Search results for: cointegration techniques

Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Yi Yang, Jiasong Sun

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Almost every aspect of our daily lives is now intertwined with some degree of human-computer interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology, and more. Our HCI courses, named the Media and Cognition course, are constantly updated to reflect state-of-the-art technological advancements such as virtual reality, augmented reality, and artificial intelligence-based interactions. For more than a decade, our course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which have gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. Our latest version of the Human-Computer Interaction course practices a semantic communication platform based on AI-generated techniques. The purpose of this semantic communication is twofold: to extract and transmit task-specific information while ensuring efficient end-to-end communication with minimal latency. An AI-generated semantic communication platform evaluates the retention of signal sources and converts low-retain ability visual signals into textual prompts. These data are transmitted through AI-generated techniques and reconstructed at the receiving end; on the other hand, visual signals with a high retain ability rate are compressed and transmitted according to their respective regions. The platform and associated research are a testament to our students' growing ability to independently investigate state-of-the-art technologies.

Keywords: human-computer interaction, media and cognition course, semantic communication, retainability, prompts

Procedia PDF Downloads 116

Authors: Salman Ahmad, Muhammad Aown Sammar Raza, Muhammad Farrukh Saleem, Rashid Iqbal, Muhammad Saqlain Zaheer, Muhammad Usman Aslam, Imran Haider, Muhammad Adnan Nazar, Muhammad Ali

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Among the various abiotic stresses, drought stress is one of the most challenging for field crops. Wheat is one of the major staple food of the world, which is highly affected by water deficit stress in the current scenario of climate change. In order to ensure food security by depleting water resources, there is an urgent need to adopt technologies which result in sufficient crop yield with less water consumption. Mulching and partial rootzone drying (PRD) are two important management techniques used for water conservation and to mitigate the negative impacts of drought. The experiment was conducted to screen out the best-suited mulch for wheat under PRD system. Two water application techniques (I1= full irrigation I2= PRD irrigation) and four mulch treatments (M0= un-mulched, M1= black plastic mulch, M2= wheat straw mulch and M4= cotton sticks mulch) were conducted in completely randomized design with four replications. The treatment, black plastic mulch was performed the best than other mulch treatments. For irrigation levels, higher values of growth, physiological and water-related parameters were recorded in control treatment while, quality traits and enzymatic activities were higher under partial root zone drying. The current study concluded that adverse effects of drought on wheat can be significantly mitigated by using mulches but black plastic mulch was best suited for partial rootzone drying irrigation system in wheat.

Keywords: antioxidants, leaf water relations, Mulches, osmolytes, partial root zone drying, photosynthesis

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Authors: Abhimanyu Sharma

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India is known for its cultural heritage. As the country is rich in diversity along its length and breadth, the state of Jammu & Kashmir is world famous for the beautiful tourist destinations in the Kashmir region of the state. However, equally destined destinations are also located in Jammu region of the said state. For most of the time in last 50-60 years, the prime focus of development was centered around Kashmir region. But now due to an ever increase in globalization, the focus is decentralizing throughout the country. Pertinently, the potential of Jammu Region needs to be incorporated into the world tourist map in particular. One such spot in the Jammu region of the state is a place called ‘Mubarak Mandi’ – the palace with the royal residence of the Maharaja of Jammu & Kashmir from the Dogra Dynasty, is located in the heart of Jammu city (the winter capital of the state). Since the place is destined with a heritage importance but yet lack the supporting infrastructure to attract the national tourist in general and worldwide tourist at large. For such places, conservation and restoration of the existing structures are the potential tools to overcome the present limiting nature of the place. The rejuvenation of this place through potential and dynamic conservation techniques is targeted through this paper. This paper deals with developing and restoring the areas within the whole campus with appropriate building materials, conservation techniques, etc. to promote a great number of visitors by developing it into a prioritised tourist attraction point. Major thrust shall be on studying the criteria’s for developing the place considering the psychological effect needed to create a socially interactive environment. Additionally, thrust shall be on the spatial elements that will aid in creating a common platform for all kinds of tourists. Accordingly, different conservation guidelines (or model) shall be targeted through this paper so that this Jammu region shall also be an equally contributor to the tourist graph of the country as the Kashmir part is.

Keywords: conservation, heritage architecture, rejuvenating, restoration

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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This paper proposes a method to optimize the layout of an emergency department (ED) based on real executions of care processes by considering several planning objectives simultaneously. Recently, demand for healthcare services has been dramatically increased. As the demand for healthcare services increases, so do the need for new healthcare buildings as well as the need for redesign and renovating existing ones. The importance of implementation of a standard set of engineering facilities planning and design techniques has been already proved in both manufacturing and service industry with many significant functional efficiencies. However, high complexity of care processes remains a major challenge to apply these methods in healthcare environments. Process mining techniques applied in this study to tackle the problem of complexity and to enhance care process analysis. Process related information such as clinical pathways extracted from the information system of an ED. A 0-1 goal programming approach is then proposed to find a single layout that simultaneously satisfies several goals. The proposed model solved by optimization software CPLEX 12. The solution reached using the proposed method has 42.2% improvement in terms of walking distance of normal patients and 47.6% improvement in walking distance of critical patients at minimum cost of relocation. It has been observed that lots of patients must unnecessarily walk long distances during their visit to the emergency department because of an inefficient design. A carefully designed layout can significantly decrease patient walking distance and related complications.

Keywords: healthcare operation management, goal programming, facility layout problem, process mining, clinical processes

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Authors: Tony R. Walker, N. Devin MacAskill, Andrew Thalhiemer

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Sydney Harbour, Nova Scotia, Canada has long been subject to effluent and atmospheric inputs of contaminants, including thousands of tons of PAHs from a large coking and steel plant which operated in Sydney for nearly a century. Contaminants comprised of coal tar residues which were discharged from coking ovens into a small tidal tributary, which became known as the Sydney Tar Ponds (STPs), and subsequently discharged into Sydney Harbour. An Environmental Impact Statement concluded that mobilization of contaminated sediments posed unacceptable ecological risks, therefore immobilizing contaminants in the STPs using solidification and stabilization was identified as a primary source control remediation option to mitigate against continued transport of contaminated sediments from the STPs into Sydney Harbour. Recent developments in contaminant mass flux techniques focus on understanding “mobile” vs. “immobile” contaminants at remediation sites. Forensic source evaluations are also increasingly used for understanding origins of PAH contaminants in soils or sediments. Flux and forensic source evaluation-informed remediation decision-making uses this information to develop remediation end point goals aimed at reducing off-site exposure and managing potential ecological risk. This study included reviews of previous flux studies, calculating current mass flux estimates and a forensic assessment using PAH fingerprint techniques, during remediation of one of Canada’s most polluted sites at the STPs. Historically, the STPs was thought to be the major source of PAH contamination in Sydney Harbour with estimated discharges of nearly 800 kg/year of PAHs. However, during three years of remediation monitoring only 17-97 kg/year of PAHs were discharged from the STPs, which was also corroborated by an independent PAH flux study during the first year of remediation which estimated 119 kg/year. The estimated mass efflux of PAHs from the STPs during remediation was in stark contrast to ~2000 kg loading thought necessary to cause a short term increase in harbour sediment PAH concentrations. These mass flux estimates during remediation were also between three to eight times lower than PAHs discharged from the STPs a decade prior to remediation, when at the same time, government studies demonstrated on-going reduction in PAH concentrations in harbour sediments. Flux results were also corroborated using forensic source evaluations using PAH fingerprint techniques which found a common source of PAHs for urban soils, marine and aquatic sediments in and around Sydney. Coal combustion (from historical coking) and coal dust transshipment (from current coal transshipment facilities), are likely the principal source of PAHs in these media and not migration of PAH laden sediments from the STPs during a large scale remediation project.

Keywords: contaminated sediment, mass flux, forensic source evaluations, remediation

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Authors: Ubaid Ur Rahman, Waqar Younas, Sooraj Kumar Chhabira

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Environmentally sustainable building construction has experienced significant growth during the past 10 years at international level. This paper shows that the conceptual framework adopts sustainability techniques in construction to develop environment friendly building called green building. Waste occurs during the different construction phases which causes the environmental problems like, deposition of waste on ground surface creates major problems such as bad smell. It also gives birth to different health diseases and produces toxic waste agent which is specifically responsible for making soil infertile. Old recycled building material is used in the construction of new building. Sustainable construction is economical and saves energy sources. Sustainable construction is the major responsibility of designer and project manager. The designer has to fulfil the client demands while keeping the design environment friendly. Project manager has to deliver and execute sustainable construction according to sustainable design. Steel is the most appropriate sustainable construction material. It is more durable and easily recyclable. Steel occupies less area and has more tensile and compressive strength than concrete, making it a better option for sustainable construction as compared to other building materials. New technology like green roof has made the environment pleasant, and has reduced the construction cost. It minimizes economic, social and environmental issues. This paper presents an overview of research related to the material use of green building and by using this research recommendation are made which can be followed in the construction industry. In this paper, we go through detailed analysis on construction material. By making suitable adjustments to project management practices it is shown that a green building improves the cost efficiency of the project, makes it environmental friendly and also meets future generation demands.

Keywords: sustainable construction, green building, recycled waste material, environment

Procedia PDF Downloads 245

Authors: Mohamed Fawzy Elzarei, Yousef Mohammed Al-Dakheel, Ali Mohamed Alseaf

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Modern molecular techniques, like single marker analysis for linked traits to these markers, can provide us with rapid and accurate genetic results. In the last two decades of the last century, the applications of molecular techniques were reached a faraway point in cattle, sheep, and pig. In goats, especially in our region, the application of molecular techniques is still far from other species. As reported by many researchers, microsatellites marker is one of the suitable markers for lie studies. The single marker linked to traits of interest is one technique allowed us to early select animals without the necessity for mapping the entire genome. Simplicity, applicability, and low cost of this technique gave this technique a wide range of applications in many areas of genetics and molecular biology. Also, this technique provides a useful approach for evaluating genetic differentiation, particularly in populations that are poorly known genetically. The expected breeding value (EBV) and yield deviation (YD) are considered as the most parameters used for studying the linkage between quantitative characteristics and molecular markers, since these values are raw data corrected for the non-genetic factors. A total of 17 microsatellites markers (from chromosomes 6, 14, 18, 20 and 23) were used in this study to search for areas that could be responsible for genetic variability for some milk traits and search of chromosomal regions that explain part of the phenotypic variance. Results of single-marker analyses were used to identify the linkage between microsatellite markers and variation in EBVs of these traits, Milk yield, Protein percentage, Fat percentage, Litter size and weight at birth, and litter size and weight at weaning. The estimates of the parameters from forward and backward solutions using stepwise regression procedure on milk yield trait, only two markers, OARCP9 and AGLA29, showed a highly significant effect (p≤0.01) in backward and forward solutions. The forward solution for different equations conducted that R2 of these equations were highly depending on only two partials regressions coefficient (βi,) for these markers. For the milk protein trait, four marker showed significant effect BMS2361, CSSM66 (p≤0.01), BMS2626, and OARCP9 (p≤0.05). By the other way, four markers (MCM147, BM1225, INRA006, andINRA133) showed highly significant effect (p≤0.01) in both backward and forward solutions in association with milk fat trait. For both litter size at birth and at weaning traits, only one marker (BM143(p≤0.01) and RJH1 (p≤0.05), respectively) showed a significant effect in backward and forward solutions. The estimates of the parameters from forward and backward solution using stepwise regression procedure on litter weight at birth (LWB) trait only one marker (MCM147) showed highly significant effect (p≤0.01) and two marker (ILSTS011, CSSM66) showed a significant effect (p≤0.05) in backward and forward solutions.

Keywords: microsatellites marker, estimated breeding value, stepwise regression, milk traits

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Authors: Rafid Doulab

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Elemental Impurities in the Pharmaceuticals industryis are indispensable to ensure pharmaceuticalssafety for 24 elements. Although atomic absorption and inductively coupled plasma are used in the U.S Pharmacopeia and the European Pharmacopoeia, FESEM with energy dispersive spectrometers can be applied as an alternative analysis method for quantitative and qualitative results for a variety of elements without chemical pretreatment, unlike other techniques. This technique characterizes by shortest time, with more less contamination, no reagent consumption, and generation of minimal residue or waste, as well as sample preparations time limiting, with minimal analysis error. Simple dilution for powder or direct analysis for liquid, we analyzed the usefulness of EDS method in testing with field emission scanning electron microscopy (FESEM, SUPRA 55 Carl Zeiss Germany) with an X-ray energy dispersion (XFlash6l10 Bruker Germany). The samples analyzed directly without coating by applied 5µ of known concentrated diluted sample on carbon stub with accelerated voltage according to sample thickness, the result for this spot was in atomic percentage, and by Avogadro converted factor, the final result will be in microgram. Conclusion and recommendation: The conclusion of this study is application of FESEM-EDS in US pharmacopeia and ICH /Q3D guideline to reach a high-precision and accurate method in element impurities analysis of drugs or bulk materials to determine the permitted daily exposure PDE in liquid or solid specimens, and to obtain better results than other techniques, by the way it does not require complex methods or chemicals for digestion, which interfere with the final results with the possibility of to keep the sample at any time for re analysis. The recommendation is to use this technique in pharmacopeia as standard methods like inductively coupled plasma both ICP-AES, ICP-OES, and ICP-MS.

Keywords: pharmacopoeia, FESEM-EDS, element impurities, atomic concentration

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Authors: Shyaka Eugene

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The efficient and safe demolition of structures is a critical challenge in civil engineering and construction. This study focuses on the development of optimal demolition strategies by investigating the crack propagation behavior in beams induced by soundless cracking agents. It is commonly used in controlled demolition and has gained prominence due to its non-explosive and environmentally friendly nature. This research employs a comprehensive experimental and computational approach to analyze the crack initiation, propagation, and eventual failure in beams subjected to soundless cracking agents. Experimental testing involves the application of various cracking agents under controlled conditions to understand their effects on the structural integrity of beams. High-resolution imaging and strain measurements are used to capture the crack propagation process. In parallel, numerical simulations are conducted using advanced finite element analysis (FEA) techniques to model crack propagation in beams, considering various parameters such as cracking agent composition, loading conditions, and beam properties. The FEA models are validated against experimental results, ensuring their accuracy in predicting crack propagation patterns. The findings of this study provide valuable insights into optimizing demolition strategies, allowing engineers and demolition experts to make informed decisions regarding the selection of cracking agents, their application techniques, and structural reinforcement methods. Ultimately, this research contributes to enhancing the safety, efficiency, and sustainability of demolition practices in the construction industry, reducing environmental impact and ensuring the protection of adjacent structures and the surrounding environment.

Keywords: expansion pressure, energy release rate, soundless chemical demolition agent, crack propagation

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Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Sumaira Zafar, Arjumand Zaidi

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During past few years, several floods have adversely affected the areas along lower Indus River. Besides other climate related anomalies, rapidly increasing urbanization and blockage of natural drains due to siltation or encroachments are two other critical causes that may be responsible for these disasters. Due to flat topography of river Indus plains and blockage of natural waterways, drainage of storm water takes time adversely affecting the crop health and soil properties of the area. Government of Sindh is taking a keen interest in revival of natural drainage network in the province and has initiated this work under Sindh Irrigation and Drainage Authority. In this paper, geospatial techniques are used to analyze landuse/land-cover changes of Larkana district over the past three decades (1980-present) and their impact on natural drainage system. Satellite derived Digital Elevation Model (DEM) and topographic sheets (recent and 1950) are used to delineate natural drainage pattern of the district. The urban landuse map developed in this study is further overlaid on drainage line layer to identify the critical areas where the natural floodwater flows are being inhibited by urbanization. Rainfall and flow data are utilized to identify areas of heavy flow, whereas, satellite data including Landsat 7 and Google Earth are used to map previous floods extent and landuse/cover of the study area. Alternatives to natural drainage systems are also suggested wherever possible. The output maps of natural drainage pattern can be used to develop a decision support system for urban planners, Sindh development authorities and flood mitigation and management agencies.

Keywords: geospatial techniques, satellite data, natural drainage, flood, urbanization

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Authors: Fikiru Temesgen Gelata

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Food security, adaptation, and climate change mitigation are all problems that can be resolved simultaneously with Climate-Smart Agriculture (CSA). This study examines determinants of climate-smart agriculture (CSA) practices among smallholder farmers, aiming to understand the factors guiding adoption decisions and evaluate the impact of CSA on smallholder farmer income in the study areas. For this study, three-stage sampling techniques were applied to select 230 smallholders randomly. Mann-Kendal test and multinomial endogenous switching regression model were used to analyze trends of decrease or increase within long-term temporal data and the impact of CSA on the smallholder farmer income, respectively. Findings revealed education level, household size, land ownership, off-farm income, climate information, and contact with extension agents found to be highly adopted CSA practices. On the contrary, erosion exerted a detrimental impact on all the agricultural practices examined within the study region. Various factors such as farming methods, the size of farms, proximity to irrigated farmlands, availability of extension services, distance to market hubs, and access to weather forecasts were recognized as key determinants influencing the adoption of CSA practices. The multinomial endogenous switching regression model (MESR) revealed that joint adoption of crop rotation and soil and water conservation practices significantly increased farm income by 1,107,245 ETB. The study recommends that counties and governments should prioritize addressing climate change in their development agendas to increase the adoption of climate-smart farming techniques.

Keywords: climate-smart practices, food security, Oincome, MERM, Ethiopia

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Authors: Victoria Molina, Wendy Franco, Sergio Benavides, José M. Troncoso, Ricardo Luna, Jose R. PéRez-Correa

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Emamectin Benzoate (EB) is a crystal antiparasitic that belongs to the avermectin family. It is one of the most common treatments used in Chile to control Caligus rogercresseyi in Atlantic salmon. However, the sea lice acquired resistance to EB when it is exposed at sublethal EB doses. The low solubility rate of EB and its degradation at the acidic pH in the fish digestive tract are the causes of the slow absorption of EB in the intestine. To protect EB from degradation and enhance its absorption, specific microencapsulation technologies must be developed. Amorphous Solid Dispersion techniques such as Spray Drying (SD) and Ionic Gelation (IG) seem adequate for this purpose. Recently, Soluplus® (SOL) has been used to increase the solubility rate of several drugs with similar characteristics than EB. In addition, alginate (ALG) is a widely used polymer in IG for biomedical applications. Regardless of the encapsulation technique, the quality of the obtained microparticles is evaluated with the following responses, yield (Y%), encapsulation efficiency (EE%) and loading capacity (LC%). In addition, it is important to know the percentage of EB released from the microparticles in gastric (GD%) and intestinal (ID%) digestions. In this work, we microencapsulated EB with SOL (EB-SD) and with ALG (EB-IG) using SD and IG, respectively. Quality microencapsulation responses and in vitro gastric and intestinal digestions at pH 3.35 and 7.8, respectively, were obtained. A central composite design was used to find the optimum microencapsulation variables (amount of EB, amount of polymer and feed flow). In each formulation, the behavior of these variables was predicted with statistical models. Then, the response surface methodology was used to find the best combination of the factors that allowed a lower EB release in gastric conditions, while permitting a major release at intestinal digestion. Two approaches were used to determine this. The desirability approach (DA) and multi-objective optimization (MOO) with multi-criteria decision making (MCDM). Both microencapsulation techniques allowed to maintain the integrity of EB in acid pH, given the small amount of EB released in gastric medium, while EB-IG microparticles showed greater EB release at intestinal digestion. For EB-SD, optimal conditions obtained with MOO plus MCDM yielded a good compromise among the microencapsulation responses. In addition, using these conditions, it is possible to reduce microparticles costs due to the reduction of 60% of BE regard the optimal BE proposed by (DA). For EB-GI, the optimization techniques used (DA and MOO) yielded solutions with different advantages and limitations. Applying DA costs can be reduced 21%, while Y, GD and ID showed 9.5%, 84.8% and 2.6% lower values than the best condition. In turn, MOO yielded better microencapsulation responses, but at a higher cost. Overall, EB-SD with operating conditions selected by MOO seems the best option, since a good compromise between costs and encapsulation responses was obtained.

Keywords: microencapsulation, multiple decision-making criteria, multi-objective optimization, Soluplus®

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Authors: Marc Sebastián-Romagosa, Woosang Cho, Rupert Ortner, Christy Li, Christoph Guger

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Neurorehabilitation based on Brain-Computer Interfaces (BCIs) shows important rehabilitation effects for patients after stroke. Previous studies have shown improvements for patients that are in a chronic stage and/or have severe hemiparesis and are particularly challenging for conventional rehabilitation techniques. For this publication, seven stroke patients in the chronic phase with hemiparesis in the lower extremity were recruited. All of them participated in 25 BCI sessions about 3 times a week. The BCI system was based on the Motor Imagery (MI) of the paretic ankle dorsiflexion and healthy wrist dorsiflexion with Functional Electrical Stimulation (FES) and avatar feedback. Assessments were conducted to assess the changes in motor improvement before, after and during the rehabilitation training. Our primary measures used for the assessment were the 10-meters walking test (10MWT), Range of Motion (ROM) of the ankle dorsiflexion and Timed Up and Go (TUG). Results show a significant increase in the gait speed in the primary measure 10MWT fast velocity of 0.18 m/s IQR = [0.12 to 0.2], P = 0.016. The speed in the TUG was also significantly increased by 0.1 m/s IQR = [0.09 to 0.11], P = 0.031. The active ROM assessment increased 4.65º, and IQR = [ 1.67 - 7.4], after rehabilitation training, P = 0.029. These functional improvements persisted at least one month after the end of the therapy. These outcomes show the feasibility of this BCI approach for chronic stroke patients and further support the growing consensus that these types of tools might develop into a new paradigm for rehabilitation tools for stroke patients. However, the results are from only seven chronic stroke patients, so the authors believe that this approach should be further validated in broader randomized controlled studies involving more patients. MI and FES-based non-invasive BCIs are showing improvement in the gait rehabilitation of patients in the chronic stage after stroke. This could have an impact on the rehabilitation techniques used for these patients, especially when they are severely impaired and their mobility is limited.

Keywords: neuroscience, brain computer interfaces, rehabilitat, stroke

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Authors: C. Fornacelli, P. Colomban, E. Mugnaioli, I. Memmi Turbanti

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When semiconductor particles are reduced in scale to nanometer dimension, their optical and electro-optical properties strongly differ from those of bulk crystals of the same composition. Since sampling is often not allowed concerning cultural heritage artefacts, the potentialities of two non-invasive techniques, such as Raman and Fiber Optic Reflectance Spectroscopy (FORS), have been investigated and the results of the analysis on some original glasses of different colours (from yellow to orange and deep red) and periods (from the second decade of the 20th century to present days) are reported in the present study. In order to evaluate the potentialities of the application of non-invasive techniques to the investigation of the structure and distribution of nanoparticles dispersed in a glass matrix, Scanning Electron Microscopy (SEM) and energy-disperse spectroscopy (EDS) mapping, together with Transmission Electron Microscopy (TEM) and Electron Diffraction Tomography (EDT) have also been used. Raman spectroscopy allows a fast and non-destructive measure of the quantum dots composition and size, thanks to the evaluation of the frequencies and the broadening/asymmetry of the LO phonons bands, respectively, though the important role of the compressive strain arising from the glass matrix and the possible diffusion of zinc from the matrix to the nanocrystals should be taken into account when considering the optical-phonons frequency values. The incorporation of Zn has been assumed by an upward shifting of the LO band related to the most abundant anion (S or Se), while the role of the surface phonons as well as the confinement-induced scattering by phonons with a non-zero wavevectors on the Raman peaks broadening has been verified. The optical band gap varies from 2.42 eV (pure CdS) to 1.70 eV (CdSe). For the compositional range between 0.5≤x≤0.2, the presence of two absorption edges has been related to the contribution of both pure CdS and the CdSxSe1-x solid solution; this particular feature is probably due to the presence of unaltered cubic zinc blende structures of CdS that is not taking part to the formation of the solid solution occurring only between hexagonal CdS and CdSe. Moreover, the band edge tailing originating from the disorder due to the formation of weak bonds and characterized by the Urbach edge energy has been studied and, together with the FWHM of the Raman signal, has been assumed as a good parameter to evaluate the degree of topological disorder. SEM-EDS mapping showed a peculiar distribution of the major constituents of the glass matrix (fluxes and stabilizers), especially concerning those samples where a layered structure has been assumed thanks to the spectroscopic study. Finally, TEM-EDS and EDT were used to get high-resolution information about nanocrystals (NCs) and heterogeneous glass layers. The presence of ZnO NCs (< 4 nm) dispersed in the matrix has been verified for most of the samples, while, for those samples where a disorder due to a more complex distribution of the size and/or composition of the NCs has been assumed, the TEM clearly verified most of the assumption made by the spectroscopic techniques.

Keywords: CdSxSe1-x, EDT, glass, spectroscopy, TEM-EDS

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Authors: Bintou Jobe

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Musculo-skeletal disorders (MSDs) are injuries or disorders of the spine disc, muscle strains, and low back injuries. It remains a major cause of occupational illness. Findings: Due to poor grips during handling, it is possible for neck, shoulder, arm, knees, ankle, fingers, waist, lower back injuries, and other muscle joints to be affected. Pregnant women are more prone to physical and hormonal changes, which lead to the relaxation of supporting ligaments. MSD continues to pose a global concern due to its impact on workers worldwide. The prevalence of the disorder is high, according to research into the workforce in Europe and developing countries. The causes are characterized by long working hours, insufficient rest breaks, poor posture, repetitive motion, poor manual handling techniques, psychological stress, and poor nutrition. To prevent MSD, the design mainly involves avoiding and assessing the risk. However, clinical solutions, policy governance, and minimizing manual labour are also an alternative. In addition, eating a balanced diet and teamwork force are key to elements in minimising the risk. This review aims to raise awareness and promote cost effectiveness prevention and understanding of MSD through research and identify proposed solutions to recognise the underlying causes of MSDs in the construction sectors. The methodology involves a literature review approach, engaging with the policy landscape of MSD, synthesising publications on MSD and a wider range of academic publications. In conclusion, training on effective manual handling techniques should be considered, and Personal Protective Equipment should be a last resort. The implementation of training guidelines has yielded significant benefits.

Keywords: musculoskeletal disorder work related, MSD, manual handling, work hazards

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Authors: Amey Kulkarni, Paavan Shetty, Amol Patil, B. Rajiv

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Fuel Efficiency plays a very important role in overall performance of an automobile. In this paper study of fuel efficiency of heavy construction, compaction machine is done. The fuel Consumption trials are performed in order to obtain the consumption of fuel in performing certain set of actions by the compactor. Usually, Heavy Construction machines are put to work in locations where refilling the fuel tank is not an easy task and also the fuel is consumed at a greater rate than a passenger automobile. So it becomes important to have a fuel efficient machine for long working hours. The fuel efficiency is the most important point in determining the future scope of the product. A heavy construction compaction machine operates in five major roles. These five roles are traveling, Static working, High-frequency Low amplitude compaction, Low-frequency High amplitude compaction, low idle. Fuel consumption readings for 1950 rpm, 2000 rpm & 2350 rpm of the engine are taken by using differential fuel flow meter and are analyzed. And the optimum RPM setting which fulfills the fuel efficiency, as well as engine performance criteria, is considered. Also, other factors such as rear end gears, Intake and exhaust restriction for an engine, vehicle operating techniques, air drag, Tribological aspects, Tires are considered for increasing the fuel efficiency of the compactor. The fuel efficiency of compactor can be precisely calculated by using Differential Fuel Flow Meter. By testing the compactor at different combinations of Engine RPM and also considering other factors such as rear end gears, Intake and exhaust restriction of an engine, vehicle operating techniques, air drag, Tribological aspects, The optimum solution was obtained which lead to significant improvement in fuel efficiency of the compactor.

Keywords: differential fuel flow meter, engine RPM, fuel efficiency, heavy construction compaction machine

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Authors: Ahmed Abdrabou, Medhat Abdalla

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The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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Authors: Dena A. Hussain

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The objective of this project is to design an Information and Communication Technologies (ICT) tool based on a standardized platform to assist the work-integrated learning process of caretakers of disabled children. The tool should assist the intercommunication between caretakers and improve the learning process through knowledge bridging between all involved caretakers. Some children are born with disabilities while others have special needs after an illness or accident. Special needs children often need help in their learning process and require tools and services in a different way. In some cases the child has multiple disabilities that affect several capabilities in different ways. These needs are to be transformed into different learning techniques that the staff or personal (called caretakers in this project) caring for the child needs to learn and adapt. The caretakers involved are also required to learn new learning or training techniques and utilities specialized for the child’s needs. In many cases the number of people caring for the child’s development is rather large; the parents, specialist pedagogues, teachers, therapists, psychologists, personal assistants, etc. Each group of specialists has different objectives and in some cases the merge between theses specifications is very unique. This makes the synchronization between different caretakers difficult, resulting often in low level cooperation. By better intercommunication between professions both the child’s development could be improved but also the caretakers’ methods and knowledge of each other’s work processes and their own profession. This introduces a unique work integrated learning environment for all personnel involve, merging learning and knowledge in the work environment and at the same time assist the children’s development process. Creating an iterative process generates a unique learning experience for all involved. Using a work integrated platform will help encourage and support the process of all the teams involved in the process.We believe that working with children who have special needs is a continues learning/working process that is always integrated to achieve one main goal, which is to make a better future for all children.

Keywords: information and communication technologies (ICT), work integrated learning (WIL), sustainable learning, special needs children

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: Ilja Käch, Abdul R. Jandali, Nadja Zechmann-Müller

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Introduction: We discuss the treatment of two young male patients suffering from scaphoid non-union after a traumatic scaphoid fracture. The currently propagated techniques for treating a scaphoid non-union in children are either the operative reconstruction of the scaphoid or the conservative treatment with splinting in a scaphoid cast. Cases: In the first case, we operated on a 13 years old male patient with a posttraumatic scaphoid non-union in the middle third with a humpback deformity. We resected the middle third of the scaphoid and grafted the defect with an iliac crest bone, and the DISI-Deformity was reduced. Fixation was performed with K-Wires and immobilisation in a scaphoid cast. In the second case a 13 years old male patient also with a posttraumatic scaphoid non-union in the middle third and humpback deformity, DISI-deformity, was treated conservatively. Immobilisation in a scaphoid cast for four months was performed. Results: Operative: One year postoperatively the patient achieved a painless free arc of motion. Flexion/Extension 70/0/60°, Radial-/Ulnarduction 30/0/30° and Pro-/Supination 90/0/90°. The computer tomogram showed complete consolidation and bony fusion of the iliac crest bone. Conservative: Six to eight months after conservative treatment the patient demonstrated painless motion and AROM Flexion/Extension 80/0/80°, Radial-/Ulnarduction and Pro-/Supination in maximum range. Complete consolidation in the computer tomogram with persistent humpback- and DISI deformity. Conclusion: In the literature, both techniques are described, either the operative scaphoid reconstruction or the conservative treatment with splinting. In our cases, both the operative and conservative treatments showed comparable good results. However, the humpback- and DISI deformity can only be addressed with a surgical approach.

Keywords: scaphoid, non-union, trauma, operative vs. non operative

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Authors: Y. Hamaizi, H. Triki, A. El-Akrmi

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In this paper, the reflection spectra, group delay and dispersion of a uniform fiber Bragg grating (FBG) are obtained. FBGs with two types of apodized variations of the refractive index were modeled to show how the side-lobes can be suppressed. Apodization techniques are used to get optimized reflection spectra. The simulation is based on solving coupled mode equations together with the transfer matrix method.

Keywords: fiber bragg gratings, coupled-mode theory, reflectivity, apodization

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Authors: Satpal Yadav, Ashish Phulkar, Krishna K. Sahu

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Aim: The research aims at doing a 3 Dimension biomechanical analysis in the shot put techniques of International throwers to evaluate the performance. Research Method: The researcher adopted the descriptive method and the data was subjected to calculate by using Pearson’s product moment correlation for the correlation of the biomechanical parameters with the performance of shot put throw. In all the analyses, the 5% critical level (p ≤ 0.05) was considered to indicate statistical significance. Research Sample: Eight (N=08) international shot putters using rotational/glide technique in male category was selected as subjects for the study. The researcher used the following methods and tools to obtain reliable measurements the instrument which was used for the purpose of present study namely the tesscorn slow-motion camera, specialized motion analyzer software, 7.260 kg Shot Put (for a male shot-putter) and steel tape. All measurement pertaining to the biomechanical variables was taken by the principal investigator so that data collected for the present study was considered reliable. Results: The finding of the study showed that negative significant relationship between the angular velocity right shoulder, acceleration distance at pre flight (-0.70), (-0.72) respectively were obtained, the angular displacement of knee, angular velocity right shoulder and acceleration distance at flight (0.81), (0.75) and (0.71) respectively were obtained, the angular velocity right shoulder and acceleration distance at transition phase (0.77), (0.79) respectively were obtained and angular displacement of knee, angular velocity right shoulder, release velocity shot, angle of release, height of release, projected distance and measured distance as the values (0.76), (0.77), (-0.83), (-0.79), (-0.77), (0.99) and (1.00) were found higher than the tabulated value at 0.05 level of significance. On the other hand, there exists an insignificant relationship between the performance of shot put and acceleration distance [m], angular displacement shot, C.G at release and horizontal release distance on the technique of shot put.

Keywords: biomechanics, analysis, shot put, international throwers

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Authors: Riya Bose, Ashok Bera, Manas R. Parida, Anirudhha Adhikari, Basamat S. Shaheen, Erkki Alarousu, Jingya Sun, Tom Wu, Osman M. Bakr, Omar F. Mohammed

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This work reports visualization of charge carrier dynamics on the surface of copper indium gallium selenide (CIGSe) nanocrystals in real space and time using four-dimensional scanning ultrafast electron microscopy (4D S-UEM) and correlates it with the optoelectronic properties of the nanocrystals. The surface of the nanocrystals plays a key role in controlling their applicability for light emitting and light harvesting purposes. Typically for quaternary systems like CIGSe, which have many desirable attributes to be used for optoelectronic applications, relative abundance of surface trap states acting as non-radiative recombination centre for charge carriers remains as a major bottleneck preventing further advancements and commercial exploitation of these nanocrystals devices. Though ultrafast spectroscopic techniques allow determining the presence of picosecond carrier trapping channels, because of relative larger penetration depth of the laser beam, only information mainly from the bulk of the nanocrystals is obtained. Selective mapping of such ultrafast dynamical processes on the surfaces of nanocrystals remains as a key challenge, so far out of reach of purely optical probing time-resolved laser techniques. In S-UEM, the optical pulse generated from a femtosecond (fs) laser system is used to generate electron packets from the tip of the scanning electron microscope, instead of the continuous electron beam used in the conventional setup. This pulse is synchronized with another optical excitation pulse that initiates carrier dynamics in the sample. The principle of S-UEM is to detect the secondary electrons (SEs) generated in the sample, which is emitted from the first few nanometers of the top surface. Constructed at different time delays between the optical and electron pulses, these SE images give direct and precise information about the carrier dynamics on the surface of the material of interest. In this work, we report selective mapping of surface dynamics in real space and time of CIGSe nanocrystals applying 4D S-UEM. We show that the trap states can be considerably passivated by ZnS shelling of the nanocrystals, and the carrier dynamics can be significantly slowed down. We also compared and discussed the S-UEM kinetics with the carrier dynamics obtained from conventional ultrafast time-resolved techniques. Additionally, a direct effect of the state trap removal can be observed in the enhanced photoresponse of the nanocrystals after shelling. Direct observation of surface dynamics will not only provide a profound understanding of the photo-physical mechanisms on nanocrystals’ surfaces but also enable to unlock their full potential for light emitting and harvesting applications.

Keywords: 4D scanning ultrafast microscopy, charge carrier dynamics, nanocrystals, optoelectronics, surface passivation, trap states

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Authors: I. Oikonomou, I. Lappa, D. Daferera, C. Kanakis, L. Kiokakis, K. Skordilis, A. Avramouli, E. Kalli, C. Pappas, P. A. Tarantilis, E. Skotti

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Grape seeds are waste products of wineries and often referred to as an important agricultural and industrial waste product with the potential to be used in pharmaceutical, food, and cosmetic applications. In this study, grape seed oil from traditional Ionian varieties was examined for the determination of the quality and the characteristics of each variety. Initially, the fatty acid methyl ester (FAME) profiles were analyzed using Gas Chromatography-Mass Spectrometry, after transesterification. Furthermore, other quality parameters of the grape seed oils were determined by Spectroscopy techniques, UV-Vis and Raman included. Moreover, the antioxidant capacity of the oil was measured by 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assays and their antioxidant capacity expressed in Trolox equivalents. K and ΔΚ indices were measured in 232, 268, 270 nm, as an oil quality index. The results indicate that the air-dried grape seed total oil content ranged from 5.26 to 8.77% w/w, which is in accordance with the other grape seed varieties tested in similar studies. The composition of grape seed oil is predominated with linoleic and oleic fatty acids, with the linoleic fatty acid ranging from 53.68 to 69.95% and both the linoleic and oleic fatty acids totaling 78-82% of FAMEs, which is analogous to the fatty acid composition of safflower oil. The antioxidant assays ABTS and DPPH scored high, exhibiting that the oils have potential in the cosmetic and culinary businesses. Above that, our results demonstrate that Ionian grape seed oils have prospects that can go further than cosmetic or culinary use, into the pharmaceuticals industry. Finally, the reclamation of grape seeds from wineries waste stream is in accordance with the bio-economy strategic framework and contributes to environmental protection.

Keywords: antioxidant capacity, fatty acid methyl esters, grape seed oil, GC-MS

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Hamidullah Binol, Abdullah Bal

Abstract:

Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: food (ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods

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Authors: Sadman Durlov, Aditya Ganesh-Ram, Hamidreza Hekmatjou, Md Najmus Salehin, Nora Shayesteh Ameri

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In the field of additive manufacturing, tungsten stands out for its exceptional resistance to high temperatures, making it an ideal candidate for use in extreme conditions. However, its inherent brittleness and vulnerability to thermal cracking pose significant challenges to its manufacturability. This study explores the microstructural evolution of tungsten processed through layer-wise rolling in laser powder bed fusion additive manufacturing, utilizing a comprehensive approach that combines advanced simulation techniques with empirical research. We aim to uncover the complex processes of plastic deformation and microstructural transformations, with a particular focus on the dynamics of grain size, boundary evolution, and phase distribution. Our methodology employs a combination of simulation and experimental data, allowing for a detailed comparison that elucidates the key mechanisms influencing microstructural alterations during the rolling process. This approach facilitates a deeper understanding of the material's behavior under additive manufacturing conditions, specifically in terms of deformation and recrystallization. The insights derived from this research not only deepen our theoretical knowledge but also provide actionable strategies for refining manufacturing parameters to improve the tungsten components' mechanical properties and functional performance. By integrating simulation with practical experimentation, this study significantly enhances the field of materials science, offering a robust framework for the development of durable materials suited for challenging operational environments. Our findings pave the way for optimizing additive manufacturing techniques and expanding the use of tungsten across various demanding sectors.

Keywords: additive manufacturing, layer wise rolling, refractory materials, in-situ microstructure modifications

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Authors: Osvaldo N. Oliveira Jr.

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The control of molecular architecture inherent in some experimental methods to produce nanostructured films has had great impact on devices of various types, including sensors and biosensors. The self-assembly monolayers (SAMs) and the electrostatic layer-by-layer (LbL) techniques, for example, are now routinely used to produce tailored architectures for biosensing where biomolecules are immobilized with long-lasting preserved activity. Enzymes, antigens, antibodies, peptides and many other molecules serve as the molecular recognition elements for detecting an equally wide variety of analytes. The principles of detection are also varied, including electrochemical methods, fluorescence spectroscopy and impedance spectroscopy. In this presentation an overview will be provided of biosensors made with nanostructured films to detect antibodies associated with tropical diseases and HIV, in addition to detection of analytes of medical interest such as cholesterol and triglycerides. Because large amounts of data are generated in the biosensing experiments, use has been made of computational and statistical methods to optimize performance. Multidimensional projection techniques such as Sammon´s mapping have been shown more efficient than traditional multivariate statistical analysis in identifying small concentrations of anti-HIV antibodies and for distinguishing between blood serum samples of animals infected with two tropical diseases, namely Chagas´ disease and Leishmaniasis. Optimization of biosensing may include a combination of another information visualization method, the Parallel Coordinate technique, with artificial intelligence methods in order to identify the most suitable frequencies for reaching higher sensitivity using impedance spectroscopy. Also discussed will be the possible convergence of technologies, through which machine learning and other computational methods may be used to treat data from biosensors within an expert system for clinical diagnosis.

Keywords: clinical diagnosis, information visualization, nanostructured films, layer-by-layer technique

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