Search results for: multi-/trans-generation

Authors: D. Supaporn, B. Julaluk

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The purposes of this study were to study symptom cluster, functional status and quality of life of patients with chronic obstructive pulmonary disease (COPD), and to examine factors related to and predicting symptom cluster, functional status and quality of life of COPD patients. The sample was 180 COPD patients multi-stage random sampling from 4 hospitals in the eastern region, Thailand. The research instruments were 8 questionnaires and recorded forms measuring personal and illness data, co-morbidity, physical and psychological symptom, health status perception, social support, and regimen adherence, functional status and quality of life. Spearman rank and Pearson correlation coefficient, exploratory factors analysis and standard multiple regression were used to analyzed data. The findings revealed that two symptom clusters were generated: physical symptom cluster including dyspnea, fatigue and insomnia; and, psychological symptom cluster including anxiety and depression. Scores of physical symptom cluster was at moderate level while that of psychological symptom cluster was at low level. Scores on functional status, social support and overall regimen adherence were at good level whereas scores on quality of life and health status perception were at moderate level. Disease severity was positively related to physical symptom cluster, psychological symptom cluster and quality of life, and was negatively related to functional status at a moderate level (rs = .512, .509, .588 and -.611, respectively). Co-morbidity was positively related to physical symptom cluster and psychological symptom cluster at a low level (r = .179 and .176, respectively). Regimen adherence was negatively related to quality of life and psychological symptom cluster at a low level (r=-.277 and -.309, respectively), and was positively related to functional status at a moderate level (r=.331). Health status perception was negatively related to physical symptom cluster, psychological symptom cluster and quality of life at a moderate to high level (r = -.567, -.640 and -.721, respectively) and was positively related to functional status at a high level (r = .732). Social support was positively related to functional status (r=.235) and was negatively related to quality of life at a low level (r=-.178). Physical symptom cluster was negatively related to functional status (r= -.490) and was positively related to quality of life at a moderate level (r=.566). Psychological symptom cluster was negatively related to functional status and was positively related to quality of life at a moderate level (r= -.566 and .559, respectively). Disease severity, co-morbidity and health status perception could predict 40.2% of the variance of physical symptom cluster. Disease severity, co-morbidity, regimen adherence and health status perception could predict 49.8% of the variance of psychological symptom cluster. Co-morbidity, regimen adherence and health status perception could predict 65.0% of the variance of functional status. Disease severity, health status perception and physical symptom cluster could predict 60.0% of the variance of quality of life in COPD patients. The results of this study can be used for enhancing quality of life of COPD patients.

Keywords: chronic obstructive pulmonary disease, functional status, quality of life, symptom cluster

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Authors: Amir Gharavi, Mohamed Hassan, Amjad Shah

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The main characteristics of unconventional reservoirs include low-to ultra low permeability and low-to-moderate porosity. As a result, hydrocarbon production from these reservoirs requires different extraction technologies than from conventional resources. An unconventional reservoir must be stimulated to produce hydrocarbons at an acceptable flow rate to recover commercial quantities of hydrocarbons. Permeability for unconventional reservoirs is mostly below 0.1 mD, and reservoirs with permeability above 0.1 mD are generally considered to be conventional. The hydrocarbon held in these formations naturally will not move towards producing wells at economic rates without aid from hydraulic fracturing which is the only technique to assess these tight reservoir productions. Horizontal well with multi-stage fracking is the key technique to maximize stimulated reservoir volume and achieve commercial production. The main objective of this research paper is to investigate development options for a tight mature oilfield. This includes multistage hydraulic fracturing and spacing by building of reservoir models in the Reveal simulator to model potential development options based on sidetracking the existing vertical well. To simulate potential options, reservoir models have been built in the Reveal. An existing Petrel geological model was used to build the static parts of these models. A FBHP limit of 40bars was assumed to take into account pump operating limits and to maintain the reservoir pressure above the bubble point. 300m, 600m and 900m lateral length wells were modelled, in conjunction with 4, 6 and 8 stages of fracs. Simulation results indicate that higher initial recoveries and peak oil rates are obtained with longer well lengths and also with more fracs and spacing. For a 25year forecast, the ultimate recovery ranging from 0.4% to 2.56% for 300m and 1000m laterals respectively. The 900m lateral with 8 fracs 100m spacing gave the highest peak rate of 120m3/day, with the 600m and 300m cases giving initial peak rates of 110m3/day. Similarly, recovery factor for the 900m lateral with 8 fracs and 100m spacing was the highest at 2.65% after 25 years. The corresponding values for the 300m and 600m laterals were 2.37% and 2.42%. Therefore, the study suggests that longer laterals with 8 fracs and 100m spacing provided the optimal recovery, and this design is recommended as the basis for further study.

Keywords: unconventional, resource, hydraulic, fracturing

Procedia PDF Downloads 281

Authors: Tessa Sellis, Marike A. Wierda, Elke Tichelman, Mirjam T. Van Lohuizen, Marjolein Berger, François Schellevis, Claudi Bockting, Lilian Peters, Huib Burger

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Introduction: Most women develop a healthy bond with their children, however, adequate mother-to-infant bonding cannot be taken for granted. Mother-to-infant bonding refers to the feelings and emotions experienced by the mother towards her child. It is an ongoing process that starts during pregnancy and develops during the first year postpartum and likely throughout early childhood. The prevalence of inadequate bonding ranges from 7 to 11% in the first weeks postpartum. An impaired mother-to-infant bond can cause long-term complications for both mother and child. Very little research has been conducted on the direct relationship between the personality of the mother and mother-to-infant bonding. This study explores the associations between maternal personality and postnatal mother-to-infant bonding. The main hypothesis is that there is a relationship between neuroticism and mother-to-infant bonding. Methods: Data for this study were used from the Pregnancy Anxiety and Depression Study (2010-2014), which examined symptoms of and risk factors for anxiety or depression during pregnancy and the first year postpartum of 6220 pregnant women who received primary, secondary or tertiary care in the Netherlands. The study was expanded in 2015 to investigate postnatal mother-to-infant bonding. For the current research 3836 participants were included. During the first trimester of gestation, baseline characteristics, as well as personality, were measured through online questionnaires. Personality was measured by the NEO Five Factor Inventory (NEO-FFI), which covers the big five of personality (neuroticism, extraversion, openness, altruism and conscientiousness). Mother-to-infant bonding was measured postpartum by the Postpartum Bonding Questionnaire (PBQ). Univariate linear regression analysis was performed to estimate the associations. Results: 5% of the PBQ-respondents reported impaired bonding. A statistically significant association was found between neuroticism and mother-to-infant bonding (p < .001): mothers scoring higher on neuroticism, reported a lower score on mother-to-infant bonding. In addition, a positive correlation was found between the personality traits extraversion (b: -.081), openness (b: -.014), altruism (b: -.067), conscientiousness (b: -.060) and mother-to-infant bonding. Discussion: This study is one of the first to demonstrate a direct association between the personality of the mother and mother-to-infant bonding. A statistically significant relationship has been found between neuroticism and mother-to-infant bonding, however, the percentage of variance predictable by a personality dimension is very small. This study has examined one part of the multi-factorial topic of mother-to-infant bonding and offers more insight into the rarely investigated and complex matter of mother-to-infant bonding. For midwives, it is important recognize the risks for impaired bonding and subsequently improve policy for women at risk.

Keywords: mother-to-infant bonding, personality, postpartum, pregnancy

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Authors: I. Yilmaz, O. Taga, F. Kosar, O. Keles

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In this study, friction and damping coefficients of folded cover mechanism were obtained in accordance with experimental studies and data. Friction and damping coefficients are the most important inputs to accomplish a mechanism analysis. Friction and damping are two objects that change the time of deployment of mechanisms and their dynamic behaviors. Though recommended friction coefficient values exist in literature, damping is differentiating feature according to mechanic systems. So the damping coefficient should be obtained from mechanism test outputs. In this study, the folded cover mechanism use torsion springs for deploying covers that are formerly close folded position. Torsion springs provide folded covers with desirable deploying time according to variable environmental conditions. To verify all design revisions with system tests will be so costly so that some decisions are taken in accordance with numerical methods. In this study, there are two folded covers required to deploy simultaneously. Scotch-yoke and crank-rod mechanisms were combined to deploy folded covers simultaneously. The mechanism was unlocked with a pyrotechnic bolt onto scotch-yoke disc. When pyrotechnic bolt was exploded, torsion springs provided rotational movement for mechanism. Quick motion camera was recording dynamic behaviors of system during deployment case. Dynamic model of mechanism was modeled as rigid body with Adams MBD (multi body dynamics) then torque values provided by torsion springs were used as an input. A well-advised range of friction and damping coefficients were defined in Adams DOE (design of experiment) then a large number of analyses were performed until deployment time of folded covers run in with test data observed in record of quick motion camera, thus the deployment time of mechanism and dynamic behaviors were obtained. Same mechanism was tested with different torsion springs and torque values then outputs were compared with numerical models. According to comparison, it was understood that friction and damping coefficients obtained in this study can be used safely when studying on folded objects required to deploy simultaneously. In addition to model generated with Adams as rigid body the finite element model of folded mechanism was generated with Abaqus then the outputs of rigid body model and finite element model was compared. Finally, the reasonable solutions were suggested about different outputs of these solution methods.

Keywords: damping, friction, pyro-technic, scotch-yoke

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Gail Louw, Helena Boshoff, Taeksun Song, Clifton Barry

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Drug resistance in Mycobacterium tuberculosis is primarily attributed to mutations in target genes. These mutations incur a fitness cost and result in bacterial generations that are less fit, which subsequently acquire compensatory mutations to restore fitness. We hypothesize that mutations in specific drug target genes influence bacterial metabolism and cellular function, which affects its ability to develop subsequent resistance to additional agents. We aim to determine whether the sequential acquisition of drug resistance and specific mutations in a well-defined clinical M. tuberculosis strain promotes or limits the development of additional resistance. In vitro mutants resistant to pretomanid, linezolid, moxifloxacin, rifampicin and kanamycin were generated from a pan-susceptible clinical strain from the Beijing lineage. The resistant phenotypes to the anti-TB agents were confirmed by the broth microdilution assay and genetic mutations were identified by targeted gene sequencing. Growth of mono-resistant mutants was done in enriched medium for 14 days to assess in vitro fitness. Double resistant mutants were generated against anti-TB drug combinations at concentrations 5x and 10x the minimum inhibitory concentration. Subsequently, mutation frequencies for these anti-TB drugs in the different mono-resistant backgrounds were determined. The initial level of resistance and the mutation frequencies observed for the mono-resistant mutants were comparable to those previously reported. Targeted gene sequencing revealed the presence of known and clinically relevant mutations in the mutants resistant to linezolid, rifampicin, kanamycin and moxifloxacin. Significant growth defects were observed for mutants grown under in vitro conditions compared to the sensitive progenitor. Mutation frequencies determination in the mono-resistant mutants revealed a significant increase in mutation frequency against rifampicin and kanamycin, but a significant decrease in mutation frequency against linezolid and sutezolid. This suggests that these mono-resistant mutants are more prone to develop resistance to rifampicin and kanamycin, but less prone to develop resistance against linezolid and sutezolid. Even though kanamycin and linezolid both inhibit protein synthesis, these compounds target different subunits of the ribosome, thereby leading to different outcomes in terms of fitness in the mutants with impaired cellular function. These observations showed that oxazolidinone treatment is instrumental in limiting the development of multi-drug resistance in M. tuberculosis in vitro.

Keywords: oxazolidinones, mutations, resistance, tuberculosis

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Authors: Rio Hirakawa, Christian Gundlach, Sven Hartwig

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In recent years, the use of aluminium has further expanded and is expected to replace steel in the future as vehicles become lighter and more recyclable in order to reduce greenhouse gas (GHG) emissions and improve fuel economy. In line with this, structures and components are becoming increasingly multi-material, with different materials, including aluminium, being used in combination to improve mechanical utility and performance. A common method of assembling dissimilar materials is mechanical fastening, but it has several drawbacks, such as increased manufacturing processes and the influence of substrate-specific mechanical properties. Adhesive bonding and fusion bonding are methods that overcome the above disadvantages. In these two joining methods, surface pre-treatment of the substrate is always necessary to ensure the strength and durability of the joint. Previous studies have shown that laser surface treatment improves the strength and durability of the joint. Yan et al. showed that laser surface treatment of aluminium alloys changes α-Al2O3 in the oxide layer to γ-Al2O3. As γ-Al2O3 has a large specific surface area, is very porous and chemically active, laser-treated aluminium surfaces are expected to undergo physico-chemical changes over time and adsorb moisture and organic substances from the air or storage atmosphere. The impurities accumulated on the laser-treated surface may be released at the adhesive and bonding interface by the heat input to the bonding system during the joining phase, affecting the strength and durability of the joint. However, only a few studies have discussed the effect of such storage periods on laser-treated surfaces. This paper, therefore, investigates the ageing of laser-treated aluminium alloy surfaces through thermal analysis, electrochemical analysis and microstructural observations.AlMg3 of 0.5 mm and 1.5 mm thickness was cut using a water-jet cutting machine, cleaned and degreased with isopropanol and surface pre-treated with a pulsed fibre laser at 1060 nm wavelength, 70 W maximum power and 55 kHz repetition frequency. The aluminium surface was then analysed using SEM, thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and cyclic voltammetry (CV) after storage in air for various periods ranging from one day to several months TGA and FTIR analysed impurities adsorbed on the aluminium surface, while CV revealed changes in the true electrochemically active surface area. SEM also revealed visual changes on the treated surface. In summary, the changes in the laser-treated aluminium surface with storage time were investigated, and the final results were used to determine the appropriate storage period.

Keywords: laser surface treatment, pre-treatment, adhesion, bonding, corrosion, durability, dissimilar material interface, automotive, aluminium alloys

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Authors: Irene Kretchy, Frances Owusu-Daaku, Samuel Danquah

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Hypertension is the leading risk factor for cardiovascular diseases, and a major cause of death and disability worldwide. This study examined whether psychosocial variables influenced patients’ perception and experience of side effects of their medicines, how they coped with these experiences and the impact on mental health and medication adherence to conventional hypertension therapies. Methods: A hospital-based mixed methods study, using quantitative and qualitative approaches was conducted on hypertensive patients. Participants were asked about side effects, medication adherence, common psychological symptoms, and coping mechanisms with the aid of standard questionnaires. Information from the quantitative phase was analyzed with the Statistical Package for Social Sciences (SPSS) version 20. The interviews from the qualitative study were audio-taped with a digital audio recorder, manually transcribed and analyzed using thematic content analysis. The themes originated from participant interviews a posteriori. Results: The experiences of side effects – such as palpitations, frequent urination, recurrent bouts of hunger, erectile dysfunction, dizziness, cough, physical exhaustion - were categorized as no/low (39.75%), moderate (53.0%) and high (7.25%). Significant relationships between depression (x 2 = 24.21, P < 0.0001), anxiety (x 2 = 42.33, P < 0.0001), stress (x 2 = 39.73, P < 0.0001) and side effects were observed. A logistic regression model using the adjusted results for this association are reported – depression [OR = 1.9 (1.03 – 3.57), p = 0.04], anxiety [OR = 1.5 (1.22 – 1.77), p = < 0.001], and stress [OR = 1.3 (1.02 – 1.71), p = 0.04]. Side effects significantly increased the probability of individuals to be non-adherent [OR = 4.84 (95% CI 1.07 – 1.85), p = 0.04] with social factors, media influences and attitudes of primary caregivers further explaining this relationship. The personal adoption of medication modifying strategies, espousing the use of complementary and alternative treatments, and interventions made by clinicians were the main forms of coping with side effects. Conclusions: Results from this study show that contrary to a biomedical approach, the experience of side effects has biological, social and psychological interrelations. The result offers more support for the need for a multi-disciplinary approach to healthcare where all forms of expertise are incorporated into health provision and patient care. Additionally, medication side effects should be considered as a possible cause of non-adherence among hypertensive patients, thus addressing this problem from a Biopsychosocial perspective in any intervention may improve adherence and invariably control blood pressure.

Keywords: biopsychosocial, hypertension, medication adherence, psychological disorders

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Samantha J. Hall, Luke Taylor, Kenneth I. Cumming, Jakki Bardsley, Scott S. P. Wildman

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Medway School of Pharmacy – a joint collaboration between the University of Kent and the University of Greenwich – is a large school of pharmacy in the United Kingdom. The school primarily delivers the accredited Master or Pharmacy (MPharm) degree programme. Reportedly, some students may feel isolated from the larger student body that extends across four separate campuses, where a diverse range of academic subjects is delivered. In addition, student engagement has been noted as being limited in some areas, as evidenced in some cases by poor attendance at some lectures. In January 2015, the University of Kent launched a new initiative dedicated to Equality, Diversity and Inclusivity (EDI). As part of this project, Medway School of Pharmacy employed ‘Student Success Project Officers’ in order to analyse past and present school data. As a result, initiatives have been implemented to i) negate disparities in attainment and ii) increase engagement, particularly for Black, Asian and Minority Ethnic (BAME) students which make up for more than 80% of the pharmacy student cohort. Social media platforms are prevalent, with global statistics suggesting that they are most commonly used by females between the ages of 16-34. Student focus groups held throughout the academic year brought to light the school’s need to use social media much more actively. Prior to the EDI initiative, social media usage for Medway School of Pharmacy was scarce. Platforms including: Facebook, Twitter, Instagram, YouTube, The Student Room and University Blogs were either introduced or rejuvenated. This action was taken with the primary aim of increasing student engagement. By using a number of varied social media platforms, the university is able to capture a large range of students by appealing to different interests. Social media is being used to disseminate important information, promote equality and diversity, recognise and celebrate student success and also to allow students to explore the student life outside of Medway School of Pharmacy. Early data suggests an increase in lecture attendance, as well as greater evidence of student engagement highlighted by recent focus group discussions. In addition, students have communicated that active social media accounts were imperative when choosing universities for 2015/16. It allows students to understand more about the University and community prior to beginning their studies. By having a lively presence on social media, the university can use a multi-faceted approach to succeed in early engagement, as well as fostering the long term engagement of continuing students.

Keywords: engagement, social media, pharmacy, community

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Authors: Sanjay Shukla

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Excessive use of antibiotics is a main problem in the treatment of wounds and other chronic infections and antibiotic treatment is frequently non-curative, thus alternative treatment is necessary. Phage therapy is considered one of the most effective approaches to treat multi-drug resistant bacterial pathogens. Infections caused by Staphylococcus aureus are very efficiently controlled with phage cocktails, containing a different individual phages lysate infecting a majority of known pathogenic S. aureus strains. The aim of current study was to investigate the efficiency of a purified phage cocktail for prophylactic as well as therapeutic application in mouse model and in large animals with chronic septic infection of wounds. A total of 150 sewage samples were collected from various livestock farms. These samples were subjected for the isolation of bacteriophage by double agar layer method. A total of 27 sewage samples showed plaque formation by producing lytic activity against S. aureus in double agar overlay method out of 150 sewage samples. In TEM recovered isolates of bacteriophages showed hexagonal structure with tail fiber. In the bacteriophage (ØVS) had an icosahedral symmetry with the head size 52.20 nm in diameter and long tail of 109 nm. Head and tail were held together by connector and can be classified as a member of the Myoviridae family under the order of Caudovirale. Recovered bacteriophage had shown the antibacterial activity against the S. aureus in vitro. Cocktail (ØVS1, ØVS5, ØVS9 and ØVS 27) of phage lysate were tested to know in vivo antibacterial activity as well as the safety profile. Result of mice experiment indicated that the bacteriophage lysate was very safe, did not show any appearance of abscess formation which indicates its safety in living system. The mice were also prophylactically protected against S. aureus when administered with cocktail of bacteriophage lysate just before the administration of S. aureus which indicates that they are good prophylactic agent. The S. aureus inoculated mice were completely recovered by bacteriophage administration with 100% recovery which was very good as compere to conventional therapy. In present study ten chronic cases of wound were treated with phage lysate and follow up of these cases was done regularly up to ten days (at 0, 5 and 10 d). Result indicated that the six cases out of ten showed complete recovery of wounds within 10 d. The efficacy of bacteriophage therapy was found to be 60% which was very good as compared to the conventional antibiotic therapy in chronic septic wounds infections. Thus, the application of lytic phage in single dose proved to be innovative and effective therapy for treatment of septic chronic wounds.

Keywords: phage therapy, phage lysate, antimicrobial resistance, S. aureus

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Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

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In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring

Procedia PDF Downloads 212

Authors: Gabriela Kalcikova, Gregor Marolt, Anita Jemec Kokalj, Andreja Zgajnar Gotvajn

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Since the 90’s, nanotechnology is one of the fastest growing fields of science. Nanomaterials are increasingly becoming part of many products and technologies. Metal oxide nanoparticles are among the most used nanomaterials. Zinc oxide nanoparticles (nZnO) is widely used due to its versatile properties; it has been used in products including plastics, paints, food, batteries, solar cells and cosmetic products. It is also a very effective photocatalyst used for water treatment. Such expanding application of nZnO increases their possible occurrence in the environment. In the aquatic ecosystem nZnO interact with natural environmental factors such as UV radiation, and thus it is essential to evaluate possible interaction between them. In this context, the aim of our study was to evaluate combined ecotoxicity of nZnO and Zn²⁺ on duckweed Lemna minor in presence or absence UV. Inhibition of vegetative growth of duckweed Lemna minor was monitored over a period of 7 days in multi-well plates. After the experiment, specific growth rate was determined. ZnO nanoparticles used were of primary size 13.6 ± 1.7 nm. The test was conducted with nominal nZnO and Zn²⁺ (in form of ZnCl₂) concentrations of 1, 10, 100 mg/L. Experiment was repeated with presence of natural intensity of UV (8h UV, 10 W/m² UVA, 0.5 W/m² UVB). Concentration of Zn during the test was determined by ICP-MS. In the regular experiment (absence of UV) the specific growth rate was slightly increased by low concentrations of nZnO and Zn²⁺ in comparison to control. However, 10 and 100 mg/L of Zn²⁺ resulted in 45% and 68% inhibition of the specific growth rate, respectively. In case of nZnO both concentrations (10 and 100 mg/L) resulted in similar ~ 30% inhibition and the response was not dose-dependent. The lack of the dose-response relationship is often observed in case of nanoparticles. The possible explanation is that the physical impact prevails instead of chemical ones. In the presence of UV the toxicity of Zn²⁺ was increased and 100 mg/L of Zn²⁺ caused total inhibition of the specific growth rate (100%). On the other hand, 100 mg/L of nZnO resulted in low inhibition (19%) in comparison to the experiment without UV (30%). It is thus expected, that tested nZnO is low photoactive, but could have a good UV absorption and/or reflective properties and thus protect duckweed against UV impacts. Measured concentration of Zn in the test suspension decreased only about 4% after 168h in the case of ZnCl₂. On the other hand concentration of Zn in nZnO test decreased by 80%. It is expected that nZnO were partially dissolved in the medium and at the same time agglomeration and sedimentation of particles took place and thus the concentration of Zn at the water level decreased. Results of our study indicated, that nZnO combined with UV of natural intensity does not increase toxicity of nZnO, but slightly protect the plant against UV negative effects. When Zn²⁺ and ZnO results are compared it seems that dissolved Zn plays a central role in the nZnO toxicity.

Keywords: duckweed, environmental factors, nanoparticles, toxicity

Procedia PDF Downloads 312

Authors: Jesus Salmeron, Carmen De Vega, Maria Soledad Vicente, Mireia Olabarria, Olaia Martinez

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Dysphagia or difficulty in swallowing affects mostly elder people: 56-78% of the institutionalized and 44% of the hospitalized. Liquid food thickening is a necessary measure in this situation because it reduces the risk of penetration-aspiration. Until now, and as proposed by the American Dietetic Association in 2002, possible consistencies have been categorized in three groups attending to their viscosity: nectar (50-350 mPa•s), honey (350-1750 mPa•s) and pudding (>1750 mPa•s). The adequate viscosity level should be identified for every patient, according to her/his impairment. Nevertheless, a systematic review on dysphagia diet performed recently indicated that there is no evidence to suggest that there is any transition of clinical relevance between the three levels proposed. It was also stated that other physical properties of the bolus (slipperiness, density or cohesiveness, among others) could influence swallowing in affected patients and could contribute to the amount of remaining residue. Texture parameters need to be evaluated as possible alternative to viscosity. The aim of this study was to evaluate the instrumental extrusion-compression test as a possible tool to characterize changes along time in water thickened with various products and in the three theoretical consistencies. Six commercial thickeners were used: NM® (NM), Multi-thick® (M), Nutilis Powder® (Nut), Resource® (R), Thick&Easy® (TE) and Vegenat® (V). All of them with a modified starch base. Only one of them, Nut, also had a 6,4% of gum (guar, tara and xanthan). They were prepared as indicated in the instructions of each product and dispensing the correspondent amount for nectar, honey and pudding consistencies in 300 mL of tap water at 18ºC-20ºC. The mixture was stirred for about 30 s. Once it was homogeneously spread, it was dispensed in 30 mL plastic glasses; always to the same height. Each of these glasses was used as a measuring point. Viscosity was measured using a rotational viscometer (ST-2001, Selecta, Barcelona). Extrusion-compression test was performed using a TA.XT2i texture analyzer (Stable Micro Systems, UK) with a 25 mm diameter cylindrical probe (SMSP/25). Penetration distance was set at 10 mm and a speed of 3 mm/s. Measurements were made at 1, 5, 10, 20, 30, 40, 50 and 60 minutes from the moment samples were mixed. From the force (g)–time (s) curves obtained in the instrumental assays, maximum force peak (F) was chosen a reference parameter. Viscosity (mPa•s) and F (g) showed to be highly correlated and had similar development along time, following time-dependent quadratic models. It was possible to predict viscosity using F as an independent variable, as they were linearly correlated. In conclusion, compression-extrusion test could be an alternative and a useful tool to assess physical characteristics of thickened liquids.

Keywords: compression-extrusion test, dysphagia, texture analyzer, thickener

Procedia PDF Downloads 349

Authors: Gurleen Kour, Mowkshi Khullar, B. K. Chandan, Parvinder Pal Singh, Kushalava Reddy Yumpalla, Gurunadham Munagala, Ram A. Vishwakarma, Zabeer Ahmed

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New chemotherapeutic compounds against multidrug-resistant Mycobacterium tuberculosis (Mtb) are urgently needed to combat drug resistance in tuberculosis (TB). Apart from in-vitro potency against the target, physiochemical properties and pharmacokinetic properties play an imperative role in the process of drug discovery. We have identified novel nitroimidazole derivatives with potential activity against mycobacterium tuberculosis. One lead candidates, MCD-017, which showed potent activity against H37Rv strain (MIC=0.5µg/ml) and was further evaluated in the process of drug development. Methods: Basic physicochemical parameters like solubility and lipophilicity (LogP) were evaluated. Thermodynamic solubility was determined in PBS buffer (pH 7.4) using LC/MS-MS. The partition coefficient (Log P) of the compound was determined between octanol and phosphate buffered saline (PBS at pH 7.4) at 25°C by the microscale shake flask method. The compound followed Lipinski’s rule of five, which is predictive of good oral bioavailability and was further evaluated for metabolic stability. In-vitro metabolic stability was determined in rat liver microsomes. The hepatotoxicity of the compound was also determined in HepG2 cell line. In vivo pharmacokinetic profile of the compound after oral dosing was also obtained using balb/c mice. Results: The compound exhibited favorable solubility and lipophilicity. The physical and chemical properties of the compound were made use of as the first determination of drug-like properties. The compound obeyed Lipinski’s rule of five, with molecular weight < 500, number of hydrogen bond donors (HBD) < 5 and number of hydrogen bond acceptors(HBA) not more then 10. The log P of the compound was less than 5 and therefore the compound is predictive of exhibiting good absorption and permeation. Pooled rat liver microsomes were prepared from rat liver homogenate for measuring the metabolic stability. 99% of the compound was not metabolized and remained intact. The compound did not exhibit cytoxicity in hepG2 cells upto 40 µg/ml. The compound revealed good pharmacokinetic profile at a dose of 5mg/kg administered orally with a half life (t1/2) of 1.15 hours, Cmax of 642ng/ml, clearance of 4.84 ml/min/kg and a volume of distribution of 8.05 l/kg. Conclusion : The emergence of multi drug resistance (MDR) and extensively drug resistant (XDR) Tuberculosis emphasize the requirement of novel drugs active against tuberculosis. Thus, the need to evaluate physicochemical and pharmacokinetic properties in the early stages of drug discovery is required to reduce the attrition associated with poor drug exposure. In summary, it can be concluded that MCD-017 may be considered a good candidate for further preclinical and clinical evaluations.

Keywords: mycobacterium tuberculosis, pharmacokinetics, physicochemical properties, hepatotoxicity

Procedia PDF Downloads 439

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 63

Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

Procedia PDF Downloads 33

Authors: Aylin W Sahin, Alice Jaeger, Laura Nyhan, Gregory Belt, Steffen Münch, Elke K. Arendt

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Our current food systems cause an increase in malnutrition resulting in more people being overweight or obese in the Western World. Additionally, our natural resources are under enormous pressure and the greenhouse gas emission increases yearly with a significant contribution to climate change. Hence, transforming our food systems is of highest priority. Plant-based food products have a lower environmental impact compared to their animal-based counterpart, representing a more sustainable protein source. However, most plant-based protein ingredients, such as soy and pea, are lacking indispensable amino acids and extremely limited in their functionality and, thus, in their food application potential. They are known to have a low solubility in water and change their properties during processing. The low solubility displays the biggest challenge in the development of milk alternatives leading to inferior protein content and protein quality in dairy alternatives on the market. Moreover, plant-based protein ingredients often possess an off-flavour, which makes them less attractive to consumers. EverPro, a plant-protein isolate originated from Brewer’s Spent Grain, the most abundant by-product in the brewing industry, represents the missing piece in the plant protein portfolio. With a protein content of >85%, it is of high nutritional value, including all indispensable amino acids which allows closing the protein quality gap of plant proteins. Moreover, it possesses high techno-functional properties. It is fully soluble in water (101.7 ± 2.9%), has a high fat absorption capacity (182.4 ± 1.9%), and a foaming capacity which is superior to soy protein or pea protein. This makes EverPro suitable for a vast range of food applications. Furthermore, it does not cause changes in viscosity during heating and cooling of dispersions, such as beverages. Besides its outstanding nutritional and functional characteristics, the production of EverPro has a much lower environmental impact compared to dairy or other plant protein ingredients. Life cycle assessment analysis showed that EverPro has the lowest impact on global warming compared to soy protein isolate, pea protein isolate, whey protein isolate, and egg white powder. It also contributes significantly less to freshwater eutrophication, marine eutrophication and land use compared the protein sources mentioned above. EverPro is the prime example of sustainable ingredients, and the type of plant protein the food industry was waiting for: nutritious, multi-functional, and environmentally friendly.

Keywords: plant-based protein, upcycled, brewers' spent grain, low environmental impact, highly functional ingredient

Procedia PDF Downloads 60

Authors: K. C. M. Wong, C. P. Y. Cheng, K. Y. Chan, G. S. C. Fung, T. F. O. Lau, K. F. C. Leung, J. P. C. Fok

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Hospital Authority (HA) is the statutory body to manage all public hospitals in Hong Kong. Occupational Care Medicine Service (OMCS) is an in-house multi-disciplinary team responsible for injury management in HA. Hospital administrative services (AS) provides essential support in hospital daily operation to facilitate the provision of quality healthcare services. An occupational health enhancement program in Tai Po Hospital (TPH) domestic service supporting unit (DSSU) was piloted in 2013 with satisfactory outcome, the keys to success were staff engagement and management support. Riding on the success, the program was rolled out to another 5 AS departments of Alice Ho Miu Ling Nethersole Hospital (AHNH) and TPH in 2015. This paper highlights the indispensable components of disability management and occupational health enhancement program in hospital settings. Objectives: 1) Facilitate workplace to support staff with health affecting work problem, 2) Enhance staff’s occupational health. Methodology: Hospital Occupational Safety and Health (OSH) team and AS departments (catering, linen services, and DSSU) of AHNH and TPH worked closely with OMCS. Focus group meetings and worksite visits were conducted with frontline staff engagement. OSH hazards were identified with corresponding OSH improvement measures introduced, e.g., invention of high dusting device to minimize working at height; tailor-made linen cart to minimize back bending at work, etc. Specific MHO trainings were offered to each AS department. A disability management workshop was provided to supervisors in order to enhance their knowledge and skills in return-to-work (RTW) facilitation. Based on injured staff's health condition, OMCS would provide work recommendation, and RTW plan was formulated with engagement of staff and their supervisors. Genuine communication among stakeholders with expectation management paved the way for realistic goals setting and success in our program. Outcome: After implementation of the program, a significant drop of 26% in musculoskeletal disorders related sickness absence day was noted in 2016 as compared to the average of 2013-2015. The improvement was postulated by innovative OSH improvement measures, teamwork, staff engagement and management support. Staff and supervisors’ feedback were very encouraging that 90% respondents rated very satisfactory in program evaluation. This program exemplified good work sharing among departments to support staff in need.

Keywords: disability management, occupational health, return to work, occupational medicine

Procedia PDF Downloads 183

Authors: Yudo Prasetyo, Hana Sugiastu Firdaus, Diyanah Diyanah

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The phenomenon of the lack of clean water supply in several big cities in Indonesia is a major problem in the development of urban areas. Moreover, in the city of Semarang, the population density and growth of physical development is very high. Continuous and large amounts of underground water (aquifer) exposure can result in a drastically aquifer supply declining in year by year. Especially, the intensity of aquifer use in the fulfilment of household needs and industrial activities. This is worsening by the land subsidence phenomenon in some areas in the Semarang city. Therefore, special research is needed to know the spatial correlation of the impact of decreasing aquifer capacity on the land subsidence phenomenon. This is necessary to give approve that the occurrence of land subsidence can be caused by loss of balance of pressure on below the land surface. One method to observe the correlation pattern between the two phenomena is the application of remote sensing technology based on radar and optical satellites. Implementation of Differential Interferometric Synthetic Aperture Radar (DINSAR) or Small Baseline Area Subset (SBAS) method in SENTINEL-1A satellite image acquisition in 2014-2017 period will give a proper pattern of land subsidence. These results will be spatially correlated with the aquifer-declining pattern in the same time period. Utilization of survey results to 8 monitoring wells with depth in above 100 m to observe the multi-temporal pattern of aquifer change capacity. In addition, the pattern of aquifer capacity will be validated with 2 underground water cavity maps from observation of ministries of energy and natural resources (ESDM) in Semarang city. Spatial correlation studies will be conducted on the pattern of land subsidence and aquifer capacity using overlapping and statistical methods. The results of this correlation will show how big the correlation of decrease in underground water capacity in influencing the distribution and intensity of land subsidence in Semarang city. In addition, the results of this study will also be analyzed based on geological aspects related to hydrogeological parameters, soil types, aquifer species and geological structures. The results of this study will be a correlation map of the aquifer capacity on the decrease in the face of the land in the city of Semarang within the period 2014-2017. So hopefully the results can help the authorities in spatial planning and the city of Semarang in the future.

Keywords: aquifer, differential interferometric synthetic aperture radar (DINSAR), land subsidence, small baseline area subset (SBAS)

Procedia PDF Downloads 167

Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

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Semi-active control system for structure under excitation of earthquake provides with the characteristics of being adaptable and requiring low energy. DSHD (Displacement Semi-Active Hydraulic Damper) was developed by our research team. Shake table test results of this DSHD installed in full scale test structure demonstrated that this device brought its energy-dissipating performance into full play for test structure under excitation of earthquake. The objective of this research is to develop a new AIC (Active Interaction Control Device) and apply shake table test to perform its dissipation of energy capability. This new proposed AIC is converting an improved DSHD (Displacement Semi-Active Hydraulic Damper) to AIC with the addition of an accumulator. The main concept of this energy-dissipating AIC is to apply the interaction function of affiliated structure (sub-structure) and protected structure (main structure) to transfer the input seismic force into sub-structure to reduce the structural deformation of main structure. This concept is tested using full-scale multi-degree of freedoms test structure, installed with this proposed AIC subjected to external forces of various magnitudes, for examining the shock absorption influence of predictive control, stiffness of sub-structure, synchronous control, non-synchronous control and insufficient control position. The test results confirm: (1) this developed device is capable of diminishing the structural displacement and acceleration response effectively; (2) the shock absorption of low precision of semi-active control method did twice as much seismic proof efficacy as that of passive control method; (3) active control method may not exert a negative influence of amplifying acceleration response of structure; (4) this AIC comes into being time-delay problem. It is the same problem of ordinary active control method. The proposed predictive control method can overcome this defect; (5) condition switch is an important characteristics of control type. The test results show that synchronism control is very easy to control and avoid stirring high frequency response. This laboratory results confirm that the device developed in this research is capable of applying the mutual interaction between the subordinate structure and the main structure to be protected is capable of transforming the quake energy applied to the main structure to the subordinate structure so that the objective of minimizing the deformation of main structural can be achieved.

Keywords: DSHD (Displacement Semi-Active Hydraulic Damper), AIC (Active Interaction Control Device), shake table test, full scale structure test, sub-structure, main-structure

Procedia PDF Downloads 502

Authors: Marinella Majorano, Rachele Ferrari, Tamara Bastianello

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The recent technological advance allows for applying innovative and multimedia screen-based assessment tools to test children's language and early literacy skills, monitor their growth over the preschool years, and test their readiness for primary school. Several are the advantages that a computer-based assessment tool offers with respect to paper-based tools. Firstly, computer-based tools which provide the use of games, videos, and audio may be more motivating and engaging for children, especially for those with language difficulties. Secondly, computer-based assessments are generally less time-consuming than traditional paper-based assessments: this makes them less demanding for children and provides clinicians and researchers, but also teachers, with the opportunity to test children multiple times over the same school year and, thus, to monitor their language growth more systematically. Finally, while paper-based tools require offline coding, computer-based tools sometimes allow obtaining automatically calculated scores, thus producing less subjective evaluations of the assessed skills and provide immediate feedback. Nonetheless, using computer-based assessment tools to test meta-phonological and language skills in children is not yet common practice in Italy. The present contribution aims to estimate the internal consistency of a computer-based assessment (i.e., the Simo-syl assessment). Sixty-three Italian pre-schoolers aged between 4;10 and 5;9 years were tested at the beginning of the last year of the preschool through paper-based standardised tools in their lexical (Peabody Picture Vocabulary Test), morpho-syntactical (Grammar Repetition Test for Children), meta-phonological (Meta-Phonological skills Evaluation test), and phono-articulatory skills (non-word repetition). The same children were tested through Simo-syl assessment on their phonological and meta-phonological skills (e.g., recognise syllables and vowels and read syllables and words). The internal consistency of the computer-based tool was acceptable (Cronbach's alpha = .799). Children's scores obtained in the paper-based assessment and scores obtained in each task of the computer-based assessment were correlated. Significant and positive correlations emerged between all the tasks of the computer-based assessment and the scores obtained in the CMF (r = .287 - .311, p < .05) and in the correct sentences in the RCGB (r = .360 - .481, p < .01); non-word repetition standardised test significantly correlates with the reading tasks only (r = .329 - .350, p < .05). Further tasks should be included in the current version of Simo-syl to have a comprehensive and multi-dimensional approach when assessing children. However, such a tool represents a good chance for the teachers to early identifying language-related problems even in the school environment.

Keywords: assessment, computer-based, early identification, language-related skills

Procedia PDF Downloads 168

Authors: Balaji Devanathan, Gokul G, Raveena Divya, Abhishek Yadav, Sudhir K.Gupta

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Background: Age estimation is a common problem in administrative settings, medico legal cases, and among athletes competing in different sports. Age estimation is a problem in medico legal problems that arise in hospitals when there has been a criminal abortion, when consenting to surgery or a general physical examination, when there has been infanticide, impotence, sterility, etc. Medical imaging progress has benefited forensic anthropology in various ways, most notably in the area of determining bone age. An efficient method for researching the epiphyseal union and other differences in the body's bones and joints is multi-slice computed tomography. There isn't a significant database on Indians available. So to obtain an Indian based database author has performed this original study. Methodologies: The appearance and fusion of ossification centre of sternoclavicular joint is evaluated, and grades were assigned accordingly. Using MSCT scans, we examined the relationship between the age of the deceased and alterations in the sternoclavicular joint during the appearance and union in 500 instances, 327 men and 173 females, in the age range of 0 to 25 years. Results: According to our research in both the male and female groups, the ossification centre for the medial end of the clavicle first appeared between the ages of 18.5 and 17.1 respectively. The age range of the partial union was 20.4 and 20.2 years old. The earliest age of complete fusion was 23 years for males and 22 years for females. For fusion of their sternebrae into one, age range is 11–24 years for females and 17–24 years. The fusion of the third and fourth sternebrae was completed by 11 years. The fusions of the first and second and second and third sternebrae occur by the age of 17 years. Furthermore, correlation and reliability were carried out which yielded significant results. Conclusion: With numerous exceptions, the projected values are consistent with a large number of the previously developed age charts. These variations may be caused by the ethnic or regional heterogeneity in the ossification pattern among the population under study. The pattern of bone maturation did not significantly differ between the sexes, according to the study. The study's age range was 0 to 25 years, and for obvious reasons, the majority of the occurrences occurred in the last five years, or between 20 and 25 years of age. This resulted in a comparatively smaller study population for the 12–18 age group, where age estimate is crucial because of current legal requirements. It will require specialized PMCT research in this age range to produce population standard charts for age estimate. The medial end of the clavicle is one of several ossification foci that are being thoroughly investigated since they are challenging to assess with a traditional X-ray examination. Combining the two has been shown to be a valid result when it comes to raising the age beyond eighteen.

Keywords: age estimation, sternoclavicular joint, medial clavicle, computed tomography

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Authors: Mitakshara Sharma, S. K. Nema, Sanjeev Narang

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Diabetes mellitus (DM) is a group of metabolic disorders characterized by metabolic abnormalities, chronic hyperglycaemia and long term macrovascular & microvascular complications. Vascular complications are due to platelet hyperactivity and dysfunction, increased inflammation, altered coagulation and endothelial dysfunction. Large proportion of patients with Type II DM suffers from preventable vascular angiopathies, and there is need to develop risk factor modifications and interventions to reduce impact of complications. These complications are attributed to platelet activation, recognised by increase in Platelet Volume Indices (PVI) including Mean Platelet Volume (MPV) and Platelet Distribution Width (PDW). The current study is prospective analytical study conducted over 2 years. Out of 1100 individuals, 930 individuals fulfilled inclusion criteria and were segregated into three groups on basis of glycosylated haemoglobin (HbA1C): - (a) Diabetic, (b) Non-Diabetic and (c) Subjects with Impaired fasting glucose (IFG) with 300 individuals in IFG and non-diabetic groups & 330 individuals in diabetic group. Further, diabetic group was divided into two groups on the basis of presence or absence of known diabetes related vascular complications. Samples for HbA1c and PVI were collected using Ethylene diamine tetraacetic acid (EDTA) as anticoagulant and processed on SYSMEX-X-800i autoanalyser. The study revealed gradual increase in PVI from non-diabetics to IFG to diabetics. PVI were markedly increased in diabetic patients. MPV and PDW of diabetics, IFG and non diabetics were (17.60 ± 2.04)fl, (11.76 ± 0.73)fl, (9.93 ± 0.64)fl and (19.17 ± 1.48)fl, (15.49 ± 0.67)fl, (10.59 ± 0.67)fl respectively with a significant p value 0.00 and a significant positive correlation (MPV-HbA1c r = 0.951; PDW-HbA1c r = 0.875). MPV & PDW of subjects with diabetes related complications were higher as compared to those without them and were (17.51±0.39)fl & (15.14 ± 1.04)fl and (20.09 ± 0.98) fl & (18.96 ± 0.83)fl respectively with a significant p value 0.00. There was a significant positive correlation between PVI and duration of diabetes across the groups (MPV-HbA1c r = 0.951; PDW-HbA1c r = 0.875). However, a significant negative correlation was found between glycaemic levels and total platelet count (PC- HbA1c r =-0.164). This is multi-parameter and comprehensive study with an adequately powered study design. It can be concluded from our study that PVI are extremely useful and important indicators of impending vascular complications in all patients with deranged glycaemic control. Introduction of automated cell counters has facilitated the availability of PVI as routine parameters. PVI is a useful means for identifying larger & active platelets which play important role in development of micro and macro angiopathic complications of diabetes leading to mortality and morbidity. PVI can be used as cost effective markers to predict and prevent impending vascular events in patients with Diabetes mellitus especially in developing countries like India. PVI, if incorporated into protocols for management of diabetes, could revolutionize care and curtail the ever increasing cost of patient management.

Keywords: diabetes, IFG, HbA1C, MPV, PDW, PVI

Procedia PDF Downloads 246

Authors: Ying-Chang Yu, Yuan-Lung Lo

Abstract:

Building envelope design is one of the most popular design fields of architectural profession in nowadays. The main design trend of such system is to highlight the designer's aesthetic intention from the outlook of building project. Due to the trend of current façade design, the building envelope contains more and more layers of components, such as double skin façade, photovoltaic panels, solar control system, or even ornamental components. These exterior components are designed for various functional purposes. Most researchers focus on how these exterior elements should be structurally sound secured. However, not many researchers consider these elements would help to improve the performance of façade system. When the exterior elements are deployed in large scale, it creates an additional layer outside of original façade system and acts like a porous interface which would interfere with the aerodynamic of façade surface in micro-scale. A standard façade performance consists with 'water penetration, air infiltration rate, operation force, and component deflection ratio', and these key performances are majorly driven by the 'Design Wind Load' coded in local regulation. A design wind load is usually determined by the maximum wind pressure which occurs on the surface due to the geometry or location of building in extreme conditions. This research was designed to identify the air damping phenomenon of micro turbulence caused by porous exterior layer leading to surface wind load reduction for improvement of façade system performance. A series of wind tunnel test on dynamic pressure sensor array covered by various scale of porous exterior skin was conducted to verify the effect of wind pressure reduction. The testing specimens were designed to simulate the typical building with two-meter extension offsetting from building surface. Multiple porous exterior skins were prepared to replicate various opening ratio of surface which may cause different level of damping effect. This research adopted 'Pitot static tube', 'Thermal anemometers', and 'Hot film probe' to collect the data of surface dynamic pressure behind porous skin. Turbulence and distributed resistance are the two main factors of aerodynamic which would reduce the actual wind pressure. From initiative observation, the reading of surface wind pressure was effectively reduced behind porous media. In such case, an actual building envelope system may be benefited by porous skin from the reduction of surface wind pressure, which may improve the performance of envelope system consequently.

Keywords: multi-layer facade, porous media, facade performance, turbulence and distributed resistance, wind tunnel test

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Authors: Gokul Prasad, Pennan Chinnasamy

Abstract:

The degradation of groundwater resources, attributed to factors such as excessive abstraction and contamination, has emerged as a global concern. This study delves into the stable isotopes of water) in a hard-rock aquifer situated in the Upper Godavari watershed, an agriculturally rich region in India underlain by Basalt. The higher groundwater draft (> 90%) poses significant risks; comprehending groundwater sources, flow patterns, and their environmental impacts is pivotal for researchers and water managers. The region has faced five droughts in the past 20 years; four are categorized as medium. The recharge rates are variable and show a very minimum contribution to groundwater. The rainfall pattern shows vast variability, with the region receiving seasonal monsoon rainfall for just four months and the rest of the year experiencing minimal rainfall. This research closely monitored monsoon precipitation inputs and examined spatial and temporal fluctuations in δ18O and δ2H in both groundwater and precipitation. By discerning individual recharge events during monsoons, it became possible to identify periods when evaporation led to groundwater quality deterioration, characterized by elevated salinity and stable isotope values in the return flow. The locally derived meteoric water line (LMWL) (δ2H = 6.72 * δ18O + 1.53, r² = 0.6) provided valuable insights into the groundwater system. The leftward shift of the Nashik LMWL in relation to the GMWL and LMWL indicated groundwater evaporation (-33 ‰), supported by spatial variations in electrical conductivity (EC) data. Groundwater in the eastern and northern watershed areas exhibited higher salinity > 3000uS/cm, expanding > 40% of the area compared to the western and southern regions due to geological disparities (alluvium vs basalt). The findings emphasize meteoric precipitation as the primary groundwater source in the watershed. However, spatial variations in isotope values and chemical constituents indicate other contributing factors, including evaporation, groundwater source type, and natural or anthropogenic (specifically agricultural and industrial) contaminants. Therefore, the study recommends focused hydro geochemistry and isotope analysis in areas with strong agricultural and industrial influence for the development of holistic groundwater management plans for protecting the groundwater aquifers' quantity and quality.

Keywords: groundwater quality, stable isotopes, salinity, groundwater management, hard-rock aquifer

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Authors: Paola Molteni, Luigi d’Alonzo

Abstract:

Background: Sensory issues are now considered one of the key aspects in defining and diagnosing autism, changing the perspectives on behavioural analysis and intervention in mainstream educational services. However, Italian teachers’ training is yet not specific on the topic of autism and its sensory-related effects and this research investigates the teacher’s capability in understanding the student’s needs and his/her challenging behaviours considering sensory perceptions. Objectives: The research aims to analyse mainstream schools teachers’ awareness on students’ sensory perceptions and how this affects classroom inclusion and learning process. The research questions are: i) Are teachers able to identify student’s sensory issues?; ii) Are trained teachers more able to identify sensory problems then untrained ones?; iii) What is the impact of sensory issues on inclusion in mainstream classrooms?; iv) What should teachers know about autistic sensory dimensions? Methods: This research was designed as a pilot study that involves a multi-methods approach, including action and collaborative research methodology. The designed research allows the researcher to catch the complexity of a province school district (from kindergarten to high school) through a deep detailed analysis of selected aspects. The researcher explored the questions described above through 133 questionnaires and 6 focus groups. The qualitative and quantitative data collected during the research were analysed using the Interpretative Phenomenological Analysis (IPA). Results: Mainstream schools teachers are not able to confidently recognise sensory issues of children included in the classroom. The research underlines: how professionals with no specific training on autism are not able to recognise sensory problems in students on the spectrum; how hearing and sight issues have higher impact on classroom inclusion and student’s learning process; how a lack of understanding is often followed by misinterpretations of the impact of sensory issues and challenging behaviours. Conclusions: As this research has shown, promoting and enhancing the importance of understanding sensory issues related to autism is fundamental to enable mainstream schools teachers to define educational and life-long plans able to properly answer the student’s needs and support his/her real inclusion in the classroom. This study is a good example of how the educational research can meet and help the daily practice in working with people on the autism spectrum and support the training design for mainstream school teachers: the emerging need of designed preparation on sensory issues is fundamental to be considered when planning school district in-service training programmes, specifically declined for inclusive services.

Keywords: autism spectrum condition, scholastic inclusion, sensory overload, teacher's training

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