Search results for: temporal sequences

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

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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

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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

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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

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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: Delaram Hosseinioun

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In their collections, Shirin Neshat, Mitra Tabrizian, Gohar Dashti and Newsha Tavakolian adopt a hybrid form of narrative to confront the restrictions imposed on women in hegemonic public and private spaces. Focusing on motives such as social marginalisation, crisis of belonging, as well as lack of agency for women, the artists depict the regression of women’s rights in their respective generations. Based on the ideas of Michael Bakhtin, namely his concept of polyphony or the plurality of contradictory voices, the views of Judith Butler on giving an account to oneself and Henri Leverbre’s theories on social space, this study illustrates the artists’ concept of identity in crisis through time and space. The research explores how the artists took their art as a novel dimension to depict and confront the hardships imposed on Iranian women. Henri Lefebvre makes a distinction between complex social structures through which individuals situate, perceive and represent themselves. By adding Bakhtin’s polyphonic view to Lefebvre’s concepts of perceived and lived spaces, the study explores the sense of social fragmentation in the works of Dashti and Tavakolian. One argument is that as the representatives of the contemporary generation of female artists who spend their lives in Iran and faced a higher degree of restrictions, their hyperbolic and theatrical styles stand as a symbolic act of confrontation against restrictive socio-cultural norms imposed on women. Further, the research explores the possibility of reclaiming one's voice and sense of agency through art, corresponding with the Bakhtinian sense of polyphony and Butler’s concept of giving an account to oneself. Works of Neshat and Tabrizian as the representatives of the previous generation who faced exile and diaspora, encompass a higher degree of misplacement, violence and decay of women’s presence. In Their works, the women’s body encompasses Lefebvre’s dismantled temporal and special setting. Notably, the ongoing social conviction and gender-based dogma imposed on women frame some of the concurrent motives among the selected collections of the four artists. By applying an interdisciplinary lens and integrating the conducted interviews with the artists, the study illustrates how the artists seek a transcultural account for themselves and women in their generations. Further, the selected collections manifest the urgency for an authentic and liberal voice and setting for women, resonating with the concurrent Women, Life, Freedom movement in Iran.

Keywords: persian modern female photographers, transcultural studies, shirin neshat, mitra tabrizian, gohar dashti, newsha tavakolian, butler, bakhtin, lefebvre

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Authors: Men An Pan, Hong Ren Chen, Chih Heng Shih, Hsing Yuan Yen

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Pingtung County is located in the southernmost region of Taiwan. During the winter season, pollutants due to insufficient dispersion caused by the downwash of the northeast monsoon lead to the poor air quality of the County. Through the implementation of various control methods, including the application of permits of air pollution, fee collection of air pollution, control oil fume of catering sectors, smoke detection of diesel vehicles, regular inspection of locomotives, and subsidies for low-polluting vehicles. Moreover, to further mitigate the air pollution, additional alternative controlling strategies are also carried out, such as construction site control, prohibition of open-air agricultural waste burning, improvement of river dust, and strengthening of road cleaning operations. The combined efforts have significantly reduced air pollutants in the County. However, in order to effectively and promptly monitor the ambient air quality, the County has subsequently deployed micro-sensors, with a total of 400 IoTs (Internet of Things) micro-sensors for PM2.5 and VOC detection and 3 air quality monitoring stations of the Environmental Protection Agency (EPA), covering 33 townships of the County. The covered area has more than 1,300 listed factories and 5 major industrial parks; thus forming an Internet of Things (IoTs) based multi-level air quality monitoring system. The results demonstrate that the IoTs multi-level air quality sensors combined with other strategies such as “sand and gravel dredging area technology monitoring”, “banning open burning”, “intelligent management of construction sites”, “real-time notification of activation response”, “nighthawk early bird plan with micro-sensors”, “unmanned aircraft (UAV) combined with land and air to monitor abnormal emissions”, and “animal husbandry odour detection service” etc. The satisfaction improvement rate of air control, through a 2021 public survey, reached a high percentage of 81%, an increase of 46% as compared to 2018. For the air pollution complaints for the whole year of 2021, the total number was 4213 in contrast to 7088 in 2020, a reduction rate reached almost 41%. Because of the spatial-temporal features of the air quality monitoring IoTs system by the application of microsensors, the system does assist and strengthen the effectiveness of the existing air quality monitoring network of the EPA and can provide real-time control of the air quality. Therefore, the hot spots and potential pollution locations can be timely determined for law enforcement. Hence, remarkable results were obtained for the two years. That is, both reduction of public complaints and better air quality are successfully achieved through the implementation of the present IoTs system for real-time air quality monitoring throughout Pingtung County.

Keywords: IoT, PM, air quality sensor, air pollution, environmental monitoring

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Authors: Monkiz Khasreen

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In the context of the global trend towards reducing new buildings carbon footprint, the design team is required to make early decisions that have a major influence on embodied and operational carbon. Sustainability strategies should be clear during early stages of building design process, as changes made later can be extremely costly. Life-Cycle Assessment (LCA) could be used as the vehicle to carry other tools and processes towards achieving the requested improvement. Although LCA is the ‘golden standard’ to evaluate buildings from 'cradle to grave', lack of details available on the concept design makes LCA very difficult, if not impossible, to be used as an estimation tool at early stages. Issues related to transparency and accessibility of information in the building industry are affecting the credibility of LCA studies. A verified database derived from LCA case studies is required to be accessible to researchers, design professionals, and decision makers in order to offer guidance on specific areas of significant impact. This database could be the build-up of data from multiple sources within a pool of research held in this context. One of the most important factors that affects the reliability of such data is the temporal factor as building materials, components, and systems are rapidly changing with the advancement of technology making production more efficient and less environmentally harmful. Recent LCA studies on different building functions, types, and structures are always needed to update databases derived from research and to form case bases for comparison studies. There is also a need to make these studies transparent and accessible to designers. The work in this paper sets out to address this need. This paper also presents life-cycle case study of a new-build educational building in England. The building utilised very current construction methods and technologies and is rated as BREEAM excellent. Carbon emissions of different life-cycle stages and different building materials and components were modelled. Scenario and sensitivity analyses were used to estimate the future of new educational buildings in England. The study attempts to form an indicator during the early design stages of similar buildings. Carbon dioxide emissions of this case study building, when normalised according to floor area, lie towards the lower end of the range of worldwide data reported in the literature. Sensitivity analysis shows that life cycle assessment results are highly sensitive to future assumptions made at the design stage, such as future changes in electricity generation structure over time, refurbishment processes and recycling. The analyses also prove that large savings in carbon dioxide emissions can result from very small changes at the design stage.

Keywords: architecture, building, carbon dioxide, construction, educational buildings, England, environmental impact, life-cycle assessment

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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 study is dedicated to the research of brain activity in bilingual inhabitants of Siberia. We compared behavioral reactions and event-related potentials in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All the healthy and right-handed participants, matched on age and sex, were students of different universities. EEG’s were recorded during the solving of linguistic tasks. In these tasks, participants had to find a syntax error in the written sentences. There were four groups of sentences: Russian, English, Tuvinian, and Yakut. All participants completed the tasks in Russian and English. Additionally, Tuvinians and Yakuts completed the tasks in Tuvinian or Yakut respectively. For Russians, EEG's were recorded using 128-channels 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 and sampling rate 1000 Hz were used. As parameters of behavioral reactions, response speed and the accuracy of recognition were used. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The behavioral reactions showed that in Russians, the response speed for Russian was faster than for English. Also, the accuracy of solving tasks was higher for Russian than for English. The peak P300 in Russians were higher for English, the peak P600 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. 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. This can be explained by the fact that they did not think carefully and gave a random answer for English. In Tuvinians, The P300 and P600 amplitudes and cortical topology were the same for Russian and Tuvinian and different for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as what Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference, and were reflected to foreign language comprehension - while the Russian language comprehension was reflected to 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, and 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, ERP, native and foreign languages comprehension, Siberian inhabitants

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Authors: Tanya Kaur Bedi, Shankha Pratim Bhattacharya

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The US Environmental Protection Agency defines indoor air quality as “The air quality within and around buildings, especially as it relates to the health and comfort of building occupants”. According to the 2021 report by the Energy Policy Institute at Chicago, Indian residents, a country which is home to the highest levels of air pollution in the world, lose about 5.9 years from life expectancy due to poor air quality and yet has numerous dwellings dependent on natural ventilation. Currently the urban population spends 90% of the time indoors, this scenario raises a concern for occupant health and well-being. The built environment can affect health directly and indirectly through immediate or long-term exposure to indoor air pollutants. Health effects associated with indoor air pollutants include eye/nose/throat irritation, respiratory diseases, heart disease, and even cancer. This study attempts to demonstrate the causal relationship between the indoor air quality and its determining aspects. Detailed indoor air quality audits were conducted in residential buildings located in Kolkata, India in the months of December and January 2021. According to the air pollution knowledge assessment city program in India, Kolkata is also the second most polluted mega-city after Delhi. Although the air pollution levels are alarming year-long, the winter months are most crucial due to the unfavorable environmental conditions. While emissions remain typically constant throughout the year, cold air is denser and moves slower than warm air, trapping the pollution in place for much longer and consequently is breathed in at a higher rate than the summers. The air pollution monitoring period was selected considering environmental factors and major pollution contributors like traffic and road dust. This study focuses on the relationship between the built environment and the spatial-temporal distribution of air pollutants in and around it. The measured parameters include, temperature, relative humidity, air velocity, particulate matter, volatile organic compounds, formaldehyde, and benzene. A total of 56 rooms were audited, selectively targeting the most dominant middle-income group. The data-collection was conducted using a set of instruments positioned in the human breathing-zone. The study assesses indoor air quality based on factors determining natural ventilation and air pollution dispersion such as surrounding environment, dominant wind, openable window to floor area ratio, windward or leeward side openings, and natural ventilation type in the room: single side or cross-ventilation, floor height, residents cleaning habits, etc.

Keywords: indoor air quality, occupant health, urban housing, air pollution, natural ventilation, architecture, urban issues

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Shaista Suhail

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As cancer populations is increasing sharply, the incidence of oral squamous cell carcinoma (OSCC) has also been expected to increase. Oral carcinogenesis is a highly complex, multistep process which involves accumulation of genetic alterations that lead to the induction of proteins promoting cell growth (encoded by oncogenes), increased enzymatic (telomerase) activity promoting cancer cell proliferation. The global increase in frequency and mortality, as well as the poor prognosis of oral squamous cell carcinoma, has intensified current research efforts in the field of prevention and early detection of this disease. The advances in the understanding of the molecular basis of oral cancer should help in the identification of new markers. The study of the carcinogenic process of the oral cancer, including continued analysis of new genetic alterations, along with their temporal sequencing during initiation, promotion and progression, will allow us to identify new diagnostic and prognostic factors, which will provide a promising basis for the application of more rational and efficient treatments. Telomerase activity has been readily found in most cancer biopsies, in premalignant lesions or germ cells. Activity of telomerase is generally absent in normal tissues. It is known to be induced upon immortalization or malignant transformation of human cells such as in oral cancer cells. Maintenance of telomeres plays an essential role during transformation of precancer to malignant stage. Mammalian telomeres, a specialized nucleoprotein structures are composed of large conctamers of the guanine-rich sequence 5_-TTAGGG-3_. The roles of telomeres in regulating both stability of genome and replicative immortality seem to contribute in essential ways in cancer initiation and progression. It is concluded that activity of telomerase can be used as a biomarker for diagnosis of malignant oral cancer and a target for inactivation in chemotherapy or gene therapy. Its expression will also prove to be an important diagnostic tool as well as a novel target for cancer therapy. The activation of telomerase may be an important step in tumorgenesis which can be controlled by inactivating its activity during chemotherapy. The expression and activity of telomerase are indispensable for cancer development. There are no drugs which can effect extremely to treat oral cancers. There is a general call for new emerging drugs or methods that are highly effective towards cancer treatment, possess low toxicity, and have a minor environment impact. Some novel natural products also offer opportunities for innovation in drug discovery. Natural compounds isolated from medicinal plants, as rich sources of novel anticancer drugs, have been of increasing interest with some enzyme (telomerase) blockage property. The alarming reports of cancer cases increase the awareness amongst the clinicians and researchers pertaining to investigate newer drug with low toxicity.

Keywords: oral carcinoma, telomere, telomerase, blockage

Procedia PDF Downloads 144

Authors: Pantana Tor-Ngern

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In the global water cycle, tree water use (Tr) largely contributes to evapotranspiration which is the total amount of water evaporated from terrestrial ecosystems to the atmosphere, regulating climates. Tree water use responds to environmental factors, including atmospheric humidity and sunlight (represented by vapor pressure deficit or VPD and photosynthetically active radiation or PAR, respectively) and soil moisture. In forests, Tr responses to such factors depend on species and their spatial and temporal variations. Tropical forests in Southeast Asia (SEA) have experienced land-use conversion from abandoned agricultural practices, resulting in patches of forests at different stages including old-growth and secondary forests. Because the inherent structures, such as canopy height and tree density, significantly vary among forests at different stages and can strongly affect their respective microclimate, Tr and its responses to changing environmental conditions in successional forests may differ. Daily and seasonal variations in the environmental factors may exert significant impacts on the respective Tr patterns. Extrapolating Tr data from short periods of days to longer periods of seasons or years can be complex and is important for estimating long-term ecosystem water use which often includes normal and abnormal climatic conditions. Thus, this study aims to investigate the diurnal variation of Tr, using measured sap flux density (JS) data, with changes in VPD in eight evergreen tree species in an old-growth forest (hereafter OF; >200 years old) and a young forest (hereafter YF, <10 years old) in Khao Yai National Park, Thailand. The studied species included Sysygium syzygoides, Aquilaria crassna, Cinnamomum subavenium, Nephelium melliferum, Altingia excelsa in OF, and Syzygium nervosum and Adinandra integerrima in YF. Only Sysygium antisepticum was found in both forest stages. Specifically, hysteresis, which indicates the asymmetrical changes of JS in response to changing VPD across daily timescale, was examined in these species. Results showed no hysteresis in all species in OF, except Altingia excelsa which exhibited a 3-hour delayed JS response to VPD. In contrast, JS of all species in YF displayed one-hour delayed responses to VPD. The OF species that showed no hysteresis indicated their well-coupling of their canopies with the atmosphere, facilitating the gas exchange which is essential for tree growth. The delayed responses in Altingia excelsa in OF and all species in YF were associated with higher JS in the morning than that in the afternoon. This implies that these species were sensitive to drying air, closing stomata relatively rapidly compared to the decreasing atmospheric humidity (VPD). Such behavior is often observed in trees growing in dry environments. This study suggests that detailed investigation of JS at sub-daily timescales is imperative for better understanding of mechanistic responses of trees to the changing climate, which will benefit the improvement of earth system models.

Keywords: sap flow, tropical forest, forest succession, thermal dissipcation probe

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Authors: Vince Liégeois

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Language of immediacy and distance: Within their discourse theory, Koch & Oesterreicher establish a distinction between a language of immediacy and a language of distance. The former refers to those discourses which are oriented more towards a spoken norm, whereas the latter entails discourses oriented towards a written norm, regardless of whether they are realised phonically or graphically. This means that an utterance can be realised phonically but oriented more towards the written language norm (e.g., a scientific presentation or eulogy) or realised graphically but oriented towards a spoken norm (e.g., a scribble or chat messages). Research desiderata: The methodological approach from Koch & Oesterreicher has often been criticised for not providing a corpus-linguistic methodology, which makes it difficult to work with quantitative data or address large text collections within this research paradigm. Consequently, the Koch & Oesterreicher approach has difficulties gaining ground in those research areas which rely more on corpus linguistic research models, like text linguistics and LSP-research. A combinatory approach: Accordingly, we want to establish a combinatory approach with corpus-based linguistic methodology. To this end, we propose to (i) include data about the context of an utterance (e.g., monologicity/dialogicity, familiarity with the speaker) – which were called “conditions of communication” in the original work of Koch & Oesterreicher – and (ii) correlate the linguistic phenomenon at the centre of the inquiry (e.g., evaluation markers) to a group of linguistic phenomena deemed typical for either distance- or immediacy-language. Based on these two parameters, linguistic phenomena and texts could then be mapped on an immediacy-distance continuum. Pilot study: To illustrate the benefits of this approach, we will conduct a pilot study on evaluation phenomena in French television weather reports, a form of domain-sensitive discourse which has often been cited as an example of a “text genre”. Within this text genre, we will look at so-called “evaluation markers,” e.g., fixed strings like bad weather, stifling hot, and “no luck today!”. These evaluation markers help to communicate the coming weather situation towards the lay audience but have not yet been studied within the Koch & Oesterreicher research paradigm. Accordingly, we want to figure out whether said evaluation markers are more typical for those weather reports which tend more towards immediacy or those which tend more towards distance. To this aim, we collected a corpus with different kinds of television weather reports,e.g., as part of the news broadcast, including dialogue. The evaluation markers themselves will be studied according to the explained methodology, by correlating them to (i) metadata about the context and (ii) linguistic phenomena characterising immediacy-language: repetition, deixis (personal, spatial, and temporal), a freer choice of tense and right- /left-dislocation. Results: Our results indicate that evaluation markers are more dominantly present in those weather reports inclining towards immediacy-language. Based on the methodology established above, we have gained more insight into the working of evaluation markers in the domain-sensitive text genre of (television) weather reports. For future research, it will be interesting to determine whether said evaluation markers are also typical for immediacy-language-oriented in other domain-sensitive discourses.

Keywords: corpus-based linguistics, evaluation markers, language of immediacy and distance, weather reports

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Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

Procedia PDF Downloads 33

Authors: Moroof, O. Oloruntola, Sunday Oladele, Daniel, O. Obasaju, Victor, O Ojekunle, Olateju, O. Bayewu, Ganiyu, O. Mosuro

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Integrated geophysical methods involving Vertical Electrical Sounding (VES) and 2D resistivity survey were deployed to gain an insight into the influence of the two varying rock types (mica-schist and granite gneiss) underlying the road alignment to the incessant highway failure along Ajaokuta-Anyigba, North-central Nigeria. The highway serves as a link-road for the single largest cement factory in Africa (Dangote Cement Factory) and two major ceramic industries to the capital (Abuja) via Lokoja. 2D Electrical Resistivity survey (Dipole-Dipole Array) and Vertical Electrical Sounding (VES) (Schlumberger array) were employed. Twenty-two (22) 2D profiles were occupied, twenty (20) conducted about 1 m away from the unstable section underlain by mica-schist with profile length each of approximately 100 m. Two (2) profiles were conducted about 1 m away from the stable section with a profile length of 100 m each due to barriers caused by the drainage system and outcropping granite gneiss at the flanks of the road. A spacing of 2 m was used for good image resolution of the near-surface. On each 2D profile, a range of 1-3 VES was conducted; thus, forty-eight (48) soundings were acquired. Partial curve matching and WinResist software were used to obtain the apparent and true resistivity values of the 1D survey, while DiprofWin software was used for processing the 2-D survey. Two exposed lithologic sections caused by abandoned river channels adjacent to two profiles as well as the knowledge of the geology of the area helped to constrain the VES and 2D processing and interpretation. Generally, the resistivity values obtained reflect the parent rock type, degree of weathering, moisture content and competency of the tested area. Resistivity values < 100; 100 – 950; 1000 – 2000 and > 2500 ohms-m were interpreted as clay, weathered layer, partly weathered layer and fresh basement respectively. The VES results and 2-D resistivity structures along the unstable segment showed similar lithologic characteristics and sequences dominated by clayey substratum for depths range of 0 – 42.2 m. The clayey substratum is a product of intensive weathering of the parent rock (mica-schist) and constitutes weak foundation soils, causing highway failure. This failure is further exacerbated by several heavy-duty trucks which ply the section round the clock due to proximity to two major ceramic industries in the state and lack of drainage system. The two profiles on the stable section show 2D structures that are remarkably different from those of the unstable section with very thin topsoils, higher resistivity weathered substratum (indicating the presence of coarse fragments from the parent rock) and shallow depth to the basement (1.0 – 7. 1 m). Also, the presence of drainage and lower volume of heavy-duty trucks are contributors to the pavement stability of this section of the highway. The resistivity surveys effectively delineated two contrasting soil profiles of the subbase/subgrade that reflect variation in the mineralogy of underlying parent rocks.

Keywords: clay, geophysical methods, pavement, resistivity

Procedia PDF Downloads 142

Authors: Eduardo Antonio Lozano Hernandez, Nancy Ramirez Alvarez, Lorena Margarita Rios Mendoza, Jose Vinicio Macias Zamora, Felix Augusto Hernandez Guzman, Jose Luis Sanchez Osorio

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Microplastics (MPs) are one of the most numerous reported wastes found in the marine ecosystem, representing one of the greatest risks for organisms that inhabit that environment due to their bioavailability. Such is the case of bivalve mollusks, since they are capable of filtering large volumes of water, which increases the risk of contamination by microplastics through the continuous exposure to these materials. This study aims to determine, quantify and characterize microplastics found in the cultured oyster Crassostrea gigas. We also analyzed if there are spatio-temporal differences in the microplastic concentration of organisms grown in two bays having quite different human population. In addition, we wanted to have an idea of the possible impact on humans via consumption of these organisms. Commercial size organisms (>6cm length; n = 15) were collected by triplicate from eight oyster farming sites in Baja California, Mexico during winter and summer. Two sites are located in Todos Santos Bay (TSB), while the other six are located in San Quintin Bay (SQB). Site selection was based on commercial concessions for oyster farming in each bay. The organisms were chemically digested with 30% KOH (w/v) and 30% H₂O₂ (v/v) to remove the organic matter and subsequently filtered using a GF/D filter. All particles considered as possible MPs were quantified according to their physical characteristics using a stereoscopic microscope. The type of synthetic polymer was determined using a FTIR-ATR microscope and using a user as well as a commercial reference library (Nicolet iN10 Thermo Scientific, Inc.) of IR spectra of plastic polymers (with a certainty ≥70% for polymers pure; ≥50% for composite polymers). Plastic microfibers were found in all the samples analyzed. However, a low incidence of MP fragments was observed in our study (approximately 9%). The synthetic polymers identified were mainly polyester and polyacrylonitrile. In addition, polyethylene, polypropylene, polystyrene, nylon, and T. elastomer. On average, the content of microplastics in organisms were higher in TSB (0.05 ± 0.01 plastic particles (pp)/g of wet weight) than found in SQB (0.02 ± 0.004 pp/g of wet weight) in the winter period. The highest concentration of MPs found in TSB coincides with the rainy season in the region, which increases the runoff from streams and wastewater discharges to the bay, as well as the larger population pressure (> 500,000 inhabitants). Otherwise, SQB is a mainly rural location, where surface runoff from streams is minimal and in addition, does not have a wastewater discharge into the bay. During the summer, no significant differences (Manne-Whitney U test; P=0.484) were observed in the concentration of MPs found in the cultured oysters of TSB and SQB, (average: 0.01 ± 0.003 pp/g and 0.01 ± 0.002 pp/g, respectively). Finally, we concluded that the consumption of oyster does not represent a risk for humans due to the low concentrations of MPs found. The concentration of MPs is influenced by the variables such as temporality, circulations dynamics of the bay and existing demographic pressure.

Keywords: FTIR-ATR, Human risk, Microplastic, Oyster

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Authors: Junali Deka

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“Pictures speak more than a thousand words”. It is the power of image which can have multiple meanings the way it is read by the viewers. This research article is an outcome of the extensive study of the phenomenon of‘selfie culture’ and dire need of self-constructed virtual identity among youths. In the recent times, there has been a revolutionary change in the concept of photography in terms of both techniques and applications. The popularity of ‘self-portraits’ mainly depend on the temporal space and time created on social networking sites like Facebook, Instagram. With reference to Stuart’s Hall encoding and decoding process, the article studies the behavior of the users who post photographs online. The photographic messages (Roland Barthes) are interpreted differently by different viewers. The notion of ‘self’, ‘self-love and practice of looking (Marita Sturken) and ways of seeing (John Berger) got new definition and dimensional together. After Oscars Night, show host Ellen DeGeneres’s selfie created the most buzz and hype in the social media. The term was judged the word of 2013, and has earned its place in the dictionary. “In November 2013, the word "selfie" was announced as being the "word of the year" by the Oxford English Dictionary. By the end of 2012, Time magazine considered selfie one of the "top 10 buzzwords" of that year; although selfies had existed long before, it was in 2012 that the term "really hit the big time an Australian origin. The present study was carried to understand the concept of ‘selfie-bug’ and the phenomenon it has created among youth (especially students) at large in developing a pseudo-image of its own. The topic was relevant and gave a platform to discuss about the cultural, psychological and sociological implications of selfie in the age of digital technology. At the first level, content analysis of the primary and secondary sources including newspapers articles and online resources was carried out followed by a small online survey conducted with the help of questionnaire to find out the student’s view on selfie and its social and psychological effects. The newspapers reports and online resources confirmed that selfie is a new trend in the digital media and it has redefined the notion of beauty and self-love. The Facebook and Instagram are the major platforms used to express one-self and creation of virtual identity. The findings clearly reflected the active participation of female students in comparison to male students. The study of the photographs of few selected respondents revealed the difference of attitude and image building among male and female users. The study underlines some basic questions about the desire of reconstruction of identity among young generation, such as - are they becoming culturally narcissist; responsible factors for cultural, social and moral changes in the society, psychological and technological effects caused by Smartphone as well, culminating into a big question mark whether the selfie is a social signifier of identity construction.

Keywords: Culture, Narcissist, Photographs, Selfie

Procedia PDF Downloads 379

Authors: Sachil Kumar, Anoop Kumar Verma, Wahid Ali, Uma Shankar Singh

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Globally approximately 55.3 million people die each year. In the India there were 95 lakh annual deaths in 2013. The number of deaths resulted from homicides, suicides and unintentional injuries in the same period was about 5.7 lakh. The ever-increasing crime rate necessitated the development of methods for determining time since death. An erroneous time of death window can lead investigators down the wrong path or possibly focus a case on an innocent suspect. In this regard a research was carried out by analyzing the temperature dependent degradation of a Cardiac Troponin-T protein (cTnT) in the myocardium postmortem as a marker for time since death. Cardiac tissue samples were collected from (n=6) medico-legal autopsies, (in the Department of Forensic Medicine and Toxicology, King George’s Medical University, Lucknow India) after informed consent from the relatives and studied post-mortem degradation by incubation of the cardiac tissue at room temperature (20±2 OC), 12 0C, 25 0C and 37 0C for different time periods ((~5, 26, 50, 84, 132, 157, 180, 205, and 230 hours). The cases included were the subjects of road traffic accidents (RTA) without any prior history of disease who died in the hospital and their exact time of death was known. The analysis involved extraction of the protein, separation by denaturing gel electrophoresis (SDS-PAGE) and visualization by Western blot using cTnT specific monoclonal antibodies. The area of the bands within a lane was quantified by scanning and digitizing the image using Gel Doc. The data shows a distinct temporal profile corresponding to the degradation of cTnT by proteases found in cardiac muscle. The disappearance of intact cTnT and the appearance of lower molecular weight bands are easily observed. Western blot data clearly showed the intact protein at 42 kDa, two major (27 kDa, 10kDa) fragments, two additional minor fragments (32 kDa) and formation of low molecular weight fragments as time increases. At 12 0C the intensity of band (intact cTnT) decreased steadily as compared to RT, 25 0C and 37 0C. Overall, both PMI and temperature had a statistically significant effect where the greatest amount of protein breakdown was observed within the first 38 h and at the highest temperature, 37 0C. The combination of high temperature (37 0C) and long Postmortem interval (105.15 hrs) had the most drastic effect on the breakdown of cTnT. If the percent intact cTnT is calculated from the total area integrated within a Western blot lane, then the percent intact cTnT shows a pseudo-first order relationship when plotted against the log of the time postmortem. These plots show a good coefficient of correlation of r = 0.95 (p=0.003) for the regression of the human heart at different temperature conditions. The data presented demonstrates that this technique can provide an extended time range during which Postmortem interval can be more accurately estimated.

Keywords: degradation, postmortem interval, proteolysis, temperature, troponin

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Emma Castiglioni, Nigel Scrutton, Derren Heyes, Alistair Fielding

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By using light as trigger, it is possible to study many biological processes, such as the activity of genes, proteins, and other molecules, with precise spatiotemporal control. Caged compounds, where biologically active molecules are generated from an inert precursor upon laser photolysis, offer the potential to initiate such biological reactions with high temporal resolution. As light acts as the trigger for cleaving the protecting group, the ‘caging’ technique provides a number of advantages as it can be intracellular, rapid and controlled in a quantitative manner. We are developing caging strategies to study the catalytic cycle of a number of enzyme systems, such as nitric oxide synthase and ethanolamine ammonia lyase. These include the use of caged substrates, caged electrons and the possibility of caging the enzyme itself. In addition, we are developing a novel freeze-quench instrument to study these reactions, which combines rapid mixing and flashing capabilities. Reaction intermediates will be trapped at low temperatures and will be analysed by using electron paramagnetic resonance (EPR) spectroscopy to identify the involvement of any radical species during catalysis. EPR techniques typically require relatively long measurement times and very often, low temperatures to fully characterise these short-lived species. Therefore, common rapid mixing techniques, such as stopped-flow or quench-flow are not directly suitable. However, the combination of rapid freeze-quench (RFQ) followed by EPR analysis provides the ideal approach to kinetically trap and spectroscopically characterise these transient radical species. In a typical RFQ experiment, two reagent solutions are delivered to the mixer via two syringes driven by a pneumatic actuator or stepper motor. The new mixed solution is then sprayed into a cryogenic liquid or surface, and the frozen sample is then collected and packed into an EPR tube for analysis. The earliest RFQ instrument consisted of a hydraulic ram unit as a drive unit with direct spraying of the sample into a cryogenic liquid (nitrogen, isopentane or petroleum). Improvements to the RFQ technique have arisen from the design of new mixers in order to reduce both the volume and the mixing time. In addition, the cryogenic isopentane bath has been coupled to a filtering system or replaced by spraying the solution onto a surface that is frozen via thermal conductivity with a cryogenic liquid. In our work, we are developing a novel RFQ instrument which combines the freeze-quench technology with flashing capabilities to enable the studies of both thermally-activated and light-activated biological reactions. This instrument also uses a new rotating plate design based on magnetic couplings and removes the need for mechanical motorised rotation, which can otherwise be problematic at cryogenic temperatures.

Keywords: caged compounds, freeze-quench apparatus, photolysis, radicals

Procedia PDF Downloads 187

Authors: Farhan A. Alenizi

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Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

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Authors: Beatriz Rebocho, Elisabete Valente, Carla Palma, Andreia Guilherme, Filipa Bessa, Paula Sobral

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The global accumulation of plastic in the oceans is a growing problem. Plastic is transported from its source to the oceans via rivers, which are considered the main route for plastic particles from land-based sources to the ocean. These plastics undergo physical and chemical degradation resulting in microplastics. The i-Plastic project aims to understand and predict the dispersion, accumulation and impacts of microplastics (5 mm to 1 µm) and nano plastics (below 1 µm) in marine environments from the tropical and temperate land-ocean interface to the open ocean under distinct flow and climate regimes. Seasonal monitoring of the fluxes of microplastics was carried out in (three) coastal areas in Brazil, Portugal and Spain. The present work shows the first results of in-situ seasonal monitoring and mapping of microplastics in ocean waters between Ovar and Vieira de Leiria (Portugal), in which 43 surface water samples and 43 water column samples were collected in contrasting seasons (spring and autumn). The spring and autumn surface water samples were collected with a 300 µm and 150 µm pore neuston net, respectively. In both campaigns, water column samples were collected using a conical mesh with a 150 µm pore. The experimental procedure comprises the following steps: i) sieving by a metal sieve; ii) digestion with potassium hydroxide to remove the organic matter original from the sample matrix. After a filtration step, the content is retained on a membrane and observed under a stereomicroscope, and physical and chemical characterization (type, color, size, and polymer composition) of the microparticles is performed. Results showed that 84% and 88% of the surface water and water column samples were contaminated with microplastics, respectively. Surface water samples collected during the spring campaign averaged 0.35 MP.m-3, while surface water samples collected during autumn recorded 0.39 MP.m-3. Water column samples from the spring campaign had an average of 1.46 MP.m-3, while those from the autumn recorded 2.54 MP.m-3. In the spring, all microplastics found were fibers, predominantly black and blue. In autumn, the dominant particles found in the surface waters were fibers, while in the water column, fragments were dominant. In spring, the average size of surface water particles was 888 μm, while in the water column was 1063 μm. In autumn, the average size of surface and water column microplastics was 1333 μm and 1393 μm, respectively. The main polymers identified by Attenuated Total Reflectance (ATR) and micro-ATR Fourier Transform Infrared (FTIR) spectroscopy from all samples were low-density polyethylene (LDPE), polypropylene (PP), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The significant difference between the microplastic concentration in the water column between the two campaigns could be due to the remixing of the water masses that occurred that week due to the occurrence of a storm. This work presents preliminary results since the i-Plastic project is still in progress. These results will contribute to the understanding of the spatial and temporal dispersion and accumulation of microplastics in this marine environment.

Keywords: microplastics, Portugal, Atlantic Ocean, water column, surface water

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Authors: Elizabeth M. Annoni, Elena G. Tolkacheva

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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that is a known prognostic marker for stroke, heart failure and death. Reentrant mechanisms of rotor formation, which are stable electrical sources of cardiac excitation, are believed to cause AF. No existing commercial mapping systems have been demonstrated to consistently and accurately predict rotor locations outside of the pulmonary veins in patients with persistent AF. There is a clear need for robust spatio-temporal techniques that can consistently identify rotors using unique characteristics of the electrical recordings at the pivot point that can be applied to clinical intracardiac mapping. Recently, we have developed four new signal analysis approaches – Shannon entropy (SE), Kurtosis (Kt), multi-scale frequency (MSF), and multi-scale entropy (MSE) – to identify the pivot points of rotors. These proposed techniques utilize different cardiac signal characteristics (other than local activation) to uncover the intrinsic complexity of the electrical activity in the rotors, which are not taken into account in current mapping methods. We validated these techniques using high-resolution optical mapping experiments in which direct visualization and identification of rotors in ex-vivo Langendorff-perfused hearts were possible. Episodes of ventricular tachycardia (VT) were induced using burst pacing, and two examples of rotors were used showing 3-sec episodes of a single stationary rotor and figure-8 reentry with one rotor being stationary and one meandering. Movies were captured at a rate of 600 frames per second for 3 sec. with 64x64 pixel resolution. These optical mapping movies were used to evaluate the performance and robustness of SE, Kt, MSF and MSE techniques with respect to the following clinical limitations: different time of recordings, different spatial resolution, and the presence of meandering rotors. To quantitatively compare the results, SE, Kt, MSF and MSE techniques were compared to the “true” rotor(s) identified using the phase map. Accuracy was calculated for each approach as the duration of the time series and spatial resolution were reduced. The time series duration was decreased from its original length of 3 sec, down to 2, 1, and 0.5 sec. The spatial resolution of the original VT episodes was decreased from 64x64 pixels to 32x32, 16x16, and 8x8 pixels by uniformly removing pixels from the optical mapping video.. Our results demonstrate that Kt, MSF and MSE were able to accurately identify the pivot point of the rotor under all three clinical limitations. The MSE approach demonstrated the best overall performance, but Kt was the best in identifying the pivot point of the meandering rotor. Artifacts mildly affect the performance of Kt, MSF and MSE techniques, but had a strong negative impact of the performance of SE. The results of our study motivate further validation of SE, Kt, MSF and MSE techniques using intra-atrial electrograms from paroxysmal and persistent AF patients to see if these approaches can identify pivot points in a clinical setting. More accurate rotor localization could significantly increase the efficacy of catheter ablation to treat AF, resulting in a higher success rate for single procedures.

Keywords: Atrial Fibrillation, Optical Mapping, Signal Processing, Rotors

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Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 330

Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

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Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

Procedia PDF Downloads 51

Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

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Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

Procedia PDF Downloads 229

Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

Procedia PDF Downloads 105