Search results for: temporal lobe epilepsy

Authors: Shreya Srivastava, Sushovan Ghosh, Sagnik Dey

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Aerosols directly affect Earth’s radiation budget by scattering and absorbing incoming solar radiation and outgoing terrestrial radiation. While the uncertainty in aerosol radiative forcing (ARF) has decreased over the years, it is still higher than that of greenhouse gas forcing, particularly in the South Asian region, due to high heterogeneity in their chemical properties. Understanding the Spatio-temporal heterogeneity of aerosol composition is critical in improving climate prediction. Studies using satellite data, in-situ and aircraft measurements, and models have investigated the Spatio-temporal variability of aerosol characteristics. In this study, we have taken aerosol data from Multi-angle Imaging Spectro-Radiometer (MISR) level-2 version 23 aerosol products retrieved at 4.4 km and radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 21 years (2000-2021) over the Indian subcontinent. MISR aerosol product includes size and shapes segregated aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). Additionally, 74 aerosol mixtures are included in version 23 data that is used for aerosol speciation. We have seasonally mapped aerosol optical and microphysical properties from MISR for India at quarter degrees resolution. Results show strong Spatio-temporal variability, with a constant higher value of AOD for the Indo-Gangetic Plain (IGP). The contribution of small-size particles is higher throughout the year, spatially during winter months. SSA is found to be overestimated where absorbing particles are present. The climatological map of short wave (SW) ARF at the top of the atmosphere (TOA) shows a strong cooling except in only a few places (values ranging from +2.5o to -22.5o). Cooling due to aerosols is higher in the absence of clouds. Higher negative values of ARF are found over the IGP region, given the high aerosol concentration above the region. Surface ARF values are everywhere negative for our study domain, with higher values in clear conditions. The results strongly correlate with AOD from MISR and ARF from CERES.

Keywords: aerosol Radiative forcing (ARF), aerosol composition, single scattering albedo (SSA), CERES

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Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

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In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Amjad Al Shammari, Ashraf Ibrahim, Laila Seada

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Background and Objectives: Incidence of thyroid carcinoma has been increasing world-wide. In the present study, we evaluated diagnostic accuracy of Fine needle aspiration (FNA) and its efficiency in early detecting neoplastic lesions of thyroid gland over a 3-year period. Methods: Data have been retrieved from pathology files in King Khalid Hospital. For each patient, age, gender, FNA, site & size of nodule and final histopathologic diagnosis were recorded. Results: Study included 490 cases where 419 of them were female and 71 male. Male to female ratio was 1:6. Mean age was 43 years for males and 38 for females. Cases with confirmed histopathology were 131. In 101/131 (77.1%), concordance was found between FNA and histology. In 30/131 (22.9%), there was discrepancy in diagnosis. Total malignant cases were 43, out of which 14 (32.5%) were true positive and 29 (67.44%) were false negative. No false positive cases could be found in our series. Conclusion: FNA could diagnose benign nodules in all cases, however, in malignant cases, ultrasound findings have to be taken into consideration to avoid missing of a microcarcinoma in the contralateral lobe.

Keywords: FNA, hail, histopathology, thyroid

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Authors: Waleed Jarjoura

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In various cases of visual impairments, the individuals are referred to expert Ophthalmologists in order to establish a correct diagnosis. Children with visual-impairments confront various challenging experiences in life since early childhood throughout lifespan. In some cases, blind infants, especially due to congenital hydrocephalus, suffer from high intra-cranial pressure and, consequently, go through a ventriculo-peritoneal shunt surgery in order to limit the neurological symptoms or decrease the cognitive impairments. In this article, a detailed description of numerous crucial implications of the V/P shunt surgery, through the right posterior-inferior parieto-temporal cortex, on the observed preliminary capabilities that are pre-requisites for the acquisition of literacy skills in braille, basic Math competencies, braille printing which suggest Gerstmann syndrome in the blind. In addition, significant difficultiesorientation and mobility skills using the Cane, in general, organizational skills, and social interactions were observed. The primary conclusion of this report focuses on raising awareness among neuro-surgeons towards the need for alternative intracranial routes for V/P shunt implantation in blind infants that preserve the right posterior-inferior parieto-temporal cortex that is hypothesized to modulate the tactual-spatial cues in braille discrimination. A second conclusion targets educators and therapists that address the acquired dysfunctionsin blind individuals due to V/P shunt surgeries.

Keywords: congenital blindness, hydrocephalus, shunt surgery, spatial orientation

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Authors: Nino Gogatishvili, Davit Kvernadze, Giorgi Japharidze

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Background and aims: Landau Kleffner syndrome (LKS) is a rare disorder with epileptic seizures and acquired aphasia. It usually starts in initially healthy children. The first symptoms are language regression and behavioral disturbances, and the sleep EEG reveals abnormal epileptiform activity. The aim was to discuss the efficacy of Clobazam for Landau Kleffner syndrome. Case report: We report a case of an 11-year-old boy with an uneventful pregnancy and delivery. He began to walk at 11 months and speak with simple phrases at the age of 2,5 years. At the age of 18 months, he had febrile convulsions; at the age of 5 years, the parents noticed language regression, stuttering, and serious behavioral dysfunction, including hyperactivity, temper outbursts. The epileptic seizure was not noticed. MRI was without any abnormality. Neuropsychological testing revealed verbal auditory agnosia. Sleep EEG showed abundant left fronto-temporal spikes, reaching over 85% during non-rapid eye movement sleep (non-REM sleep). Treatment was started with Clobazam. After ten weeks, EEG was improved. Stuttering and behavior also improved. Results: Since the start of Clobazam treatment, stuttering and behavior improved. Now, he is 11 years old, without antiseizure medication. Sleep EEG shows fronto-temporal spikes on the left side, over 10-49 % of non-REM sleep, bioccipital spikes, and slow-wave discharges and spike-waves. Conclusions: This case provides further support for the efficacy of Clobazam in patients with LKS.

Keywords: Landau-Kleffner syndrome, antiseizure medication, stuttering, aphasia

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Authors: Mace Bentley, Zhuojun Duan, Tobias Gerken, Dudley Bonsal, Henry Way, Endre Szakal, Mia Pham, Hunter Donaldson, Chelsea Lang, Hayden Abbott, Leah Wilcynzski

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Air pollution has the potential to modify the lifespan and intensity of thunderstorms and the properties of lightning. Using data mining and geovisualization, we investigate how background climate and weather conditions shape variability in urban air pollution and how this, in turn, shapes thunderstorms as measured by the intensity, distribution, and frequency of cloud-to-ground lightning. A spatiotemporal analysis was conducted in order to identify thunderstorms using high-resolution lightning detection network data. Over seven million lightning flashes were used to identify more than 196,000 thunderstorms that occurred between 2006 - 2020 in the Washington, DC Metropolitan Region. Each lightning flash in the dataset was grouped into thunderstorm events by means of a temporal and spatial clustering algorithm. Once the thunderstorm event database was constructed, hourly wind direction, wind speed, and atmospheric thermodynamic data were added to the initiation and dissipation times and locations for the 196,000 identified thunderstorms. Hourly aerosol and air quality data for the thunderstorm initiation times and locations were also incorporated into the dataset. Developing thunderstorm climatologies using a lightning tracking algorithm and lightning detection network data was found to be useful for visualizing the spatial and temporal distribution of urban augmented thunderstorms in the region.

Keywords: lightning, urbanization, thunderstorms, climatology

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Authors: Fidan Z. Aliyeva

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In the presented article, the formation of the microbiological regime in the Takhtakorpu water complex, as well as spatial-temporal changes in the quantitative indicators of bacterioplankton, were studied. Taktakorpu water complex was built as a continuation of the reconstruction and expansion project of the Samur-Absheron irrigation system in Shabran on the northeastern slope of our republic. It should be noted that with the implementation of the project, the water supply of up to 150 thousand ha of useful land in the northern region has been improved, and the drinking, technical, and irrigation water needs of the population of Baku, Sumgayit and also the Absheron Peninsula, and industrial and agricultural areas, joining the agricultural circulation of new soil areas, Takhtakorpu reservoir with a volume of 238.4 million m³, connected with them -Valvalachay- Takhtakorpu and Takhtakorpu-Jeyranbatan canals have been created, conditions have been created to increase the resources of the Jeyranbatan reservoir. Special attention is paid to the study of saprophytic bacteria in order to determine the development dynamics and biochemical activity of the microbiological regime in the Takhtakorpu Water Complex, which is of great strategic importance for our republic, to evaluate changes under the influence of anthropogenic factors, as well as to evaluate the properties of self-cleaning, mineralization features of organic substances of allochthon and autochthonous origin. One of the main goals of our research is to determine the main structural indicators of bacterioplankton in the upper part of Takhtakorpu water complex in the first three stations and analyzing their quantitative values in a certain time aspect.

Keywords: water, irrigation, sewage, wastewater

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Authors: Ben Morrow, Patrick O'Hara, Natalie Ban, Tunai Marques, Molly Fraser, Christopher Bone

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Relative to commercial fisheries, recreational fisheries are often poorly understood and pose various challenges for monitoring frameworks. In British Columbia (BC), Canada, Pacific salmon are heavily targeted by recreational fishers while also being a key source of nutrient flow and crucial prey for a variety of marine and terrestrial fauna, including endangered Southern Resident killer whales (Orcinus orca). Although commercial fisheries were historically responsible for the majority of salmon retention, recreational fishing now comprises both greater effort and retention. The current monitoring scheme for recreational salmon fisheries involves aerial-roving creel surveys. However, this method has been identified as costly and having low predictive power as it is often limited to sampling fragments of fluid and temporally dynamic fisheries. This study used imagery from two shore-based autonomous cameras in a highly active recreational fishery around Sooke, BC, and evaluated their efficacy in supplementing existing aerial-roving surveys for monitoring a recreational salmon fishery. This study involved continuous monitoring and high temporal resolution (over one million images analyzed in a single fishing season), using a deep learning-based vessel detection algorithm and a custom image annotation tool to efficiently thin datasets. This allowed for the quantification of peak-season effort from a busy harbour, species-specific retention estimates, high levels of detected fishing events at a nearby popular fishing location, as well as the proportion of the fishery management area represented by cameras. Then, this study demonstrated how it could substantially enhance the temporal resolution of a fishery through diel activity pattern analyses, scaled monthly to visualize clusters of activity. This work also highlighted considerable off-season fishing detection, currently unaccounted for in the existing monitoring framework. These results demonstrate several distinct applications of autonomous cameras for providing enhanced detail currently unavailable in the current monitoring framework, each of which has important considerations for the managerial allocation of resources. Further, the approach and methodology can benefit other studies that apply shore-based camera monitoring, supplement aerial-roving creel surveys to improve fine-scale temporal understanding, inform the optimal timing of creel surveys, and improve the predictive power of recreational stock assessments to preserve important and endangered fish species.

Keywords: cameras, monitoring, recreational fishing, stock assessment

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Yun Chen, David Penton, Fazlul Karim, Santosh Aryal, Shahriar Wahid, Peter Taylor, Susan M. Cuddy

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Droughts have severely affected Afghanistan over the last four decades, leading to critical food shortages where two-thirds of the country’s population are in a food crisis. Long years of conflict have lowered the country’s ability to deal with hazards such as drought, which can rapidly escalate into disasters. Understanding the spatial and temporal distribution of droughts is needed to be able to respond effectively to disasters and plan for future occurrences. This study used Standardized Precipitation Evapotranspiration Index (SPEI) at monthly, seasonal, and annual temporal scales to map the spatiotemporal change dynamics of drought characteristics (distribution, frequency, duration, and severity) in Afghanistan. SPEI indices were mapped for river basins, disaggregated into 189 sub-catchments, using monthly precipitation and potential evapotranspiration derived from temperature station observations from 1980 to 2017. The results show these multi-dimensional drought characteristics vary along different years, change among sub-catchments, and differ across temporal scales. During the 38 years, the driest decade and period are the 2000s and 1999–2022, respectively. The 2000–01 water year is the driest, with the whole country experiencing ‘severe’ to ‘extreme’ drought, more than 53% (87 sub-catchments) suffering the worst drought in history, and about 58% (94 sub-catchments) having ‘very frequent’ drought (7 to 8 months) or ‘extremely frequent’ drought (9 to 10 months). The estimated seasonal duration and severity present significant variations across the study area and throughout the study period. The nation also suffered from recurring droughts with varying length and intensity in 2004, 2006, 2008, and, most recently, 2011. There is a trend towards increasing drought with longer duration and higher severity extending all over sub-catchments from southeast to north and central regions. These datasets and maps help to fill the knowledge gap on detailed sub-catchment scale meteorological drought characteristics in Afghanistan. The study findings improve our understanding of the influences of climate change on drought dynamics and can guide catchment planning for reliable adaptation to and mitigation against future droughts.

Keywords: SPEI, precipitation, evapotranspiration, climate extremes

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Authors: Pholosho M. Kgopa, Phatu W. Mashela, Alen Manyevere

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Increasing incidents of drought spells in most Sub-Saharan Africa call for using alternative sources of water for irrigation in arid and semi-arid regions. A study was conducted to investigate chemical composition of borehole and treated wastewater from different sampling disposal sites at University of Limpopo Experimental Farm (ULEF). A 4 × 5 factorial experiment, with the borehole as a reference sampling site and three other sampling sites along the wastewater disposal system was conducted over five months. Water samples were collected at four sites namely, (a) exit from Pond 16 into the furrow, (b) entry into night-dam, (c) exit from night dam to irrigated fields and (d) exit from borehole to irrigated fields. Water samples were collected in the middle of each month, starting from July to November 2016. Samples were analysed for pH, EC, Ca, Mg, Na, K, Al, B, Zn, Cu, Cr, Pb, Cd and As. The site × time interactions were highly significant for Ca, Mg, Zn, Cu, Cr, Pb, Cd, and As variables, but not for Na and K. Sampling site was highly significant on all variables, with sampling period not significant for K and Na. Relative to water from the borehole, Na concentration in wastewater samples from the night-dam exit, night-dam entry and Pond16 exit were lower by 69, 34 and 55%, respectively. Relative to borehole water, Al was higher in wastewater sampling sites. In conclusion, both sampling site and period affected the chemical composition of treated wastewater.

Keywords: irrigation water quality, spatial effects, temporal effects, water reuse, water scarcity

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Authors: C. S. Seema, P. R. Prince

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The characterization of spatio-temporal inhomogeneities occurring in the ionospheric F₂ layer is remarkable since these variations are direct consequences of electrodynamical coupling between magnetosphere and solar events. The temporal and spatial variations of the F₂ layer, which occur with a period of several days or even years, mainly owe to geomagnetic and meteorological activities. The hourly F₂ layer critical frequency (foF2) over 23rd solar cycle (1996-2008) of three ionosonde stations (Wakkanai, Kokunbunji, and Okinawa) in northern hemisphere, which falls within same longitudinal span, is analyzed using continuous wavelet techniques. Morlet wavelet is used to transform continuous time series data of foF2 to a two dimensional time-frequency space, quantifying the time evolution of the oscillatory modes. The presence of significant time patterns (periodicities) at a particular time period and the time location of each periodicity are detected from the two-dimensional representation of the wavelet power, in the plane of scale and period of the time series. The mean strength of each periodicity over the entire period of analysis is studied using global wavelet spectrum. The quasi biennial, annual, semiannual, 27 day, diurnal and 12 hour variations of foF2 are clearly evident in the wavelet power spectra in all the three stations. Critical frequency oscillations with multi-day periods (2-3 days and 9 days in the low latitude station, 6-7 days in all stations and 15 days in mid-high latitude station) are also superimposed over large time scaled variations.

Keywords: continuous wavelet analysis, critical frequency, ionosphere, solar cycle

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Authors: Rawad Asfour, Salam Khamas, Edward A. Ball

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This paper is focused on the design of an mm-wave phased array. To date, linear polarization is adapted in the reported designs of phased arrays. However, linear polarization faces several well-known challenges. As such, an advanced design for phased array antennas is required that offers circularly polarized (CP) radiation. A feasible solution for achieving CP phased array antennas is proposed using open-circular loop antennas. To this end, a 3-element circular loop phased array antenna is designed to operate at 28GHz. In addition, the array ability to control the direction of the main lobe is investigated. The results show that the highest achievable field of view (FOV) is 100°, i.e., 50° to the left and 50° to the right-hand side directions. The results are achieved with a CP bandwidth of 15%. Furthermore, the results demonstrate that a high broadside gain of circa 11 dBi can be achieved for the steered beam. Besides, a radiation efficiency of 97 % can also be achieved based on the proposed design.

Keywords: loop antenna, phased array, beam steering, wide bandwidth, circular polarization, CST

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Hanyu Wang, Guangdong Wang

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County-level areas serve as vital spatial units for advancing new urbanization and implementing the principles of low-carbon development, representing critical regions where conflicts between the two are pronounced. Using the 142 county-level units in the Chengdu-Chongqing city clusters as a case study, a coupled coordination model is employed to investigate the coupled coordination relationship and its spatiotemporal evolution between county-level new urbanization and low-carbon development levels. Results indicate that (1) from 2005 to 2020, the overall levels of new urbanization and low-carbon development in the Chengdu-Chongqing city clusters showed an upward trend but with significant regional disparities. The new urbanization level exhibited a spatial differentiation pattern of "high in the suburban areas, low in the distant suburbs, and some counties standing out." The temporal change in low-carbon development levels was not pronounced, yet spatial disparities were notable. (2) The overall coupling coordination degree between new urbanization and low-carbon development is transitioning from barely coordinated to moderately coordinated. The lag in new urbanization levels serves as a primary factor constraining the coordinated development of most counties. (3) Based on the temporal evolution of development states, all county units can be categorized into four types: coordinated demonstration areas, synergistic improvement areas, low-carbon transformation areas, and development lag areas. The research findings offer crucial reference points for spatial planning and the formulation of low-carbon development policies.

Keywords: county units, coupling coordination, low-carbon development, new urbanization

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Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

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Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

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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: 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: C. Bunsanit

Abstract:

This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband

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Authors: Florian Wagner, Christoph Schmidt, Vincent Bagnoud

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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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