Search results for: SURF(Speed-Up Robust Features)

Authors: M. A. Brown, K. Hugill, D. Meredith

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Since the establishment of midwifery, as a professional identity in its own right, in the early years of the 20th century, midwifery-led models of childbirth have prevailed in many parts of the world. However, in many locations midwives’ scope of practice remains underdeveloped or absent. In Qatar, all births take place in hospital and are under the professional jurisdiction of obstetricians, predominately supported by internationally trained nurse-midwives and obstetric nurses. The strategic vision for health services in Qatar endorsed a desire to provide women with the ‘Best Care Always’ and the introduction of midwifery was seen as a way to achieve this. In 2015 the process of recruiting postgraduate educated Clinical Midwife Specialists from international sources began. The midwives were brought together to initiate an in hospital and community service transformation plan. This plan set out a series of wide-ranging actions to transform maternity and neonatal services to make care safer and give women more health choices. Change in any organization is a complex and dynamic process. This is made even more complex when multifaceted professional and cross cultural factors are involved. This presentation reports upon the motivations and challenges that exist and the progress around introducing a multicultural midwifery model of childbirth care in the state of Qatar. The paper examines and reflects upon the drivers and unique features of childbirth in the country. Despite accomplishments, progress still needs to be made in order to fully implement sustainable changes to further improve care and ensure women and neonates get the ‘Best Care Always’. The progress within the transformation plan highlights how midwifery may coexist with competing models of maternity care to create an innovative, eclectic and culturally sensitive paradigm that can best serve women and neonatal health needs.

Keywords: culture, managing change, midwifery, neonatal, service transformation plan

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Authors: Elitsa Kolentsova, Dimitar Dimitrov, Vasko Idakiev, Tatyana Tabakova, Krasimir Ivanov

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Formaldehyde production by selective oxidation of methanol is an important industrial process. The main by-products in the waste gas are CO and dimethyl ether (DME). The idea of this study is to combine the advantages of both Cu-Mn and Cu-Co catalytic systems by obtaining a new mixed Cu-Mn-Co catalyst with high activity and selectivity at the simultaneous oxidation of CO, methanol, and DME. Two basic Cu-Mn samples with high activity were selected for further investigation: (i) manganese-rich Cu-Mn/γ–Al2O3 catalyst with Cu/Mn molar ratio 1:5 and (ii) copper-rich Cu-Mn/γ-Al2O3 catalyst with Cu/Mn molar ratio 2:1. Manganese in these samples was replaced by cobalt in the whole concentration region, and catalytic properties were determined. The results show a general trend of decreasing the activity toward DME oxidation and increasing the activity toward CO and methanol oxidation with the increase of cobalt up to 60% for both groups of catalyst. This general trend, however, contains specific features, depending on the composition of the catalyst and the nature of the oxidized gas. The catalytic activity of the sample with Cu/(Mn+Co) molar ratio of 2:1 is gradually changed with increasing the cobalt content. The activity of the sample with Cu/(Mn+Co) molar ratio of 1: 5 passes through a maximum at 60% manganese replacement by cobalt, probably due to the formation of highly dispersed Co-based spinel structures (Co3O4 and/or MnCo2O4). In conclusion, the present study demonstrates that the Cu-Mn-Co/γ–alumina supported catalysts have enhanced activity toward CO, methanol and DME oxidation. Cu/(Mn+Co) molar ratio 1:5 and Co/Mn molar ratio 1.5 in the active component can ensure successful oxidation of CO, CH3OH and DME. The active component of the mixed Cu-Mn-Co/γ–alumina catalysts consists of at least six compounds - CuO, Co3O4, MnO2, Cu1.5Mn1.5O4, MnCo2O4 and CuCo2O4, depending on the Cu/Mn/Co molar ratio. Chemical composition strongly influences catalytic properties, this effect being quite variable with regards to the different processes.

Keywords: Cu-Mn-Co catalysts, oxidation, carbon oxide, VOCs

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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Authors: Tooran Tavangar, Masoud Hosseinpoor, Jeffrey S. Marshall, Ammar Yahia, Kamal Henri Khayat

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In this study, a four-way coupled CFD-DEM methodology was used to simulate the behavior of concrete pipe flow. Fresh concrete, characterized as a biphasic suspension, features aggregates comprising the solid-suspended phase with diverse particle-size distributions (PSD) within a non-Newtonian cement paste/mortar matrix forming the liquid phase. The fluid phase was simulated using CFD, while the aggregates were modeled using DEM. Interaction forces between the fluid and solid particles were considered through CFD-DEM computations. To capture the viscoelastic characteristics of the suspending fluid, a bi-viscous approach was adopted, incorporating a critical shear rate proportional to the yield stress of the mortar. In total, three diphasic suspensions were simulated, each featuring distinct particle size distributions and a concentration of 10% for five subclasses of spherical particles ranging from 1 to 17 mm in a suspending fluid. The adopted bi-viscous approach successfully simulated both un-sheared (plug flow) and sheared zones. Furthermore, shear-induced particle migration (SIPM) was assessed by examining coefficients of variation in particle concentration across the pipe. These SIPM values were then compared with results obtained using CFD-DEM under the Newtonian assumption. The study highlighted the crucial role of yield stress in the mortar phase, revealing that lower yield stress values can lead to increased flow rates and higher SIPM across the pipe.

Keywords: computational fluid dynamics, concrete pumping, coupled CFD-DEM, discrete element method, plug flow, shear-induced particle migration.

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

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Authors: Katarina Ott, Velibor Mačkić, Mihaela Bronić, Branko Stanić

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The determinants of national budget transparency have been widely discussed in the literature, while research on determinants of local budget transparency are scarce and empirically inconclusive, particularly in the new, fiscally centralised, EU member states. To fill the gap, we combine two strands of the literature: that concerned with public administration and public finance, shedding light on the economic and financial determinants of local budget transparency, and that on the political economy of transparency (principal agent theory), covering the relationships among politicians and between politicians and voters. Our main hypothesis states that variables describing residents’ capacity have a greater impact on local budget transparency than variables indicating the institutional capacity of local government units (LGUs). Additional subhypotheses test the impact of each variable analysed on local budget transparency. We address the determinants of local budget transparency in Croatia, measured by the number of key local budget documents published on the LGUs’ websites. By using a data set of 128 cities and 428 municipalities over the 2015-2017 period and by applying panel data analysis based on Poisson and negative binomial distribution, we test our main hypothesis and sub-hypotheses empirically. We measure different characteristics of institutional and residents’ capacity for each LGU. Age, education and ideology of the mayor/municipality head, political competition indicators, number of employees, current budget revenues and direct debt per capita have been used as a measure of the institutional capacity of LGU. Residents’ capacity in each LGU has been measured through the numbers of citizens and their average age as well as by average income per capita. The most important determinant of local budget transparency is average residents' income per capita at both city and municipality level. The results are in line with most previous research results in fiscally decentralised countries. In the context of a fiscally centralised country with numerous small LGUs, most of whom have low administrative and fiscal capacity, this has a theoretical rationale in the legitimacy and principal-agent theory (opportunistic motives of the incumbent). The result is robust and significant, but because of the various other results that change between city and municipality levels (e.g. ideology and political competition), there is a need for further research (both on identifying other determinates and/or methods of analysis). Since in Croatia the fiscal capacity of a LGU depends heavily on the income of its residents, units with higher per capita incomes in many cases have also higher budget revenues allowing them to engage more employees and resources. In addition, residents’ incomes might be also positively associated with local budget transparency because of higher citizen demand for such transparency. Residents with higher incomes expect more public services and have more access to and experience in using the Internet, and will thus typically demand more budget information on the LGUs’ websites.

Keywords: budget transparency, count data, Croatia, local government, political economy

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Authors: Oleg Redkin, Olga Bernikova

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Globalization and migrations have made cross-cultural contacts more frequent and intensive. Sometimes, these contacts may lead to misunderstanding between partners of communication and misinterpretations of the verbal messages that some researchers tend to consider as the 'clash of civilizations'. In most cases, reasons for that may be found in cultural and linguistic differences and hence misinterpretations of intentions and behavior. The current research examines factors of verbal and non-verbal communication that should be taken into consideration in verbal and non-verbal contacts. Language is one of the most important manifestations of the cultural code, and it is often considered as one of the special features of a civilization. The Arabic language, in particular, is commonly associated with Islam and the language and the Arab-Muslim civilization. It is one of the most important markers of self-identification for more than 200 million of native speakers. Arabic is the language of the Quran and hence the symbol of religious affiliation for more than one billion Muslims around the globe. Adequate interpretation of Arabic texts requires profound knowledge of its grammar, semantics of its vocabulary. Communicating sides who belong to different cultural groups are guided by different models of behavior and hierarchy of values, besides that the vocabulary each of them uses in the dialogue may convey different semantic realities and vary in connotations. In this context direct, literal translation in most cases cannot adequately convey the original meaning of the original message. Besides that peculiarities and diversities of the extralinguistic information, such as the body language, communicative etiquette, cultural background and religious affiliations may make the dialogue even more difficult. It is very likely that the so called 'clash of civilizations' in most cases is due to misinterpretation of counterpart's means of discourse such as language, cultural codes, and models of behavior rather than lies in basic contradictions between partners of communication. In the process of communication, one has to rely on universal values rather than focus on cultural or religious peculiarities, to take into account current linguistic and extralinguistic context.

Keywords: Arabic, civilization, discourse, language, linguistic

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Authors: Raj Chandran, Saul Datwyler, Jaime Marino, Daniel West, Karla Grasso, Adam Buss, Hina Syed, Zina Al Sahouri, Jennifer Yen, Krista Caudle, Beth McQuiston

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The Alinity i TBI test is Therapeutic Goods Administration (TGA) registered and is a panel of in vitro diagnostic chemiluminescent microparticle immunoassays for the measurement of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) in plasma and serum. The Alinity i TBI performance was evaluated in a multi-center pivotal study to demonstrate the capability to assist in determining the need for a CT scan of the head in adult subjects (age 18+) presenting with suspected mild TBI (traumatic brain injury) with a Glasgow Coma Scale score of 13 to 15. TBI has been recognized as an important cause of death and disability and is a growing public health problem. An estimated 69 million people globally experience a TBI annually1. Blood-based biomarkers such as glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) have shown utility to predict acute traumatic intracranial injury on head CT scans after TBI. A pivotal study using prospectively collected archived (frozen) plasma specimens was conducted to establish the clinical performance of the TBI test on the Alinity i system. The specimens were originally collected in a prospective, multi-center clinical study. Testing of the specimens was performed at three clinical sites in the United States. Performance characteristics such as detection limits, imprecision, linearity, measuring interval, expected values, and interferences were established following Clinical and Laboratory Standards Institute (CLSI) guidance. Of the 1899 mild TBI subjects, 120 had positive head CT scan results; 116 of the 120 specimens had a positive TBI interpretation (Sensitivity 96.7%; 95% CI: 91.7%, 98.7%). Of the 1779 subjects with negative CT scan results, 713 had a negative TBI interpretation (Specificity 40.1%; 95% CI: 37.8, 42.4). The negative predictive value (NPV) of the test was 99.4% (713/717, 95% CI: 98.6%, 99.8%). The analytical measuring interval (AMI) extends from the limit of quantitation (LoQ) to the upper LoQ and is determined by the range that demonstrates acceptable performance for linearity, imprecision, and bias. The AMI is 6.1 to 42,000 pg/mL for GFAP and 26.3 to 25,000 pg/mL for UCH-L1. Overall, within-laboratory imprecision (20 day) ranged from 3.7 to 5.9% CV for GFAP and 3.0 to 6.0% CV for UCH-L1, when including lot and instrument variances. The Alinity i TBI clinical performance results demonstrated high sensitivity and high NPV, supporting the utility to assist in determining the need for a head CT scan in subjects presenting to the emergency department with suspected mild TBI. The GFAP and UCH-L1 assays show robust analytical performance across a broad concentration range of GFAP and UCH-L1 and may serve as a valuable tool to help evaluate TBI patients across the spectrum of mild to severe injury.

Keywords: biomarker, diagnostic, neurology, TBI

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Authors: Mudassir Ghafoor, Irsalan Arif, Shuaib Salamat

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This paper presents modeling and analysis of different intake bump (compression surface) configurations and comparison with an existing supersonic aircraft having bump intake configuration. Many successful aircraft models have shown that Diverter less Supersonic Inlet (DSI) as compared to conventional intake can reduce weight, complexity and also maintenance cost. The research is divided into two parts. In the first part, four different intake bumps are modeled for comparative analysis keeping in view the consistency of outer perimeter dimensions of fighter aircraft and various characteristics such as flow behavior, boundary layer diversion and pressure recovery are analyzed. In the second part, modeled bumps are integrated with intake duct for performance analysis and comparison with existing supersonic aircraft data is carried out. The bumps are named as uniform large (Config 1), uniform small (Config 2), uniform sharp (Config 3), non-uniform (Config 4) based on their geometric features. Analysis is carried out at different Mach Numbers to analyze flow behavior in subsonic and supersonic regime. Flow behavior, boundary layer diversion and Pressure recovery are examined for each bump characteristics, and comparative study is carried out. The analysis reveals that at subsonic speed, Config 1 and Config 2 give similar pressure recoveries as diverterless supersonic intake, but difference in pressure recoveries becomes significant at supersonic speed. It was concluded from research that Config 1 gives better results as compared to Config 3. Also, higher amplitude (Config 1) is preferred over lower (Config 2 and 4). It was observed that maximum height of bump is preferred to be placed near cowl lip of intake duct.

Keywords: bump intake, boundary layer, computational fluid dynamics, diverter-less supersonic inlet

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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Authors: Frea Van Steenweghen, Lander Hollevoet, Johan A. Martens

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Compared to other hydrogen (H₂) carriers, ammonia (NH₃) is one of the most promising carriers as it contains 17.6 wt% hydrogen. It is easily liquefied at ≈ 9–10 bar pressure at ambient temperature. More importantly, NH₃ is a carbon-free hydrogen carrier with no CO₂ emission at final decomposition. Ammonia has a well-defined regulatory framework and a good track record regarding safety concerns. Furthermore, the industry already has an existing transport infrastructure consisting of pipelines, tank trucks and shipping technology, as ammonia has been manufactured and distributed around the world for over a century. While NH₃ synthesis and transportation technological solutions are at hand, a missing link in the hydrogen delivery scheme from ammonia is an energy-lean and efficient technology for cracking ammonia into H₂ and N₂. The most explored option for ammonia decomposition is thermo-catalytic cracking which is, by itself, the most energy-efficient approach compared to other technologies, such as plasma and electrolysis, as it is the most energy-lean and robust option. The decomposition reaction is favoured only at high temperatures (> 300°C) and low pressures (1 bar) as the thermocatalytic ammonia cracking process is faced with thermodynamic limitations. At 350°C, the thermodynamic equilibrium at 1 bar pressure limits the conversion to 99%. Gaining additional conversion up to e.g. 99.9% necessitates heating to ca. 530°C. However, reaching thermodynamic equilibrium is infeasible as a sufficient driving force is needed, requiring even higher temperatures. Limiting the conversion below the equilibrium composition is a more economical option. Thermocatalytic ammonia cracking is documented in scientific literature. Among the investigated metal catalysts (Ru, Co, Ni, Fe, …), ruthenium is known to be most active for ammonia decomposition with an onset of cracking activity around 350°C. For establishing > 99% conversion reaction, temperatures close to 600°C are required. Such high temperatures are likely to reduce the round-trip efficiency but also the catalyst lifetime because of the sintering of the supported metal phase. In this research, the first focus was on catalyst bed design, avoiding diffusion limitation. Experiments in our packed bed tubular reactor set-up showed that extragranular diffusion limitations occur at low concentrations of NH₃ when reaching high conversion, a phenomenon often overlooked in experimental work. A second focus was thermocatalyst development for ammonia cracking, avoiding the use of noble metals. To this aim, candidate metals and mixtures were deposited on a range of supports. Sintering resistance at high temperatures and the basicity of the support were found to be crucial catalyst properties. The catalytic activity was promoted by adding alkaline and alkaline earth metals. A third focus was studying the optimum process configuration by process simulations. A trade-off between conversion and favorable operational conditions (i.e. low pressure and high temperature) may lead to different process configurations, each with its own pros and cons. For example, high-pressure cracking would eliminate the need for post-compression but is detrimental for the thermodynamic equilibrium, leading to an optimum in cracking pressure in terms of energy cost.

Keywords: ammonia cracking, catalyst research, kinetics, process simulation, thermodynamic equilibrium

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Authors: M. Grandcolas, N. Rival, H. Bu, S. Jahren, R. Schmid, H. Johnsen

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The concept of an autonomic self-healing material, where initiation of repair is integrated to the material, is now being considered for engineering applications and is a hot topic in the literature. Among several concepts/techniques, two are most interesting: i) Capsules: Integration of microcapsules in or at the surface of coatings or fibre-like structures has recently gained much attention. Upon damage-induced cracking, the microcapsules are broken by the propagating crack fronts resulting in a release of an active chemical (healing agent) by capillary action, subsequently repairing and avoiding further crack growth. ii) Self-healing polymers: Interestingly, the introduction of dynamic covalent bonds into polymer networks has also recently been used as a powerful approach towards the design of various intrinsically self-healing polymer systems. The idea behind this is to reconnect the chemical crosslinks which are broken when a material fractures, restoring the integrity of the material and thereby prolonging its lifetime. We propose here to integrate both self-healing concepts (capsules, self-healing polymers) in electrospun fibres and coatings. Different capsule preparation approaches have been investigated in SINTEF. The most advanced method to produce capsules is based on emulsification to create a water-in-oil emulsion before polymerisation. The healing agent is a polyurethane-based dispersion that was encapsulated in shell materials consisting of urea-benzaldehyde resins. Results showed the successful preparation of microcapsules and release of the agent when capsules break. Since capsules are produced in water-in-oil systems we mainly investigated organic solvent based coatings while a major challenge resides in the incorporation of capsules into water-based coatings. We also focused on developing more robust microcapsules to prevent premature rupture of the capsules. The capsules have been characterized in terms of size, and encapsulation and release might be visualized by incorporating fluorescent dyes and examine the capsules by microscopy techniques. Alternatively, electrospinning is an innovative technique that has attracted enormous attention due to unique properties of the produced nano-to-micro fibers, ease of fabrication and functionalization, and versatility in controlling parameters. Especially roll-to-roll electrospinning is a unique method which has been used in industry to produce nanofibers continuously. Electrospun nanofibers can usually reach a diameter down to 100 nm, depending on the polymer used, which is of interest for the concept with self-healing polymer systems. In this work, we proved the feasibility of fabrication of POSS-based (POSS: polyhedral oligomeric silsesquioxanes, tradename FunzioNano™) nanofibers via electrospinning. Two different formulations based on aqueous or organic solvents have shown nanofibres with a diameter between 200 – 450nm with low defects. The addition of FunzioNano™ in the polymer blend also showed enhanced properties in term of wettability, promising for e.g. membrane technology. The self-healing polymer systems developed are here POSS-based materials synthesized to develop dynamic soft brushes.

Keywords: capsules, coatings, electrospinning, fibers

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Authors: Elena Chernyak, Ryan Ceresola

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Intimate partner violence is a serious social problem that affects a million women worldwide and impacts their health and wellbeing. Some risk factors for intimate partner violence against women (e.g., disobeying or arguing with a partner, women’s age, education, and employment) are similar in many countries, both developed and developing. However, one of the principal and most significant contributors to women’s vulnerability to violence perpetrated by their intimate partners is the witnessing of interparental aggression in the family of origin. Witnessing interparental violence may lead to acceptance of intimate partner violence as a normal way to resolve conflicts. Thus, utilization of violence becomes the behavioral model: men who witnessed the parental violence are more likely to employ physical violence against their female partners whereas women who observed their fathers beating their mothers learn to tolerate aggressive behavior and become victims of domestic violence themselves. Taking into consideration the importance of this subject matter, the association between witnessing intimate partner violence in family-of-origin and experience of intimate partner violence in adulthood requires further attention. The objective of this research is to analyze and compare the prevalence of intimate partner violence in ten developing countries in different regions, namely: Mali, Haiti, Jordan, Peru, the Philippines, Pakistan, Cambodia, Egypt, the Dominican Republic and Nigeria. Specifically, this research asks whether witnessing interparental violence in a family of origin is associated with the woman’s experience of intimate partner violence during adulthood and to what extent this factor varies among the countries under investigation. This study contributes to the literature on domestic violence against women, prevalence and experience of intimate partner violence against women in developing countries, and the risk factors, using recently collected, nationally representative population-based data from above-mentioned countries. The data used in this research are derived from the demographic and health surveys conducted in the ten mentioned above countries from 2013-2016. These surveys are cross-sectional, nationally representative surveys of ever-married or cohabitating women of reproductive age and the good source of high quality and comprehensive information about women, their children, partners, and households. To complete this analysis, multivariate logistic regression was run for each of the countries, and the results are presented with odds ratios, in order to highlight the effect of witnessing intimate partner violence controlling for other factors. The results of this study indicated that having witnessed partner violence in a family of origin significantly (by 50-500%) increases the likelihood of experiencing later abuse for respondents in all countries. This finding provides robust support for the intergenerational transmission of violence theory that explains the link between interparental aggression and intimate partner violence in subsequent relationships in adulthood as a result of a learned model of behavior observed in childhood. Furthermore, it was found that some of the control variables (e.g., education, number of children, and wealth) are associated with intimate partner violence in some countries under investigation while are not associated with male partner’s abusive behavior in some other, which may be explained by specific cultural and economic factors.

Keywords: intimate partner violence, domestic violence against women, developing countries, demographic and health surveys, risk factors

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Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Laura Villamizar, David Wright, Claudia Baena, Marie Foxwell, Maureen O'Callaghan

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Leguminous crops can be self-sufficient for their nitrogen requirements when their roots are nodulated with an effective Rhizobium strain and for this reason seed or soil inoculation is practiced worldwide to ensure nodulation and nitrogen fixation in grain and forage legumes. The most widely used method of applying commercially available inoculants is using peat cultures which are coated onto seeds prior to sowing. In general, rhizobia survive well in peat, but some species die rapidly after inoculation onto seeds. The development of improved formulation methodology is essential to achieve extended persistence of rhizobia on seeds, and improved efficacy. Formulations could be solid or liquid. Most popular solid formulations or delivery systems are: wettable powders (WP), water dispersible granules (WG), and granules (DG). Liquid formulation generally are: suspension concentrates (SC) or emulsifiable concentrates (EC). In New Zealand, R. leguminosarum bv. trifolii strain TA1 has been used as a commercial inoculant for white clover over wide areas for many years. Seeds inoculation is carried out by mixing the seeds with inoculated peat, some adherents and lime, but rhizobial populations on stored seeds decline over several weeks due to a number of factors including desiccation and antibacterial compounds produced by the seeds. In order to develop a more stable and suitable delivery system to incorporate rhizobia in pastures, two strains of R. leguminosarum (TA1 and CC275e) and several formulations and processes were explored (peat granules, self-sticky peat for seed coating, emulsions and a powder containing spray dried microcapsules). Emulsions prepared with fresh broth of strain TA1 were very unstable under storage and after seed inoculation. Formulations where inoculated peat was used as the active ingredient were significantly more stable than those prepared with fresh broth. The strain CC275e was more tolerant to stress conditions generated during formulation and seed storage. Peat granules and peat inoculated seeds using strain CC275e maintained an acceptable loading of 108 CFU/g of granules or 105 CFU/g of seeds respectively, during six months of storage at room temperature. Strain CC275e inoculated on peat was also microencapsulated with a natural biopolymer by spray drying and after optimizing operational conditions, microparticles containing 107 CFU/g and a mean particle size between 10 and 30 micrometers were obtained. Survival of rhizobia during storage of the microcapsules is being assessed. The development of a stable product depends on selecting an active ingredient (microorganism), robust enough to tolerate some adverse conditions generated during formulation, storage, and commercialization and after its use in the field. However, the design and development of an adequate formulation, using compatible ingredients, optimization of the formulation process and selecting the appropriate delivery system, is possibly the best tool to overcome the poor survival of rhizobia and provide farmers with better quality inoculants to use.

Keywords: formulation, Rhizobium leguminosarum, storage stability, white clover

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Authors: Mansoor Soomro

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The evolution of power electronic equipment has been pivotal in making industrial processes productive, efficient and safe. Despite its attractive features, it has been due to nonlinear loads which make it vulnerable to power quality conditions. Harmonics is one of the power quality problem in which the harmonic frequency is integral multiple of supply frequency. Therefore, the supply voltage and supply frequency do not last within their tolerable limits. As a result, distorted current and voltage waveform may appear. Attributes of low power quality confirm that an electrical device or equipment is likely to malfunction, fail promptly or unable to operate under all applied conditions. The electrical power system is designed for delivering power reliably, namely maximizing power availability to customers. However, power quality events are largely untracked, and as a result, can take out a process as many as 20 to 30 times a year, costing utilities, customers and suppliers of load equipment, a loss of millions of dollars. The ill effects of current harmonics reduce system efficiency, cause overheating of connected equipment, result increase in electrical power and air conditioning costs. With the passage of time and the rapid growth of power electronic converters has highlighted the damages of current harmonics in the electrical power system. Therefore, it has become essential to address the bad influence of current harmonics while planning any suitable changes in the electrical installations. In this paper, an effort has been made to mitigate the effects of dominant 3rd order current harmonics. Passive filtering technique with six pulse multiplication converter has been employed to mitigate them. Since, the standards of power quality are to maintain the supply voltage and supply current within certain prescribed standard limits. For this purpose, the obtained results are validated as per specifications of IEEE 519-1992 and IEEE 519-2014 performance standards.

Keywords: current harmonics, power quality, passive filters, power electronic converters

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Authors: Justin Nwabanne, Sam Omenyi, Jeremiah Chukwuneke

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This work presents structural nonlinear static analysis of a horizontal taut cable using Finite Element Analysis (FEA) method. The FEA was performed analytically to determine the tensions at each nodal point and subsequently, performed based on finite element displacement method computationally using the FEA software, ANSYS 14.0 to determine their behaviour under the influence of aerodynamic forces imposed on the cable. The convergence procedure is adapted into the method to prevent excessive displacements through the computations. The work compared the two FEA cases by examining the effectiveness of the analytical model in describing the response with few degrees of freedom and the ability of the nonlinear finite element procedure adopted to capture the complex features of cable dynamics with reference to the aerodynamic external influence. Results obtained from this work explain that the analytic FEM results without aerodynamic influence show a parabolic response with an optimum deflection at nodal points 12 and 13 with the cable weight at nodes 12 and 13 having the value -1.002936N while for the cable tension shows an optimum deflection value for nodes 12 and 13 at -189396.97kg/km. The maximum displacement for the cable system was obtained from ANSYS 14.0 as 4483.83 mm for X, Y and Z components of displacements at node number 2 while the maximum displacement obtained is 4218.75mm for all the directional components. The dynamic behaviour of a taut cable investigated has application in a typical power transmission line. Aerodynamic influences on the cables were considered using FEA approach by employing ANSYS 14.0 showed a complex modal behaviour as expected.

Keywords: aerodynamics, cable tension and weight, finite element analysis, nodal, non-linear model, optimum deflection, suspended cable, transmission line

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Authors: Zulkifli, I. W. Eltara, Anawati

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Understanding the complementary roles of surface energy and roughness on natural nonwetting surfaces has led to the development of a number of biomimetic superhydrophobic surfaces, which exhibit apparent contact angles with water greater than 150 degrees and low contact angle hysteresis. However, superoleophobic surfaces—those that display contact angles greater than 150 degrees with organic liquids having appreciably lower surface tensions than that of water—are extremely rare. In addition to chemical composition and roughened texture, a third parameter is essential to achieve superoleophobicity, namely, re-entrant surface curvature in the form of overhang structures. The overhangs can be realized as fibers. Superoleophobic surfaces are appealing for example, antifouling, since purely superhydrophobic surfaces are easily contaminated by oily substances in practical applications, which in turn will impair the liquid repellency. On the other studied have demonstrate that such aqueous nanofibrillar gels are unexpectedly robust to allow formation of highly porous aerogels by direct water removal by freeze-drying, they are flexible, unlike most aerogels that suffer from brittleness, and they allow flexible hierarchically porous templates for functionalities, e.g. for electrical conductivity. No crosslinking, solvent exchange nor supercritical drying are required to suppress the collapse during the aerogel preparation, unlike in typical aerogel preparations. The aerogel used in current work is an ultralight weight solid material composed of native cellulose nanofibers. The native cellulose nanofibers are cleaved from the self-assembled hierarchy of macroscopic cellulose fibers. They have become highly topical, as they are proposed to show extraordinary mechanical properties due to their parallel and grossly hydrogen bonded polysaccharide chains. We demonstrate that superoleophobic nanocellulose aerogels coating by sol-gel method, the aerogel is capable of supporting a weight nearly 3 orders of magnitude larger than the weight of the aerogel itself. The load support is achieved by surface tension acting at different length scales: at the macroscopic scale along the perimeter of the carrier, and at the microscopic scale along the cellulose nanofibers by preventing soaking of the aerogel thus ensuring buoyancy. Superoleophobic nanocellulose aerogels have recently been achieved using unmodified cellulose nanofibers and using carboxy methylated, negatively charged cellulose nanofibers as starting materials. In this work, the aerogels made from unmodified cellulose nanofibers were subsequently treated with fluorosilanes. To complement previous work on superoleophobic aerogels, we demonstrate their application as cargo carriers on oil, gas permeability, plastrons, and drag reduction, and we show that fluorinated nanocellulose aerogels are high-adhesive superoleophobic surfaces. We foresee applications including buoyant, gas permeable, dirt-repellent coatings for miniature sensors and other devices floating on generic liquid surfaces.

Keywords: superoleophobic, nanocellulose, aerogel, sol-gel

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Authors: Saeeda Batool, Ather Maqsood Ahmed

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This study investigates the impact of public healthcare facilities and socio-economic circumstances on the status of child health in Pakistan. The complete analysis is carried out in correspondence with fourth and sixth millennium development goals. Further, the health variables chosen are also inherited from targeted indicators of the mentioned goals (MDGs). Trends in the Human Opportunity Index (HOI) for both health inequalities and coverage are analyzed using the Pakistan Social and Living Standards Measurement (PLSM) data set for 2001-02 to 2012-13 at the national and provincial level. To reveal the relative importance of each circumstance in achieving the targeted values for child health, Shorrocks decomposition is applied on HOI. The annual point average growth rate of HOI is used to simulate the time period for the achievement of target set by MDGs and universal access also. The results indicate an improvement in HOI for a reduction in child mortality rates from 52.1% in 2001-02 to 67.3% in 2012-13, which confirms the availability of healthcare opportunities to a larger segment of society. Similarly, immunization against measles and other diseases such as Diphtheria, Polio, Bacillus Calmette-Guerin (BCG), and Hepatitis has also registered an improvement from 51.6% to 69.9% during the period of study at the national level. On a positive note, no gender disparity has been found for child health indicators and that health outcome is mostly affected by the parental and geographical features and availability of health infrastructure. However, the study finds that this achievement has been uneven across provinces. Pakistan is not only lagging behind in achieving its health goals, disappointingly with the current rate of health care provision, but it will take many additional years to achieve its targets.

Keywords: socio-economic circumstances, unmet MDGs, public healthcare services, child and infant mortality

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Authors: Aymen Laadhari

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During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

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Authors: Tarun Kumar Dalakoti, Debajyoti Majumder, Aditya Prasad Das, Samir Chandra Saxena

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India’s ambitious target to achieve a 50 percent share of energy from non-fossil fuels and the 500-gigawatt (GW) renewable energy capacity before the deadline of 2030, coupled with the global pursuit of sustainable development, will compel the nation to embark on a rapid clean energy transition. As a result, electricity market reforms will emerge as critical policy instruments to facilitate this transition and achieve ambitious environmental targets. This paper will present a comprehensive analysis of the various electricity market reforms to be introduced in the Indian Electricity sector to facilitate the integration of clean energy sources and will assess their impact on the overall energy landscape. The first section of this paper will delve into the policy mechanisms to be introduced by the Government of India and the Central Electricity Regulatory Commission to promote clean energy deployment. These mechanisms include extensive provisions for the integration of renewables in the Indian Electricity Grid Code, 2023. The section will also cover the projection of RE Generation as highlighted in the National Electricity Plan, 2023. It will discuss the introduction of Green Energy Market segments, the waiver of Inter-State Transmission System (ISTS) charges for inter-state sale of solar and wind power, the notification of Promoting Renewable Energy through Green Energy Open Access Rules, and the bundling of conventional generating stations with renewable energy sources. The second section will evaluate the tangible impact of these electricity market reforms. By drawing on empirical studies and real-world case examples, the paper will assess the penetration rate of renewable energy sources in India’s electricity markets, the decline of conventional fuel-based generation, and the consequent reduction in carbon emissions. Furthermore, it will explore the influence of these reforms on electricity prices, the impact on various market segments due to the introduction of green contracts, and grid stability. The paper will also discuss the operational challenges to be faced due to the surge of RE Generation sources as a result of the implementation of the above-mentioned electricity market reforms, including grid integration issues, intermittency concerns with renewable energy sources, and the need for increasing grid resilience for future high RE in generation mix scenarios. In conclusion, this paper will emphasize that electricity market reforms will be pivotal in accelerating the global transition towards clean energy systems. It will underscore the importance of a holistic approach that combines effective policy design, robust regulatory frameworks, and active participation from market actors. Through a comprehensive examination of the impact of these reforms, the paper will shed light on the significance of India’s sustained commitment to a cleaner, more sustainable energy future.

Keywords: renewables, Indian electricity grid code, national electricity plan, green energy market

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Authors: Kayla Belanger, Pascale Vigneron, Guy Schlatter, Bernard Devauchelle, Christophe Egles

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A severe injury to a peripheral nerve leads to its degeneration and the loss of sensory and motor function. To this day, there still lacks a more effective alternative to the autograft which has long been considered the gold standard for nerve repair. In order to overcome the numerous drawbacks of the autograft, tissue engineered biomaterials may be effective alternatives. Silk fibroin is a favorable biomaterial due to its many advantageous properties such as its biocompatibility, its biodegradability, and its robust mechanical properties. In this study, bio-mimicking multi-channeled nerve guidance conduits made of aligned nanofibers achieved by electrospinning were functionalized with signaling biomolecules and were tested in vitro and in vivo for nerve regeneration support. Silk fibroin (SF) extracted directly from silkworm cocoons was put in solution at a concentration of 10wt%. Poly(ethylene oxide) (PEO) was added to the resulting SF solution to increase solution viscosity and the following three electrospinning solutions were made: (1) SF/PEO solution, (2) SF/PEO solution with nerve growth factor and ciliary neurotrophic factor, and (3) SF/PEO solution with nerve growth factor and neurotrophin-3. Each of these solutions was electrospun into a multi-layer architecture to obtain mechanically optimized aligned nanofibrous mats. For in vitro studies, aligned fibers were treated to induce β-sheet formation and thoroughly rinsed to eliminate presence of PEO. Each material was tested using rat embryo neuron cultures to evaluate neurite extension and the interaction with bio-functionalized or non-functionalized aligned fibers. For in vivo studies, the mats were rolled into 5mm long multi-, micro-channeled conduits then treated and thoroughly rinsed. The conduits were each subsequently implanted between a severed rat sciatic nerve. The effectiveness of nerve repair over a period of 8 months was extensively evaluated by cross-referencing electrophysiological, histological, and movement analysis results to comprehensively evaluate the progression of nerve repair. In vitro results show a more favorable interaction between growing neurons and bio-functionalized silk fibers compared to pure silk fibers. Neurites can also be seen having extended unidirectionally along the alignment of the nanofibers which confirms a guidance factor for the electrospun material. The in vivo study has produced positive results for the regeneration of the sciatic nerve over the length of the study, showing contrasts between the bio-functionalized material and the non-functionalized material along with comparisons to the experimental control. Nerve regeneration has been evaluated not only by histological analysis, but also by electrophysiological assessment and motion analysis of two separate natural movements. By studying these three components in parallel, the most comprehensive evaluation of nerve repair for the conduit designs can be made which can, therefore, more accurately depict their overall effectiveness. This work was supported by La Région Picardie and FEDER.

Keywords: electrospinning, nerve guidance conduit, peripheral nerve regeneration, silk fibroin

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Authors: Ruby Jean Hornsby

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In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

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Authors: Camilo Andrés Agudelo Vélez, Lina María Martínez Sánchez, Isabel Cristina Ortiz Trujillo, Evert Armando Jiménez Cotes, Natalia Perilla Hernández, María de los Ángeles Rodríguez Gázquez, Daniel Duque Restrepo, Felipe Hernández Restrepo, Dayana Andrea Quintero Moreno, Juan José Builes Gómez, Camilo Ruiz Mejía, Ana Lucia Arango Gómez

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Preeclampsia is a clinical complication during pregnancy with high incidence in Colombia; therefore, it is important to evaluate the influence of external conditions and medical interventions, in order to promote measures that encourage improvements in the quality of life. Objective: Determine clinical and sociodemographic variables in women with preeclampsia. Methods: This cross-sectional study enrolled 50 patients with the diagnosis of preeclampsia, from a private institution in Medellin, during 2015. We used the software SPSS ver.20 for statistical analysis. For the qualitative variables, we calculated the mean and standard deviation, while, for ordinal and nominal levels of quantitative variables, ratios were estimated. Results: The average age was 26.8±5.9 years. The predominant characteristics were socioeconomic stratum 2 (48%), students (55%), mixed race (46%) and middle school as level of education (38%). As for clinical features, 72% of the cases were mild preeclampsia, and 22% were severe forms. The most common clinical manifestations were edema (46%), headache (62%), and proteinuria (55%). As for the Gyneco-obstetric history, 8% reported previous episodes of this disease and it was the first pregnancy for 60% of the patients. Conclusions: Preeclampsia is a frequent condition in young women; on the other hand, headache and edema were the most common reasons for consultation, therefore, doctors need to be aware of these symptoms in pregnant women.

Keywords: pre-eclampsia, hypertension, pregnancy complications, pregnancy, abdominal, edema

Procedia PDF Downloads 347