the ozone forming potential of isoprene is very high. It is mainly emitted by vegetation & a small but significant portion is also released by vehicular exhaust of petrol operated vehicles. This study investigates the spatial and temporal variations of quantitative measurements of isoprene emissions along with different traffic tracers in 2 different seasons (post-monsoon & winter) at four different locations of Delhi. For the quantification of anthropogenic and biogenic isoprene, two sites from traffic intersections (Punjabi Bagh & CRRI) and two sites from vegetative locations (JNU & Yamuna Biodiversity Park) were selected in the vicinity of isoprene emitting tree species like Ficus religiosa, Dalbergia sissoo, Eucalyptus species etc. The concentrations of traffic tracers like benzene, toluene were also determined & their robust ratios with isoprene were used to differentiate anthropogenic isoprene with biogenic portion at each site. The ozone forming potential (OFP) of all selected species along with isoprene was also estimated. For collection of intra-day samples (3 times a day) in each season, a pre-conditioned fenceline monitoring (FLM) carbopack X thermal desorption tubes were used and further analysis was done with Gas chromatography attached with mass spectrometry (GC-MS). The results of the study proposed that the ambient air isoprene is always higher in post-monsoon season as compared to winter season at all the sites because of high temperature & intense sunlight. The maximum isoprene emission flux was always observed during afternoon hours in both seasons at all sites. The maximum isoprene concentration was found to be 13.95 ppbv at Biodiversity Park during afternoon time in post monsoon season while the lower concentration was observed as low as 0.07 ppbv at the same location during morning hours in winter season. OFP of isoprene at vegetation sites is very high during post-monsoon because of high concentrations. However, OFP for other traffic tracers were high during winter seasons & at traffic locations. Furthermore, high correlation between isoprene emissions with traffic volume at traffic sites revealed that a noteworthy share of its emission also originates from road traffic.

Keywords: biogenic VOCs, isoprene emission, anthropogenic isoprene, urban vegetation

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: M. A. Akulov, V. O. Zaharov, A. A. Tomskij

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Introduction: Scapulohumeral periarthrosis, resulting as a reaction to mechanical injury of shoulder tendons and muscles, is associated with high incidence of temporal and permanent disability. There is a strong need for investigation of treatment of that patient group. Severe pain leads to limitation of movements range, which result in secondary alterations of joint capsule and ligamentous apparatus. Muscle tension and edema, swelling of fascial and fibrous structures result in nerve and vascular compression in intramuscular and osseo-muscular-fibrous spaces. Botulinum toxin injection leads to decrease of muscle tone, increase of movements range and associated pain alleviation. Study aim: Optimization of rehabilitation process in scapolohumeral periarthrosis using Xeomin. Patients and methods: 40 patients aged 37-56 years with scapulohumeral periarthrosis were evaluated. Patients were divided into two groups according to treatment regimen. The first (main) group included 21 patients, receiving intramuscular Xeomin 150-200 U in the area of brachio-scapular joint and trigger points (inducing motion range limitation and pain). Treatment procedures were combined with physical therapy and osteopathic procedures. The second (control) group included 19 patients, receiving conventional physical therapy and osteopathic procedures. The evaluation and efficacy comparison was carried out using McGill pain questionnaire, Clinical Global Impression scale (CGI), and patient-reported increase of brachio-scapular joint movement range and pain decrease at 1, 3 and 6 months of treatment. Results. The study demonstrated a significant improvement in the main group after one month of treatment, which persisted during months of treatment. At baseline, rank pain index on McGill pain questionnaire was 18,4±4,9 and 17,8±5,1 in the main and control group, respectively (p > 0,05). At 1 month of treatment we observed a significant decrease of pain syndrome (no pain or modest pain) and increase of movement range in angular degrees in the main group (р < 0,05). In the control group significant improvements were observed only on the 3 month of treatment (р < 0,05), but at 6 months of treatment the improvement in pain syndrome and motion range in brachio-scapular joint was significantly smaller, than in the main group. Rank pain index on McGill pain scale was 5,2±1,8 in the main group compared to 12,0±2,6 in the control group (р < 0,05). At 6 months of treatment patients in the first group reported a significant/highly significant improvement of general health on CGI, whereas in the second group most patients reported a minimal improvement. We observed a sustained and persistent improvement of motion range in brachio-scapular joint in the main group. Conclusion: Xeomin injections as a part of rehabilitation process in scapulohumeral periarthrosis lead to reduced time and increased quality of rehabilitation.

Keywords: botulinum toxin, rehabilitation, scapulohumeral periarthrosis

Procedia PDF Downloads 279

Authors: A. Maghoul, A. Rostampouryasouri, MR. Maghami

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The development of an urban design and power network planning has been gaining momentum in recent years. The integration of renewable energy with urban design has been widely regarded as an increasingly important solution leading to climate change and energy security. Through the use of passive strategies and solar integration with Urban Building Energy Modeling (UBEM) tools, architects and designers can create high-quality designs that meet the needs of clients and stakeholders. To determine the most effective ways of combining renewable energy with urban development, we analyze the relationship between urban form and renewable energy production. The procedure involved in this practice include passive solar gain (in building design and urban design), solar integration, location strategy, and 3D models with a case study conducted in Tehran, Iran. The study emphasizes the importance of spatial and temporal considerations in the development of sector coupling strategies for solar power establishment in arid and semi-arid regions. The substation considered in the research consists of two parallel transformers, 13 lines, and 38 connection points. Each urban load connection point is equipped with 500 kW of solar PV capacity and 1 kWh of battery Energy Storage (BES) to store excess power generated from solar, injecting it into the urban network during peak periods. The simulations and analyses have occurred in EnergyPlus software. Passive solar gain involves maximizing the amount of sunlight that enters a building to reduce the need for artificial lighting and heating. Solar integration involves integrating solar photovoltaic (PV) power into smart grids to reduce emissions and increase energy efficiency. Location strategy is crucial to maximize the utilization of solar PV in an urban distribution feeder. Additionally, 3D models are made in Revit, and they are keys component of decision-making in areas including climate change mitigation, urban planning, and infrastructure. we applied these strategies in this research, and the results show that it is possible to create sustainable and energy-efficient urban environments. Furthermore, demand response programs can be used in conjunction with solar integration to optimize energy usage and reduce the strain on the power grid. This study highlights the influence of ancient Persian architecture on Iran's urban planning system, as well as the potential for reducing pollutants in building construction. Additionally, the paper explores the advances in eco-city planning and development and the emerging practices and strategies for integrating sustainability goals.

Keywords: energy-efficient urban planning, sustainable architecture, solar energy, sustainable urban design

Procedia PDF Downloads 76

Authors: Jesús Horacio, Alfredo Ollero, Víctor Bouzas-Blanco, Augusto Pérez-Alberti

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Rivers have traditionally been classified, assessed and managed in terms of hydrological, chemical and / or biological criteria. Geomorphological classifications had in the past a secondary role, although proposals like River Styles Framework, Catchment Baseline Survey or Stroud Rural Sustainable Drainage Project did incorporate geomorphology for management decision-making. In recent years many studies have been attracted to the geomorphological component. The geomorphological processes and their associated forms determine the structure of a river system. Understanding these processes and forms is a critical component of the sustainable rehabilitation of aquatic ecosystems. The fluvial auto-classification approach suggests that a river is a self-built natural system, with processes and forms designed to effectively preserve their ecological function (hydrologic, sedimentological and biological regime). Fluvial systems are formed by a wide range of elements with multiple non-linear interactions on different spatial and temporal scales. Besides, the fluvial auto-classification concept is built using data from the river itself, so that each classification developed is peculiar to the river studied. The variables used in the classification are specific stream power and mean grain size. A discriminant analysis showed that these variables are the best characterized processes and forms. The statistical technique applied allows to get an individual discriminant equation for each geomorphological type. The geomorphological classification was developed using sites with high naturalness. Each site is a control point of high ecological and geomorphological quality. The changes in the conditions of the control points will be quickly recognizable, and easy to apply a right management measures to recover the geomorphological type. The study focused on Galicia (NW Spain) and the mapping was made analyzing 122 control points (sites) distributed over eight river basins. In sum, this study provides a method for fluvial geomorphological classification that works as an open and flexible tool underlying the fluvial auto-classification concept. The hydrographic mapping is the visual expression of the results, such that each river has a particular map according to its geomorphological characteristics. Each geomorphological type is represented by a particular type of hydraulic geometry (channel width, width-depth ratio, hydraulic radius, etc.). An alteration of this geometry is indicative of a geomorphological disturbance (whether natural or anthropogenic). Hydrographic mapping is also dynamic because its meaning changes if there is a modification in the specific stream power and/or the mean grain size, that is, in the value of their equations. The researcher has to check annually some of the control points. This procedure allows to monitor the geomorphology quality of the rivers and to see if there are any alterations. The maps are useful to researchers and managers, especially for conservation work and river restoration.

Keywords: fluvial auto-classification concept, mapping, geomorphology, river

Procedia PDF Downloads 367

Authors: Caroline Lavratti, Pedro Dal Lago, Gustavo Reinaldo, Gilson Dorneles, Andreia Bard, Laira Fuhr, Daniela Pochmann, Alessandra Peres, Luciane Wagner, Viviane Elsner

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Approximately 1% of the world's population is affected by schizophrenia (SZ), a chronic and debilitating neurodevelopmental disorder. Among possible factors, reduced levels of Brain-derived neurotrophic factor (BDNF) has been recognized in physiopathogenesis and course of SZ. In this context, peripheral BDNF levels have been used as a biomarker in several clinical studies, since this neurotrophin is able to cross the blood-brain barrier in a bi-directional manner and seems to present a strong correlation with the central nervous system fluid levels. The patients with SZ usually adopts a sedentary lifestyle, which has been partly associated with the increase in obesity incidence rates, metabolic syndrome, type 2 diabetes and coronary heart disease. On the other hand, exercise, a non-invasive and low cost intervention, has been considered an important additional therapeutic option for this population, promoting benefits to physical and mental health. To our knowledge, few studies have been pointed out that the positive effects of exercise in SZ patients are mediated, at least in part, to enhanced levels of BDNF after training. However, these studies are focused on evaluating the effect of single bouts of exercise of chronic interventions, data concerning the short- and long-term exercise outcomes on BDNF are scarce. Therefore, this study aimed to evaluate the effect of a concurrent exercise protocol (CEP) on plasma BDNF levels of SZ patients in different time-points. Material and Methods: This study was approved by the Research Ethics Committee of the Centro Universitário Metodista do IPA (no 1.243.680/2015). The participants (n=15) were subbmited to the CEP during 90 days, 3 times a week for 60 minutes each session. In order to evaluate the short and long-term effects of exercise, blood samples were collected pre, 30, 60 and 90 days after the intervention began. Plasma BDNF levels were determined with the ELISA method, from Sigma-Aldrich commercial kit (catalog number RAB0026) according to manufacturer's instructions. Results: A remarkable increase on plasma BDNF levels at 90 days after training compared to baseline (p=0.006) and 30 days (p=0.007) values were observed. Conclusion: Our data are in agreement with several studies that show significant enhancement on BDNF levels in response to different exercise protocols in SZ individuals. We might suggest that BDNF upregulation after training in SZ patients acts in a dose-dependent manner, being more pronounced in response to chronic exposure. Acknowledgments: This work was supported by Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS)/Brazil.

Keywords: exercise, BDNF, schizophrenia, time-points

Procedia PDF Downloads 252

Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

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Authors: Fabio N. Moreno, Letícia B. Marinho, Beatriz D. Ruiz, Maria Helena R. B. Martins

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Brazil is a top consumer of pesticides worldwide, and the São Paulo State is one of the highest consumers among the Brazilian federative states. However, representative data about the occurrence of pesticides in surface waters of the São Paulo State is scarce. This paper aims to present the results of pesticides monitoring executed within the Water Quality Monitoring Network of CETESB (The Environmental Agency of the São Paulo State) between the 2018-2022 period. Surface water sampling points (21 to 25) were selected within basins of predominantly agricultural land-use (5 to 85% of cultivated areas). The samples were collected throughout the year, including high-flow and low-flow conditions. The frequency of sampling varied between 6 to 4 times per year. Selection of pesticide molecules for monitoring followed a prioritizing process from EMBRAPA (Brazilian Agricultural Research Corporation) databases of pesticide use. Pesticides extractions in aqueous samples were performed according to USEPA 3510C and 3546 methods following quality assurance and quality control procedures. Determination of pesticides in water (ng L-1) extracts were performed by high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) and by gas chromatography with nitrogen phosphorus (GC-NPD) and electron capture detectors (GC-ECD). The results showed higher frequencies (20- 65%) in surface water samples for Carbendazim (fungicide), Diuron/Tebuthiuron (herbicides) and Fipronil/Imidaclopride (insecticides). The frequency of observations for these pesticides were generally higher in monitoring points located in sugarcane cultivated areas. The following pesticides were most frequently quantified above the Aquatic life benchmarks for freshwater (USEPA Office of Pesticide Programs, 2023) or Brazilian Federal Regulatory Standards (CONAMA Resolution no. 357/2005): Atrazine, Imidaclopride, Carbendazim, 2,4D, Fipronil, and Chlorpiryfos. Higher median concentrations for Diuron and Tebuthiuron in the rainy months (october to march) indicated pesticide transport through surface runoff. However, measurable concentrations in the dry season (april to september) for Fipronil and Imidaclopride also indicates pathways related to subsurface or base flow discharge after pesticide soil infiltration and leaching or dry deposition following pesticide air spraying. With exception to Diuron, no temporal trends related to median concentrations of the most frequently quantified pesticides were observed. These results are important to assist policymakers in the development of strategies aiming at reducing pesticides migration to surface waters from agricultural areas. Further studies will be carried out in selected points to investigate potential risks as a result of pesticides exposure on aquatic biota.

Keywords: pesticides monitoring, são paulo state, water quality, surface waters

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Authors: Roberta Martino, Viviana Ventre

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Intertemporal choices are choices under conditions of uncertainty in which the consequences are distributed over time. The Discounted Utility Model is the essential reference for describing the individual in the context of intertemporal choice. The model is based on the idea that the individual selects the alternative with the highest utility, which is calculated by multiplying the cardinal utility of the outcome, as if the reception were instantaneous, by the discount function that determines a decrease in the utility value according to how the actual reception of the outcome is far away from the moment the choice is made. Initially, the discount function was assumed to have an exponential trend, whose decrease over time is constant, in line with a profile of a rational investor described by classical economics. Instead, empirical evidence called for the formulation of alternative, hyperbolic models that better represented the actual actions of the investor. Attitudes that do not comply with the principles of classical rationality are termed anomalous, i.e., difficult to rationalize and describe through normative models. The development of behavioral finance, which describes investor behavior through cognitive psychology, has shown that deviations from rationality are due to the limited rationality condition of human beings. What this means is that when a choice is made in a very difficult and information-rich environment, the brain does a compromise job between the cognitive effort required and the selection of an alternative. Moreover, the evaluation and selection phase of the alternative, the collection and processing of information, are dynamics conditioned by systematic distortions of the decision-making process that are the behavioral biases involving the individual's emotional and cognitive system. In this paper we present an original decomposition of the discount function to investigate the psychological principles of hyperbolic discounting. It is possible to decompose the curve into two components: the first component is responsible for the smaller decrease in the outcome as time increases and is related to the individual's impatience; the second component relates to the change in the direction of the tangent vector to the curve and indicates how much the individual perceives the indeterminacy of the future indicating his or her aversion to uncertainty. This decomposition allows interesting conclusions to be drawn with respect to the concept of impatience and the emotional drives involved in decision-making. The contribution that neuroscience can make to decision theory and inter-temporal choice theory is vast as it would allow the description of the decision-making process as the relationship between the individual's emotional and cognitive factors. Neurofinance is a discipline that uses a multidisciplinary approach to investigate how the brain influences decision-making. Indeed, considering that the decision-making process is linked to the activity of the prefrontal cortex and amygdala, neurofinance can help determine the extent to which abnormal attitudes respect the principles of rationality.

Keywords: impatience, intertemporal choice, neurofinance, rationality, uncertainty

Procedia PDF Downloads 129

Authors: Zhang Xin

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Barrier lakes are lakes formed by storing water in valleys, river valleys or riverbeds after being blocked by landslide, earthquake, debris flow, and other factors. They have great potential safety hazards. When the water is stored to a certain extent, it may burst in case of strong earthquake or rainstorm, and the lake water overflows, resulting in large-scale flood disasters. In order to ensure the safety of people's lives and property in the downstream, it is very necessary to monitor the barrier lake. However, it is very difficult and time-consuming to manually monitor the barrier lake in high altitude areas due to the harsh climate and steep terrain. With the development of earth observation technology, remote sensing monitoring has become one of the main ways to obtain observation data. Compared with a single satellite, multi-satellite remote sensing cooperative observation has more advantages; its spatial coverage is extensive, observation time is continuous, imaging types and bands are abundant, it can monitor and respond quickly to emergencies, and complete complex monitoring tasks. Monitoring with multi-temporal and multi-platform remote sensing satellites can obtain a variety of observation data in time, acquire key information such as water level and water storage capacity of the barrier lake, scientifically judge the situation of the barrier lake and reasonably predict its future development trend. In this study, The Sarez Lake, which formed on February 18, 1911, in the central part of the Pamir as a result of blockage of the Murgab River valley by a landslide triggered by a strong earthquake with magnitude of 7.4 and intensity of 9, is selected as the research area. Since the formation of Lake Sarez, it has aroused widespread international concern about its safety. At present, the use of mechanical methods in the international analysis of the safety of Lake Sarez is more common, and remote sensing methods are seldom used. This study combines remote sensing data with field observation data, and uses the 'space-air-ground' joint observation technology to study the changes in water level and water storage capacity of Lake Sarez in recent decades, and evaluate its safety. The situation of the collapse is simulated, and the future development trend of Lake Sarez is predicted. The results show that: 1) in recent decades, the water level of Lake Sarez has not changed much and remained at a stable level; 2) unless there is a strong earthquake or heavy rain, it is less likely that the Lake Sarez will be broken under normal conditions, 3) lake Sarez will remain stable in the future, but it is necessary to establish an early warning system in the Lake Sarez area for remote sensing of the area, 4) the coordinative remote sensing observation technology is feasible for the high altitude barrier lake of Sarez.

Keywords: coordinative observation, disaster, remote sensing, geographic information system, GIS

Procedia PDF Downloads 127

Authors: Nasser Salah Eldin Mohammed Salih Shebka

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Current problematic issues in AI fields are mainly due to those of knowledge representation conceptual theories, which in turn reflected on the entire scope of cognitive sciences. Knowledge representation methods and tools are driven from theoretical concepts regarding human scientific perception of the conception, nature, and process of knowledge acquisition, knowledge engineering and knowledge generation. And although, these theoretical conceptions were themselves driven from the study of the human knowledge representation process and related theories; some essential factors were overlooked or underestimated, thus causing critical methodological deficiencies in the conceptual theories of human knowledge and knowledge representation conceptions. The evaluation criteria of human cumulative knowledge from the perspectives of nature and theoretical aspects of knowledge representation conceptions are affected greatly by the very materialistic nature of cognitive sciences. This nature caused what we define as methodological deficiencies in the nature of theoretical aspects of knowledge representation concepts in AI. These methodological deficiencies are not confined to applications of knowledge representation theories throughout AI fields, but also exceeds to cover the scientific nature of cognitive sciences. The methodological deficiencies we investigated in our work are: - The Segregation between cognitive abilities in knowledge driven models.- Insufficiency of the two-value logic used to represent knowledge particularly on machine language level in relation to the problematic issues of semantics and meaning theories. - Deficient consideration of the parameters of (existence) and (time) in the structure of knowledge. The latter requires that we present a more detailed introduction of the manner in which the meanings of Existence and Time are to be considered in the structure of knowledge. This doesn’t imply that it’s easy to apply in structures of knowledge representation systems, but outlining a deficiency caused by the absence of such essential parameters, can be considered as an attempt to redefine knowledge representation conceptual approaches, or if proven impossible; constructs a perspective on the possibility of simulating human cognition on machines. Furthermore, a redirection of the aforementioned expressions is required in order to formulate the exact meaning under discussion. This redirection of meaning alters the role of Existence and time factors to the Frame Work Environment of knowledge structure; and therefore; knowledge representation conceptual theories. Findings of our work indicate the necessity to differentiate between two comparative concepts when addressing the relation between existence and time parameters, and between that of the structure of human knowledge. The topics presented throughout the paper can also be viewed as an evaluation criterion to determine AI’s capability to achieve its ultimate objectives. Ultimately, we argue some of the implications of our findings that suggests that; although scientific progress may have not reached its peak, or that human scientific evolution has reached a point where it’s not possible to discover evolutionary facts about the human Brain and detailed descriptions of how it represents knowledge, but it simply implies that; unless these methodological deficiencies are properly addressed; the future of AI’s qualitative progress remains questionable.

Keywords: cognitive sciences, knowledge representation, ontological reasoning, temporal logic

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Authors: Marcel Schulze, Behrem Aslan, Silke Lux, Alexandra Philipsen

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Objective: Patients with Attention Deficit/Hyperactivity Disorder (ADHD) often report that they are being flooded by sensory impressions. Studies investigating sensory processing show hypersensitivity for sensory inputs across the senses in children and adults with ADHD. Especially the auditory modality is affected by deficient acoustical inhibition and modulation of signals. While studying unimodal signal-processing is relevant and well-suited in a controlled laboratory environment, everyday life situations occur multimodal. A complex interplay of the senses is necessary to form a unified percept. In order to achieve this, the unimodal sensory modalities are bound together in a process called multisensory integration (MI). In the current study we investigate MI in an adult ADHD sample using the McGurk-effect – a well-known illusion where incongruent speech like phonemes lead in case of successful integration to a new perceived phoneme via late top-down attentional allocation . In ADHD neuronal dysregulation at rest e.g., aberrant within or between network functional connectivity may also account for difficulties in integrating across the senses. Therefore, the current study includes resting-state functional connectivity to investigate a possible relation of deficient network connectivity and the ability of stimulus integration. Method: Twenty-five ADHD patients (6 females, age: 30.08 (SD:9,3) years) and twenty-four healthy controls (9 females; age: 26.88 (SD: 6.3) years) were recruited. MI was examined using the McGurk effect, where - in case of successful MI - incongruent speech-like phonemes between visual and auditory modality are leading to a perception of a new phoneme. Mann-Whitney-U test was applied to assess statistical differences between groups. Echo-planar imaging-resting-state functional MRI was acquired on a 3.0 Tesla Siemens Magnetom MR scanner. A seed-to-voxel analysis was realized using the CONN toolbox. Results: Susceptibility to McGurk was significantly lowered for ADHD patients (ADHDMdn:5.83%, ControlsMdn:44.2%, U= 160.5, p=0.022, r=-0.34). When ADHD patients integrated phonemes, reaction times were significantly longer (ADHDMdn:1260ms, ControlsMdn:582ms, U=41.0, p<.000, r= -0.56). In functional connectivity medio temporal gyrus (seed) was negatively associated with primary auditory cortex, inferior frontal gyrus, precentral gyrus, and fusiform gyrus. Conclusion: MI seems to be deficient for ADHD patients for stimuli that need top-down attentional allocation. This finding is supported by stronger functional connectivity from unimodal sensory areas to polymodal, MI convergence zones for complex stimuli in ADHD patients.

Keywords: attention-deficit hyperactivity disorder, audiovisual integration, McGurk-effect, resting-state functional connectivity

Procedia PDF Downloads 127

Authors: D. Courault, L. Hossard, V. Demarez, E. Ndikumana, D. Ho Tong Minh, N. Baghdadi, F. Ruget

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In the global change context, efficient management of the available resources has become one of the most important topics, particularly for sustainable crop development. Timely assessment with high precision is crucial for water resource and pest management. Rice cultivated in Southern France in the Camargue region must face a challenge, reduction of the soil salinity by flooding and at the same time reduce the number of herbicides impacting negatively the environment. This context has lead farmers to diversify crop rotation and their agricultural practices. The objective of this study was to evaluate this crop diversity both in crop systems and in agricultural practices applied to rice paddy in order to quantify the impact on the environment and on the crop production. The proposed method is based on the combined use of crop models and multispectral data acquired from the recent Sentinel 2 satellite sensors launched by the European Space Agency (ESA) within the homework of the Copernicus program. More than 40 images at fine spatial resolution (10m in the optical range) were processed for 2016 and 2017 (with a revisit time of 5 days) to map crop types using random forest method and to estimate biophysical variables (LAI) retrieved by inversion of the PROSAIL canopy radiative transfer model. Thanks to the high revisit time of Sentinel 2 data, it was possible to monitor the soil labor before flooding and the second sowing made by some farmers to better control weeds. The temporal trajectories of remote sensing data were analyzed for various rice cultivars for defining the main parameters describing the phenological stages useful to calibrate two crop models (STICS and SAFY). Results were compared to surveys conducted with 10 farms. A large variability of LAI has been observed at farm scale (up to 2-3m²/m²) which induced a significant variability in the yields simulated (up to 2 ton/ha). Observations on more than 300 fields have also been collected on land use. Various maps were elaborated, land use, LAI, flooding and sowing, and harvest dates. All these maps allow proposing a new typology to classify these paddy crop systems. Key phenological dates can be estimated from inverse procedures and were validated against ground surveys. The proposed approach allowed to compare the years and to detect anomalies. The methods proposed here can be applied at different crops in various contexts and confirm the potential of remote sensing acquired at fine resolution such as the Sentinel2 system for agriculture applications and environment monitoring. This study was supported by the French national center of spatial studies (CNES, funded by the TOSCA).

Keywords: agricultural practices, remote sensing, rice, yield

Procedia PDF Downloads 274

Authors: Roberta Martino, Viviana Ventre

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Every day we face choices whose consequences are deferred in time. These types of choices are the intertemporal choices and play an important role in the social, economic, and financial world. The Discounted Utility Model is the mathematical model of reference to calculate the utility of intertemporal prospects. The discount rate is the main element of the model as it describes how the individual perceives the indeterminacy of subsequent periods. Empirical evidence has shown a discrepancy between the behavior expected from the predictions of the model and the effective choices made from the decision makers. In particular, the term temporal inconsistency indicates those choices that do not remain optimal with the passage of time. This phenomenon has been described with hyperbolic models of the discount rate which, unlike the linear or exponential nature assumed by the discounted utility model, is not constant over time. This paper explores the problem of inconsistency by tracing the decision-making process through the concept of impatience. The degree of impatience and the degree of decrease of impatience are two parameters that allow to quantify the weight of emotional factors and cognitive limitations during the evaluation and selection of alternatives. In fact, although the theory assumes perfectly rational decision makers, behavioral finance and cognitive psychology have made it possible to understand that distortions in the decision-making process and emotional influence have an inevitable impact on the decision-making process. The degree to which impatience is diminished is the focus of the first part of the study. By comparing consistent and inconsistent preferences over time, it was possible to verify that some anomalies in the discounted utility model are a result of the combination of cognitive bias and emotional factors. In particular: the delay effect and the interval effect are compared through the concept of misperception of time; starting from psychological considerations, a criterion is proposed to identify the causes of the magnitude effect that considers the differences in outcomes rather than their ratio; the sign effect is analyzed by integrating in the evaluation of prospects with negative outcomes the psychological aspects of loss aversion provided by Prospect Theory. An experiment implemented confirms three findings: the greatest variation in the degree of decrease in impatience corresponds to shorter intervals close to the present; the greatest variation in the degree of impatience occurs for outcomes of lower magnitude; the variation in the degree of impatience is greatest for negative outcomes. The experimental phase was implemented with the construction of the hyperbolic factor through the administration of questionnaires constructed for each anomaly. This work formalizes the underlying causes of the discrepancy between the discounted utility model and the empirical evidence of preference reversal.

Keywords: decreasing impatience, discount utility model, hyperbolic discount, hyperbolic factor, impatience

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Authors: Tak Mau Simon Chan, Ying Chuen Lance Chan

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Homelessness has been a popular and controversial debate in Hong Kong, a city which is densely populated and well-known for very expensive housing. The constitution of the homeless as threats to the community and environmental hygiene is ambiguous and debatable in the Hong Kong context. The lack of an intervention model is the critical research gap thus far, aside from the tangible services delivered. The life story approach (LSA), with its unique humanistic orientation, has been well applied in recent decades to depict the needs of various target groups, but not the homeless. It is argued that the life story approach (LSA), which has been employed by health professionals in the landscape of dementia, and health and social care settings, can be used as a reference in the local Chinese context through indigenization. This study, therefore, captures the viewpoints of service providers and users by constructing an indigenous intervention model that refers to the LSA in serving the chronically homeless. By informing 13 social workers and 27 homeless individuals in 8 focus groups whilst 12 homeless individuals have participated in individual in-depth interviews, a framework of LSA in homeless people is proposed. Through thematic analysis, three main themes of their life stories was generated, namely, the family, negative experiences and identity transformation. The three domains solidified framework that not only can be applied to the homeless, but also other disadvantaged groups in the Chinese context. Based on the three domains of family, negative experiences and identity transformation, the model is applied in the daily practices of social workers who help the homeless. The domain of family encompasses familial relationships from the past to the present to the speculated future with ten sub-themes. The domain of negative experiences includes seven sub-themes, with reference to the deviant behavior committed. The last domain, identity transformation, incorporates the awareness and redefining of one’s identity and there are a total of seven sub-themes. The first two domains are important components of personal histories while the third is more of an unknown, exploratory and yet to-be-redefined territory which has a more positive and constructive orientation towards developing one’s identity and life meaning. The longitudinal temporal dimension of moving from the past – present - future enriches the meaning making process, facilitates the integration of life experiences and maintains a more hopeful dialogue. The model is tested and its effectiveness is measured by using qualitative and quantitative methods to affirm the extent that it is relevant to the local context. First, it contributes to providing a clear guideline for social workers who can use the approach as a reference source. Secondly, the framework acts as a new intervention means to address problem saturated stories and the intangible needs of the homeless. Thirdly, the model extends the application to beyond health related issues. Last but not least, the model is highly relevant to the local indigenous context.

Keywords: homeless, indigenous intervention, life story approach, social work practice

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Authors: Shanlong Lu, Jiming Jin, Xiaochun Wang

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The Tibetan Plateau has the largest number of inland lakes with the highest elevation on the planet. These massive and large lakes are mostly in natural state and are less affected by human activities. Their shrinking or expansion can truly reflect regional climate and environmental changes and are sensitive indicators of global climate change. However, due to the sparsely populated nature of the plateau and the poor natural conditions, it is difficult to effectively obtain the change data of the lake, which has affected people's understanding of the temporal and spatial processes of lake water changes and their influencing factors. By using the MODIS (Moderate Resolution Imaging Spectroradiometer) MOD09Q1 surface reflectance images as basic data, this study produced the 8-day lake water surface data set of the Tibetan Plateau from 2000 to 2012 at 250 m spatial resolution, with a lake water surface extraction method of combined with lake water surface boundary buffer analyzing and lake by lake segmentation threshold determining. Then based on the dataset, the lake water surface variations and their influencing factors were analyzed, by using 4 typical natural geographical zones of Eastern Qinghai and Qilian, Southern Qinghai, Qiangtang, and Southern Tibet, and the watersheds of the top 10 lakes of Qinghai, Siling Co, Namco, Zhari NamCo, Tangra Yumco, Ngoring, UlanUla, Yamdrok Tso, Har and Gyaring as the analysis units. The accuracy analysis indicate that compared with water surface data of the 134 sample lakes extracted from the 30 m Landsat TM (Thematic Mapper ) images, the average overall accuracy of the lake water surface data set is 91.81% with average commission and omission error of 3.26% and 5.38%; the results also show strong linear (R2=0.9991) correlation with the global MODIS water mask dataset with overall accuracy of 86.30%; and the lake area difference between the Second National Lake Survey and this study is only 4.74%, respectively. This study provides reliable dataset for the lake change research of the plateau in the recent decade. The change trends and influencing factors analysis indicate that the total water surface area of lakes in the plateau showed overall increases, but only lakes with areas larger than 10 km2 had statistically significant increases. Furthermore, lakes with area larger than 100 km2 experienced an abrupt change in 2005. In addition, the annual average precipitation of Southern Tibet and Southern Qinghai experienced significant increasing and decreasing trends, and corresponding abrupt changes in 2004 and 2006, respectively. The annual average temperature of Southern Tibet and Qiangtang showed a significant increasing trend with an abrupt change in 2004. The major reason for the lake water surface variation in Eastern Qinghai and Qilian, Southern Qinghai and Southern Tibet is the changes of precipitation, and that for Qiangtang is the temperature variations.

Keywords: lake water surface variation, MODIS MOD09Q1, remote sensing, Tibetan Plateau

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

Abstract:

As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

Abstract:

Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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