Search results for: Jonathan Thomas

Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

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The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

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Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

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Authors: Parth Mehta, Vedasri Bai Khavala, Prabhu Rajagopal, Tiju Thomas

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There is an increasing need for alternative clean fuels, and hydrogen (H₂) has long been considered a promising solution with a high calorific value (142MJ/kg). However, the storage of H₂ and expensive processes for its generation have hindered its usage. Sodium borohydride (NaBH₄) can potentially be used as an economically viable means of H₂ storage. Thus far, there have been attempts to optimize the life of NaBH₄ (half-life) in aqueous media by stabilizing it with sodium hydroxide (NaOH) for various pH values. Other reports have shown that H₂ yield and reaction kinetics remained constant for all ratios of H₂O to NaBH₄ > 30:1, without any acidic catalysts. Here we highlight the importance of pH and H₂O: NaBH₄ ratio (80:1, 40:1, 20:1 and 10:1 by weight), for NaBH₄ stabilization (half-life reaction time at room temperature) and corrosion minimization of H₂ reactor components. It is interesting to observe that at any particular pH>10 (e.g., pH = 10, 11 and 12), the H₂O: NaBH₄ ratio does not have the expected linear dependence with stability. On the contrary, high stability was observed at the ratio of 10:1 H₂O: NaBH₄ across all pH>10. When the H₂O: NaBH₄ ratio is increased from 10:1 to 20:1 and beyond (till 80:1), constant stability (% degradation) is observed with respect to time. For practical usage (consumption within 6 hours of making NaBH₄ solution), 15% degradation at pH 11 and NaBH₄: H₂O ratio of 10:1 is recommended. Increasing this ratio demands higher NaOH concentration at the same pH, thus requiring a higher concentration or volume of acid (e.g., HCl) for H₂ generation. The reactions are done with tap water to render the results useful from an industrial standpoint. The observed stability regimes are rationalized based on complexes associated with NaBH₄ when solvated in water, which depend sensitively on both pH and NaBH₄: H₂O ratio.

Keywords: hydrogen, sodium borohydride, stability optimization, H₂O:NaBH₄ ratio

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Authors: Ava Faridi, Pouya Faridi, Aleksandr Kakinen, Ibrahim Javed, Thomas P. Davis, Pu Chun Ke

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Human islet amyloid polypeptide (IAPP) is a hormone associated with glycemic control and type 2 diabetes. Biophysically, the chirality of IAPP fibrils has been little explored with respect to the aggregation and toxicity of the peptide. Biochemically, it remains unclear as for how protein expression in pancreatic beta cells may be altered by cell exposure to the peptide, and how such changes may be mitigated by nanoparticle inhibitors for IAPP aggregation. In this study, we first demonstrated the elimination of the IAPP nucleation phase and shortening of its elongation phase by silica nanoribbons. This accelerated IAPP fibrillization translated to reduced toxicity, especially for the right-handed silica nanoribbons, as revealed by cell viability, helium ion microscopy, as well as zebrafish embryo survival, developmental and behavioral assays. We then examined the proteomes of βTC6 pancreatic beta cells exposed to the three main aggregation states of monomeric, oligomeric and amyloid fibrillar IAPP, and compared that with cellular protein expression modulated by graphene quantum dots (GQDs). A total of 29 proteins were significantly regulated by different forms of IAPP, and the majority of these proteins were nucleotide-binding proteins. A regulatory capacity of GQDs against aberrant protein expression was confirmed. These studies have demonstrated the great potential of employing nanomaterials targeting the mesoscopic enantioselectivity and protein expression dysregulation in pancreatic beta cells.

Keywords: graphene quantum dots, IAPP, silica nanoribbons, protein expression, toxicity

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Authors: Jitendra Pratap, Jonathan Sivyer

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Introduction: Dual energy/Spectral CT scanning permits simultaneous acquisition of two x-ray spectra datasets and can complement radiological diagnosis by allowing tissue characterisation (e.g., uric acid vs. non-uric acid renal stones), enhancing structures (e.g. boost iodine signal to improve contrast resolution), and quantifying substances (e.g. iodine density). However, the latter showed inconsistent results between the 2 main modes of dual energy scanning (i.e. dual source vs. dual layer). Therefore, the present study aimed to determine which technology is more accurate in quantifying iodine density. Methods: Twenty vials with known concentrations of iodine solutions were made using Optiray 350 contrast media diluted in sterile water. The concentration of iodine utilised ranged from 0.1 mg/ml to 1.0mg/ml in 0.1mg/ml increments, 1.5 mg/ml to 4.5 mg/ml in 0.5mg/ml increments followed by further concentrations at 5.0 mg/ml, 7mg/ml, 10 mg/ml and 15mg/ml. The vials were scanned using Dual Energy scan mode on a Siemens Somatom Force at 80kV/Sn150kV and 100kV/Sn150kV kilovoltage pairing. The same vials were scanned using Spectral scan mode on a Philips iQon at 120kVp and 140kVp. The images were reconstructed at 5mm thickness and 5mm increment using Br40 kernel on the Siemens Force and B Filter on Philips iQon. Post-processing of the Dual Energy data was performed on vendor-specific Siemens Syngo VIA (VB40) and Philips Intellispace Portal (Ver. 12) for the Spectral data. For each vial and scan mode, the iodine concentration was measured by placing an ROI in the coronal plane. Intraclass correlation analysis was performed on both datasets. Results: The iodine concentrations were reproduced with a high degree of accuracy for Dual Layer CT scanner. Although the Dual Source images showed a greater degree of deviation in measured iodine density for all vials, the dataset acquired at 80kV/Sn150kV had a higher accuracy. Conclusion: Spectral CT scanning by the dual layer technique has higher accuracy for quantitative measurements of iodine density compared to the dual source technique.

Keywords: CT, iodine density, spectral, dual-energy

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

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Authors: Katyana A. Vert-Pre, James T. Thorson, Thomas Trancart, Eric Feunteun

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In marine ecosystems, spatial and temporal species structure is an important component of ecosystems’ response to anthropological and environmental factors. Although spatial distribution patterns and fish temporal series of abundance have been studied in the past, little research has been allocated to the joint dynamic spatio-temporal functional patterns in marine ecosystems and their use in multispecies management and conservation. Each species represents a function to the ecosystem, and the distribution of these species might not be random. A heterogeneous functional distribution will lead to a more resilient ecosystem to external factors. Applying a Vector-Autoregressive Spatio-Temporal (VAST) model for count data, we estimate the spatio-temporal distribution, shift in time, and abundance of 140 species of the Eastern English Chanel, Bay of Biscay and Mediterranean Sea. From the model outputs, we determined spatio-temporal clusters, calculating p-values for hierarchical clustering via multiscale bootstrap resampling. Then, we designed a functional map given the defined cluster. We found that the species distribution within the ecosystem was not random. Indeed, species evolved in space and time in clusters. Moreover, these clusters remained similar over time deriving from the fact that species of a same cluster often shifted in sync, keeping the overall structure of the ecosystem similar overtime. Knowing the co-existing species within these clusters could help with predicting data-poor species distribution and abundance. Further analysis is being performed to assess the ecological functions represented in each cluster.

Keywords: cluster distribution shift, European marine ecosystems, functional distribution, spatio-temporal model

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Authors: Meena Kumari, Ajitha Sharma, Mohan Babu Amberkar, Hasitha Manohar, Joseph Thomas, K. L. Bairy

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Aim: To evaluate the pattern of occurrence of adverse drug reactions (ADRs) with platinum compounds in cancer chemotherapy at a tertiary care hospital. Methods: It was a retrospective, descriptive case record study done on patients admitted to the medical oncology ward of Kasturba Hospital, Manipal from July to November 2012. Inclusion criteria comprised of patients of both sexes and all ages diagnosed with cancer and were on platinum compounds, who developed at least one adverse drug reaction during or after the treatment period. CDSCO proforma was used for reporting ADRs. Causality was assessed using Naranjo Algorithm. Results: A total of 65 patients was included in the study. Females comprised of 67.69% and rest males. Around 49.23% of the ADRs were seen in the age group of 41-60 years, followed by 20 % in 21-40 years, 18.46% in patients over 60 years and 12.31% in 1-20 years age group. The anticancer agents which caused adverse drug reactions in our study were carboplatin (41.54%), cisplatin (36.92%) and oxaliplatin (21.54%). Most common adverse drug reactions observed were oral candidiasis (21.53%), vomiting (16.92%), anaemia (12.3%), diarrhoea (12.3%) and febrile neutropenia (0.08%). The results of the causality assessment of most of the cases were probable. Conclusion: The adverse effect of chemotherapeutic agents is a matter of concern in the pharmacological management of cancer as it affects the quality of life of patients. This information would be useful in identifying and minimizing preventable adverse drug reactions while generally enhancing the knowledge of the prescribers to deal with these adverse drug reactions more efficiently.

Keywords: adverse drug reactions, platinum compounds, cancer, chemotherapy

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Authors: Fabrice Houngnandan, Celia Fery, Thomas Bockel, Julie Deter

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Getting water cleaner and stopping global biodiversity loss requires indices to measure changes and evaluate the achievement of objectives. The endemic and protected seagrass species Posidonia oceanica is a biological indicator used to monitor the ecological quality of marine Mediterranean waters. One ecosystem index (EBQI), two biotic indices (PREI, Bipo), and several landscape indices, which measure the composition and configuration of the P. oceanica seagrass at the population scale have been developed. While the formers are measured at monitoring sites, the landscape indices can be calculated for the entire seabed covered by this ecosystem. This present work aims to search on the link between these indices and the best scale to be used in order to maximize this link. We used data collected between 2014 to 2019 along the French Mediterranean coastline to calculate EBQI, PREI, and Bipo at 100 sites. From the P. oceanica seagrass distribution map, configuration and composition indices around these different sites in 6 different grid sizes (100 m x 100 to 1000 m x 1000 m) were determined. Correlation analyses were first used to find out the grid size presenting the strongest and most significant link between the different types of indices. Finally, several models were compared basis on various metrics to identify the one that best explains the nature of the link between these indices. Our results showed a strong and significant link between biotic indices and the best correlations between biotic and landscape indices within the 600 m x 600 m grid cells. These results showed that the use of landscape indices is possible to monitor the health of seagrass beds at a large scale.

Keywords: ecological indicators, decline, conservation, submerged aquatic vegetation

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Authors: Atousa Mirzapour Kouhdasht

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The Great Gatsby is a 1925 novel set in the Jazz Age on Long Island by American writer F. Scott Fitzgerald. The novel depicts interactions between the first-person narrator, Nick Carraway, and his mysterious millionaire neighbor, Jay Gatsby, and his obsession to reunite with his former lover, Daisy Buchanan. During World War II, the Council on Books in Wartime sent free copies to American soldiers, so the novel experienced an unanticipated wave in popularity. This newfound popularity brought up critical literary re-examination. The work soon became a part of most American high school curricula and, as a result, a part of American popular culture. Multiple adaptations, on stage and screen, followed in the succeeding decades. The novel's treatment of social class, old money versus those who do not have familial wealth, gender, race, and its cynical attitude towards the American Dream is now a matter of discussion. The old money does not allow the new money to present itself due to its fear of changes. Although Gatsby is now a wealthy man who throws many parties, he is not considered equal to Thomas Buchanan, Daisy's husband, a millionaire who lives in East Egg. Even Gatsby feels shame when it comes to the history of his family, who was not actually from the bourgeoisie. Furthermore, the patriarchal system restrains women's behavior in society and puts them in the second position after men to follow what men ask them to do. The female characters are not able to make decisions for themselves. So the researcher uses The Great Gatsby, patriarchal theory, and Marxist feminist perspective to investigate the influence of gender and social status on women's position in a patriarchal society.

Keywords: Marxist, feminist, class status, gender, the American dream, The Great Gatsby, Fitzgerald

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Adrian Craig, Jonathan Easaw, Rose Jordan, Ben Hall

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The prescription of intravenous fluids is a fundamental component of inpatient management, but it is one which usually lacks thought. Fluids are a drug, which like any other can cause harm when prescribed inappropriately or wrongly. However, it is well recognised that it is poorly done, especially in the acute portals. The National Institute for Health and Care Excellence (NICE) recommends 1mmol/kg of potassium, sodium, and chloride per day. With various options of fluids, clinicians tend to face difficulty in choosing the most appropriate maintenance fluid, and there is a reluctance to prescribe potassium as part of an intravenous maintenance fluid regime. The aim was to prospectively audit the prescription of the first bag of intravenous maintenance fluids, the use of urea and electrolytes results to guide the choice of fluid and the use of fluid prescription charts, in a busy emergency department of a major trauma centre in Stoke-on-Trent, United Kingdom. This was undertaken over a week in early November 2016. Of those prescribed maintenance fluid only 8.9% were prescribed a fluid which was most appropriate for their daily electrolyte requirements. This audit has helped to highlight further the issues that are faced in busy Emergency Departments within hospitals that are stretched and lack capacity for prompt transfer to a ward. It has supported the findings of NICE, that emergency admission portals such as Emergency Departments poorly prescribed intravenous fluid therapy. The findings have enabled simple steps to be taken to educate clinicians about their fluid of choice. This has included: posters to remind clinicians to consider the urea and electrolyte values before prescription, suggesting the inclusion of a suggested intravenous fluid of choice in the prescription chart of the trust and the inclusion of a session within the introduction programme revising intravenous fluid therapy and daily electrolyte requirements. Moving forward, once the interventions have been implemented then, the data will be reaudited in six months to note any improvement in maintenance fluid choice. Alongside this, an audit of the rate of intravenous maintenance fluid therapy would be proposed to further increase patient safety by avoiding unintentional fluid overload which may cause unnecessary harm to patients within the hospital. In conclusion, prescription of maintenance fluid therapy was poor within the Emergency Department, and there is a great deal of opportunity for improvement. Therefore, the measures listed above will be implemented and the data reaudited.

Keywords: chloride, electrolyte, emergency department, emergency medicine, fluid, fluid therapy, intravenous, maintenance, major trauma, potassium, sodium, trauma

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Authors: Alan Berman, Mark Brady

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The phenomenon of homophobia and transphobia in the United States detrimentally impacts the health, wellbeing, and dignity of school students who identify with the LGBTQ+ community. These negative impacts also compromise the participation of LGBTQ+ individuals in the wider life of educational domains and endanger the potential economic, social and cultural contribution this community can make to American society. The recent 6:3 majority decision of the US Supreme Court in Dobbs v Jackson Women’s Health Organization expressly overruled the 1973 decision in Roe v Wade and the 1992 Planned Parenthood v Casey decision. This study will canvass the bases upon which the court in Dobbs overruled longstanding precedent established in Roe and Casey. It will examine the potential implications for the LGBTQ community of the result in Dobbs. The potential far-reaching consequences of this case are foreshadowed in a concurring opinion by Justice Clarence Thomas, suggesting the Court should revisit all substantive due process cases. This includes notably the Lawrence v Texas case (invalidating sodomy laws criminalizing same-sex relations) and the Obergefellcase (upholding same-sex marriage). Finally, the study will examine the likely impact of the uncertainty brought about by the decision in Doddsfor LGBTQ students in US educational institutions. The actions of several states post-Dobbs, reflects and exacerbates the problems facing LGBTQ+ students and uncovers and highlights societal homophobia and transphobia.

Keywords: human rights, LGBT rights, right to personal dignity and autonomy, substantive due process rights

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Authors: Jonathan Magala

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Context: Adolescents in Uganda face significant challenges related to sexual health due to inadequate sexual information. This lack of information puts young people at risk of early pregnancies, sexually transmitted infections, and poverty. Therefore, it is essential to understand the sources, content, and challenges of acquiring sexual information among secondary school-going adolescents in Uganda. Research Aim: The aim of this study was to establish the sources, content, and challenges of acquiring sexual information among secondary school-going adolescents in Luwero Town Council, Uganda. Methodology: This study used a cross-sectional approach with both qualitative and quantitative methods. Questionnaires and in-depth interviews were conducted with 384 school-going adolescents aged between 13-19 years in Luwero Town Council, Uganda. Findings: The results of the study revealed that adolescents receive sexual information from various sources, with schools being the most common source, followed by parents and religious institutions being the least utilized. Adolescents received information on various topics related to sexuality, including puberty and sexual changes, pregnancy and reproduction, STD information, abstinence, and family planning. However, the content of sexual information was inadequate in addressing the challenges facing adolescents, and there were generation gaps, lack of role models, peer influence, and government policies. The male character from all the sources was the least in offering sexual information to adolescents. Theoretical Importance: The study's findings highlight the need for policy implementation to strengthen sexual education in school curriculum, as the sources of sexual information and the content are inadequate. The various topics should be addressed in schools to provide comprehensive education on sexual health for adolescents. Data Collection and Analysis Procedures: Data collection involved questionnaires and in-depth interviews with school-going adolescents. The data gathered were analyzed using descriptive statistics and thematic analysis. Questions Addressed: The study aimed to answer questions about the sources of sexual information among school-going adolescents, the content of sexual information provided, the challenges faced in accessing the information, and the importance of sex education policy implementation. Conclusion: The study concludes that schools are a popular source of sexual information among school-going adolescents in Uganda. However, the content of the information provided is inadequate in addressing the challenges that adolescents face regarding their sexual health. Therefore, policy implementation is essential in strengthening sexual education in the school curriculum and addressing various topics related to sexual health.

Keywords: adolescents, sexual information, schools, reproductive health

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Authors: Anissa Mary Thomas Thattil, Nancy Angeline Gnanaselvam, B. Ramakrishna Goud

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Faecal sludge management (FSM) is an unorganized sector, and in India, there is an absence of regulations regarding the collection, transport, treatment, and disposal of faecal sludge. FSM has a high degree of occupational hazards that need to be thoroughly understood in order to shape effective solutions. On-field observations of five FSM operations were conducted in Anekal Taluk of southern Karnataka. All five of the FSM operations were privately owned and snowball method of sampling was employed. Two types of FS operations observed were: mechanical emptying involving direct human contact with faecal sludge and mechanical emptying without direct human contact with faecal sludge. Each operation was manned by 3-4 faecal sludge operators (FSOs). None of the observed FSOs used personal protective equipment. According to the WHO semi-quantitative risk assessment, the very high risk occupational hazards identified were dermal contact with faecal sludge, inhalation of toxic gases, and social stigma. The high risk hazards identified were trips and falls, injuries, ergonomic hazards, substance abuse, and mental health problems. In all five FSM operations, the collected faecal sludge was discharged untreated onto abandoned land. FSM in India is fraught with occupational and environmental hazards which need to be urgently addressed. This includes formalizing the institution of FSM, contextualized behaviour change communication, capacity building of local bodies, awareness programmes among agriculturists and FSOs, and designation of sites for the safe harnessing of faecal sludge as soil nutrient.

Keywords: faecal sludge, faecal sludge management, FSM, occupational hazards, sanitation

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Authors: Omar Alhamd, Peter A. Thomas, Trevor J. Greenhough, Annette K. Shrive

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The Pseudomonas syringae species complex includes many plant pathogenic strains with highly specific interactions with varied host species and cultivars. The rapid spread of these bacteria over the last ten years has become a cause for concern. Nanoparticles have previously shown promise in microbiological action. We have therefore investigated in vitro and in vivo the effects of different types and sizes of nanoparticles in order to provide quantitative information about their effect on the bacteria. The effects of several different nanoparticles against several bacteria strains were investigated. The effect of NP on bacterial growth was studied by measuring the optical density, biochemical and nutritional tests, and transmission electron microscopy (TEM) to determine the shape and size of NP. Our results indicate that their effects varied, with either a negative or a positive impact on both bacterial and plant growth. Additionally, the methods of exposure to nanoparticles have a crucial role in accumulation, translocation, growth response and bacterial growth. The results of our studies on the behaviour and effects of nanoparticles in model plants showed. Cerium oxide (CeO₂) and silver (Ag) NP showed significant antibacterial activity against several pathogenic bacteria. It was found that titanium nanoparticles (TiO₂) can have either a negative or a positive impact, according to concentration and size. It is also thought that environmental conditions can have a major influence on bacterial growth. Studies were therefore also carried out under some environmental stress conditions to test bacterial survival and to assess bacterial virulence. All results will be presented including information about the effects of different nanoparticles on Pseudomonas syringae bacteria.

Keywords: plant microbiome, nanoparticles, 16S rRNA gene sequencing, bacterial survival

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Authors: Filip Buruiana, Alexander Hall, Reimar Hofmann, Thomas Hofmann, Silviu Ganceanu, Alexandru Tudorica

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In-memory column-stores make interactive analysis feasible for many big data scenarios. PowerDrill is a system used internally at Google for exploration in logs data. Even though it is a highly parallelized column-store and uses in memory caching, interactive response times cannot be achieved for all datasets (note that it is common to analyze data with 50 billion records in PowerDrill). In this paper, we investigate two orthogonal approaches to optimize performance at the expense of an acceptable loss of accuracy. Both approaches can be implemented as outer wrappers around existing database engines and so they should be easily applicable to other systems. For the first optimization we show that memory is the limiting factor in executing queries at speed and therefore explore possibilities to improve memory efficiency. We adapt some of the theory behind data sketches to reduce the size of particularly expensive fields in our largest tables by a factor of 4.5 when compared to a standard compression algorithm. This saves 37% of the overall memory in PowerDrill and introduces a 0.4% relative error in the 90th percentile for results of queries with the expensive fields. We additionally evaluate the effects of using sampling on accuracy and propose a simple heuristic for annotating individual result-values as accurate (or not). Based on measurements of user behavior in our real production system, we show that these estimates are essential for interpreting intermediate results before final results are available. For a large set of queries this effectively brings down the 95th latency percentile from 30 to 4 seconds.

Keywords: big data, in-memory column-store, high-performance SQL queries, approximate SQL queries

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Authors: Rajesha Kumar Alambi, Mansour Ahmed, Garudachari Bhadrachari, Safiyah Al-Muqahwi, Mansour Al-Rughaib, Jibu P. Thomas

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Membrane-based pressure assisted osmosis (PAO) for seawater desalination has the potential to overcome the challenges of forward osmosis technology. PAO technology is gaining interest among the research community to ensure the sustainability of freshwater with a significant reduction in energy. The requirements of PAO membranes differ from the FO membrane; as it needs a slightly higher porous with sufficient mechanical strength to overcome the applied hydraulic pressure. The porous metal-organic framework (MOF) as a filler for the membrane synthesis has demonstrated a great potential to generate new channels for water transport, high selectivity, and reduced fouling propensity. Accordingly, this study is aimed at fabricating the UiO-66 MOF-based thin film nanocomposite membranes with specific characteristics for water desalination by PAO. A PAO test unit manufactured by Trevi System, USA, was used to determine the performance of the synthesized membranes. Further, the synthesized membranes were characterized in terms of morphological features, hydrophilicity, surface roughness, and mechanical properties. The 0.05 UiO-66 loaded membrane produced highest flux of 38L/m2h and with low reverse salt leakage of 2.1g/m²h for the DI water as feed solution and 2.0 M NaCl as draw solutions at the inlet feed pressure of 0.6 MPa. The new membranes showed a good tolerance toward the applied hydraulic pressure attributed to the fabric support used during the membrane synthesis.

Keywords: metal organic framework, composite membrane, desalination, salt rejection, flux

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Authors: Thomas Trouton, Sebastian Tanner, Manvir Sandher

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The use of simulation in undergraduate and postgraduate medical curricula is ever-growing, is a useful addition to the traditional apprenticeship model of learning within medical education, and better prepares graduates for the team-based approach to healthcare seen in real-life clinical practice. As a learning tool, however, undergraduate medical students often have little understanding of the theory behind the use of medical simulation and have little experience in planning and delivering their own simulated teaching sessions. We designed and implemented a student-selected component (SSC) as part of the undergraduate medical curriculum at the University of Buckingham Medical School to introduce students to the concepts behind the use of medical simulation in education and allow them to plan and deliver their own simulated medical scenario to their peers. The SSC took place over a 2-week period in the 3rd year of the undergraduate course. There was a mix of lectures, seminars and interactive group work sessions, as well as hands-on experience in the simulation suite, to introduce key concepts related to medical simulation, including technical considerations in simulation, human factors, debriefing and troubleshooting scenarios. We evaluated the success of our SSC using “Net Promotor Scores” (NPS) to assess students’ confidence in planning and facilitating a simulation-based teaching session, as well as leading a debrief session. In all three domains, we showed an increase in the confidence of the students. We also showed an increase in confidence in the management of common medical emergencies as a result of the SSC. Overall, the students who chose our SSC had the opportunity to learn new skills in medical education, with a particular focus on the use of simulation-based teaching, and feedback highlighted that a number of students would take these skills forward in their own practice. We demonstrated an increase in confidence in several domains related to the use of medical simulation in education and have hopefully inspired a new generation of medical educators.

Keywords: simulation, SSC, teaching, medical students

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Authors: Mark De Ste Croix, Jonathan Hughes, Francisco Ayala, Michal Lehnert

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There are well-known challenges to implementing injury prevention training for youth players but no data are available on the knowledge and understanding of deliverers of such programmes at grass root level. To increase adoption and adherence to such programmes coach knowledge and understanding of injury risk and prevention is essential. Therefore, the purpose of this study was to examine grass-root coaches knowledge and understanding of injury risk and prevention in youth players. 68 grass root coaches (18 females and 50 males) who were attending a one-day injury prevention workshop completed a modified validated questionnaire exploring knowledge and understanding of injury risk and prevention in youth players. Only 59% of coaches agreed that youth players are at a high risk of suffering an injury. There were high levels of agreement that injuries can have negative impacts on team performance (75%) and can cause physical problems in later life (85%), however only around half of coaches felt that injuries affect youth players current quality of life (59%). There was strong agreement that it is possible to prevent injuries in youth players (84%), but coaches were generally unaware of programs to help prevent injuries (84%), and only 9% used some form of injury prevention program. Despite this, nearly all coaches felt that their coaching could benefit from a greater understanding of growth and maturation (91%), injury prevention programmes (91%) and specific exercises (93%) for youth athletes. 17% of coaches rated their knowledge of injury prevention as good/very good at the start of the workshop and this increased to 94% at the end of the workshop. 62% of coaches identified their attitude towards injury prevention as indifferent at the start of the workshop compared with only 1% at the end. Only 14% of coaches at the start of the workshop were confident to deliver an injury prevention session but 83% stated they were confident by the end of the workshop. Finally, 98% of coaches felt that the workshop provided them with the confidence and the knowledge to deliver an injury prevention session and 98% suggested that they would implement injury prevention into their coaching. These data suggest that there is a lack of understanding of grass root coaches that children are a high-risk group for injuries, and that such injuries impact on current quality of life. Despite understanding that injuries can be prevented most grass root coaches do not have the knowledge to implement injury prevention into their coaching and very few do. There is a common consensus amongst these coaches that a greater understanding of such programmes will enhance their coaching. The injury prevention workshop appears to have increased the knowledge and changed the attitude of coaches towards injury prevention. All coaches felt that the workshop provided them with the tools to adopt, implement and deliver injury prevention in their coaching. These data highlight that there is a clear need for education regarding injury risk and prevention to be embedded within the coach education pathway, especially at grass root level.

Keywords: coach education, injury prevention, knowledge, and understanding, youth

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Authors: Ambreen Aslam, Tahira Aziz Mughal, Skye R. Thomas-Hall, Peer M. Schenk

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Biodiesel is an alternative to petroleum-derived fuel mainly composed of fatty acid from oleaginous microalgae feedstock. Microalgae produced fatty acid methyl esters (FAMEs) as they can store high levels of lipids without competing for food productivity. After lipid extraction and esterification, fatty acid profile from algae feedstock possessed the abundance of fatty acids with carbon chain length specifically C16 and C18. The qualitative analysis of FAME was done by cultivating mix microalgae consortia under three different CO₂ concentrations (1%, 3%, and 5.5%) from a coal fired flue gas. FAME content (280.3 µg/mL) and productivity (18.69 µg/mL/D) was higher under 1% CO₂ (flue gas) as compare to other treatments. Whereas, Mixed C. (F) supplemented with 5.5% CO₂ (50% flue gas) had higher SFA (36.28%) and UFA (63.72%) which improve the oxidative stability of biodiesel. Subsequently, low Iodine value (136.3 gI₂/100g) and higher Cetane number (52) of Mixed C.+P (F) were found to be in accordance with European (EN 14214) standard under 5.5% CO₂ along with 50mM phosphate buffer. Experimental results revealed that sufficient phosphate reduced FAME productivity but significantly enhance biodiesel quality. This research aimed to develop an integrated approach of utilizing flue gas (as CO₂ source) for significant improvement in biodiesel quality under surplus phosphorus. CO₂ sequestration from industrial flue gas not only reduce greenhouse gases (GHG) emissions but also ensure sustainability and eco-friendliness of the biodiesel production process through microalgae.

Keywords: biodiesel analysis, carbon dioxide, coal fired flue gas, FAME productivity, fatty acid profile, fuel properties, lipid content, mixed culture microalgae

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Authors: Michael Zhang, Nicholas Marriage, Valerie Astle, Marie-Louise Ratican, Jonathan Ash, Haddijatou Hughes

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Objective: Young infants are often brought to the Emergency Department (ED) with a variety of complaints, some of them are non-specific and present as a diagnostic challenge to the attending clinician. Whilst invasive investigations such as blood tests and lumbar puncture are necessary in some cases to exclude serious infections, some basic clinical tools in additional to thorough clinical history can be useful to assess the risks of serious conditions in these young infants. This study aimed to examine the utilization of one of clinical tools in this regard. Methods: This retrospective observational study examined the medical records of infants under 6 months presenting to a mixed urban ED between January 2013 and December 2014. The infants deemed to have non-specific complaints or diagnoses by the emergency clinicians were selected for analysis. The ones with clear systemic diagnoses were excluded. Among all relevant clinical information and investigation results, utilization of Standard Paediatric Observation Chart (SPOC) was particularly scrutinized in these medical records. This specific chart was developed by the expert clinicians in local health department. It categorizes important clinical signs into some color-coded zones as a visual cue for serious implication of some abnormalities. An infant is regarded as SPOC positive when fulfills 1 red zone or 2 yellow zones criteria, and the attending clinician would be prompted to investigate and treat for potential serious conditions accordingly. Results: Eight hundred and thirty-five infants met the inclusion criteria for this project. The ones admitted to the hospital for further management were more likely to have SPOC positive criteria than the discharged infants (Odds ratio: 12.26, 95% CI: 8.04 – 18.69). Similarly, Sepsis alert criteria on SPOC were positive in a higher percentage of patients with serious infections (56.52%) in comparison to those with mild conditions (15.89%) (p < 0.001). The SPOC sepsis criteria had a sensitivity of 56.5% (95% CI: 47.0% - 65.7%) and a moderate specificity of 84.1% (95% CI: 80.8% - 87.0%) to identify serious infections. Applying to this infant population, with a 17.4% prevalence of serious infection, the positive predictive value was only 42.8% (95% CI: 36.9% - 49.0%). However, the negative predictive value was high at 90.2% (95% CI: 88.1% - 91.9%). Conclusions: Standard Paediatric Observation Chart has been applied as a useful clinical tool in the clinical practice to help identify and manage young sick infants in ED effectively.

Keywords: clinical tool, infants, non-specific complaints, Standard Paediatric Observation Chart

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Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera

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This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.

Keywords: automation, hydroponics, internet of things, monitoring system, urban farming

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Authors: Alok Kumar, Hari Ram, Lebin Thomas, Ved Pal Singh

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Organic solvent tolerant amylases and proteases of microbial origin are in great demand for their application in transglycosylation of water-insoluble flavanoids and in peptide synthesizing reaction in organic media. Most of the amylases and proteases are unstable in presence of organic solvent. In the present work two different bacterial strains M-11 and VP-07 were isolated from the soil sample of a dairy farm in Delhi, India, for the efficient production of extracellular amylase and protease through their screening on starch agar (SA) and skimmed milk agar (SMA) plates, respectively. Both the strains (M-11 and VP-07) were identified based on morphological, biochemical and 16S rRNA gene sequencing methods. After analysis through Ez-Taxon software, the strains M-11 and VP-07 were found to have maximum pairwise similarity of 98.63% and 100% with Bacillus subtilis subsp. inaquosorum BGSC 3A28 and Bacillus anthracis ATCC 14578 and were therefore identified as Bacillus sp. UKS1 and Bacillus sp. UKS2, respectively. Time course study of enzyme activity and bacterial growth has shown that both strains exhibited typical sigmoid growth behavior and maximum production of amylase (180 U/ml) and protease (78 U/ml) by these strains (UKS1 and UKS2) was commenced during stationary phase of growth at 24 and 20 h, respectively. Thereafter, both amylase and protease were tested for their tolerance towards organic solvents and were found to be active as well stable in p-xylene (130% and 115%), chloroform (110% and 112%), isooctane (119% and 107%), benzene (121% and 104%), n-hexane (116% and 103%) and toluene (112% and 101%, respectively). Owing to such properties, these enzymes can be exploited for their potential application in industries for organic synthesis.

Keywords: amylase, enzyme activity, industrial applications, organic solvent tolerant, protease

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Authors: Sylvain Amailland, Jean-Hugh Thomas, Charles Pézerat, Romuald Boucheron, Jean-Claude Pascal

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The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.

Keywords: acoustic imaging, boundary layer noise denoising, inverse problems, model adaptation

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Authors: Rohit Kumar Shrivastava, Amalia Thomas, Nathalie Vriend, Stefan Luding

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A mechanical wave or vibration propagating through granular media exhibits a specific signature in time. A coherent pulse or wavefront arrives first with multiply scattered waves (coda) arriving later. The coherent pulse is micro-structure independent i.e. it depends only on the bulk properties of the disordered granular sample, the sound wave velocity of the granular sample and hence bulk and shear moduli. The coherent wavefront attenuates (decreases in amplitude) and broadens with distance from its source. The pulse attenuation and broadening effects are affected by disorder (polydispersity; contrast in size of the granules) and have often been attributed to dispersion and scattering. To study the effect of disorder and initial amplitude (non-linearity) of the pulse imparted to the system on the coherent wavefront, numerical simulations have been carried out on one-dimensional sets of particles (granular chains). The interaction force between the particles is given by a Hertzian contact model. The sizes of particles have been selected randomly from a Gaussian distribution, where the standard deviation of this distribution is the relevant parameter that quantifies the effect of disorder on the coherent wavefront. Since, the coherent wavefront is system configuration independent, ensemble averaging has been used for improving the signal quality of the coherent pulse and removing the multiply scattered waves. The results concerning the width of the coherent wavefront have been formulated in terms of scaling laws. An experimental set-up of photoelastic particles constituting a granular chain is proposed to validate the numerical results.

Keywords: discrete elements, Hertzian contact, polydispersity, weakly nonlinear, wave propagation

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Authors: Wilman Septina, Rajiv R. Prabhakar, Thomas Moehl, David Tilley

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Cupric oxide (CuO) is a promising absorber material for the fabrication of scalable, low cost solar energy conversion devices, due to the high abundance and low toxicity of copper. It is a p-type semiconductor with a band gap of around 1.5 eV, absorbing a significant portion of the solar spectrum. One of the main challenges in using CuO as solar absorber in an aqueous system is its tendency towards photocorrosion, generating Cu2O and metallic Cu. Although there have been several reports of CuO as a photocathode for hydrogen production, it is unclear how much of the observed current actually corresponds to H2 evolution, as the inevitability of photocorrosion is usually not addressed. In this research, we investigated the effect of the deposition of overlayers onto CuO thin films for the purpose of enhancing its photostability as well as performance for water splitting applications. CuO thin film was fabricated by galvanic electrodeposition of metallic copper onto gold-coated FTO substrates, followed by annealing in air at 600 °C. Photoelectrochemical measurement of the bare CuO film using 1 M phosphate buffer (pH 6.9) under simulated AM 1.5 sunlight showed a current density of ca. 1.5 mA cm-2 (at 0.4 VRHE), which photocorroded to Cu metal upon prolonged illumination. This photocorrosion could be suppressed by deposition of 50 nm-thick TiO2, deposited by atomic layer deposition. In addition, we found that insertion of an n-type CdS layer, deposited by chemical bath deposition, between the CuO and TiO2 layers was able to enhance significantly the photocurrent compared to without the CdS layer. A photocurrent of over 2 mA cm-2 (at 0 VRHE) was observed using the photocathode stack FTO/Au/CuO/CdS/TiO2/Pt. Structural, electrochemical, and photostability characterizations of the photocathode as well as results on various overlayers will be presented.

Keywords: CuO, hydrogen, photoelectrochemical, photostability, water splitting

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Authors: Ikpesu, Thomas Ohwofasa, Babtunde Ilesanmi

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The effects of anthropogenic activities on fish and fisheries products in Niger Delta water bodies were investigated. The rivers were selected based on their close proximity to contaminants and dredging activities. Three stations were chosen per river. The stations chosen to depicting downstream and upstream stations were visited and samples collected on monthly basis. The down streams stations are the polluted and heavily dredged sites, where the upstream station is far, without any evidence of pollution or human activities. During these periods, the fishes of the same species were collected and analyzed for morphological and physiological changes, after which they were returned back to the rivers. The physico-chemicals parameters of these stations were also taken. Morphological changes such as skin ulcerations and other lesions, as well as fungi infections were observed in the down streams fishes. The fish in up streams look healthier and bigger (though the age could not be affirmed) than the downstream fishes. The physico-chemical parameters between the up streams and down streams stations vary significantly (p < 0.01). These anthropogenic effects must have interfere with the normal migration pattern of these fishes, because there were changes in the composition of population and species diversity in the samples sites, with the upstream having true species diversity. The release of pollutants into the water in the Niger Delta areas may triggers off naturally occurring bio toxicity cycles and other fish poisoning. There is risk of biomagnifications of these poisons along the tropic level. This makes the normally valuable food resource dangerous for human consumption and thereby instances of human death caused by such poisoning.

Keywords: anthropogenic, dredging, fisheries, niger delta, pollution, rivers

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Authors: Pimpak Phumat, Sakornrat Khongkhunthian, Thomas Rades, Anette Müllertz, Siriporn Okonogi

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Self-nanoemulsifying drug delivery systems (SNEDDS) containing 4-allylpyrocatechol (AP) extracted from Piper betle were developed to enhance water solubility of AP by using modeling and design (MODDE) program. The amount of AP in each SNEDDS formulation was determined by using high-performance liquid chromatography. The formulation consisted of 20% Miglyol®812N, 40 % Kolliphor®RH40, 30 % Maisine®35-1 and 10 % ethanol was found to be the best SNEDDS that provided the highest loading capacity of AP. (141.48±15.64 mg/g SNEDDS). The system also showed miscibility with water. The particle shape and size of the AP-SNEDDS after dispersing in water was investigated by using a transmission electron microscope and photon correlation spectrophotometer, respectively. The results showed that they were a spherical shape, having a particle size of 34.27 ± 1.14 nm with a narrow size distribution of 0.17 ± 0.04. The particles showed negative zeta potential with a value of -21.66 ± 2.09 mV. Antibacterial activity of AP-SNEDDS containing 1.5 mg/mL of AP was investigated against Streptococcus intermedius. The effect of this system on S. intermedius cells was observed by a scanning electron microscope (SEM). The results from SEM revealed that the bacterial cells were obviously destroyed. Killing kinetic study of AP-SNEDDS was carried out. It was found that the killing rate of AP-SNEDDS against S. intermedius was dose-dependent and the bacterial reduction was 79.86 ± 0.45 % within 30 min. In comparison with chlorhexidine (CHX), AP-SNEDDS showed similar antibacterial effects against S. intermedius. It is concluded that SNEDDS is a potential system for enhancing water solubility of AP. The antibacterial study reveals that AP-SNEDDS can be a promising system to treat bacterial infection caused by S. intermedius.

Keywords: SNEDDS, 4-allylpyrocathecol, solubility, antibacterial activity, Streptococcus intermedius

Procedia PDF Downloads 96