Search results for: open jet testing

Authors: Mayantoinette F. Watson

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During such an unprecedented time of the largest public health crisis, the COVID-19 pandemic, nursing students are of the utmost concern regarding their psychological and physical well-being. Questions are emerging and circulating about what will happen to the nursing students and the long-term effects of the pandemic, especially now that hospitals are being overwhelmed with a significant need for nursing staff. Expectations, demands, change, and the fear of the unknown during this unprecedented time can only contribute to the many stressors that accompany nursing students through laborious clinical and didactic courses in nursing programs. The risk of psychological distress is at a maximum, and its effects can negatively impact not only nursing students but also nursing education and academia. The high exposures to interpersonal, economic, and academic demands contribute to the major health concerns, which include a potential risk for psychological distress. Achievement of educational success among nursing students is directly affected by the high exposure to anxiety and depression from experiences within the program. Working relationships and achieving academic success is imperative to positive student outcomes within the nursing program. The purpose of this study is to identify and establish influences and associations within multilevel factors, including the effects of the COVID-19 pandemic on psychological distress in nursing students. Neuman’s Systems Model Theory was used to determine nursing students’ responses to internal and external stressors. The research in this study utilized a mixed-methods, convergent study design. The study population included undergraduate nursing students from Southeastern U.S. The research surveyed a convenience sample of undergraduate nursing students. The quantitative survey was completed by 202 participants, and 11 participants participated in the qualitative follow-up interview surveys. Participants completed the Kessler Psychological Distress Scale (K6), the Perceived Stress Scale (PSS4), and the Dundee Readiness Educational Environment Scale (DREEM12) to measure psychological distress, perceived stress, and perceived educational environment. Participants also answered open-ended questions regarding their experience during the COVID-19 pandemic. Statistical tests, including bivariate analyses, multiple linear regression analyses, and binary logistics regression analyses were performed in effort to identify and highlight the effects of independent variables on the dependent variable, psychological distress. Coding and qualitative content analysis were performed to identify overarching themes within participants’ interviews. Quantitative data were sufficient in identifying correlations between psychological distress and multilevel factors of coping, marital status, COVID-19 stress, perceived stress, educational environment, and social support in nursing students. Qualitative data were sufficient in identifying common themes of students’ perceptions during COVID-19 and included online learning, workload, finances, experience, breaks, time, unknown, support, encouragement, unchanged, communication, and transmission. The findings are significant, specifically regarding contributing factors to nursing students’ psychological distress, which will help to improve learning in the academic environment.

Keywords: nursing education, nursing students, pandemic, psychological distress

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Authors: V. V. Fomin, A. P. Mikhailovich, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Ground-level landscape photos can be used as a source of objective data on woody vegetation and vegetation dynamics. We proposed a method for processing, analyzing, and presenting ground photographs, which has the following advantages: 1) researcher has to form holistic representation of the study area in form of a set of interlapping ground-level landscape photographs; 2) it is necessary to define or obtain characteristics of the landscape, objects, and phenomena present on the photographs; 3) it is necessary to create new or supplement existing textual descriptions and annotations for the ground-level landscape photographs; 4) single or multiple ground-level landscape photographs can be used to develop specialized geoinformation layers, schematic maps or thematic maps; 5) it is necessary to determine quantitative data that describes both images as a whole, and displayed objects and phenomena, using algorithms for automated image analysis. It is suggested to match each photo with a polygonal geoinformation layer, which is a sector consisting of areas corresponding with parts of the landscape visible in the photos. Calculation of visibility areas is performed in a geoinformation system within a sector using a digital model of a study area relief and visibility analysis functions. Superposition of the visibility sectors corresponding with various camera viewpoints allows matching landscape photos with each other to create a complete and wholesome representation of the space in question. It is suggested to user-defined data or phenomenons on the images with the following superposition over the visibility sector in the form of map symbols. The technology of geoinformation layers’ spatial superposition over the visibility sector creates opportunities for image geotagging using quantitative data obtained from raster or vector layers within the sector with the ability to generate annotations in natural language. The proposed method has proven itself well for relatively open and clearly visible areas with well-defined relief, for example, in mountainous areas in the treeline ecotone. When the polygonal layers of visibility sectors for a large number of different points of photography are topologically superimposed, a layer of visibility of sections of the entire study area is formed, which is displayed in the photographs. Also, as a result of this overlapping of sectors, areas that did not appear in the photo will be assessed as gaps. According to the results of this procedure, it becomes possible to obtain information about the photos that display a specific area and from which points of photography it is visible. This information may be obtained either as a query on the map or as a query for the attribute table of the layer. The method was tested using repeated photos taken from forty camera viewpoints located on Ray-Iz mountain massif (Polar Urals, Russia) from 1960 until 2023. It has been successfully used in combination with other ground-based and remote sensing methods of studying the climate-driven dynamics of woody vegetation in the Polar Urals. Acknowledgment: This research was collaboratively funded by the Russian Ministry for Science and Education project No. FEUG-2023-0002 (image representation) and Russian Science Foundation project No. 24-24-00235 (automated textual description).

Keywords: woody, vegetation, repeated, photographs

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Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: S. Toufigh Bararpour, Davood Karami, Nader Mahinpey

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Dependence of global economics on fossil fuels has led to a large growth in the emission of greenhouse gases (GHGs). Among the various GHGs, carbon dioxide is the main contributor to the greenhouse effect due to its huge emission amount. To mitigate the threatening effect of CO₂, carbon capture and sequestration (CCS) technologies have been studied widely in recent years. For the combustion processes, three main CO₂ capture techniques have been proposed such as post-combustion, pre-combustion and oxyfuel combustion. Post-combustion is the most commonly used CO₂ capture process as it can be readily retrofit into the existing power plants. Multiple advantages have been reported for the post-combustion by solid sorbents such as high CO₂ selectivity, high adsorption capacity, and low required regeneration energy. Chemical adsorption of CO₂ over alkali-metal-based solid sorbents such as K₂CO₃ is a promising method for the selective capture of diluted CO₂ from the huge amount of nitrogen existing in the flue gas. To improve the CO₂ capture performance, K₂CO₃ is supported by a stable and porous material. Al₂O₃ has been employed commonly as the support and enhanced the cyclic CO₂ capture efficiency of K₂CO₃. Different phases of alumina can be obtained by setting the calcination temperature of boehmite at 300, 600 (γ-alumina), 950 (δ-alumina) and 1200 °C (α-alumina). By increasing the calcination temperature, the regeneration capacity of alumina increases, while the surface area reduces. However, sorbents with lower surface areas have lower CO₂ capture capacity as well (except for the sorbents prepared by hydrophilic support materials). To resolve this issue, a highly efficient alumina-aerogel support was synthesized with a BET surface area of over 2000 m²/g and then calcined at a high temperature. The synthesized alumina-aerogel was impregnated on K₂CO₃ based on 50 wt% support/K₂CO₃, which resulted in the preparation of a sorbent with remarkable CO₂ capture performance. The effect of synthesis conditions such as types of alcohols, solvent-to-co-solvent ratios, and aging times was investigated on the performance of the support. The best support was synthesized using methanol as the solvent, after five days of aging time, and at a solvent-to-co-solvent (methanol-to-toluene) ratio (v/v) of 1/5. Response surface methodology was used to investigate the effect of operating parameters such as carbonation temperature and H₂O-to-CO₂ flowrate ratio on the CO₂ capture capacity. The maximum CO₂ capture capacity, at the optimum amounts of operating parameters, was 7.2 mmol CO₂ per gram K₂CO₃. Cyclic behavior of the sorbent was examined over 20 carbonation and regenerations cycles. The alumina-aerogel-supported K₂CO₃ showed a great performance compared to unsupported K₂CO₃ and γ-alumina-supported K₂CO₃. Fundamental performance analyses and long-term thermal and chemical stability test will be performed on the sorbent in the future. The applicability of the sorbent for a bench-scale process will be evaluated, and a corresponding process model will be established. The fundamental material knowledge and respective process development will be delivered to industrial partners for the design of a pilot-scale testing unit, thereby facilitating the industrial application of alumina-aerogel.

Keywords: alumina-aerogel, CO₂ capture, K₂CO₃, optimization

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Authors: Atin Adhikari, Sushma Kurella, Pratik Banerjee, Nabanita Mukherjee, Yamini M. Chandana Gollapudi, Bushra Shah

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Different sharp instruments, drilling machines, and high speed rotary instruments are routinely used in dental clinics during dental cleaning. Therefore, these cleaning procedures release a lot of oral microorganisms including bacteria in clinic air and may cause significant occupational bioaerosol exposure risks for dentists, dental hygienists, patients, and dental clinic employees. Two major goals of this study were to quantify volumetric airborne concentrations of bacteria and to assess overall microbial activity in this type of occupational environment. The study was conducted in several dental clinics of southern Georgia and 15 dental cleaning procedures were targeted for sampling of airborne bacteria and testing of overall microbial activity in settled dusts over clinic floors. For air sampling, a Biostage viable cascade impactor was utilized, which comprises an inlet cone, precision-drilled 400-hole impactor stage, and a base that holds an agar plate (Tryptic soy agar). A high-flow Quick-Take-30 pump connected to this impactor pulls microorganisms in air at 28.3 L/min flow rate through the holes (jets) where they are collected on the agar surface for approx. five minutes. After sampling, agar plates containing the samples were placed in an ice chest with blue ice and plates were incubated at 30±2°C for 24 to 72 h. Colonies were counted and converted to airborne concentrations (CFU/m3) followed by positive hole corrections. Most abundant bacterial colonies (selected by visual screening) were identified by PCR amplicon sequencing of 16S rRNA genes. For understanding overall microbial activity in clinic floors and estimating a general cleanliness of the clinic surfaces during or after dental cleaning procedures, ATP levels were determined in swabbed dust samples collected from 10 cm2 floor surfaces. Concentration of ATP may indicate both the cell viability and the metabolic status of settled microorganisms in this situation. An ATP measuring kit was used, which utilized standard luciferin-luciferase fluorescence reaction and a luminometer, which quantified ATP levels as relative light units (RLU). Three air and dust samples were collected during each cleaning procedure (at the beginning, during cleaning, and immediately after the procedure was completed (n = 45). Concentrations at the beginning, during, and after dental cleaning procedures were 671±525, 917±1203, and 899±823 CFU/m3, respectively for airborne bacteria and 91±101, 243±129, and 139±77 RLU/sample, respectively for ATP levels. The concentrations of bacteria were significantly higher than typical indoor residential environments. Although an increasing trend for airborne bacteria was observed during cleaning, the data collected at three different time points were not significantly different (ANOVA: p = 0.38) probably due to high standard deviations of data. The ATP levels, however, demonstrated a significant difference (ANOVA: p <0.05) in this scenario indicating significant change in microbial activity on floor surfaces during dental cleaning. The most common bacterial genera identified were: Neisseria sp., Streptococcus sp., Chryseobacterium sp., Paenisporosarcina sp., and Vibrio sp. in terms of frequencies of occurrences, respectively. The study concluded that bacterial exposure in dental clinics could be a notable occupational biohazard, and appropriate respiratory protections for the employees are urgently needed.

Keywords: bioaerosols, hospital hygiene, indoor air quality, occupational biohazards

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Authors: Farhana Karim, Abdullah N. S. Khan, Mohiuddin A. K. Chowdhury, Nabila Zaka, Alexander Manu, Shams El Arifeen, Sk Masum Billah

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Breastfeeding, an integral part of newborn care, can reduce 55-87% of all-cause neonatal mortality and morbidity. Early initiation of breastfeeding within 1 hour of birth can avert 22% of newborn mortality. Only 45% of world’s newborns and 42% of newborns in South-Asia are put to the breast within one hour of birth. In Bangladesh, only a half of the mothers practice early initiation of breastfeeding which is less likely to be practiced if the baby is born in a health facility. This study aims to generate strong evidence for early initiation of breastfeeding practices in the government health facilities and to explore the associated factors influencing the practice. The study was conducted in selected health facilities in three neighbouring districts of Northern Bangladesh. Total 249 normal vaginal delivery cases were observed for 24 hours since the time of birth. The outcome variable was initiation of breastfeeding within 1 hour while the explanatory variables included type of health facility, privacy, presence of support person, stage of labour at admission, need for augmentation of labour, complications during delivery, need for episiotomy, spontaneous cry of the newborn, skin-to-skin contact with mother, post-natal contact with the service provider, receiving a post-natal examination and counselling on breastfeeding during postnatal contact. The simple descriptive statistics were employed to see the distribution of samples according to socio-demographic characteristics. Kruskal-Wallis test was carried out for testing the equality of medians among two or more categories of each variable and P-value is reported. A series of simple logistic regressions were conducted with all the potential explanatory variables to identify the determining factors for breastfeeding within 1 hour in a health facility. Finally, multiple logistic regression was conducted including the variables found significant at bi-variate analyses. Almost 90% participants initiated breastfeeding at the health facility and median time to initiate breastfeeding was 38 minutes. However, delivering in a sub-district hospital significantly delayed the breastfeeding initiation in comparison to delivering in a district hospital. Maintenance of adequate privacy and presence of separate staff for taking care of newborn significantly reduced the time in early breastfeeding initiation. Initiation time was found longer if the mother had an augmented labour, obstetric complications, and the newborn needed resuscitation. However, the initiation time was significantly early if the baby was put skin-to-skin on mother’s abdomen and received a postnatal examination by a provider. After controlling for the potential confounders, the odds of initiating breastfeeding within one hour of birth is higher if mother gives birth in a district hospital (AOR 3.0: 95% CI 1.5, 6.2), privacy is well-maintained (AOR 2.3: 95% CI 1.1, 4.5), babies cry spontaneously (AOR 7.7: 95% CI 3.3, 17.8), babies are put to skin-to-skin contact with mother (AOR 4.6: 95% CI 1.9, 11.2) and if the baby is examined by a provider in the facility (AOR 4.4: 95% CI 1.4, 14.2). The evidence generated by this study will hopefully direct the policymakers to identify and prioritize the scopes for creating and supporting early initiation of breastfeeding in the health facilities.

Keywords: Bangladesh, early initiation of breastfeeding, health facility, normal vaginal delivery, skin to skin contact

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Authors: Chen Jiang, Eric Jordan, Maurice Gell, Balakrishnan Nair

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Nuclear fusion, one of the most promising options for reliably generating large amounts of carbon-free energy in the future, has seen a plethora of ground-breaking technological advances in recent years. An efficient and durable “breeding blanket”, needed to ensure a reactor’s self-sufficiency by maintaining the optimal coolant temperature as well as by minimizing radiation dosage behind the blanket, still remains a technological challenge for the various reactor designs for commercial fusion power plants. A relatively new dual-coolant lead-lithium (DCLL) breeder design has exhibited great potential for high-temperature (>700oC), high-thermal-efficiency (>40%) fusion reactor operation. However, the structural material, namely reduced activation ferritic-martensitic (RAFM) steel, is not chemically stable in contact with molten Pb-17%Li coolant. Thus, to utilize this new promising reactor design, the demand for effective corrosion-resistant coatings on RAFM steels represents a pressing need. Solution Spray Technologies LLC (SST) is developing a double-layer ceramic coating design to address the corrosion protection of RAFM steels, using a novel solution and solution/suspension plasma spray technology through a US Department of Energy-funded project. Plasma spray is a coating deposition method widely used in many energy applications. Novel derivatives of the conventional powder plasma spray process, known as the solution-precursor and solution/suspension-hybrid plasma spray process, are powerful methods to fabricate thin, dense ceramic coatings with complex compositions necessary for the corrosion protection in DCLL breeders. These processes can be used to produce ultra-fine molten splats and to allow fine adjustment of coating chemistry. Thin, dense ceramic coatings with chosen chemistry for superior chemical stability in molten Pb-Li, low activation properties, and good radiation tolerance, is ideal for corrosion-protection of RAFM steels. A key challenge is to accommodate its CTE mismatch with the RAFM substrate through the selection and incorporation of appropriate bond layers, thus allowing for enhanced coating durability and robustness. Systematic process optimization is being used to define the optimal plasma spray conditions for both the topcoat and bond-layer, and X-ray diffraction and SEM-EDS are applied to successfully validate the chemistry and phase composition of the coatings. The plasma-sprayed double-layer corrosion resistant coatings were also deposited onto simulated RAFM steel substrates, which are being tested separately under thermal cycling, high-temperature moist air oxidation as well as molten Pb-Li capsule corrosion conditions. Results from this testing on coated samples, and comparisons with bare RAFM reference samples will be presented and conclusions will be presented assessing the viability of the new ceramic coatings to be viable corrosion prevention systems for DCLL breeders in commercial nuclear fusion reactors.

Keywords: breeding blanket, corrosion protection, coating, plasma spray

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Authors: Rohan M. Dalal, Elena Pirondini, Shanu Somvanshi

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Introduction: The current state of reproductive health outcomes in lower-income countries is poor, with inadequate knowledge and culture among adolescent boys. Moreover, boys have traditionally not been a priority target. To explore the opportunity to educate adolescent boys in the developing world regarding accurate reproductive health information, the purpose of this study is to investigate how adolescent boys in the developing world engage and use technology, utilizing cell phones. This electronic survey and video interview study were conducted to determine the feasibility of a mobile phone platform for an educational video game specifically designed for boys that will improve health knowledge, influence behavior, and change health outcomes, namely teen pregnancies. Methods: With the assistance of Plan India, a subsidiary of Plan International, informed consent was obtained from parents of adolescent males who participated in an electronic survey and video interviews via Microsoft Teams. An electronic survey was created with 27 questions, including topics of mobile phone usage, gaming preferences, and sexual and reproductive health, with a sample size of 181 adolescents, ages 11-25, near New Delhi, India. The interview questions were written to explore more in-depth topics after the completion of the electronic survey. Eight boys, aged 15, were interviewed for 40 minutes about gaming and usage of mobile phones as well as sexual and reproductive health. Data/Results. 154 boys and 27 girls completed the survey. They rated their English fluency as relatively high. 97% of boys (149/154) had access to mobile phones. The majority of phones were smartphones (97%, 143/148). 48% (71/149) of boys borrowed cell phones. The most popular phone platform was Samsung (22%, 33/148). 36% (54/148) of adolescent males looked at their phones 1-10 times per day for 1-2 hours. 55% (81/149) of the boys had parental restrictions. 51% (76/148) had 32 GB of storage on their phone. 78% (117/150) of the boys had wifi access. 80% (120/150) of respondents reported ease in downloading apps. 97% (145/150) of male adolescents had social media, including WhatsApp, Facebook, and YouTube. 58% (87/150) played video games. Favorite video games included Free Fire, PubG, and other shooting games. In the video interviews, the boys revealed what made games fun and engaging, including customized avatars, progression to higher levels, realistic interactive platforms, shooting/guns, the ability to perform multiple actions, and a variety of worlds/settings/adventures. Ideas to improve engagement in sexual and reproductive health classes included open discussions in the community, enhanced access to information, and posting on social media. Conclusion: This study involving an electronic survey and video interviews provides an initial foray into understanding mobile phone usage among adolescent males and understanding sexual and reproductive health education in New Delhi, India. The data gathered from this study support using mobile phone platforms, and this will be used to create a serious video game to educate adolescent males about sexual and reproductive health in an attempt to lower the rate of unwanted pregnancies in the world.

Keywords: adolescent males, India, mobile phone, sexual and reproductive health

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Authors: Tomasz Balabanski, Anna Biedunkiewicz

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Research on basic bacteriological and physicochemical parameters conducted by state institutions (Provincial Sanitary and Epidemiological Station and District Sanitary and Epidemiological Station) are limited to bathing waters under constant sanitary and epidemiological supervision. Unfortunately, no routine or monitoring tests are carried out for the presence of microfungi. This also applies to beach sand used for recreational purposes. The purpose of the planned own research was to determine the diversity of the mycobiota present on supervised and unsupervised sandy beaches, on the shores of lakes, of municipal baths used for recreation. The research material consisted of microfungi isolated from April to October 2019 from sandy beaches of supervised and unsupervised lakes located within the administrative boundaries of the city of Olsztyn (North-Eastern Poland, Europe). Four lakes, out of the fifteen available (Tyrsko, Kortowskie, Skanda, and Ukiel), whose bathing waters are subjected to routine bacteriological tests, were selected for testing. To compare the diversity of the mycobiota composition on the surface and below the sand mixing layer, samples were taken from two depths (10 cm and 50 cm), using a soil auger. Micro-fungi from sand samples were obtained by surface inoculation on an RBC medium from the 1st dilution (1:10). After incubation at 25°C for 96-144 h, the average number of CFU/dm³ was counted. Morphologically differing yeast colonies were passaged into Sabouraud agar slants with gentamicin and incubated again. For detailed laboratory analyses, culture methods (macro- and micro-cultures) and identification methods recommended in diagnostic mycological laboratories were used. The conducted research allowed obtaining 140 yeast isolates. The total average population ranged from 1.37 × 10⁻² CFU/dm³ before the bathing season (April 2019), 1.64 × 10⁻³ CFU/dm³ in the season (May-September 2019), and 1.60 × 10⁻² CFU/dm³ after the end of the season (October 2019). More microfungi were obtained from the surface layer of sand (100 isolates) than from the deeper layer (40 isolates). Reported microfungi may circulate seasonally between individual elements of the lake ecosystem. From the sand/soil from the catchment area beaches, they can get into bathing waters, stopping periodically on the coastal phyllosphere. The sand of the beaches and the phyllosphere are a kind of filter for the water reservoir. The presence of microfungi with various pathogenicity potential in these places is of major epidemiological importance. Therefore, full monitoring of not only recreational waters but also sandy beaches should be treated as an element of constant control by appropriate supervisory institutions, allowing recreational areas for public use so that the use of these places does not involve the risk of infection. Acknowledgment: 'Development Program of the University of Warmia and Mazury in Olsztyn', POWR.03.05.00-00-Z310/17, co-financed by the European Union under the European Social Fund from the Operational Program Knowledge Education Development. Tomasz Bałabański is a recipient of a scholarship from the Programme Interdisciplinary Doctoral Studies in Biology and Biotechnology (POWR.03.05.00-00-Z310/17), which is funded by the 'European Social Fund'.

Keywords: beach, microfungi, sand, yeasts

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Authors: Andrew Laming, John Hattie, Mark Wilson

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Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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Authors: Sara Mosteller, Larissa K. Samuelson, Sobanawartiny Wijeakumar, John P. Spencer

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This study was designed to examine how humans are able to teach and learn semantic information as well as cooperate in order to jointly achieve sophisticated goals. Specifically, we are measuring individual differences in how these abilities develop from foundational building blocks in early childhood. The current study adopts a paradigm for novel noun learning developed by Samuelson, Smith, Perry, and Spencer (2011) to a hyperscanning paradigm [Cui, Bryant and Reiss, 2012]. This project measures coordinated brain activity between a parent and child using simultaneous functional near infrared spectroscopy (fNIRS) in pairs of 2.5, 3.5 and 4.5-year-old children and their parents. We are also separately testing pairs of adult friends. Children and parents, or adult friends, are seated across from one another at a table. The parent (in the developmental study) then teaches their child the names of novel toys. An experimenter then tests the child by presenting the objects in pairs and asking the child to retrieve one object by name. Children are asked to choose from both pairs of familiar objects and pairs of novel objects. In order to explore individual differences in cooperation with the same participants, each dyad plays a cooperative game of Jenga, in which their joint score is based on how many blocks they can remove from the tower as a team. A preliminary analysis of the noun-learning task showed that, when presented with 6 word-object mappings, children learned an average of 3 new words (50%) and that the number of objects learned by each child ranged from 2-4. Adults initially learned all of the new words but were variable in their later retention of the mappings, which ranged from 50-100%. We are currently examining differences in cooperative behavior during the Jenga playing game, including time spent discussing each move before it is made. Ongoing analyses are examining the social dynamics that might underlie the differences between words that were successfully learned and unlearned words for each dyad, as well as the developmental differences observed in the study. Additionally, the Jenga game is being used to better understand individual and developmental differences in social coordination during a cooperative task. At a behavioral level, the analysis maps periods of joint visual attention between participants during the word learning and the Jenga game, using head-mounted eye trackers to assess each participant’s first-person viewpoint during the session. We are also analyzing the coherence in brain activity between participants during novel word-learning and Jenga playing. The first hypothesis is that visual joint attention during the session will be positively correlated with both the number of words learned and with the number of blocks moved during Jenga before the tower falls. The next hypothesis is that successful communication of new words and success in the game will each be positively correlated with synchronized brain activity between the parent and child/the adult friends in cortical regions underlying social cognition, semantic processing, and visual processing. This study probes both the neural and behavioral mechanisms of learning and cooperation in a naturalistic, interactive and developmental context.

Keywords: communication, cooperation, development, interaction, neuroscience

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Authors: Joanna Marie A. Paulino-Morente, Vaneza Valentina L. Penolio, Grace Sabado

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Ovarian cancer is extremely hard to diagnose in its early stages, and those afflicted at the time of diagnosis are typically asymptomatic and in the late stages of the disease, with metastasis to other organs. Ovarian cancers often occur sporadically, with only 5% associated with hereditary mutations. Mutations in the BRCA1 and BRCA2 tumor suppressor genes have been found to be responsible for the majority of hereditary ovarian cancers. One type of ovarian tumor is Malignant Mixed Mullerian Tumor (MMMT), which is a very rare and aggressive type, accounting for only 1% of all ovarian cancers. Reported is a case of a 43-year-old G3P3 (3003), who came into our institution due to a 2-month history of difficulty of breathing. Family history reveals that her eldest and younger sisters both died of ovarian malignancy, with her younger sister having a histopathology report of endometrioid ovarian carcinoma, left ovary stage IIIb. She still has 2 asymptomatic sisters. Physical examination pointed to pleural effusion of right lung, and presence of bilateral ovarian new growth, which had a Sassone score of 13. Admitting Diagnosis was G3P3 (3003), Ovarian New Growth, bilateral, Malignant; Pleural effusion secondary to malignancy. BRCA was requested to establish a hereditary mutation; however, the patient had no funds. Once the patient was stabilized, TAHBSO with surgical staging was performed. Intraoperatively, the pelvic cavity was occupied by firm, irregularly shaped ovaries, with a colorectal metastasis. Microscopic sections from both ovaries and the colorectal metastasis had pleomorphic tumor cells lined by cuboidal to columnar epithelium exhibiting glandular complexity, displaying nuclear atypia and increased nuclear-cytoplasmic ratio, which are infiltrating the stroma, consistent with the features of Malignant Mixed Mullerian Tumor, since MMMT is composed histologically of malignant epithelial and sarcomatous elements. In conclusion, discussed is the clinic-pathological feature of a patient with primary ovarian Malignant Mixed Mullerian Tumor, a rare malignancy comprising only 1% of all ovarian neoplasms. Also, by understanding the hereditary ovarian cancer syndromes and its relation to this patient, it cannot be overemphasized that a comprehensive family history is really fundamental for early diagnosis. The familial association of the disease, given that the patient has two sisters who were diagnosed with an advanced stage of ovarian cancer and succumbed to the disease at a much earlier age than what is reported in the general population, points to a possible hereditary syndrome which occurs in only 5% of ovarian neoplasms. In a low-resource setting, being in a third world country, the following will be recommended for monitoring and/or screening women who are at high risk for developing ovarian cancer, such as the remaining sisters of the patient: 1) Physical examination focusing on the breast, abdomen, and rectal area every 6 months. 2) Transvaginal sonography every 6 months. 3) Mammography annually. 4) CA125 for postmenopausal women. 5) Genetic testing for BRCA1 and BRCA2 will be reserved for those who are financially capable.

Keywords: BRCA, hereditary breast-ovarian cancer syndrome, malignant mixed mullerian tumor, ovarian cancer

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 46

Authors: Zofija Tupikovskaja-Omovie, David Tyler, Sam Dhanapala, Steve Hayes

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The UK is leading in online retail and mobile adoption. However, there is a dearth of information relating to mobile apparel retail, and developing an understanding about consumer browsing and purchase behavior in m-retail channel would provide apparel marketers, mobile website and app developers with the necessary understanding of consumers’ needs. Despite the rapid growth of mobile retail businesses, no published study has examined shopping behaviour on fashion mobile websites and apps. A mixed method approach helped to understand why fashion consumers prefer websites on mobile devices, when mobile apps are also available. The following research methods were employed: survey, eye-tracking experiments, observation, and interview with retrospective think aloud. The mobile gaze tracking device by SensoMotoric Instruments was used to understand frustrations in navigation and other issues facing consumers in mobile channel. This method helped to validate and compliment other traditional user-testing approaches in order to optimize user experience and enhance the development of mobile retail channel. The study involved eight participants - females aged 18 to 35 years old, who are existing mobile shoppers. The participants used the Topshop mobile app and website on a smart phone to complete a task according to a specified scenario leading to a purchase. The comparative study was based on: duration and time spent at different stages of the shopping journey, number of steps involved and product pages visited, search approaches used, layout and visual clues, as well as consumer perceptions and expectations. The results from the data analysis show significant differences in consumer behaviour when using a mobile app or website on a smart phone. Moreover, two types of problems were identified, namely technical issues and human errors. Having a mobile app does not guarantee success in satisfying mobile fashion consumers. The differences in the layout and visual clues seem to influence the overall shopping experience on a smart phone. The layout of search results on the website was different from the mobile app. Therefore, participants, in most cases, behaved differently on different platforms. The number of product pages visited on the mobile app was triple the number visited on the website due to a limited visibility of products in the search results. Although, the data on traffic trends held by retailers to date, including retail sector breakdowns for visits and views, data on device splits and duration, might seem a valuable source of information, it cannot explain why consumers visit many product pages, stay longer on the website or mobile app, or abandon the basket. A comprehensive list of pros and cons was developed by highlighting issues for website and mobile app, and recommendations provided. The findings suggest that fashion retailers need to be aware of actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added to which is the challenge of retaining existing and acquiring new customers. There seem to be differences in the way fashion consumers search and shop on mobile, which need to be explored in further studies.

Keywords: consumer behavior, eye-tracking technology, fashion retail, mobile app, m-retail, smart phones, topshop, user experience, website

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Authors: Marie-Helena Docherty, Sion Edryd Williams

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The prevalence of diabetes mellitus is increasing worldwide. In Sub-Saharan Africa, type 2 diabetes represents over 90% of all types of diabetes with the number of diabetic patients expected to rise. This represents a huge economic burden in an area already contending with high rates of other significant diseases, including the highest worldwide prevalence of HIV. Diabetic complications considerably impact on morbidity and mortality. The epidemiological data for the region quotes high rates of retinopathy (7-63%), neuropathy (27-66%) and microalbuminuria (10-83%). It is therefore imperative that diabetic screening programmes are established. It is recognised that in many parts of the developing world the implementation and management of such programmes is limited by a lack of available resources. The International Diabetes Federation produced guidelines in 2012 taking these limitations into account suggesting that all diabetic patients should have access to basic screening. These guidelines are consistent with the national diabetic guidelines produced by the Lesotho Medical Council. However, diabetic care in Lesotho is delivered at the local level, with variable levels of quality. A cross sectional study was performed in the outpatient department of Maluti Hospital in Mapoteng, Lesotho, a busy rural hospital in the Berea district. Demographic data on gender, age and modality of treatment were collected over a six-week time period. Information regarding 3 basic screening parameters was obtained. These parameters included eye screening (defined as a documented ophthalmology review within the last 12 months), foot screening (defined as a documented foot health assessment by any health care professional within the last 12 months) and secondary prevention (defined as a documented blood pressure and lipid profile reading within the last 12 months). These parameters were selected on the basis of the absolute minimum level of resources in Maluti Hospital. Renal screening was excluded, as the hospital does not have access to reliable renal profile checks or urinalysis. There is however a fully functioning on-site ophthalmology department run by a senior ophthalmologist with the ability to provide retinal photography, retinal surgery and photocoagulation therapy. Data was collected on 183 type 2 diabetics. 112 patients were male and 71 were female. The average age was 43 years. 4 patients were diet controlled, 140 patients were on oral hypoglycaemic agents (metformin and/or glibenclamide), and 39 patients were on a combination of insulin and oral hypoglycaemics. In the preceding 12 months, 5 patients had undergone eye screening (3%), 24 patients had undergone foot screening (13%), and 31 patients had lipid profile testing (17%). All patients had a documented blood pressure reading (100%). Our results show that screening is poorly performed in the basic indicators suggested by the IDF and the Lesotho Medical Council. On the basis of these results, a screening programme was developed using the mnemonic SaFE; secondary prevention, foot and eye care. This is simple, memorable and transferable between healthcare professionals. In the future, the expectation would be to expand upon this current programme to include renal screening, and to further develop screening pertaining to secondary prevention.

Keywords: Africa, complications, rural, screening

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Authors: Evans Oteng, Clement Yeboah, Alexander Otechere-Fianko

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In today’s economy, despite achievements and advances in the banking and financial institutions, there are challenges that will require intensive attempts on the portion of the banks in Ghana. The perceived decline in profitability of banks seems to have emanated from ineffective branding. Hence, the purpose of this quantitative descriptive-correlational study was to examine the effects of branding on the profitability of banks in Ghana. The researchers purposively sampled some 116 banks in Ghana. Self-developed Likert scale questionnaires were administered to the finance officers of the financial institutions. The results were found to be statistically significant, F (1, 114) = 4. 50, p = .036. This indicates that those banks in Ghana with good branding practices have strong marketing tools to identify and sell their products and services and, as such, have a big market share. The correlation coefficients indicate that branding has a positive correlation with profitability and are statistically significant (r=.207, p<0.05), which signifies that as branding increases, the return on equity’s profitability indicator improves and vice versa. Future researchers can consider other factors beyond branding, such as online banking. The study has significant implications for the success and competitive advantage of those banks that effective branding allows them to differentiate themselves from their competitors. A strong and unique brand identity can help a bank stand out in a crowded market, attract customers, and build customer loyalty. This can lead to increased market share and profitability. Branding influences customer perception and trust. A well-established and reputable brand can create a positive image in the minds of customers, enhancing their confidence in the bank's products and services. This can result in increased customer acquisition, customer retention and a positive impact on profitability. Banks with strong brands can leverage their reputation and customer trust to cross-sell additional products and services. When customers have confidence in the brand, they are more likely to explore and purchase other offerings from the same institution. Cross-selling can boost revenue streams and profitability. Successful branding can open up opportunities for brand extensions and diversification into new products or markets. Banks can leverage their trusted brand to introduce new financial products or expand their presence into related areas, such as insurance or investment services. This can lead to additional revenue streams and improved profitability. This study can have implications for education. Thus, increased profitability of banks due to effective branding can result in higher financial resources available for corporate social responsibility (CSR) activities. Banks may invest in educational initiatives, such as scholarships, grants, research projects, and sponsorships, to support the education sector in Ghana. Also, this study can have implications for logistics and supply chain management. Thus, strong branding can create trust and credibility among customers, leading to increased customer loyalty. This loyalty can positively impact the bank's relationships with its suppliers and logistics partners. It can result in better negotiation power, improved supplier relationships, and enhanced supply chain coordination, ultimately leading to more efficient and cost-effective logistics operations.

Keywords: branding, profitability, competitors, customer loyalty, customer retention, corporate social responsibility, cost-effective, logistics operations

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Authors: Aberdam Edith, Sangari Linda, Petit Isabelle, Aberdam Daniel

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Background and Rationale: Transparent avascularised cornea is essential for normal vision and depends on limbal stem cells (LSC) that reside between the cornea and the conjunctiva. Ocular burns or injuries may destroy the limbus, causing limbal stem cell deficiency (LSCD). The cornea becomes vascularised by invaded conjunctival cells, the stroma is scarring, resulting in corneal opacity and loss of vision. Grafted autologous limbus or cultivated autologous LCS can restore the vision, unless the two eyes are affected. Alternative cellular sources have been tested in the last decades, including oral mucosa or hair follicle epithelial cells. However, only partial success has been achieved by the use of these cells since they were not able to uniformly commit into corneal epithelial cells. Human pluripotent stem cells (iPSC) display both unlimited growth capacity and ability to differentiate into any cell type. Our goal was to design a standardized and reproducible protocol to produce transplantable autologous LSC from patients through cell reprogramming technology. Methodology: First, keratinocyte primary culture was established from a small number of plucked hair follicles of healthy donors. The resulting epithelial cells were reprogrammed into induced pluripotent stem cells (iPSCs) and further differentiate into corneal epithelial cells (CEC), according to a robust protocol that recapitulates the main step of corneal embryonic development. qRT-PCR analysis and immunofluorescent staining during the course of differentiation confirm the expression of stage specific markers of corneal embryonic lineage. First appear ectodermal progenitor-specific cytokeratins K8/K18, followed at day 7 by limbal-specific PAX6, TP63 and cytokeratins K5/K14. At day 15, K3/K12+-corneal cells are present. To amplify the iPSC-derived LSC (named COiPSC), intact small epithelial colonies were detached and cultivated in limbal cell-specific medium. In that culture conditions, the COiPSC can be frozen and thaw at any passage, while retaining their corneal characteristics for at least eight passages. To evaluate the potential of COiPSC as an alternative ocular toxicity model, COiPSC were treated at passage P0 to P4 with increasing amounts of SDS and Benzalkonium. Cell proliferation and apoptosis of treated cells was compared to LSC and the SV40-immortalized human corneal epithelial cell line (HCE) routinely used by cosmetological industrials. Of note, HCE are more resistant to toxicity than LSC. At P0, COiPSC were systematically more resistant to chemical toxicity than LSC and even to HCE. Remarkably, this behavior changed with passage since COiPSC at P2 became identical to LSC and thus closer to physiology than HCE. Comparative transcriptome analysis confirmed that COiPSC from P2 are similar to a mixture of LSC and CEC. Finally, by organotypic reconstitution assay, we demonstrated the ability of COiPSC to produce a 3D corneal epithelium on a stromal equivalent made of keratocytes. Conclusion: COiPSC could become valuable for two main applications: (1) an alternative robust tool to perform, in a reproducible and physiological manner, toxicity assays for cosmetic products and pharmacological tests of drugs. (2). COiPSC could become an alternative autologous source for cornea transplantation for LSCD.

Keywords: Limbal stem cell deficiency, iPSC, cornea, limbal stem cells

Procedia PDF Downloads 389

Authors: Fabio Rodriguez Sanchez, Josef Bruers, Iciar Arteagoitia, Carlos Rodriguez Andres

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Background: Oral implants are a routine treatment to replace lost teeth. Although they have a high rate of success, implant failures do occur. Perioperative antibiotics have been suggested to prevent postoperative infections and dental implant failures, but they remain a controversial treatment among healthy patients. The objective of this study was to determine whether antibiotic prophylaxis is a common treatment in the Netherlands among general dentists, maxillofacial-surgeons, periodontists and implantologists in conjunction with oral implant surgery among healthy patients and to assess the nature of antibiotics prescriptions in order to evaluate whether any consensus has been reached and the current recommendations are being followed. Methodology: Observational cross-sectional study based on a web-survey reported according to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines. A validated questionnaire, developed by Deeb et al. (2015), was translated and slightly adjusted to circumstances in the Netherlands. It was used with the explicit permission of the authors. This questionnaire contained both close-ended and some open-ended questions in relation to the following topics: demographics, qualification, antibiotic type, prescription-duration and dosage. An email was sent February 2018 to a sample of 600 general dentists and all 302 oral implantologists, periodontists and maxillofacial surgeons who were recognized by the Dutch Association of Oral Implantology (NVOI) as oral health care providers placing oral implants. The email included a brief introduction about the study objectives and a link to the web questionnaire, which could be filled in anonymously. Overall, 902 questionnaires were sent. However, 29 questionnaires were not correctly received due to an incorrect email address. So a total number of 873 professionals were reached. Collected data were analyzed using SPSS (IBM Corp., released 2012, Armonk, NY). Results: The questionnaire was sent back by a total number of 218 participants (response rate=24.2%), 45 female (20.8%) and 171 male (79.2%). Two respondents were excluded from the study group because they were not currently working as oral health providers. Overall 151 (69.9%) placed oral implants on regular basis. Approximately 79 (52.7%) of these participants prescribed antibiotics only in determined situations, 66 (44.0%) prescribed antibiotics always and 5 dentists (3.3%) did not prescribe antibiotics at all when placing oral implants. Overall, 83 participants who prescribed antibiotics, did so both pre- and postoperatively (58.5%), 12 exclusively postoperative (8.5%), and 47 followed an exclusive preoperative regime (33.1%). A single dose of 2,000 mg amoxicillin orally 1-hour prior treatment was the most prescribed preoperative regimen. The most frequent prescribed postoperative regimen was 500 mg amoxicillin three times daily for 7 days after surgery. On average, oral health professionals prescribed 6,923 mg antibiotics in conjunction with oral implant surgery, varying from 500 to 14,600 mg. Conclusions: Antibiotic prophylaxis in conjunction with oral implant surgery is prescribed in the Netherlands on a rather large scale. Dutch professionals might prescribe antibiotics more cautiously than in other countries and there seems to be a lower range on the different antibiotic types and regimens being prescribed. Anyway, recommendations based on last-published evidence are frequently not being followed.

Keywords: clinical decision making, infection control, antibiotic prophylaxis, dental implants

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Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

Procedia PDF Downloads 105

Authors: Arfanara Najnin, Michael W. Roach, Jr., Dr. Jianhong Cecilia Xia

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The SkyCar Rapid Transit System (SRT) is an innovative intelligent transport system for the sustainable urban transport system. This system will increase the urban area network connectivity and decrease urban area traffic congestion. The SRT system is designed as a suspended Personal Rapid Transit (PRT) system that travels under a guideway 5m above the ground. A driver-less passenger is via pod-cars that hang from slender beams supported by columns that replace existing lamp posts. The beams are setup in a series of interconnecting loops providing non-stop travel from beginning to end to assure journey time. The SRT forward movement is effected by magnetic motors built into the guideway. Passenger stops are at either at line level 5m above the ground or ground level via a spur guideway that curves off the main thoroughfare. The main objective of this paper is to propose an integrated Automated Transit Network (ATN) technology for the future intelligent transport system in the urban built environment. To fulfil the objective a 4D simulated model in the urban built environment has been proposed by using the concept of SRT-ATN system. The methodology for the design, construction and testing parameters of a Technology Demonstrator (TD) for proof of concept and a Simulator (S) has been demonstrated. The completed TD and S will provide an excellent proving ground for the next development stage, the SRT Prototype (PT) and Pilot System (PS). This paper covered by a 4D simulated model in the virtual built environment is to effectively show how the SRT-ATN system works. OpenSim software has been used to develop the model in a virtual environment, and the scenario has been simulated to understand and visualize the proposed SkyCar Rapid Transit Network model. The SkyCar system will be fabricated in a modular form which is easily transported. The system would be installed in increasingly congested city centers throughout the world, as well as in airports, tourist resorts, race tracks and other special purpose for the urban community. This paper shares the lessons learnt from the proposed innovation and provides recommendations on how to improve the future transport system in urban built environment. Safety and security of passengers are prime factors to be considered for this transit system. Design requirements to meet the safety needs to be part of the research and development phase of the project. Operational safety aspects would also be developed during this period. The vehicles, the track and beam systems and stations are the main components that need to be examined in detail for safety and security of patrons. Measures will also be required to protect columns adjoining intersections from errant vehicles in vehicular traffic collisions. The SkyCar Rapid Transit takes advantage of all current disruptive technologies; batteries, sensors and 4G/5G communication and solar energy technologies which will continue to reduce the costs and make the systems more profitable. SkyCar's energy consumption is extremely low compared to other transport systems.

Keywords: SkyCar, rapid transit, Intelligent Transport System (ITS), Automated Transit Network (ATN), urban built environment, 4D Visualization, smart city

Procedia PDF Downloads 195

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

Abstract:

Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Suikinai Nobre Santos, Ranko Gacesa, Paul F. Long, Itamar Soares de Melo

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Extremophilic microorganism are adapted to biotopes combining several stress factors (temperature, pressure, radiation, salinity and pH), which indicate the richness valuable resource for the exploitation of novel biotechnological processes and constitute unique models for investigations their biomolecules (1, 2). The above information encourages us investigate bioprospecting synthesized compounds by a noval actinomycete, designated thermotolerant Streptomyces caatingaensis CMAA 1322, isolated from sample soil tropical dry forest (Caatinga) in the Brazilian semiarid region (3-17°S and 35-45°W). This set of constrating physical and climatic factores provide the unique conditions and a diversity of well adapted species, interesting site for biotechnological purposes. Preliminary studies have shown the great potential in the production of cytotoxic, pesticidal and antimicrobial molecules (3). Thus, to extend knowledge of the genes clusters responsible for producing biosynthetic pathways of natural products in strain CMAA1322, whole-genome shotgun (WGS) DNA sequencing was performed using paired-end long sequencing with PacBio RS (Pacific Biosciences). Genomic DNA was extracted from a pure culture grown overnight on LB medium using the PureLink genomic DNA kit (Life Technologies). An approximately 3- to 20-kb-insert PacBio library was constructed and sequenced on an 8 single-molecule real-time (SMRT) cell, yielding 116,269 reads (average length, 7,446 bp), which were allocated into 18 contigs, with 142.11x coverage and N50 value of 20.548 bp (BioProject number PRJNA288757). The assembled data were analyzed by Rapid Annotations using Subsystems Technology (RAST) (4) the genome size was found to be 7.055.077 bp, comprising 6167 open reading frames (ORFs) and 413 subsystems. The G+C content was estimated to be 72 mol%. The closest-neighbors tool, available in RAST through functional comparison of the genome, revealed that strain CMAA1322 is more closely related to Streptomyces hygroscopicus ATCC 53653 (similarity score value, 537), S. violaceusniger Tu 4113 (score value, 483), S. avermitilis MA-4680 (score value, 475), S. albus J1074 (score value, 447). The Streptomyces sp. CMAA1322 genome contains 98 tRNA genes and 135 genes copies related to stress response, mainly osmotic stress (14), heat shock (16), oxidative stress (49). Functional annotation by antiSMASH version 3.0 (5) identified 41 clusters for secondary metabolites (including two clusters for lanthipeptides, ten clusters for nonribosomal peptide synthetases [NRPS], three clusters for siderophores, fourteen for polyketide synthetase [PKS], six clusters encoding a terpene, two clusters encoding a bacteriocin, and one cluster encoding a phenazine). Our work provide in comparative analyse of genome and extract produced (data no published) by lineage CMAA1322, revealing the potential of microorganisms accessed from extreme environments as Caatinga” to produce a wide range of biotechnological relevant compounds.

Keywords: caatinga, streptomyces, environmental stresses, biosynthetic pathways

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Authors: Nahla Elsherbiny, Ahmed Ahmed, Hamada Mohammed, Mohamed Ali

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Background: The enterococci may be considered as opportunistic agents particularly in immunocompromised patients. It is one of the top three pathogens causing many healthcare associated infections (HAIs). Resistance to several commonly used antimicrobial agents is a remarkable characteristic of most species which may carry various genes contributing to virulence. Objectives: to determine the prevalence of enterococci species in different intensive care units (ICUs) causing health care-associated infections (HAIs), intestinal carriage and environmental contamination. Also, to study the antimicrobial susceptibility pattern of the isolates with special reference to vancomycin resistance. In addition to phenotypic and genotypic detection of gelatinase, cytolysin and biofilm formation among isolates. Patients and Methods: This study was carried out in the infection control laboratory at Assiut University Hospitals over a period of one year. Clinical samples were collected from 285 patients with various (HAIs) acquired after admission to different ICUs. Rectal swabs were taken from 14 cases for detection of enterococci carriage. In addition, 1377 environmental samples were collected from the surroundings of the patients. Identification was done by conventional bacteriological methods and confirmed by analytical profile index (API). Antimicrobial sensitivity testing was performed by Kirby Bauer disc diffusion method and detection of vancomycin resistance was done by agar screen method. For the isolates, phenotypic detection of cytolysin, gelatinase production and detection of biofilm by tube method, Congo red method and microtiter plate. We performed polymerase chain reaction (PCR) for detection of some virulence genes (gelE, cylA, vanA, vanB and esp). Results: Enterococci caused 10.5% of the HAIs. Respiratory tract infection was the predominant type (86.7%). The commonest species were E.gallinarum (36.7%), E.casseliflavus (30%), E.faecalis (30%), and E.durans (3.4 %). Vancomycin resistance was detected in a total of 40% (12/30) of those isolates. The risk factors associated with acquiring vancomycin resistant enterococci (VRE) were immune suppression (P= 0.031) and artificial feeding (P= 0.008). For the rectal swabs, enterococci species were detected in 71.4% of samples with the predominance of E. casseliflavus (50%). Most of the isolates were vancomycin resistant (70%). Out of a total 1377 environmental samples, 577 (42%) samples were contaminated with different microorganisms. Enterococci were detected in 1.7% (10/577) of total contaminated samples, 50% of which were vancomycin resistant. All isolates were resistant to penicillin, ampicillin, oxacillin, ciprofloxacin, amikacin, erythromycin, clindamycin and trimethoprim-sulfamethaxazole. For the remaining antibiotics, variable percentages of resistance were reported. Cytolysin and gelatinase were detected phenotypically in 16% and 48 % of the isolates respectively. The microtiter plate method showed the highest percentages of detection of biofilm among all isolated species (100%). The studied virulence genes gelE, esp, vanA and vanB were detected in 62%, 12%, 2% and 12% respectively, while cylA gene was not detected in any isolates. Conclusions: A significant percentage of enterococci was isolated from patients and environments in the ICUs. Many virulence factors were detected phenotypically and genotypically among isolates. The high percentage of resistance, coupled with the risk of cross transmission to other patients make enterococci infections a significant infection control issue in hospitals.

Keywords: antimicrobial resistance, enterococci, ICUs, virulence factors

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Authors: Bijit Kalita, K. V. N. Surendra

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The pulley works under both compressive loading due to contacting belt in tension and central torque due to cause rotation. In a power transmission system, the belt pulley assemblies offer a contact problem in the form of two mating cylindrical parts. In this work, we modeled a pulley as a heavy two-dimensional circular disk. Stress analysis due to contact loading in the pulley mechanism is performed. Finite element analysis (FEA) is conducted for a pulley to investigate the stresses experienced on its inner and outer periphery. In most of the heavy-duty applications, most frequently used mechanisms to transmit power in applications such as automotive engines, industrial machines, etc. is Belt Drive. Usually, very heavy circular disks are used as pulleys. A pulley could be entitled as a drum and may have a groove between two flanges around the circumference. A rope, belt, cable or chain can be the driving element of a pulley system that runs over the pulley inside the groove. A pulley is experienced by normal and shear tractions on its contact region in the process of motion transmission. The region may be belt-pulley contact surface or pulley-shaft contact surface. In 1895, Hertz solved the elastic contact problem for point contact and line contact of an ideal smooth object. Afterward, this hypothesis is generally utilized for computing the actual contact zone. Detailed stress analysis in such contact region of such pulleys is quite necessary to prevent early failure. In this paper, the results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. Based on the literature on contact stress problem induced in the wide field of applications, generated stress distribution on the shaft-pulley and belt-pulley interfaces due to the application of high-tension and torque was evaluated in this study using FEA concepts. Finally, the results obtained from ANSYS (APDL) were compared with the Hertzian contact theory. The study is mainly focused on the fatigue life estimation of a rotating part as a component of an engine assembly using the most famous Paris equation. Digital Image Correlation (DIC) analyses have been performed using the open-source software. From the displacement computed using the images acquired at a minimum and maximum force, displacement field amplitude is computed. From these fields, the crack path is defined and stress intensity factors and crack tip position are extracted. A non-linear least-squares projection is used for the purpose of the estimation of fatigue crack growth. Further study will be extended for the various application of rotating machinery such as rotating flywheel disk, jet engine, compressor disk, roller disk cutter etc., where Stress Intensity Factor (SIF) calculation plays a significant role on the accuracy and reliability of a safe design. Additionally, this study will be progressed to predict crack propagation in the pulley using maximum tangential stress (MTS) criteria for mixed mode fracture.

Keywords: crack-tip deformations, contact stress, stress concentration, stress intensity factor

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Authors: Guillaume Bélanger, Jean-Philippe Fontaine, Clémence Hauduc

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There is an undeniable thirst from organic chemists and from the pharmaceutical industry to access complex alkaloids with short syntheses. While medicinal chemists are interested in the fascinating wide range of biological properties of alkaloids, synthetic chemists are rather interested in finding new routes to access these challenging natural products of often low availability from nature. To synthesize complex polycyclic cores of natural products, reaction cascades or sequences performed one-pot offer a neat advantage over classical methods for their rapid increase in molecular complexity in a single operation. In counterpart, reaction cascades need to be run on substrates bearing all the required functional groups necessary for the key cyclizations. Chemoselectivity is thus a major issue associated with such a strategy, in addition to diastereocontrol and regiocontrol for the overall transformation. In the pursuit of synthetic efficiency, our research group developed an innovative one-pot transformation of linear substrates into bi- and tricyclic adducts applied to the construction of Aspidospermatan-type alkaloids. The latter is a rich class of indole alkaloids bearing a unique bridged azatricyclic core. Despite many efforts toward the synthesis of members of this family, efficient and versatile synthetic routes are still coveted. Indeed, very short, non-racemic approaches are rather scarce: for example, in the cases of aspidospermidine and aspidospermine, syntheses are all fifteen steps and over. We envisaged a unified approach to access several members of the Aspidospermatan alkaloids family. The key sequence features a highly chemoselective formamide activation that triggers a Vilsmeier-Haack cyclization, followed by an azomethine ylide generation and intramolecular cycloaddition. Despite the high density and variety of functional groups on the substrates (electron-rich and electron-poor alkenes, nitrile, amide, ester, enol ether), the sequence generated three new carbon-carbon bonds and three rings in a single operation with good yield and high chemoselectivity. A detailed study of amide, nucleophile, and dipolarophile variations to finally get to the successful combination required for the key transformation will be presented. To complete the indoline fragment of the natural products, we developed an original approach. Indeed, all reported routes to Aspidospermatan alkaloids introduce the indoline or indole early in the synthesis. In our work, the indoline needs to be installed on the azatricyclic core after the key cyclization sequence. As a result, typical Fischer indolization is not suited since this reaction is known to fail on such substrates. We thus envisaged a unique photocatalyzed decarboxylative radical cyclization. The development of this reaction as well as the scope and limitations of the methodology, will also be presented. The original Vilsmeier-Haack and azomethine ylide cyclization sequence as well as the new photocatalyzed decarboxylative radical cyclization will undoubtedly open access to new routes toward polycyclic indole alkaloids and derivatives of pharmaceutical interest in general.

Keywords: Aspidospermatan alkaloids, azomethine ylide cycloaddition, decarboxylative radical cyclization, indole and indoline synthesis, one-pot sequential cyclizations, photocatalysis, Vilsmeier-Haack Cyclization

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Authors: Byron Baron

Abstract:

Typical of the Mediterranean region, the Maltese islands exhibit calcareous soils containing low organic carbon content and high salinity, in addition to being relatively shallow. This has lead to the common practice of applying copious amounts of artificial fertilisers as well as other chemical inputs, together with the use of ground water having high salinity. Such intensive agricultural activities, over a prolonged time period, on such land has lead further to the loss of any soil fertility, together with direct negative impacts on the quality of fresh water reserves and the local ecosystem. The aim of this study was to investigate whether the natural resources on the island would be sufficient to apply ecological intensification i.e. the use of natural processes to replace anthropological inputs without any significant loss in food production. This was implementing through a sustainable agricultural system based on permaculture practices. Ecological intensification following permaculture principles was implemented for two years in order to capture the seasonal changes in duplicate. The areas dedicated to wild plants were only trimmed back to avoid excessive seeding but never mowing. A number of local staple crops were grown throughout this period, also in duplicate. Concomitantly, a number of practices were implemented following permaculture principles such as reducing land tilling, applying only natural fertiliser, mulching, monitoring of soil parameters using sensors, no use of herbicides or pesticides, and precision irrigation linked to a desalination system. Numerous environmental parameters were measured at regular intervals so as to quantify any improvements in ecological conditions. Crop output was also measured as kilos of produce per area. The results clearly show that over the two year period, the variety of wild plant species increased, the number of visiting pollinators increased, there were no pest infestations (although an increase in the number of pests was observed), and a slight improvement in overall soil health was also observed. This was obviously limited by the short duration of the testing implementation. Dedicating slightly less than 15% of total land area to wild plants in the form of borders around plots of crops assisted pollination and provided a foraging area for gleaning bats (measured as an increased number of feeding buzzes) whilst not giving rise to any pest infestations and no apparent yield losses or ill effects to the crops. Observed increases in crop yields were not significant. The study concluded that with the right support for the initial establishment of a healthy ecosystem and controlled intervention, the available natural resources on the island can substantially improve the condition of the local agricultural land area, resulting is a more prolonged economical output with greater ecological sustainability. That being said, more comprehensive and long-term monitoring is required in order to fully validate these results and design a sustainable agriculture system that truly achieves the best outcome for the Maltese context.

Keywords: ecological intensification, soil health, sustainable agriculture, permaculture

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Authors: O. Zlatkin-Troitschanskaia, J. Fischer, C. Lautenbach, H. A. Pant

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In 21st century higher education (HE), the diversity among students has increased in recent years due to the internationalization and higher mobility. Offering and providing equal and fair opportunities based on students’ individual skills and abilities instead of their social or cultural background is one of the major aims of HE. In this context, valid, objective and transparent assessments of students’ preconditions and academic competencies in HE are required. However, as analyses of the current states of research and practice show, a substantial research gap on assessment practices in HE still exists, calling for the development of effective solutions. These demands lead to significant conceptual and methodological challenges. Funded by the German Federal Ministry of Education and Research, the research program 'Modeling and Measuring Competencies in Higher Education – Validation and Methodological Challenges' (KoKoHs) focusses on addressing these challenges in HE assessment practice by modeling and validating objective test instruments. Including 16 cross-university collaborative projects, the German-wide research program contributes to bridging the research gap in current assessment research and practice by concentrating on practical and policy-related challenges of assessment in HE. In this paper, we present a differentiated overview of existing assessments of HE at the national and international level. Based on the state of research, we describe the theoretical and conceptual framework of the KoKoHs Program as well as results of the validation studies, including their key outcomes. More precisely, this includes an insight into more than 40 developed assessments covering a broad range of transparent and objective methods for validly measuring domain-specific and generic knowledge and skills for five major study areas (Economics, Social Science, Teacher Education, Medicine and Psychology). Computer-, video- and simulation-based instruments have been applied and validated to measure over 20,000 students at the beginning, middle and end of their (bachelor and master) studies at more than 300 HE institutions throughout Germany or during their practical training phase, traineeship or occupation. Focussing on the validity of the assessments, all test instruments have been analyzed comprehensively, using a broad range of methods and observing the validity criteria of the Standards for Psychological and Educational Testing developed by the American Educational Research Association, the American Economic Association and the National Council on Measurement. The results of the developed assessments presented in this paper, provide valuable outcomes to predict students’ skills and abilities at the beginning and the end of their studies as well as their learning development and performance. This allows for a differentiated view of the diversity among students. Based on the given research results practical implications and recommendations are formulated. In particular, appropriate and effective learning opportunities for students can be created to support the learning development of students, promote their individual potential and reduce knowledge and skill gaps. Overall, the presented research on competency assessment is highly relevant to national and international HE practice.

Keywords: 21st century skills, academic competencies, innovative assessments, KoKoHs

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