Search results for: temporal modalities

Authors: Vemula Amalakrishna, S. Pushpavanam

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Change and motion characterize and persistently reshape the world around us, on scales from molecular to global. The subtle interplay between change (Reaction) and motion (Diffusion) gives rise to an astonishing intricate spatial or temporal pattern. These pattern formation in nature has been intellectually appealing for many scientists since antiquity. Periodic precipitation patterns, also known as Liesegang patterns (LP), are one of the stimulating examples of such self-assembling reaction-diffusion (RD) systems. LP formation has a great potential in micro and nanotechnology. So far, the research on LPs has been concentrated mostly on how these patterns are forming, retrieving information to build a universal mathematical model for them. Researchers have developed various theoretical models to comprehensively construct the geometrical diversity of LPs. To the best of our knowledge, simulation studies of LPs assume an arbitrary value of RD parameters to explain experimental observation qualitatively. In this work, existing models were studied to understand the mechanism behind this phenomenon and challenges pertaining to models were understood and explained. These models are not computationally effective due to the presence of discontinuous precipitation rate in RD equations. To overcome the computational challenges, smoothened Heaviside functions have been introduced, which downsizes the computational time as well. Experiments were performed using a conventional LP system (AgNO₃-K₂Cr₂O₇) to understand the effects of different gels and temperatures on formed LPs. The model is extended for real parameter values to compare the simulated results with experimental data for both 1-D (Cartesian test tubes) and 2-D(cylindrical and Petri dish).

Keywords: reaction-diffusion, spatio-temporal patterns, nucleation and growth, supersaturation

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Authors: Muhammad Tayyab Afzal, Muhammad Arslan, Mirza Muhammad Waqar

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Snow constitutes an important component of the cryosphere, characterized by high temporal and spatial variability. Because of the contribution of snow melt to water availability, snow is an important focus for research on climate change and adaptation. MODIS satellite data have been used to identify spatial-temporal trends in snow cover in the upper Indus basin. For this research MODIS satellite 8 day composite data of medium resolution (250m) have been analysed from 2001-2005.Pixel based supervised classification have been performed and extent of snow have been calculated of all the images. Results show large variation in snow cover between years while an increasing trend from west to east is observed. Temperature data for the Upper Indus Basin (UIB) have been analysed for seasonal and annual trends over the period 2001-2005 and calibrated with the results acquired by the research. From the analysis it is concluded that there are indications that regional warming is one of the factor that is affecting the hydrology of the upper Indus basin due to accelerated glacial melting during the simulation period, stream flow in the upper Indus basin can be predicted with a high degree of accuracy. This conclusion is also supported by the research of ICIMOD in which there is an observation that the average annual precipitation over a five year period is less than the observed stream flow and supported by positive temperature trends in all seasons.

Keywords: indus basin, MODIS, remote sensing, snow cover

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Authors: Amidu Owolabi Ayeni

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Studies have shown that spatio-temporal distribution and variability of climatic variables, urban land use, and population have had substantial impact on water supply. It is based on these facts that the impacts of climate, urbanization, and population on water supply in Lagos State Nigeria remain the focus of this study. Population and water production data on Lagos State between 1963 and 2006 were collected, and used for time series and projection analyses. Multi-temporal land-sat images of 1975, 1995 and NigeriaSat-1 imagery of 2007 were used for land use change analysis. The population of Lagos State increased by about 557.1% between 1963 and 2006, correspondingly, safe water supply increased by 554%. Currently, 60% of domestic water use in urban areas of Lagos State is from groundwater while 75% of rural water is from unsafe surface water. Between 1975 and 2007, urban land use increased by about 235.9%. The 46years climatic records revealed that temperature and evaporation decreased slightly while rainfall and Relatively Humidity (RH) decreased consistently. Based on these trends, the Lagos State population and required water are expected to increase to about 19.8millions and 2418.9ML/D respectively by the year 2026. Rainfall is likely to decrease by -6.68mm while temperature will increase by 0.950C by 2026. Urban land use is expected to increase by 20% with expectation of serious congestion in the suburb areas. With these results, over 50% of the urban inhabitants will be highly water poor in future if the trends continue unabated.

Keywords: challenges, climate change, urbanization, water supply

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Authors: Anshul Raja

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Cystic lesions of the spleen are rare and splenic hydatid cysts account for only 0.5% to 8% of all hydatidosis. Authors hereby report a case where a 50-year-old female presented to our hospital with the complains of heaviness and pain over left upper abdomen over the past 8-10 years. On radiological examination, ultrasonography revealed findings consistent with isolated splenic hydatid cyst and was later on confirmed on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). No other organ or system involvement was seen. The patient underwent splenectomy and hydatid cyst was confirmed on histopathology. Owing to its rarity, it offers a diagnostic challenge to physicians but can reliably be diagnosed with great confidence employing various imaging modalities like CT and MRI.

Keywords: gastrointestinal radiology, abdominal imaging, hydatid cyst, medical and health sciences

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Authors: Ateeth Shetty, K. S. Jayappa, Ratheesh Ramakrishnan, A. S. Rajawat

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Suspended Sediment Concentration (SSC) was estimated for the period of four months (November, 2013 to February 2014) using Oceansat-2 (Ocean Colour Monitor) satellite images to understand the coastal dynamics and regional sediment transport, especially distribution and budgeting in coastal waters. The coastal zone undergoes continuous changes due to natural processes and anthropogenic activities. The importance of the coastal zone, with respect to safety, ecology, economy and recreation, demands a management strategy in which each of these aspects is taken into account. Monitoring and understanding the sediment dynamics and suspended sediment transport is an important issue for coastal engineering related activities. A study of the transport mechanism of suspended sediments in the near shore environment is essential not only to safeguard marine installations or navigational channels, but also for the coastal structure design, environmental protection and disaster reduction. Such studies also help in assessment of pollutants and other biological activities in the region. An accurate description of the sediment transport, caused by waves and tidal or wave-induced currents, is of great importance in predicting coastal morphological changes. Satellite-derived SSC data have been found to be useful for Indian coasts because of their high spatial (360 m), spectral and temporal resolutions. The present paper outlines the applications of state‐of‐the‐art operational Indian Remote Sensing satellite, Oceansat-2 to study the dynamics of sediment transport.

Keywords: suspended sediment concentration, ocean colour monitor, sediment transport, case – II waters

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies indicate that a large fronto-parieto-temporal network support nouns and their features, with some areas store semantic knowledge (visual, auditory, olfactory, gustatory,…), other areas store lexical representation and other areas are implicated in general semantic processing. However, it is not well understood how this fronto-parieto-temporal network can be modulated by different semantic tasks and different semantic relations between nouns. In this study, we combine a behavioral semantic network, functional MRI studies involving object’s related nouns and brain network studies to explain how different semantic tasks and different semantic relations between nouns can modulate the activity within the brain network of nouns and their features. We first describe how nouns and their features form a large scale brain network. For this end, we examine the connectivities between areas recruited during the processing of nouns to know which configurations of interaction areas are possible. We can thus identify if, for example, brain areas that store semantic knowledge communicate via functional/structural links with areas that store lexical representations. Second, we examine how this network is modulated by different semantic tasks involving nouns and finally, we examine how category specific activation may result from the semantic relations among nouns. The results indicate that brain network of nouns and their features is highly modulated and flexible by different semantic tasks and semantic relations. At the end, this study can be used as a guide to help neurosientifics to interpret the pattern of fMRI activations detected in the semantic processing of nouns. Specifically; this study can help to interpret the category specific activations observed extensively in a large number of neuroimaging studies and clinical studies.

Keywords: nouns, features, network, category specificity

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Florian Wagner, Christoph Schmidt, Vincent Bagnoud

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Understanding the interaction of ultra-intense laser pulses with overcritical targets is of major interest for many applications such as laser-driven ion acceleration, fast ignition in the frame of inertial confinement fusion or high harmonic generation and the creation of attosecond pulses. One particular aspect of this interaction is the shift of the critical surface, where the laser pulse is stopped and the absorption is at maximum, due to the radiation pressure induced by the laser pulse, also referred to as laser hole boring. We investigate laser-hole boring experimentally by measuring the backscattered spectrum which is doppler-broadened because of the movement of the reflecting surface. Using the high-power, high-energy laser system PHELIX in Darmstadt, we gathered an extensive set of data for different laser intensities ranging from 10^18 W/cm2 to 10^21 W/cm2, two different levels of the nanosecond temporal contrast (10^6 vs. 10^11), elliptical and linear polarization and varying target configurations. In this contribution we discuss how the maximum velocity of the critical surface depends on these parameters. In particular we show that by increasing the temporal contrast the maximum hole boring velocity is decreased by more than a factor of three. Our experimental findings are backed by a basic analytical model based on momentum and mass conservation as well as particle in cell simulations. These results are of particular importance for fast ignition since they contribute to a better understanding of the transport of the ignitor pulse into the overdense region.

Keywords: laser-hole boring, interaction of ultra-intense lasers with overcritical targets, fast ignition, relativistic laser motter interaction

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Authors: Zair Nadje, Attoui Badra, Miloudi Abdelmonem

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This study aims to assess sensitivity to nitrate pollution and monitor the temporal evolution of nitrate contents in groundwater using statistical models and map their spatial distribution. The nitrate levels observed in the waters of the town of El-Oued differ from one aquifer to another. Indeed, the waters of the Quaternary aquifer are the richest in nitrates, with average annual contents varying from 6 mg/l to 85 mg/l, for an average of 37 mg/l. These levels are higher than the WHO standard (50 mg/l) for drinking water. At the water level of the Terminal Complex (CT) aquifer, the annual average nitrate levels vary from 14 mg/l to 37 mg/l, with an average of 18 mg/l. In the Terminal Complex, excessive nitrate levels are observed in the central localities of the study area. The spatial distribution of nitrates in the waters of the Quaternary aquifer shows that the majority of the catchment points of this aquifer are subject to nitrate pollution. This study shows that in the waters of the Terminal Complex aquifer, nitrate pollution evolves in two major areas. The first focus is South-North, following the direction of underground flow. The second is West-East, progressing towards the East zone. The temporal distribution of nitrate contents in the water of the Terminal Complex aquifer in the city of El-Oued showed that for decades, nitrate contents have suffered a decline after an increase. This evolution of nitrate levels is linked to demographic growth and the rapid urbanization of the city of El-Oued.

Keywords: anthropogenic activities, groundwater, nitrates, pollution, arid zones city of El-Oued, Algeria

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Authors: Bansal Ashwani

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Cartographic depiction and visualization of wetland changes is an important tool to map spatial-temporal information about the wetland dynamics effectively and to comprehend the response of these water bodies in maintaining the groundwater and surrounding ecosystem. This is true for the states of North Western India, i.e., J&K, Himachal, Punjab, and Haryana that are bestowed upon with several natural wetlands in the flood plains or on the courses of its rivers. Thus, the present study documents, analyses and reconstructs the lost wetlands, which existed in the flood plains of the major river basins of these states, i.e., Chenab, Jhelum, Satluj, Beas, Ravi, and Ghagar, in the beginning of the 20th century. To achieve the objective, the study has used multi-temporal datasets since the 1960s using high to medium resolution satellite datasets, e.g., Corona (1960s/70s), Landsat (1990s-2017) and Sentinel (2017). The Sentinel (2017) satellite image has been used for making the wetland inventory owing to its comparatively higher spatial resolution with multi-spectral bands. In addition, historical records, repeated photographs, historical maps, field observations including geomorphological evidence were also used. The water index techniques, i.e., band rationing, normalized difference water index (NDWI), modified NDWI (MNDWI) have been compared and used to map the wetlands. The wetland types found in the north-western states have been categorized under 19 classes suggested by Space Application Centre, India. These enable the researcher to provide with the wetlands inventory and a series of cartographic representation that includes overlaying multiple temporal wetlands extent vectors. A preliminary result shows the general state of wetland shrinkage since the 1960s with varying area shrinkage rate from one wetland to another. In addition, it is observed that majority of wetlands have not been documented so far and even do not have names. Moreover, the purpose is to emphasize their elimination in addition to establishing a baseline dataset that can be a tool for wetland planning and management. Finally, the applicability of cartographic depiction and visualization, historical map sources, repeated photographs and remote sensing data for reconstruction of long term wetlands fluctuations, especially in the northern part of India, will be addressed.

Keywords: cartographic depiction and visualization, wetland changes, NDWI/MDWI, geomorphological evidence and remote sensing

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Authors: Andrea S. Badillo-Perez, Alexis D. Mitchell, Sara M. Levens

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Overeating, and obesity have been associated with addictive behavior, primarily due to behaviors like reward-based eating, the tendency to overeat due to factors such as lack of control, preoccupation over food, and lack of satiation. Temporal discounting (TD), the ability to select future rewards over short term gains, and mindfulness, the process of maintaining present moment awareness, have been suggested to have significant, differential impacts on health-related behaviors. An individual’s health locus of control, the degree to which they feel that they have control over their health is also known to have an impact on health outcomes. The goal of this study was to investigate the relationship between health locus of control and reward-based eating, as well as the relation between TD and mindfulness in a sample (N = 126) of overweight or obese participants from larger health-focused study. Through the use of questionnaires (including the Five Facet Mindfulness Questionnaire (FFMQ), Reward-Based Eating Drive (RED), and Multidimensional Health Locus of Control (MHLOC)), anthropometric measurements, and a computerized TD task, a series of regressions tested the association between subscales of these measures. Results revealed differences in how the mindfulness subscales are associated with TD measures. Specifically the ‘Observing’ (beta =-.203) and ‘Describing’ (beta =.26) subscales were associated with lower TD rates and a longer subjective devaluation time-frame respectively. In contrast, the ‘Acting with Awareness’ subscale was associated with a shorter subjective devaluation timeframe (beta =-.23). These findings suggest that the reflective perspective initiated through the observing and describing components of mindfulness may facilitate delay of gratification, whereas the acting with awareness component of mindfulness, which focuses on the present moment, may make delay of gratification more challenging. Results also indicated that a higher degree of reward-based eating was associated with a higher degree of an external health locus of control based on the power of chance (beta =.10). However, an external locus of control based on the power of others had no significant association with reward-based eating. This finding implies that the belief that health is due to chance is associated with greater reward-based eating behavior, suggesting that interventions that focus on locus of control may be helpful. Overall, findings demonstrate that weight loss interventions may benefit from health locus of control and mindfulness exercises, but caution should be taken as the components of mindfulness appear to have different effects on increasing or decreasing delay of gratification.

Keywords: health locus of control, mindfulness, obesity, reward-based eating, temporal discounting

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Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall

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Authors: Matthew Montebello

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Student engagement within a virtual learning environment generates masses of data points that can significantly contribute to the learning analytics that lead to decision support. Ideally, similar data is collected during student interaction with a physical learning space, and as a consequence, data is present at a large scale, even in relatively small classes. In this paper, we report of such an occurrence during classes held in a HiFlex modality as we investigate the advantages of adopting such a methodology. We plan to take full advantage of the learner-generated data in an attempt to further enhance the effectiveness of the adopted learning environment. This could shed crucial light on operating modalities that higher education institutions around the world will switch to in a post-COVID era.

Keywords: HiFlex, big data in higher education, learning analytics, virtual learning environment

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Authors: Helen Yetunde Omoboye, Adebukola Adenike Adedeji, Israel Funso Adeniyi

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This study of the biodiversity, community structure, and production capacity of the zooplankton community is an aspect of bio-monitoring of the aquatic ecosystem. Samples were selected horizontally and vertically from Esa-Odo Reservoir using improvised Meyer’s water sampler. Planktonic samples were collected at two months intervals for two years. Net and total plankton were sampled by filtration and sedimentation methods. Planktonic samples were preserved as 5% formalin and 1% Lugol’s solution. Measurement, enumeration, and scaled pictures of the recorded zooplankton were taken using a photomicrograph. The taxonomic composition of zooplankton biota was determined using identification keys. Eighty three (83) species of zooplankton recorded in this study belong to 4 groups: Rotifera, Cladocera, Copepoda, and Insecta. Rotifera was the most represented group (61.21%). Horizontally, 24 species with the highest mean abundance characterized the lacustrine; while 12 species and 10 species were unique to the transition and riverine zones, respectively. Vertically, most species had their mean abundance decreased from the surface to the bottom of the reservoir. A total of nine (9), two (2), and one (1) species were peculiar to the surface, bottom and mid-depth, respectively. Zooplankton was most abundant during the dry season. In conclusion, Esa-Odo Reservoir comprised highly diversified zooplankton fauna with great potential to support a rich aquatic community and fishery production. The reservoir can be classified as fairly clean based on the abundance of the rotifer group. However, the lake should be subjected to regular proper monitoring because of the presence of some pollution tolerant copepod species identified among the zooplankton fauna.

Keywords: zooplankton, spatial, temporal, abundance, biodiversity, reservoir

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Authors: Zia Ullah, Ruh Ullah

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A research study was conceded in four locations (Swat, Dir, Kakul and Balakot) of Khyber Pakhtunkhwa, to find agro-climatic classes by using aridity index, Growing Degree Days of wheat and maize, crop growth index and Spatio-temporal analysis of rainfall by using long term climatic data (1970-2010). The climatic data used for research was acquired from Pakistan Meteorological Department (PMD) Islamabad, Agriculture Research Institute, Weather Station Peshawar and Tarnab Peshawar. Agro-climatic classes of each location were determined using three criteria mean temperature of the coldest month, mean temperature of the warmest month and aridity index. The agro-climatic classes of Dir, Swat, Kakul and Balakot were classified as Humid, Cold and very Warm (H-K-VW). Average aridity index of wheat for Dir, Swat, Kakul, and Balakot was 2.23, 2.67, 1.94 and 2.34 and for Maize was 1.31, 1.26, 1.97, and 2.83 respectively. The overall and decade-wise trend of GDD of Wheat and Maize was declined in Swat and Kakul while increased in Dir and Balakot.The average maximum CGI (1.26) and (0.73) of Wheat and Maize was observed for Balakot and Dir, while the minimum (1.09) and (0.62) was observed for Swat and Kakul. Spatio-temporal analysis of rainfall shows that the trend has increased in Swat while decreased in Dir, Kakul and Balakot. From the relation between rainfalls with altitude showed that there was an increasing trend between rainfalls with altitude. The maximum average rainfall was in Swat (2703mm) on altitude 2000m while the minimum average rainfall was observed in Kakul (1410mm) on altitude of 1255m.

Keywords: agro-climatic zones, aridity index, GDD, rainfall

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Authors: Auj-E Taqaddas

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The use of proton beam therapy is increasing globally. It seems to offer dosimetric advantages, especially in paediatric central nervous system (CNS) and brain tumours. A short E-survey was conducted to assess the clinical, technical, and educational resources and strategies employed in the state of the art proton beam therapy (PBT) centres in the USA to determine the current status of proton beam therapy. The study also aimed at finding out which PBT skills are in demand as well as what improvements are needed to ensure efficient treatment planning, delivery, and dosimetry. The study resulted in identifying areas for future research and development and in identifying cancers for which PBT is most suitable compared to other modalities to facilitate the implementation and use of PBT in clinical settings for cancer treatment.

Keywords: cancer, intensity modulated proton therapy, proton beam therapy, single field uniform scanning

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Authors: Oliver Chunho Ma, Tszying Chang

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Background: Traditional Chinese Medicine (TCM) has been widely used in the treatment of eczema. However, there is currently a lack of comprehensive research on the overall effectiveness of TCM in treating eczema, particularly using the Eczema Area and Severity Index (EASI) score as an evaluation tool. Meta-analysis can integrate the results of multiple studies to provide more convincing evidence. Objective: To conduct a systematic review and meta-analysis based on the EASI score to evaluate the overall effectiveness of TCM in the treatment of eczema. Specifically, the study will review and analyze published clinical studies that investigate TCM treatments for eczema and use the EASI score as an outcome measure, comparing the differences in improving the severity of eczema between TCM and other treatment modalities, such as conventional Western medicine treatments. Methods: Relevant studies, including randomized controlled trials (RCTs) and non-randomized controlled trials, that involve TCM treatment for eczema and use the EASI score as an outcome measure will be searched in medical literature databases such as PubMed, CNKI, etc. Relevant data will be extracted from the selected studies, including study design, sample size, treatment methods, improvement in EASI score, etc. The methodological quality and risk of bias of the included studies will be assessed using appropriate evaluation tools (such as the Cochrane Handbook). The results of the selected studies will be statistically analyzed, including pooling effect sizes (such as standardized mean differences, relative risks, etc.), subgroup analysis (e.g., different TCM syndromes, different treatment modalities), and sensitivity analysis (e.g., excluding low-quality studies). Based on the results of the statistical analysis and quality assessment, the overall effectiveness of TCM in improving the severity of eczema will be interpreted. Expected outcomes: By integrating the results of multiple studies, we expect to provide more convincing evidence regarding the specific effects of TCM in improving the severity of eczema. Additionally, subgroup analysis and sensitivity analysis can further elucidate whether the effectiveness of TCM treatment is influenced by different factors. Besides, we will compare the results of the meta-analysis with the clinical data from our clinic. For both the clinical data and the meta-analysis results, we will perform descriptive statistics such as means, standard deviations, percentages, etc. and compare the differences between the two using statistical tests such as independent samples t-test or non-parametric tests to assess the statistical differences between them.

Keywords: Eczema, traditional Chinese medicine, EASI, systematic review, meta-analysis

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Authors: H. Lee, J. Park

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In this present study, for the first time, we retrieved the Formaldehyde (HCHO) Vertical Column Density (HCHOVCD) using Pandora instruments in Seoul, a megacity in northeast Asia, for the period between 2012 and 2014 and investigated the temporal characteristics of HCHOVCD. HCHO Slant Column Density (HCHOSCD) was obtained using the Differential Optical Absorption Spectroscopy (DOAS) method. HCHOSCD was converted to HCHOVCD using geometric Air Mass Factor (AMFG) as Pandora is the direct-sun measurement. The HCHOVCDs is low at 12:00 Local Time (LT) and is high in the morning (10:00 LT) and late afternoon (16:00 LT) except for winter. The maximum (minimum) values of Pandora HCHOVCD are 2.68×1016 (1.63×10¹⁶), 3.19×10¹⁶ (2.23×10¹⁶), 2.00×10¹⁶ (1.26×10¹⁶), and 1.63×10¹⁶ (0.82×10¹⁶) molecules cm⁻² in spring, summer, autumn, and winter, respectively. In terms of seasonal variations, HCHOVCD was high in summer and low in winter which implies that photo-oxidation plays an important role in HCHO production in Seoul. In comparison with the Ozone Monitoring Instrument (OMI) measurements, the HCHOVCDs from the OMI are lower than those from Pandora. The correlation coefficient (R) between monthly HCHOVCDs values from Pandora and OMI is 0.61, with slop of 0.35. Furthermore, to understand HCHO mixing ratio within Planetary Boundary Layer (PBL) in Seoul, we converted Pandora HCHOVCDs to HCHO mixing ratio in the PBL using several meteorological input data from the Atmospheric InfraRed Sounder (AIRS). Seasonal HCHO mixing ratio in PBL converted from Pandora (OMI) HCHOVCDs are estimated to be 6.57 (5.17), 7.08 (6.68), 7.60 (4.70), and 5.00 (4.76) ppbv in spring, summer, autumn, and winter, respectively.

Keywords: formaldehyde, OMI, Pandora, remote sensing

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Authors: Guoqin Ge, Minhui Huang, Yazhou Zhou

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The growth of the Chengdu-Chongqing urban agglomeration has been designated as a national strategy in China. Analyzing its spatial evolution characteristics is crucial for devising relevant development strategies. This paper enhances the gravitational model by using temporal distance as a factor. It applies this improved model to assess the economic interconnection and concentration level of each geographical unit within the Chengdu-Chongqing urban agglomeration between 2011 and 2019. On this basis, this paper examines the spatial correlation characteristics of economic agglomeration intensity and urban-rural development equalization by employing spatial autocorrelation analysis. The study findings indicate that the spatial integration in the Chengdu-Chongqing urban agglomeration is currently in the "point-axis" development stage. The spatial organization structure is becoming more flattened, and there is a stronger economic connection between the core of the urban agglomeration and the peripheral areas. The integration of the Chengdu-Chongqing urban agglomeration is currently hindered by conflicting interests and institutional heterogeneity between Chengdu and Chongqing. Additionally, the connections between the relatively secondary spatial units are largely loose and weak. The strength and scale of economic ties and the level of urban-rural equilibrium among spatial units within the Chengdu-Chongqing urban agglomeration have increased, but regional imbalances have continued to widen, and such positive and negative changes have been characterized by the spatial and temporal synergistic evolution of the "core-periphery". Ultimately, this paper presents planning ideas for the future integration development of the Chengdu-Chongqing urban agglomeration, drawing from the findings.

Keywords: integration, planning strategy, space organization, space evolution, urban agglomeration

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Authors: James Forren

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This research paper details a recent demonstrator project in which digital form found textile structures were built by human craftspersons wearing augmented reality (AR) head-worn displays (HWDs). The project utilized a wet-state natural fiber / cementitious matrix composite to generate minimal bending shapes in tension which, when cured and rotated, performed as minimal-bending compression members. The significance of the project is that it synthesizes computational structural simulations with visually guided handcraft production. Computational and physical form-finding methods with textiles are well characterized in the development of architectural form. One difficulty, however, is physically building computer simulations: often requiring complicated digital fabrication workflows. However, AR HWDs have been used to build a complex digital form from bricks, wood, plastic, and steel without digital fabrication devices. These projects utilize, instead, the tacit knowledge motor schema of the human craftsperson. Computational simulations offer unprecedented speed and performance in solving complex structural problems. Human craftspersons possess highly efficient complex spatial reasoning motor schemas. And textiles offer efficient form-generating possibilities for individual structural members and overall structural forms. This project proposes that the synthesis of these three modalities of structural problem-solving – computational, human, and material - may not only develop efficient structural form but offer further creative potentialities when the respective intelligence of each modality is productively leveraged. The project methodology pertains to its three modalities of production: 1) computational, 2) human, and 3) material. A proprietary three-dimensional graphic statics simulator generated a three-legged arch as a wireframe model. This wireframe was discretized into nine modules, three modules per leg. Each module was modeled as a woven matrix of one-inch diameter chords. And each woven matrix was transmitted to a holographic engine running on HWDs. Craftspersons wearing the HWDs then wove wet cementitious chords within a simple falsework frame to match the minimal bending form displayed in front of them. Once the woven components cured, they were demounted from the frame. The components were then assembled into a full structure using the holographically displayed computational model as a guide. The assembled structure was approximately eighteen feet in diameter and ten feet in height and matched the holographic model to under an inch of tolerance. The construction validated the computational simulation of the minimal bending form as it was dimensionally stable for a ten-day period, after which it was disassembled. The demonstrator illustrated the facility with which computationally derived, a structurally stable form could be achieved by the holographically guided, complex three-dimensional motor schema of the human craftsperson. However, the workflow traveled unidirectionally from computer to human to material: failing to fully leverage the intelligence of each modality. Subsequent research – a workshop testing human interaction with a physics engine simulation of string networks; and research on the use of HWDs to capture hand gestures in weaving seeks to develop further interactivity with rope and chord towards a bi-directional workflow within full-scale building environments.

Keywords: augmented reality, cementitious composites, computational form finding, textile structures

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Authors: Guilherme Henrique Gabriel, Lucí Hidalgo Nunes

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An important feature of rainfall regimes is the variability, which is subject to the atmosphere’s general and regional dynamics, geographical position and relief. Despite being inherent to the climate system, it can harshly impact virtually all human activities. In turn, global climate change has the ability to significantly affect smaller-scale rainfall regimes by altering their current variability patterns. In this regard, it is useful to know if regional climates are changing over time and whether it is possible to link these variations to climate change trends observed globally. This study is part of an international project (Metropole-FAPESP, Proc. 2012/51876-0 and Proc. 2015/11035-5) and the objective was to identify and evaluate possible changes in rainfall behavior in the state of São Paulo, southeastern Brazil, using rainfall data from 79 rain gauges for the last forty years. Cluster analysis and gamma distribution parameters were used for evaluating spatial and temporal trends, and the outcomes are presented by means of geographic information systems tools. Results show remarkable changes in rainfall distribution patterns in São Paulo over the years: changes in shape and scale parameters of gamma distribution indicate both an increase in the irregularity of rainfall distribution and the probability of occurrence of extreme events. Additionally, the spatial outcome of cluster analysis along with the gamma distribution parameters suggest that changes occurred simultaneously over the whole area, indicating that they could be related to remote causes beyond the local and regional ones, especially in a current global climate change scenario.

Keywords: climate change, cluster analysis, gamma distribution, rainfall

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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

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

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

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Authors: Berhanu Terfa, Nengcheng C.

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The study deals with the analysis of urban expansion and land transformation of Hawass City using remote sensing data and landscape metrics during last three decades (1987–2017). Remote sensing data from Various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used to examine the urban expansion, growth types, and spatial isolation within the urban landscape to develop an understanding the trends of built-up growth in Hawassa City, Ethiopia. Landscape metrics and built-up density were employed to analyze the pattern, process and overall growth status. The area under investigation was divided into concentric circles with a consecutive circle of 1 km incremental radius from the central pixel (Central Business District) for analysis. The result exhibited that the built-up area had increased by 541.32% between 1987 and 2017and an extension growth types (more than 67 %) was observed. The major growth took place in north-west direction followed by north direction in haphazard manner during 1987–1995 period, whereas predominant built-up development was observed in south and southwest direction during 1995–2017 period. Land scape metrics result revealed that the of urban patches density, total edge and edge density increased, while mean nearest neighbors’ distance decreased showing the tendency of sprawl.

Keywords: landscape metrics, spatial patterns, remote sensing, multi-temporal, urban sprawl

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Authors: Amit Kumar, Bhupendra Pratap Singh, Manoj Singh, Monika Punia, Krishan Kumar, V. K. Jain

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Ambient concentrations of volatile organic compounds (VOCs) were investigated in order to find out temporal variations and their ozone forming potentials (OFP) at rural site in Delhi National Capital Region during summer 2013. Sampling was performed for continuous five days, to identify the differences in working days and weekend VOCs concentration levels. Sampling and analytical procedure for VOCs were done using National Institute for Occupational Safety and Health (NIOSH) standard method. On each sampling day, VOCs samples were collected for 3-hours in the morning, afternoon and evening. There has been observed a noticeable contrast in the concentration of VOCs levels between working days and weekend. However, most of the VOCs showed diurnal fluctuations with higher concentrations in the morning and evening as compared to afternoon which might be due to change in meteorology. The results showed that mean toluene/benzene and m-/p-xylene/benzene ratios were higher in the afternoon while it was lower during morning and evening. The relative contribution of the VOCs to ozone formation, total propylene equivalent concentrations and OFP were calculated. Toluene was the most contributing organic contaminant to ozone formation as well as ambient VOCs concentrations. Results obtained in current study demonstrate that ozone formation at rural site in Delhi is probably limited by the emissions of VOCs.

Keywords: VOCs, rural, NIOSH, ozone forming potential, propylene equivalent concentration

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Letizia Maria Drammis, Maria Antonella Brandimonte

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The idea that people use space representations to think about time and number received support from several lines of research. However, how these representations develop in children and then shape space-time and space-number mappings is still a debated issue. In the present study, 40 children (20 pre-schoolers and 20 elementary-school children) performed 4 main tasks, which required the use of more concrete (non-symbolic) or more abstract (symbolic) space-time and space-number associations. In the non-symbolic conditions, children were required to order pictures of everyday-life events occurring in a specific temporal order (Temporal sequences) and of quantities varying in numerosity (Numerical sequences). In the symbolic conditions, they were asked to perform the typical time-to-position and number-to-position tasks by mapping time-related words and numbers onto lines. Results showed that children performed reliably better in the non-symbolic Time conditions than the symbolic Time conditions, independently of age, whereas only pre-schoolers performed worse in the Number-to-position task (symbolic) as compared to the Numerical sequence (non-symbolic) task. In addition, only older children mapped time-related words onto space following the typical left-right orientation, pre-schoolers’ performance being somewhat mixed. In contrast, mapping numbers onto space showed a clear left-right orientation, independently of age. Overall, these results indicate a cross-domain difference in the way younger and older children process time and number, with time-related tasks being more difficult than number-related tasks only when space-time tasks require symbolic representations.

Keywords: space-time associations, space-number associations, orientation, children

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Authors: Noori Shafiqullah

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Millions of people reside downstream of river basins that heavily rely on snowmelt originating from the Hindu Kush (HK) region. Snowmelt plays a critical role as a primary water source in these areas. This study aimed to evaluate snowfall and snowmelt characteristics in the HK region across altitudes ranging from 2019m to 4533m. To achieve this, the study employed a combination of remote sensing techniques and the Snow Model (SM) to analyze the spatial and temporal distribution of Snow Water Equivalent (SWE). By integrating the simulated Snow-cover Area (SCA) with data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the study optimized the Precipitation Gradient (PG), snowfall assessment, and the degree-day factor (DDF) for snowmelt distribution. Ground observed data from various elevations were used to calculate a temperature lapse rate of -7.0 (°C km-1). Consequently, the DDF value was determined as 3 (mm °C-1 d-1) for altitudes below 3000m and 3 to 4 (mm °C-1 d-1) for higher altitudes above 3000m. Moreover, the distribution of precipitation varies with elevation, with the PG being 0.001 (m-1) at lower elevations below 4000m and 0 (m-1) at higher elevations above 4000m. This study successfully utilized the SM to assess SCA and SWE by incorporating the two optimized parameters. The analysis of simulated SCA and MODIS data yielded coefficient determinations of R2, resulting in values of 0.95 and 0.97 for the years 2014-2015, 2015-2016, and 2016-2017, respectively. These results demonstrate that the SM is a valuable tool for managing water resources in mountainous watersheds such as the HK, where data scarcity poses a challenge."

Keywords: improved MODIS, experiment, snow water equivalent, snowmelt

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Elochukwu A. Nwankwo, Matthias U. Agboeze

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Many heritage sites abound in the shores of Nigeria with enormous tourism potentials. Heritage sites do not only depict the cultural and historical transmutation of people but also functions in the image design and promotion of a locality. This reveals the unique role of heritage sites to structural development of an area. Heritage sites have of recent been a victim of degradation and social abuse arising from seasonal ignorance; hence minimizing its potentials to the socio-economic development of an area. This paper is emphasizing on the adoption of community development approaches in heritage preservation in Igbo area. Its modalities, applications, challenges and prospect were discussed. Such understanding will serve as a catalyst in aiding general restoration and preservation of heritage sites in Nigeria and other African states.

Keywords: heritage resources, community development, preservation, sustainable development, approaches

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