Search results for: individual patient data

Authors: Akshita Jindal, Renu Chadha, Maninder Karan

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Supramolecular chemistry has gained recent eminence in a flurry of research documents demonstrating the formation of new crystalline forms with potentially advantageous characteristics. Mesalamine (5-amino salicylic acid) belongs to anti-inflammatory class of drugs, is used to treat ulcerative colitis and Crohn’s disease. Unfortunately, mesalamine suffer from poor solubility and therefore very low bioavailability. This work is focused on preparation and characterization of cocrystal of mesalamine with nicotinamide (MNIC) a coformer of GRAS status. Cocrystallisation was achieved by solvent drop grinding in stoichiometric ratio of 1:1 using acetonitrile as solvent and was characterized by various techniques including DSC (Differential Scanning Calorimetry), PXRD (X-ray Powder Diffraction), and FTIR (Fourier Transform Infrared Spectrometer). The co-crystal depicted single endothermic transitions (254°C) which were different from the melting peaks of both drug (288°C) and coformer (128°C) indicating the formation of a new solid phase. Different XRPD patterns and FTIR spectrums for the co-crystals from those of individual components confirms the formation of new phase. Enhancement in apparent solubility study and intrinsic dissolution study showed effectiveness of this cocrystal. Further improvement in pharmacokinetic profile has also been observed with 2 folds increase in bioavailability. To conclude, our results show that application of nicotinamide as a coformer is a viable approach towards the preparation of cocrystals of potential drug molecule having limited solubility.

Keywords: cocrystal, mesalamine, nicotinamide, solvent drop grinding

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Authors: Zhanfeng Ma, Zhiping Xiong, Hu Yin, Zhengwei She, Aditya P. Gurajada, Tianlun Chen, Ying Li

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Many RDBMS vendors use B-tree index to achieve high performance for point queries and range queries, and some of them also employ hash index to further enhance the performance as hash table is more efficient for point queries. However, there are extra overheads to maintain a separate hash index, for example, hash mapping for all data records must always be maintained, which results in more memory space consumption; locking, logging and other mechanisms are needed to guarantee ACID, which affects the concurrency and scalability of the system. To relieve the overheads, Hash Cached B-tree (HCB) index is proposed in this paper, which consists of a standard disk-based B-tree index and an additional in-memory lock-free hash table. Initially, only the B-tree index is constructed for all data records, the hash table is built on the fly based on runtime workload, only data records accessed by point queries are indexed using hash table, this helps reduce the memory footprint. Changes to hash table are done using compare-and-swap (CAS) without performing locking and logging, this helps improve the concurrency and avoid contention. The hash table is also optimized to be cache conscious. HCB index is implemented in SAP ASE database, compared with the standard B-tree index, early experiments and customer adoptions show significant performance improvement. This paper provides an overview of the design of HCB index and reports the experimental results.

Keywords: B-tree, compare-and-swap, lock-free hash table, point queries, range queries, SAP ASE database

Procedia PDF Downloads 281

Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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Authors: Brian Marsh

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Nitrogen fertilizer is the most used and often the most mismanaged nutrient input. Nitrogen management has tremendous implications on crop productivity, quality and environmental stewardship. Sufficient nitrogen is needed to optimum yield and quality. Soil and in-season plant tissue testing for nitrogen status are a time consuming and expensive process. Real time sensing of plant nitrogen status can be a useful tool in managing nitrogen inputs. The objectives of this project were to assess the reliability of remotely sensed non-destructive plant nitrogen measurements compared to wet chemistry data from sampled plant tissue, develop in-season nitrogen recommendations based on remotely sensed data for improved nitrogen use efficiency and assess the potential for determining yield and quality from remotely sensed data. Very good correlations were observed between early-season remotely sensed crop nitrogen status and plant nitrogen concentrations and subsequent in-season fertilizer recommendations. The transmittance/absorbance type meters gave the most accurate readings. Early in-season fertilizer recommendation would be to apply 40 kg nitrogen per hectare plus 16 kg nitrogen per hectare for each unit difference measured with the SPAD meter between the crop and reference area or 25 kg plus 13 kg per hectare for each unit difference measured with the CCM 200. Once the crop was sufficiently fertilized meter readings became inconclusive and were of no benefit for determining nitrogen status, silage yield and quality and grain yield and protein.

Keywords: wheat, nitrogen fertilization, chlorophyll meter

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Authors: Ahmed Ishtiaq, Maeeda Khalid, Umair Sajjad

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In the fast-moving world, information is the key to success. If information is easily available, then it makes work easy. The Internet is the biggest collection and source of information nowadays, and with every single day, the data on internet increases, and it becomes difficult to find required data. Everyone wants to make his/her website at the top of search results. This can be possible when you have applied some techniques of SEO inside your application or outside your application, which are two types of SEO, onsite and offsite SEO. SEO is an abbreviation of Search Engine Optimization, and it is a set of techniques, methods to increase users of a website on World Wide Web or to rank up your website in search engine indexing. In this paper, we have compared different techniques of Onpage and Offpage SEO, and we have suggested many things that should be changed inside webpage, outside web page and mentioned some most powerful and search engine considerable elements and techniques in both types of SEO in order to gain high ranking on Search Engine.

Keywords: auto-suggestion, search engine optimization, SEO, query, web mining, web crawler

Procedia PDF Downloads 140

Authors: Ju-Hong Lee, Ching-Wei Liao

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Owing to close antenna spacing between antenna sensors within a compact space, a part of data in one antenna sensor would outflow to other antenna sensors when the antenna sensors in an antenna array operate simultaneously. This phenomenon is called mutual coupling effect (MCE). It has been shown that the performance of antenna array systems can be degraded when the antenna sensors are in close proximity. Especially, in a systems equipped with massive antenna sensors, the degradation of beamforming performance due to the MCE is significantly inevitable. Moreover, it has been shown that even a small angle error between the true direction angle of the desired signal and the steering angle deteriorates the effectiveness of an array beamforming system. However, the true direction vector of the desired signal may not be exactly known in some applications, e.g., the application in land mobile-cellular wireless systems. Therefore, it is worth developing robust techniques to deal with the problem due to the MCE and steering angle error for array beamforming systems. In this paper, we present an efficient technique for performing adaptive beamforming with robust capabilities against the MCE and the steering angle error. Only the data vector received by an antenna array is required by the proposed technique. By using the received array data vector, a correlation matrix is constructed to replace the original correlation matrix associated with the received array data vector. Then, the mutual coupling matrix due to the MCE on the antenna array is estimated through a recursive algorithm. An appropriate estimate of the direction angle of the desired signal can also be obtained during the recursive process. Based on the estimated mutual coupling matrix, the estimated direction angle, and the reconstructed correlation matrix, the proposed technique can effectively cure the performance degradation due to steering angle error and MCE. The novelty of the proposed technique is that the implementation procedure is very simple and the resulting adaptive beamforming performance is satisfactory. Simulation results show that the proposed technique provides much better beamforming performance without requiring complicated complexity as compared with the existing robust techniques.

Keywords: adaptive beamforming, mutual coupling effect, recursive algorithm, steering angle error

Procedia PDF Downloads 319

Authors: Helen Pushkarskaya, David Tolin, Lital Ruderman, Ariel Kirshenbaum, J. MacLaren Kelly, Christopher Pittenger, Ifat Levy

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Obsessive-Compulsive Disorder (OCD) produces profound morbidity. Difficulties with decision making and intolerance of uncertainty are prominent clinical features of OCD. The nature and etiology of these deficits are poorly understood. We used a well-validated choice task, grounded in behavioral economic theory, to investigate differences in valuation and value-based choice during decision making under uncertainty in 20 unmedicated participants with OCD and 20 matched healthy controls. Participants’ choices were used to assess individual decision-making characteristics. Compared to controls, individuals with OCD were less consistent in their choices and less able to identify options that were unambiguously preferable. These differences correlated with symptom severity. OCD participants did not differ from controls in how they valued uncertain options when outcome probabilities were known (risk) but were more likely than controls to avoid uncertain options when these probabilities were imprecisely specified (ambiguity). These results suggest that the underlying neural mechanisms of valuation and value-based choices during decision-making are abnormal in OCD. Individuals with OCD show elevated intolerance of uncertainty, but only when outcome probabilities are themselves uncertain. Future research focused on the neural valuation network, which is implicated in value-based computations, may provide new neurocognitive insights into the pathophysiology of OCD. Deficits in decision-making processes may represent a target for therapeutic intervention.

Keywords: obsessive compulsive disorder, decision-making, uncertainty intolerance, risk aversion, ambiguity aversion, valuation

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Authors: Autjira Songjan, Poramatdha Chutimant

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This research is intended to study the operational quality assurance of private schools in Bangkok according to the opinions of administrators and teachers. Second is comparing the opinions of administrators and teachers about operating quality assurance process by gender, job and work experience. The sample include administrators and teachers of private schools in the Education School in Bangkok by using a proportion random technic. The questionnaire are used as query operations quality assurance to collect the data of private schools, the statistics that are used to analyze the data using the percentage, mean, standard deviation and Test the difference value and test of variance. The research found that the administrators and teachers have different sex, positions and duties have the different opinions about quality assurance in different statistically insignificant level 0.05 in the elements of performance management and the quality of the service that provided to students in the school.

Keywords: educational quality assurance, performance management, private schools in Bangkok, quality of the service

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Authors: Mareike Dornhoefer, Madjid Fathi

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Water supply and water quality are key problems of mankind at the moment and - due to increasing population - in the future. Management disciplines like water, environment and quality management therefore need to closely interact, to establish a high level of water quality and to guarantee water supply in all parts of the world. Groundwater remediation is one aspect in this process. From a knowledge management perspective it is only possible to solve complex ecological or environmental problems if different factors, expert knowledge of various stakeholders and formal regulations regarding water, waste or chemical management are interconnected in form of a knowledge base. In general knowledge management focuses the processes of gathering and representing existing and new knowledge in a way, which allows for inference or deduction of knowledge for e.g. a situation where a problem solution or decision support are required. A knowledge base is no sole data repository, but a key element in a knowledge based system, thus providing or allowing for inference mechanisms to deduct further knowledge from existing facts. In consequence this knowledge provides decision support. The given paper introduces an environmental knowledge system in water management. The proposed environmental knowledge system is part of a research concept called Green Knowledge Management. It applies semantic technologies or concepts such as ontology or linked open data to interconnect different data and information sources about environmental aspects, in this case, water quality, as well as background material enriching an established knowledge base. Examples for the aforementioned ecological or environmental factors threatening water quality are among others industrial pollution (e.g. leakage of chemicals), environmental changes (e.g. rise in temperature) or floods, where all kinds of waste are merged and transferred into natural water environments. Water quality is usually determined with the help of measuring different indicators (e.g. chemical or biological), which are gathered with the help of laboratory testing, continuous monitoring equipment or other measuring processes. During all of these processes data are gathered and stored in different databases. Meanwhile the knowledge base needs to be established through interconnecting data of these different data sources and enriching its semantics. Experts may add their knowledge or experiences of previous incidents or influencing factors. In consequence querying or inference mechanisms are applied for the deduction of coherence between indicators, predictive developments or environmental threats. Relevant processes or steps of action may be modeled in form of a rule based approach. Overall the environmental knowledge system supports the interconnection of information and adding semantics to create environmental knowledge about water environment, supply chain as well as quality. The proposed concept itself is a holistic approach, which links to associated disciplines like environmental and quality management. Quality indicators and quality management steps need to be considered e.g. for the process and inference layers of the environmental knowledge system, thus integrating the aforementioned management disciplines in one water management application.

Keywords: water quality, environmental knowledge system, green knowledge management, semantic technologies, quality management

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Authors: Sachin Deshmukh

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Mind and body synchronization occurs through memory and sensation production. Sensations are the guiding language of subconscious mind for conscious mind to take a proper action. Mind-mechanism is based upon memories collected so far since intrauterine life. There are three universal triggers for memory creation; they are persons, situations and objects. Memory is created as sensations experienced by special senses. Based upon experiencing comfort or discomfort, the triggers are categorized as safe or unsafe triggers. A memory comprises of ‘safe or unsafe feeling for triggers, and actions taken for that feeling’. Memories for triggers are created slowly, thoughtfully and consciously by the conscious mind, and archived in the subconscious mind for future references. Later on, similar triggers can come in contact with the individual. Subconscious mind uses these stored feelings to decide whether these triggers are safe or unsafe. It produces comfort or discomfort sensations as emotions accordingly and reacts in the same way as has been recorded in memory. Speed of sensing and processing the triggers, and reacting by subconscious mind is that of the speed of bioelectricity. Hence, formula for human emotions has been designed in this paper as follows: Emotion (Stress or Peace) = Trigger (Person or Situation or object) x Mass of feelings (stressful or peaceful) associated with the Trigger x Speed of Light². We also establish modern medical scientific facts about relationship between reflex activity and memory. This research further develops the ‘Rational Memory Therapy’ focusing on therapeutic feelings conversion techniques, for stress prevention and management.

Keywords: memory, sensations, feelings, emotions, rational memory therapy

Procedia PDF Downloads 251

Authors: Emna Ketata, Wafa Farhat

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Introduction: Hyponatremia is defined by a blood sodium level of ≤ 136 mmol/L; it is associated with a high risk of morbidity and mortality in the emergency room. This was explained by transit disorders, including diarrhea and inappropriate antidiuretic hormone secretion (Syndrome of inappropriate antidiuretic hormone secretion). Pneumonia can cause dyspnea, stress-causing SIADH and digestive symptoms (diarrhea and vomiting). Aim: The purpose of this study was to determine the link between pneumonia and hyponatremia as a predictor of patient’s prognosis and intra-hospital mortality. Methodology: This is a prospective observational study over a period of 3 years in the emergency department. Inclusion :patients (age > 14 years), with clinical signs in favor of pneumonia. Natremia was measured. Natremia was classified as mild to moderate with a blood sodium level between 121 and 135 mmol/L and as severe with a blood sodium level ≤ 120 mmol/L. Results: This study showed an average serum sodium value of 135 mmol/L (range 114–159 mmol/L) in these patients. Hyponatremia was observed in 123 patients (43.6%), 115 patients (97,8%) had mild to moderate hyponatremia and 2,8% had severe hyponatremia. The mean age was 65±17 years with a sex ratio of 1.05. The main reason for consultation in patients with hyponatremia was cough in 58 patients (47.2%), and digestive symptoms were present in 25 patients (20.3. An altered state of consciousness was observed in 11 patients (3%). Patients with hyponatremia had greater heart rate (p=0.02),white blood cell count (p=0.009) , plasmatic lactate (p=0.002) and higher rate of pneumonia recurrence (p=0.001) .In addition, 80% of them have a positive CURB65 score (>=2). hyponatremia had higher rates of use of oxygen therapy compared to patients with normo-natremia (54% vs. 45%). The analytical study showed that hyponatremia is significantly associated with intra-hospital mortality with( p=0.01), severe hyponatremia p=0.04. Conclusion: Hyponatremia is a predictor of mortality and worse prognosis. Recognition of the pathophysiological mechanisms of hyponatremia in pneumonia will probably allow better management of it.

Keywords: oxygenotherapy, mortality, recurrence, positif curb65

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

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Authors: Kanmanas Muensak, Somphoom Saweangkun

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The objectives of this research were to study the consumer behavior that affects the customer loyalty of CP Fresh Mart in Bangkok province. The sample of the study comprised 400 consumers over 15 years old who made the purchase through CP Fresh Mart in Bangkok. The questionnaires were used as the data gathering instrument, and the data were analyzed applying Percentage, Mean, Standard Deviation, Independent Sample t-test, Two- Way ANOVA, and Least Significant Difference, and Pearson’s Correlation Coefficient also. The result of hypothesis testing showed that the respondents of different gender, age, level of education, income, marital status and occupation had differences in consumer behavior through customer loyalty of CP Fresh Mart and the factors on customer loyalty in the aspects of re-purchase, word of mouth and price sensitive, promotion, process, and personnel had positive relationship with the consumer behavior through of CP Fresh Mart in Bangkok as well as.

Keywords: consumers in Bangkok, consumer behavior, customer loyalty, CP Fresh Mart, operating budget

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Authors: B. Keawaram, P. Dumrongchai

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The volume of overburden and coal excavations in open-pit mine is generally determined by conventional survey such as total station. This study aimed to evaluate the accuracy of terrestrial laser scanner (TLS) used to measure overburden and coal excavations, and to compare TLS survey data sets with the data of the total station. Results revealed that, the reference points measured with the total station showed 0.2 mm precision for both horizontal and vertical coordinates. When using TLS on the same points, the standard deviations of 4.93 cm and 0.53 cm for horizontal and vertical coordinates, respectively, were achieved. For volume measurements covering the mining areas of 79,844 m², TLS yielded the mean difference of about 1% and the surface error margin of 6 cm at the 95% confidence level when compared to the volume obtained by total station.

Keywords: mine, survey, terrestrial laser scanner, total station

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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: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Sulistyaningtyas

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The topic about death and dying is interesting to discuss since it is strongly related to every individual life. As represented in its title, Adonais: An Elegy on the Death of John Keats is a mournful poem written in 1821 by Percy Bysshe Shelley to mourn the loss of young poet John Keats. To compare, In Memoriam A.H.H. is an elegy written in 1850 about the death of Lord Tennyson’s dearest friend, Arthur Henry Hallam. Although both elegies were written to grieve the authors’ loved ones, their grief affects differently to the psychological being of the narrators. Thus, this research aims to examine the essence of death in affecting the narrators psychologically. By using psychoanalytic criticism, this research reveals the different essence of death in the two elegies as the result of the analysis. Moreover, these two elegies also portray the concept of the afterlife, immortality, and the figure of God. In Adonais, the grief of the narrator to Keats leads him to question the very purpose of life. The loss of his favorite poet which makes him feel sorrowful and mad along his 55 stanzas brings him to a higher psychological level to understand himself. He even sees himself as a Christ-like figure, which shows the idea that God is imaginable. Different from Adonais, the narrator of In Memoriam finds something more spiritual by doing his passionate mourning to Hallam. Through some contemplation in his 133 cantos, in the end, he is convinced that the dear one now dwells with a great Spirit who controls the world. He believes that all of the creation in the universe has to follow one law which is set by God. Hence, it can be concluded that death might bring different consequence to the psyche of every living creature.

Keywords: elegy, comparative study, psychoanalytic criticism, the essence of death

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Authors: Kang-Hyun Leem, Myung-Gyou Kim, Hye Kyung Kim

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Deer antler, traditionally used as a tonic and valuable drug in oriental medicine, has been considered to possess bone-strengthening activity. The upper section, mid section, and base of the antler has been known to exhibit different biological properties. Present study was performed to examine the effects of different parts of deer antler extract (DH) on osteogenic gene expressions in MG-63 cells and longitudinal bone growth in adolescent male rats. The expressions of osteogenic genes, collagen, alkaline phosphatase, osteocalcin, and osteopontin, were measured by quantitative real-time PCR. Longitudinal bone growth was measured in 3-week-old male Sprague-Dawley rats using fluorescence microscopy. To examine the effects on the growth plate metabolism, the total height of growth plate and bone morphogenetic protein-2 (BMP-2) were measured. Collagen and osteocalcin mRNA expressions were increased by all three parts of the DH treatment while osteopontin gene expression was not affected by any of the DH treatment. Alkaline phosphatase gene expression was increased by upper and mid part of DH while base part of DH fails to affect alkaline phosphatase gene expression. The upper and mid parts of the DH treatment enhanced longitudinal bone growth and total height of growth plate. The induction of BMP-2 protein expression in growth plate assessed by immunostaining was also promoted by upper and mid parts of the DH treatment. These results suggest that DH, especially upper and mid parts, stimulate osteogenic gene expressions and have the effect on bone growth in adolescent rats and might be used for the growth delayed adolescent and inherent growth failure patient.

Keywords: bone morphogenetic protein-2, deer antler, longitudinal bone growth, osteogenic genes

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Authors: Oluwatofunmi Musa-Ajakaiye, Paul Olorunfemi M.D MPH, John Obafaiye

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Introduction: The U.S Food and Drug Administration (FDA) reports the public notices for recalled FDA-regulated products over periods of time. It study reviewed the primary reasons for recalls of products of various types over a period of 7 years. Methods: The study analyzed data provided in the FDA’s archived recalls for the years 2010-2017. It identified the various reasons for product recalls in the categories of foods, beverages, drugs, medical devices, animal and veterinary products, and dietary supplements. Using SPSS version 29, descriptive statistics and chi-square analysis of the data were performed. Results (numbers, percentages, p-values, chi-square): Over the period of analysis, a total of 931 recalls were reported. The most frequent reason for recalls was undeclared products (36.7%). The analysis showed that the most recalled product type in the data set was foods and beverages, representing 591 of all recalled products (63.5%).In addition, it was observed that foods and beverages represent 77.2% of products recalled due to the presence of microorganisms. Also, a sub-group analysis of recall reasons of food and beverages found that the most prevalent reason for such recalls was undeclared products (50.1%) followed by Listeria (17.3%) then Salmonella (13.2%). Conclusion: This analysis shows that foods and beverages have the greatest percentages of total recalls due to the presence of undeclared products listeria contamination and Salmonella contamination. The prevalence of Salmonella and Listeria contamination suggests that there is a high risk of microbial contamination in FDA-approved products and further studies on the effects of such contamination must be conducted to ensure consumer safety.

Keywords: food, beverages, listeria, salmonella, FDA, contamination, microbial

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Authors: Brigitte Wabuyabo-Okonga

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Little research has been done to establish the level of success of Coca Cola Company in recycling and reusing their glass bottles. This paper attempts to establish retail managers’ perception of the company’s self acclaimed success. Retail managers of supermarkets in the CBD of Nairobi, Kenya were considered for the study. Data were collected through questionnaires and analyzed using descriptive (mean, frequencies and percentages) and inferential statistics (correlation analysis) were used to analyze the data. The study found out that there is relative success although a lot needs to be done. For example, improving in communicating policy issues and in practice enhance the actual collection of broken and/or non-broken Coca Cola Company glass bottles through providing drop-off points in open areas such as on the streets and in parks.

Keywords: Coca Cola Company glass bottles, Kenya, Nairobi, packaging, retail manager

Procedia PDF Downloads 310

Authors: Conor Mccartney, Mark Lee

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Background: An essential component in ambulatory breast augmentation surgery is good analgesia. The demographic undergoing this operation is usually fit, low risk with few comorbidities. These patients do not require long-term hospitalization and do not want to spend excessive time in the hospital for financial reasons. Opiate analgesia can have significant side effects such as nausea, vomiting and sedation. Reducing volumes of postoperative opiates allows faster ambulation and discharge from day surgery. We have developed two targeted nerve blocks that can be applied by the operating surgeon in a matter of seconds under direct vision, not requiring imaging. Anecdotally we found that these targeted nerve blocks reduced opiate requirements and allowed accelerated discharge and faster return to normal activities. This was then tested in a prospective randomized, double-blind trial. Methods: 20 patients were randomized into saline (n = 10) or Ropivicaine adrenaline solution (n = 10). The operating surgeon and anesthetist were blinded to the solution. All patients were closely followed up and morphine equivalents were accurately recorded. Follow-up pain scores were recorded using the Overall Benefit of Analgesia pain questionnaire. Findings: The Ropivicaine nerve blocks significantly reduced opiate requirements postoperatively (p<0.05). Pain scores were significantly decreased in the study group (p<0.05). There were no side effects attributable to the nerve blocks. Conclusions: Intraoperative targeted nerve blocks significantly reduce postoperative opiate requirements in breast augmentation surgery. This results in faster recovery and higher patient satisfaction.

Keywords: breast augmentation, nerve block, postoperative recovery, opiate analgesia, inter pectoral block, sub serratus block

Procedia PDF Downloads 126

Authors: Gae Hee Song

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This paper aims to address the evolution of public-private partnerships for mainstreaming an evaluation approach in the community-based education project. It examines the distinctive features of Save the Children’s School Me project in terms of empowerment evaluation principles introduced by David M. Fetterman, especially community ownership, capacity building, and organizational learning. School Me is a Save the Children Korea funded-project, having been implemented in Cote d’Ivoire and Sierra Leone since 2016. The objective of this project is to reduce gender-based disparities in school completion and learning outcomes by creating an empowering learning environment for girls and boys. Both quasi-experimental and experimental methods for impact evaluation have been used to explore changes in learning outcomes, gender attitudes, and learning environments. To locate School Me in the public-private partnership framework for community empowerment and sustainability, the data have been collected from School Me progress/final reports, baseline, and endline reports, fieldwork observations, inter-rater reliability of baseline and endline data collected from a total of 75 schools in Cote d’Ivoire and Sierra Leone. The findings of this study show that School Me project has a significant evaluation component, including qualitative exploratory research, participatory monitoring, and impact evaluation. It strongly encourages key actors, girls, boys, parents, teachers, community leaders, and local education authorities, to participate in the collection and interpretation of data. For example, 45 community volunteers collected baseline data in Cote d’Ivoire; on the other hand, three local government officers and fourteen enumerators participated in the follow-up data collection of Sierra Leone. Not only does this public-private partnership improve local government and community members’ knowledge and skills of monitoring and evaluation, but the evaluative findings also help them find their own problems and solutions with a strong sense of community ownership. Such community empowerment enables Save the Children country offices and member offices to gain invaluable experiences and lessons learned. As a result, empowerment evaluation leads to community-oriented governance and the sustainability of the School Me project.

Keywords: community empowerment, Cote d’Ivoire, empowerment evaluation, public-private partnership, save the children, school me, Sierra Leone, sustainability

Procedia PDF Downloads 119

Authors: Aarushi Agarwal, Tara Singh, I.L Singh, Anju Lata Singh, Trayambak Tiwari

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Simple discrimination in near absence of attention has been widely observed. Dual-task studies with natural scenes studies have been claimed as being preattentive in nature that facilitated categorization simultaneously with the attentional demanding task. So in this study, multiple images at the periphery are presented, initiating parallel processing in near absence of attention. For the central demanding task rotated letters were presented in both conditions, while in periphery natural and animal images were presented. To understand the breakpoint of ability to perform in near absence of attention one, two and three peripheral images were presented simultaneously with central task and subjects had to respond when all belong to the same category. Individual participant performance did not show a significant difference in both conditions central and peripheral task when the single peripheral image was shown. In case of two images high-level parallel processing could take place with little attentional resources. The eye tracking results supports the evidence as no major saccade was made in a large number of trials. Three image presentations proved to be a breaking point of the capacities to perform outside attentional assistance as participants showed a confused eye gaze pattern which failed to make the natural and animal image discriminations. Thus, we can conclude attention and awareness being independent mechanisms having limited capacities.

Keywords: attention, dual task pardigm, parallel processing, break point, saccade

Procedia PDF Downloads 212

Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

Procedia PDF Downloads 171

Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari

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H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.

Keywords: Google Scholar, H-index, Scopus, performance indicator

Procedia PDF Downloads 265

Authors: Chia-li Wang

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The surge of service and commerce platforms, such as e-commerce and internet-of-things, have rapidly changed our lives. How to avoid the congestion and get the job done in the platform is now a common problem that many people encounter every day. This requires platform users to make decisions about when to enter the platform. To that end, we investigate the strategic entering time of a simple platform containing random numbers of buyers and sellers of some item. Upon a trade, the buyer and the seller gain respective profits, yet they pay the cost of waiting in the platform. To maximize their expected payoffs from trading, both buyers and sellers can choose their entering times. This creates an interesting and practical framework of a game that is played among buyers, among sellers, and between them. That is, a strategy employed by a player is not only against players of its type but also a response to those of the other type, and, thus, a strategy profile is composed of strategies of buyers and sellers. The players' best response, the Nash equilibrium (NE) strategy profile, is derived by a pair of differential equations, which, in turn, are used to establish its existence and uniqueness. More importantly, its structure sheds valuable insights of how the entering strategy of one side (buyers or sellers) is affected by the entering behavior of the other side. These results provide a base for the study of dynamic pricing for stochastic demand-supply imbalances. Finally, comparisons between the social welfares (the sum of the payoffs incurred by individual participants) obtained by the optimal strategy and by the NE strategy are conducted for showing the efficiency loss relative to the socially optimal solution. That should help to manage the platform better.

Keywords: double-sided queue, non-cooperative game, nash equilibrium, price of anarchy

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Authors: Maria Gabrielle "Abby" Dalmacio

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Social-emotional learning is a concept that is garnering more importance when considering the development of young children. The aim of this scoping literature review is to explore the implementation of social-emotional learning programs conducted with first-generation immigrant young children ages 3-12 years in North America. This review of literature focuses on social-emotional learning programs taking place in early childhood education centres and elementary school settings that include the first-generation immigrant children population to determine if and how their understanding of social-emotional learning skills may be impacted by the curriculum being taught through North American educational pedagogy. Research on early childhood education and social-emotional learning reveals the lack of inter-cultural adaptability in social emotional learning programs and the potential for immigrant children as being assessed as developmentally delayed due to programs being conducted through standardized North American curricula. The results of this review point to a need for more research to be conducted with first-generation immigrant children to help reform social-emotional learning programs to be conducive for each child’s individual development. There remains to be a gap of knowledge in the current literature on social-emotional learning programs and how educators can effectively incorporate the intercultural perspectives of first-generation immigrant children in early childhood education.

Keywords: early childhood education, social-emotional learning, first-generation immigrant children, north america, inter-cultural perspectives, cultural diversity, early educational frameworks

Procedia PDF Downloads 90

Authors: Abu Zafor Sadek

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Pharmaceuticals were one of the least impacted business sectors during the corona pandemic as they are the center point of Covid-19 fight. Emergency use authorization, unproven indication of some commonly used drugs, self-medication, research and production capacity of an individual country, capacity of producing vaccine by many countries, Active Pharmaceutical Ingredients (APIs) related uncertainty, information gap among manufacturer, practitioners and user, export restriction, duration of lock-down, lack of harmony in transportation, disruption in the regulatory approval process, sudden increased demand of hospital items and protective equipment, panic buying, difficulties in in-person product promotion, e-prescription, geo-politics and associated issues added a new dimension to this industry. Although the industry maintains a reasonable growth throughout Covid-19 days; however, it has been characterized by both long- and short-term effects. Short-term effects have already been visible to so many countries, especially those who are import-dependent and have limited research capacity. On the other hand, it will take a few more time to see the long-term effects. Nevertheless, supply chain disruption, changes in strategic planning, new communication model, squeezing of job opportunity, rapid digitalization are the major short-term effects, whereas long-term effects include a shift towards self-sufficiency, growth pattern changes of certain products, special attention towards clinical studies, automation in operations, the increased arena of ethical issues etc. Therefore, this qualitative and exploratory study identifies the post-covid-19 landscape of the global pharmaceutical industry.

Keywords: covid-19, pharmaceutical, businees, landscape

Procedia PDF Downloads 89

Authors: Bahram Khan, Anderson Rocha Ramos, Rui R. Paulo, Fernando J. Velez

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With the growing demand for a new blend of applications, the users dependency on the internet is increasing day by day. Mobile internet users are giving more attention to their own experiences, especially in terms of communication reliability, high data rates and service stability on move. This increase in the demand is causing saturation of existing radio frequency bands. To address these challenges, researchers are investigating the best approaches, Carrier Aggregation (CA) is one of the newest innovations, which seems to fulfill the demands of the future spectrum, also CA is one the most important feature for Long Term Evolution - Advanced (LTE-Advanced). For this purpose to get the upcoming International Mobile Telecommunication Advanced (IMT-Advanced) mobile requirements (1 Gb/s peak data rate), the CA scheme is presented by 3GPP, which would sustain a high data rate using widespread frequency bandwidth up to 100 MHz. Technical issues such as aggregation structure, its implementations, deployment scenarios, control signal techniques, and challenges for CA technique in LTE-Advanced, with consideration of backward compatibility, are highlighted in this paper. Also, performance evaluation in macro-cellular scenarios through a simulation approach is presented, which shows the benefits of applying CA, low-complexity multi-band schedulers in service quality, system capacity enhancement and concluded that enhanced multi-band scheduler is less complex than the general multi-band scheduler, which performs better for a cell radius longer than 1800 m (and a PLR threshold of 2%).

Keywords: component carrier, carrier aggregation, LTE-advanced, scheduling

Procedia PDF Downloads 193