Search results for: leafy green processing

Authors: Parnaz Boodagh, Danila Vella, Antonio Damore, Laura Modica De Mohac, Sang-Ho Ye, Garret Coyan, Gaetano Burriesci, William Wagner, Federica Cosentino

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The use of cardiac patches is among the main therapeutic solution for cardiovascular diseases, a leading mortality cause in the world with an increasing trend, responsible of 19 millions deaths in 2020. Several classes of biomaterials serve that purpose, both of synthetic origin and biological derivation, and many bioengineered treatment alternatives were proposed to satisfy two main requirements, providing structural support and promoting tissue remodeling. The objective of this paper is to compare the mechanical properties and the characterization of four cardiac patches: the Adeka, PhotoFix, CorPatch, and CardioCel patches. In vitro and in vivo tests included: biaxial, uniaxial, ball burst, suture retention for mechanical characterization; 2D surface topography, 3D volume and microstructure, and histology assessments for structure characterization; in vitro test to evaluate platelet deposition, calcium deposition, and macrophage polarization; rat right ventricular outflow tract (RVOT) models at 8- and 16-week time points to characterize the patch-host interaction. Lastly, the four patches were used to produce four stented aortic valve prosthesis, subjected to hydrodynamic assessment as well as durability testing to verify compliance with the standard ISO.

Keywords: cardiac patch, cardiovascular disease, cardiac repair, blood contact biomaterial

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Authors: W. Ketren, J. Wannapeera, Z. Heishun, A. Ryuichi, K. Toshiteru, M. Kouichi, O. Hideaki

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Degradative solvent extraction is the method developed for biomass upgrading by dewatering and fractionation of biomass under the mild condition. However, the conversion mechanism of the degradative solvent extraction method has not been fully understood so far. The rice straw was treated in 1-methylnaphthalene (1-MN) at a different solvent-treatment temperature varied from 250 to 350 ^oC with the residence time for 60 min. The liquid membrane-Fourier Transform Infrared Spectroscopy (FTIR) technique is applied to study the processing mechanism in-depth without separation of the solvent. It has been found that the strength of the oxygen-hydrogen stretching  (3600-3100 cm^-1) decreased slightly with increasing temperature in the range of 300-350 ^oC. The decrease of the hydroxyl group in the solvent soluble suggested dehydration reaction taking place between 300 and 350 ^oC. FTIR spectra in the carbonyl stretching region (1800-1600 cm^-1) revealed the presence of esters groups, carboxylic acid and ketonic groups in the solvent-soluble of biomass. The carboxylic acid increased in the range of 200 to 250 ^oC and then decreased. The prevailing of aromatic groups showed that the aromatization took place during extraction at above 250 ^oC. From 300 to 350 ^oC, the carbonyl functional groups in the solvent-soluble noticeably decreased. The removal of the carboxylic acid and the decrease of esters into the form of carbon dioxide indicated that the decarboxylation reaction occurred during the extraction process.

Keywords: biomass waste, degradative solvent extraction, mechanism, upgrading

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Authors: Aprajita Singh, Anamika Tripathi, Surya P. Dwivedi

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Moradabad is a small town in the Northern area of Uttar Pradesh, India. It is situated on the bank of river Ramganga which is also known as ‘Brass City of India’. There is eventually increase in the environmental pollution due to uncontrolled and inappropriate e-waste burning (recycling) activities which have been reported in many areas of Moradabad. In this paper, analysis of toxic heavy metals, causing pollution to the surrounding environment released from the e-waste burning and much other recycling process. All major e-waste burning sites are situated on the banks of the river which is burned in open environmental conditions. Soil samples were collected from seven (n=3) different sites including control site, after digestion of soil samples using triacid mixture, analysis of different toxic metals (Pb, Ar, Hg, Cd, Cr, Cu, Zn, Fe, and Ni) has been carried out with the help of instrument ICP-AAS. After the study, the outcome is that the soil of those areas contains a relatively high level of the toxic metals in order of Cu>Fe>Pb>Cd>Cr>Zn>Ar>Hg. The concentration of Cd, Pb, Cr, Ar and Zn (the majority of samples experimentally proved) exceeded the maximum standard level of WHO. Sequentially this study showed that uncontrolled e-waste processing operations caused serious pollution to local soil and release of toxic metals in the environment is also causing adverse effect on the health of people living in the nearby areas making them more prone to various harmful diseases.

Keywords: brass city, environment pollution, e-waste, toxic heavy metals

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Authors: Jim J. Catina, Jackee M. Gwynn, Jin S. Kang

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Additive manufacturing (AM) for hybrid rocket engines is becoming increasingly attractive due to its ability to create complex grain configurations with improved regression rates when compared to cast grains. However, the presence of microvoids in parts produced through the additive manufacturing method of Fused Deposition Modeling (FDM) results in a lower fuel density and is believed to cause a decrease in regression rate compared to ideal performance. In this experiment, FDM was used to create hybrid rocket fuel grains with a star configuration composed of acrylonitrile butadiene styrene (ABS). Testing was completed to determine the effect of heat treatment as a post-processing method to improve the combustion performance of hybrid rocket fuel grains manufactured by FDM. For control, three ABS star configuration grains were printed using FDM and hot fired using gaseous oxygen (GOX) as the oxidizer. Parameters such as thrust and mass flow rate were measured. Three identical grains were then heat treated to varying degrees and hot fired under the same conditions as the control grains. This paper will quantitatively describe the amount of improvement in engine performance as a result of heat treatment of the AM hybrid fuel grain. Engine performance is measured in this paper by specific impulse, which is determined from the thrust measurements collected in testing.

Keywords: acrylonitrile butadiene styrene, additive manufacturing, fused deposition modeling, heat treatment

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Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

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The biodegradable family of polymers polyhydroxyalkanoates are interesting substitutes for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization

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Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

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Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: calibration model, celitement, cementitious material, NIR spectroscopy

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Authors: Allen Yushark Fosu, Ndue Kanari, James Vaughan, Alexandre Changes

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Spodumene is a lithium-bearing mineral of great interest due to increasing demand of lithium in emerging electric and hybrid vehicles. The conventional method of processing the mineral for the metal requires inevitable thermal transformation of α-phase to the β-phase followed by roasting with suitable reagents to produce lithium salts for downstream processes. The selection of appropriate reagent for roasting is key for the success of the process and overall lithium recovery. Several researches have been conducted to identify good reagents for the process efficiency, leading to sulfation, alkaline, chlorination, fluorination, and carbonizing as the methods of lithium recovery from the mineral.HSC Chemistry is a thermochemical software that can be used to model metallurgical process feasibility and predict possible reaction products prior to experimental investigation. The software was employed to investigate and explain the various reagent characteristics as employed in literature during spodumene roasting up to 1200°C. The simulation indicated that all used reagents for sulfation and alkaline were feasible in the direction of lithium salt production. Chlorination was only feasible when Cl2 and CaCl2 were used as chlorination agents but not NaCl nor KCl. Depending on the kind of lithium salt formed during carbonizing and fluorination, the process was either spontaneous or nonspontaneous throughout the temperature range investigated. The HSC software was further used to simulate and predict some promising reagents which may be equally good for roasting the mineral for efficient lithium extraction but have not yet been considered by researchers.

Keywords: thermochemical modelling, HSC chemistry software, lithium, spodumene, roasting

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Authors: Esther Burkitt

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Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.

Keywords: emotion, childhood, self, other

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Authors: Erica Siqueira, Adriana Bin, Rachel Stefanuto

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The paper aims to identify and to discuss the impact and results of ex-ante, mid-term and ex-post evaluation initiatives in Brazilian Social Enterprises from the point of view of the entrepreneurs and investors, highlighting the processes involved in these activities and their aftereffects. The study was conducted using a descriptive methodology, primarily qualitative. A multiple-case study was used, and, for that, semi-structured interviews were conducted with ten entrepreneurs in the (i) social finance, (ii) education, (iii) health, (iv) citizenship and (v) green tech fields, as well as three representatives of various impact investments, which are (i) venture capital, (ii) loan and (iii) equity interest areas. Convenience (non-probabilistic) sampling was adopted to select both businesses and investors, who voluntarily contributed to the research. The evaluation is still incipient in most of the studied business cases. Some stand out by adopting well-known methodologies like Global Impact Investing Report System (GIIRS), but still, have a lot to improve in several aspects. Most of these enterprises use nonexperimental research conducted by their own employees, which is ordinarily not understood as 'golden standard' to some authors in the area. Nevertheless, from the entrepreneur point of view, it is possible to identify that most of them including those routines in some extent in their day-by-day activities, despite the difficulty they have of the business in general. In turn, the investors do not have overall directions to establish evaluation initiatives in respective enterprises; they are funding. There is a mechanism of trust, and this is, usually, enough to prove the impact for all stakeholders. The work concludes that there is a large gap between what the literature states in regard to what should be the best practices in these businesses and what the enterprises really do. The evaluation initiatives must be included in some extension in all enterprises in order to confirm social impact that they realize. Here it is recommended the development and adoption of more flexible evaluation mechanisms that consider the complexity involved in these businesses’ routines. The reflections of the research also suggest important implications for the field of Social Enterprises, whose practices are far from what the theory preaches. It highlights the risk of the legitimacy of these enterprises that identify themselves as 'social impact', sometimes without the proper proof based on causality data. Consequently, this makes the field of social entrepreneurship fragile and susceptible to questioning, weakening the ecosystem as a whole. In this way, the top priorities of these enterprises must be handled together with the results and impact measurement activities. Likewise, it is recommended to perform further investigations that consider the trade-offs between impact versus profit. In addition, research about gender, the entrepreneur motivation to call themselves as Social Enterprises, and the possible unintended consequences from these businesses also should be investigated.

Keywords: evaluation practices, impact, results, social enterprise, social entrepreneurship ecosystem

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Vertika Goswami, Gargi Sharma

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The rapid evolution of fintech has led to the rise of robo-advisor platforms that utilize artificial intelligence (AI) and machine learning to offer personalized investment solutions efficiently and cost-effectively. This research paper conducts a comprehensive sentiment analysis of investor experiences with these platforms, employing natural language processing (NLP) and sentiment classification techniques. The study investigates investor perceptions, engagement, and satisfaction, identifying key drivers of positive sentiment such as clear communication, low fees, consistent returns, and robust security. Conversely, negative sentiment is linked to issues like inconsistent performance, hidden fees, poor customer support, and a lack of transparency. The analysis reveals that addressing these pain points—through improved transparency, enhanced customer service, and ongoing technological advancements—can significantly boost investor trust and satisfaction. This paper contributes valuable insights into the fields of behavioral finance and fintech innovation, offering actionable recommendations for stakeholders, practitioners, and policymakers. Future research should explore the long-term impact of these factors on investor loyalty, the role of emerging technologies, and the effects of ethical investment choices and regulatory compliance on investor sentiment.

Keywords: artificial intelligence in finance, automated investment, financial technology, investor satisfaction, investor sentiment, robo-advisors, sentimental analysis

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Authors: Daniel R. McDougall, Martin D. de Jonge, Gordon M. Miskelly, Duncan J. McGillivray, Andrew G. Jeffs

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The chelating agent ethylenediaminetetraacetic acid (EDTA) is commonly added as a cure-all to seawater in aquaculture hatcheries around the world to reduce heavy metal toxicity, significantly improve the survival of larval shellfish, and to therefore improve the overall production efficiency of the aquaculture industry. However, EDTA is not a biodegradable chemical and is considered to be a persistent organic pollutant, which will accumulate in the environment over time. This makes the use of EDTA unsustainable environmentally, and therefore alternatives should be considered. Ethylenediaminedisuccinic acid (EDDS) is a biodegradable alternative to EDTA with very similar metal chelation properties. This study investigates the effect of EDTA and EDDS at two different concentrations, on metal concentrations found within developing New Zealand green-lipped mussel (Perna canaliculus) larvae. P. canaliculus is New Zealand’s main shellfish aquaculture species, providing a major export for New Zealand’s economy, with excellent potential for increased production in the near future. It is well known that the early stages of bivalve development are the most vulnerable to metal toxicity and P. canaliculus is no exception. The commercially used concentration (12 µmol L⁻¹) of EDTA added to P. canaliculus larval rearing tanks often increases the yield of D-larvae by over 80%. This concentration of EDTA and EDDS will be tested in this study, along with a lower concentration (3 µmol L⁻¹). After 48 hours of larval development, the D-larvae will be analyzed for heavy metal content with Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and heavy metal distribution with synchrotron X-ray Fluorescence Microscopy (XFM). In this study, we found that EDDS also improves the yield of P. canaliculus larvae and could be a viable alternative to EDTA in aquaculture. Furthermore, results suggest a higher concentration of chelating agent is more effective for improving the yield of developing P. canaliculus larvae. Metals with significant differences in concentration with the addition of EDTA were Cr, Cu, Zn, Cd and Pb (P < 0.05). We observed for the first time to the author’s best knowledge, metal distribution within 100 µm P. canaliculus D-larvae using synchrotron XFM and found changes in the distribution of metals with the addition of EDTA. XFM also has the potential to provide information about the chemical state of the metals within mussel larvae. This research provides greater insight into the reasons for the effectiveness of adding the chelating agent to aquaculture culture water, and a more environmentally conscious alternative to the currently used EDTA, which could be extremely valuable for the aquaculture industry.

Keywords: EDDS, EDTA, heavy metals, P. canaliculus, toxicity, water treatment

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Authors: Meenakshi Pappu

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The terms like liveability, Sustainable Development Goals and pandemic have been widely analysed in proving sustainable cities and community living in growing urban areas by 2030. The pandemic has made us all ruminate about how we look into different fast-growing cities which vary in geographical location, climatic zones, terrains, land use and varying cultural backgrounds & traditions belong to the mother soil. India has taken up huge steps to move towards achieving UN-SDGs. Smart city missions have played a vital role in moving towards SDG. Visakhapatnam city is the executive capital in the state of Andhra Pradesh. Located on the Eastern Ghats in South India, it is surrounded by a mountain range on three sides and the Indian Ocean on one side. This unique geographical location and fast urbanization in the last two decades, has put up immense pressure on the natural environment and recourses. It's observed that a lot of investigation to address the existing and proposed land-use, spatial, natural resources, air quality, environmental challenges, and a range of socio-economic, economic challenges were identified during the assessment phase. The citizen concerns with quality and quantity of access to water, sewerage, energy, transportation (public & private) and safety for the public were found out through surveying. Urban infrastructure plays a major part in city building. These cities are occupied by people who come for a better living. This paper aims to provide off-center way of approach to citizens-oriented community habits by addressing SDG 11: Sustainable cities & community by enkindling a characteristic framework of amalgamating 1.eco-design principal, 2. three factors of liveability and 3. a local traditional planning solution. Aiming towards a sustainable development utilized with the focus on the quality of the life and experience of the people who live in urban areas integrating life with soil & water. Building strong social agenda that includes affordable housing for all levels of households, secure and place for good quality public realm for the local people with activity in green corridor, open meeting space & adding recreational places for advantage..

Keywords: livability, eco-design, smart city mission, sustainable

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Authors: Justyna Minkiewicz

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Artificial Intelligence (AI) applied in the arts may influence the development of AI knowledge in other sectors and then also impact mutual collaboration with the artistic environment. Hence this collaboration may also impact the development of art projects. The paper will reflect the qualitative research outcomes based on in-depth (IDI) interviews within the marketing sector in Poland and desk research. Art is a reflection of the spirit of our times. Moreover, now we are experiencing a significant acceleration in the development of technologies and their use in various sectors. The leading technologies that contribute to the development of the economy, including the creative sector, embrace technologies such as artificial intelligence, blockchain, extended reality, voice processing, and virtual beings. Artificial intelligence is one of the leading technologies developed for several decades, which is currently reaching a high level of interest and use in various sectors. However, the conducted research has shown that there is still low awareness of artificial intelligence and its wide application in various sectors. The study will show how artists use artificial intelligence in their art projects and how it can be translated into practice within the business. At the same time, the paper will raise awareness of the need for businesses to be inspired by the artistic environment. The research proved that there is still a need to popularize knowledge about this technology which is crucial for many sectors. Art projects are tools to develop knowledge and awareness of society and also various sectors. At the same time, artists may benefit from such collaboration. The paper will include selected aspects of mutual relations, areas of possible inspiration, and possible transfers of technological solutions. Those are AI applications in creative industries such as advertising and film, image recognition in art, and projects from different sectors.

Keywords: artificial intelligence, business, art, creative industry, technology

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Authors: Tami A. Ulhiza, Noor I. M. Puad, Azlin S. Azmi, Mohd. I. A. Malek

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High amount of chemical oxygen demand (COD) in starchy waste can be harmful to the environment. In common practice, starch processing wastewater is discharged to the river without proper treatment. However, starchy waste still contains complex sugars and organic acids. By the right pretreatment method, the complex sugar can be hydrolyzed into more readily digestible sugars which can be utilized to be converted into more valuable products. At the same time, the global demand of energy is inevitable. The continuous usage of fossil fuel as the main source of energy can lead to energy scarcity. Hydrogen is a renewable form of energy which can be an alternative energy in the future. Moreover, hydrogen is clean and carries the highest energy compared to other fuels. Biohydrogen produced from waste has significant advantages over chemical methods. One of the major problems in biohydrogen production is the raw material cost. The carbohydrate-rich starchy wastes such as tapioca, maize, wheat, potato, and sago wastes is a promising candidate to be used as a substrate in producing biohydrogen. The utilization of those wastes for biohydrogen production can provide cheap energy generation with simultaneous waste treatment. Therefore this paper aims to review variety source of starchy wastes that has been widely used to synthesize biohydrogen. The scope includes the source of waste, the performance in yielding hydrogen, the pretreatment method and the type of culture that is suitable for starchy waste.

Keywords: biohydrogen, dark fermentation, renewable energy, starchy waste

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Authors: Pauline Cuenin, Marcelo Leles Romarco Oliveira

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Based on their localities and following their ecological rationality, family-based farmers have experimented, adapted and innovated to improve their production systems continuously for millennia. With the technological package transfer processes of the so-called Green Revolution for agricultural holdings, farmers have become increasingly dependent on ready-made "recipes" built from so-called "universal" and global knowledge to face the problems that emerge in the management of local agroecosystems, thus reducing their creative and experiential capacities. However, the production of novelties within farms is fundamental to the transition to more sustainable agro food systems. In fact, as the fruits of local knowledge and / or the contextualization of exogenous knowledge, novelties are seen as seeds of transition. By presenting new techniques, new organizational forms and epistemological approaches, agroecology was pointed out as a way to encourage and promote the creative capacity of farmers. From this perspective, this theoretical work aims to analyze how agroecology encourages the innovative capacity of farmers, and in general, the production of novelties. For this, an analysis was made of the theoretical and methodological bases of agroecology through a literature review, specifically looking for the way in which it articulates the local with the global, complemented by an analysis of agro ecological Brazilian experiences. It was emphasized that, based on the peasant way of doing agriculture, that is, on ecological / social co-evolution or still called co-production (interaction between human beings and living nature), agroecology recognizes and revalues peasant involves the deep interactions of the farmer with his site (bio-physical and social). As a "place science," practice and movement, it specifically takes into consideration the local and empirical knowledge of farmers, which allows questioning and modifying the paradigms that underpin the current agriculture that have disintegrated farmers' creative processes. In addition to upgrade the local, agroecology allows the dialogue of local knowledge with global knowledge, essential in the process of changes to get out of the dominant logic of thought and give shape to new experiences. In order to reach this articulation, agroecology involves new methodological focuses seeking participatory methods of study and intervention that express themselves in the form of horizontal spaces of socialization and collective learning that involve several actors with different knowledge. These processes promoted by agroecology favor the production of novelties at local levels for expansion at other levels, such as the global, through trans local agro ecological networks.

Keywords: agroecology, creativity, global, local, novelty

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Authors: Khairul Bariah Sulaiman, Tajul Aris Yang

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Malaysian dried cocoa beans have been reported to have low quality flavour and are often sold at discounted prices. Various efforts have been made to improve the Malaysian beans quality. Among these efforts is introduction of the shallow box fermentation technique and pulp preconditioned through pods storage. However, after nearly four decades of the effort was done, Malaysian cocoa farmers still received lower prices for their beans. So, this study was carried out in order to assess the flavour quality of dried cocoa beans produced by shallow box fermentation techniques, combination of shallow box fermentation with pods storage and compared to dried cocoa beans obtained from Ghana. A total of eight samples of dried cocoa was used in this study, which one of the samples was Ghanaian beans (coded with no.8), while the rest were Malaysian cocoa beans with different post-harvest processing (coded with no. 1, 2, 3, 4, 5, 6 and 7). Cocoa liquor was prepared from all samples in the prescribed techniques and sensory evaluation was carried out using Quantitative Descriptive Analysis (QDA) Method with 0-10 scale by Malaysian Cocoa Board trained panelist. Sensory evaluation showed that cocoa attributes for all cocoa liquors ranging from 3.5 to 5.3, whereas bitterness was ranging from 3.4 to 4.6 and astringent attribute ranging from 3.9 to 5.5, respectively. Meanwhile, all cocoa liquors were having acid or sourness attribute ranging from 1.6 to 3.6, respectively. In general cocoa liquor prepared from sample coded no 4 has almost similar flavour profile and no significantly different at p < 0.05 with Ghana, in term of most flavour attributes as compared to the other six samples.

Keywords: cocoa beans, flavour, fermentation, shallow box, pods storage

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Authors: Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam

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Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.

Keywords: automated testing, natural language, restricted user story modeling, software engineering, software testing, test case specification, transformation and automation, user story, web application testing

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Authors: Tamer El-Messery, Teresa Sanchez-Moya, Ruben Lopez-Nicolas, Gaspar Ros, Esmat Aly

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Olive leaves (OLs), the main by-product of the olive oil industry, have a considerable amount of phenolic compounds. The exploitation of these compounds represents the current trend in food processing. In this study, OLs polyphenols were microencapsulated with polycaprolactone (PCL) and utilized in formulating novel functional yoghurt. PCL-microcapsules were characterized by scanning electron microscopy, and Fourier transform infrared spectrometry analysis. Their total phenolic (TPC), total flavonoid (TFC) contents, and antioxidant activities (DPPH, FRAP, ABTS), and polyphenols bioaccessibility were measured after oral, gastric, and intestinal steps of in vitro digestion. The four yoghurt formulations (containing 0, 25, 50, and 75 mg of PCL-microsphere/100g yoghurt) were evaluated for their pH, acidity, syneresis viscosity, and color during storage. In vitro digestion significantly affected the phenolic composition in non-encapsulated extract while had a lower impact on encapsulated phenolics. Higher protection was provided for encapsulated OLs extract, and their higher release was observed at the intestinal phase. Yoghurt with PCL-microsphere had lower viscosity, syneresis, and color parameters, as compared to control yoghurt. Thus, OLs represent a valuable and cheap source of polyphenols which can be successfully applied, in microencapsulated form, to formulate functional yoghurt.

Keywords: yoghurt quality attributes, olive leaves, phenolic and flavonoids compounds, antioxidant activity, polycaprolactone as microencapsulant

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Authors: Aysha Al Sha'aibi

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Algal blooms of the dinoflagellate species Noctiluca scintillans became frequent events in Omani waters. The current study aims at elucidating the abundance, size variation and observations on the feeding mechanism performed by this species during the winter bloom. An attempt was made, to relate observed biological parameters of the Noctiluca population to environmental factors. Field studies spanned the period from December 2014 to April 2015. Samples were collected from Bandar Rawdah (Muscat region) by Bongo nets, twice per week, from the surface and the integrated upper mixed layer. The measured environmental variables were: temperature, salinity, dissolved oxygen, chlorophyll a, turbidity, nitrite, phosphate, wind speed and rainfall. During the winter bloom (from December 2014 through February 2015), the abundance exhibited the highest concentration on 17 February (640.24×106 cell.L-1) in oblique samples and 83.9x103 cell.L-1 in surface samples, with a subsequent decline up to the end of April. The average number of food vacuoles inside Noctiluca cells was 1.5 per cell; the percentage of feeding Noctiluca compared to the entire population varied from 0.01% to 0.03%. Both the surface area of the Noctiluca symbionts (Pedinomonas noctilucae) and cell diameter were maximal in December. In oblique samples the highest average cell diameter and the surface area of symbiont algae were 751.7 µm and 179.2x103 µm2 respectively. In surface samples, highest average cell diameter and the surface area of symbionts were 760 µm and 284.05x103 µm2 respectively. No significant correlations were detected between Noctiluca’s biological parameters and environmental variables except for the correlation between cell diameter and chlorophyll a, also between symbiotic algae surface area and chlorophyll a. The high correlation of chlorophyll a was as a reason of endosymbiotic algae Pedinomonas noctilucae and green Noctiluca enhanced chlorophyll during bloom. All correlations among biological parameters were significant; they are perhaps one of major factors that mediating high growth rates, generating millions of cell per liter in a short time range. The results gained from this study will provide a beneficial background for understanding deeply the development of coastal algal blooms of Noctiluca scintillans. Moreover, results could be used in different applications related to marine environment.

Keywords: abundance, feeding activities, Noctiluca scintillans, Oman

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Michel A. Thomet

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A discrete-event simulation model was used to perform a Reliability-Availability-Maintainability (RAM) study of a large petrochemical complex which included sixteen process units, and seven feeds and intermediate streams. All the feeds and intermediate streams have associated storage tanks, so that if a processing unit fails and shuts down, the downstream units can keep producing their outputs. This also helps the upstream units which do not have to reduce their outputs, but can store their excess production until the failed unit restart. Each process unit and each pipe section carrying the feeds and intermediate streams has a probability of failure with an associated distribution and a Mean Time Between Failure (MTBF), as well as a distribution of the time to restore and a Mean Time To Restore (MTTR). The utilities supporting the process units can also fail and have their own distributions with specific MTBF and MTTR. The model runs are for ten years or more and the runs are repeated several times to obtain statistically relevant results. One of the main results is the On-Stream factor (OSF) of each process unit (percent of hours in a year when the unit is running in nominal conditions). One of the objectives of the study was to investigate if the storage capacity of each of the feeds and the intermediate stream was adequate. This was done by increasing the storage capacities in several steps and through running the simulation to see if the OSF were improved and by how much. Other objectives were to see if the failure of the utilities were an important factor in the overall OSF, and what could be done to reduce their failure rates through redundant equipment.

Keywords: business continuity, on-stream factor, petrochemical, RAM study, simulation, MTBF

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: H. Shahid

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Due to Ozone layer depletion on earth, the incoming ultraviolet (UV) radiation is recorded at its high index levels such as 25 in South Peru (13.5° S, 3360 m a.s.l.) Also, the planning of human inhabitation on Mars is under discussion where UV radiations are quite high. The exposure to UV is health hazardous and is avoided by UV filters. On the other hand, artificial UV sources are in use for water thermolysis to generate Hydrogen and Oxygen, which are later used as fuels. This paper presents the utility of employing UVA (315-400nm) and UVB (280-315nm) electromagnetic radiation from the solar spectrum to design and implement an optically active, Hydrogen and Oxygen generation system via thermolysis of desalinated seawater. The proposed system finds its utility on earth and can be deployed in the future on Mars (UVB). In this system, by using Fresnel lens arrays as an optical filter and via active tracking, the ultraviolet light from the sun is concentrated and then allowed to fall on two sub-systems of the proposed system. The first sub-system generates electrical energy by using UV based tandem photovoltaic cells such as GaAs/GaInP/GaInAs/GaInAsP and the second elevates temperature of water to lower the electric potential required to electrolyze the water. An empirical analysis is performed at 30 atm and an electrical potential is observed to be the main controlling factor for the rate of production of Hydrogen and Oxygen and hence the operating point (Q-Point) of the proposed system. The hydrogen production rate in the case of the commercial system in static mode (650ᵒC, 0.6V) is taken as a reference. The silicon oxide electrolyzer cell (SOEC) is used in the proposed (UV) system for the Hydrogen and Oxygen production. To achieve the same amount of Hydrogen as in the case of the reference system, with minimum chamber operating temperature of 850ᵒC in static mode, the corresponding required electrical potential is calculated as 0.3V. However, practically, the Hydrogen production rate is observed to be low in comparison to the reference system at 850ᵒC at 0.3V. However, it has been shown empirically that the Hydrogen production can be enhanced and by raising the electrical potential to 0.45V. It increases the production rate to the same level as is of the reference system. Therefore, 850ᵒC and 0.45V are assigned as the Q-point of the proposed system which is actively stabilized via proportional integral derivative controllers which adjust the axial position of the lens arrays for both subsystems. The functionality of the controllers is based on maintaining the chamber fixed at 850ᵒC (minimum operating temperature) and 0.45V; Q-Point to realize the same Hydrogen production rate as-is for the reference system.

Keywords: hydrogen, oxygen, thermolysis, ultraviolet

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Abhinay Puvvala, Veerendra Kumar Rai

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A bottleneck situation arises when the outflow is lesser than the inflow in a pipe-like setup. A more practical interpretation of bottlenecks emphasizes on the realization of Service Level Objectives (SLOs) at given workloads. Our approach detects two key aspects of bottlenecks – when and where. To identify ‘when’ we continuously poll on certain key metrics such as resource utilization, processing time, request backlog and throughput at a system level. Further, when the slope of the expected sojourn time at a workload is greater than ‘K’ times the slope of expected sojourn time at the previous step of the workload while the workload is being gradually increased in discrete steps, a bottleneck situation arises. ‘K’ defines the threshold condition and is computed based on the system’s service level objectives. The second aspect of our approach is to identify the location of the bottleneck. In multi-tier systems with a complex network of layers, it is a challenging problem to locate bottleneck that affects the overall system performance. We stage the system by varying workload incrementally to draw a correlation between load increase and system performance to the point where Service Level Objectives are violated. During the staging process, multiple metrics are monitored at hardware and application levels. The correlations are drawn between metrics and the overall system performance. These correlations along with the Service Level Objectives are used to arrive at the threshold conditions for each of these metrics. Subsequently, the same method used to identify when a bottleneck occurs is used on metrics data with threshold conditions to locate bottlenecks.

Keywords: bottleneck, workload, service level objectives (SLOs), throughput, system performance

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Emmanuel Ikechuckwu Onwubuya, Afees Adebayo Oladejo

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Background: The use of medicinal plants in the treatment of chronic diseases especially myocardial infarction, is gaining wide acceptance globally. Andrographis paniculata (Acanthaceae) is a medicinal plant commonly known as the king of bitters in Nigeria and has been acclaimed for several therapeutic activities. Materials and methods: This study investigated the cardio-protective effect of the leaf extract of A. paniculata in isoproterenol-induced myocardial infarction. Fresh green leaves of A paniculata were harvested from the Faculty of Agriculture farmland, Nnamdi Azikiwe University, Awka, Nigeria. Identification and authentication of the plant were carried out at the Department of Botany, Nnamdi Azikiwe University and a voucher specimen was deposited at the herbarium. The plant material was then shredded, air-dried under shade and pulverized. The fine powders obtained were weighed and extraction was done via a solvent combination of water and ethanol (3:7) for 72 hr via maceration. The filtrate gotten was evaporated to dryness to obtain the ethanol extract, which was used for further bioassay study. The bioactive constituents of the plant extract were quantitatively analyzed by Gas chromatography-mass spectrometry (GC-MS). The animals were administered the extract of A. paniculata orally for seven days at a divided dose of 100 mg/kg, 200 mg/kg and 400 mg/kg body weights. On the eighth day, myocardial infarction was induced through subcutaneous administration of isoproterenol at a dose of 150 mg/kg/day diluted in 2 ml of saline on two consecutive days. Subsequently, the blood pressures were monitored and blood was collected for bioassay studies. Results: The results of the study showed that the leaf extract of A. paniculata was rich in Dodecanoic acid (8.261%), 4-Dibenzofuranamine (6.03%), Cyclotrisiloxane (4.679 %). The findings also showed a significant decrease (p>0.05) in the Mean arterial blood pressure, heart rate, aspartate transaminase, alanine transaminase, creatinine kinase and lactate dehydrogenase activities of the treatment group compared with the untreated control group while the antioxidant (superoxide dismutase, catalase and glutathione) activities were significantly increased in the treatment group, compared with the untreated control group. Conclusion: The findings of this work have shown that the leaf of A. paniculata was rich in bioactive compounds, which could be synthesized to produce plant-based products to fight cardiovascular diseases, especially myocardial infarction.

Keywords: cardiovascular disease, myocardial infarction, medicinal plant, andrographis paniculata, isoproterenol

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Authors: A. Somaya Madkour, B. Abeer sheta, C. Fatma Badr El Dine, D. Yasser Elwakeel, E. Nermine AbdAllah

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Criminal offenders have a fundamental goal not to leave any traces at the crime scene. Some may suppose that items recovered underwater will have no forensic value, therefore, they try to destroy the traces by throwing items in water. These traces are subjected to the destructive environmental effects. This can represent a challenge for Forensic experts investigating finger marks. Accordingly, the present study was conducted to determine the optimal method for latent fingerprints development on non-porous surfaces submerged in aquatic environments at different time interval. The two factors analyzed in this study were the nature of aquatic environment and length of submerged time. In addition, the quality of developed finger marks depending on the used method was also assessed. Therefore, latent fingerprints were deposited on metallic, plastic and glass objects and submerged in fresh or sea water for one, two, and ten days. After recovery, the items were subjected to cyanoacrylate fuming, black powder and small particle reagent processing and the prints were examined. Each print was evaluated according to fingerprint quality assessment scale. The present study demonstrated that the duration of submersion affects the quality of finger marks; the longer the duration, the worse the quality.The best results of visualization were achieved using cyanoacrylate either in fresh or sea water. This study has also revealed that the exposure to sea water had more destructive influence on the quality of detected finger marks.

Keywords: fingerprints, fresh water, sea, non-porous

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Authors: Mehari Kahsay, Krishna Murthy Kyathegowda, Temesgen Berhanu

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Aluminum matrix composites have gained focus on research and industrial use, especially those not requiring extreme loading or thermal conditions, for the last few decades. Their relatively low cost, simple processing and attractive properties are the reasons for the widespread use of aluminum matrix composites in the manufacturing of automobiles, aircraft, military, and sports goods. In this article, the microstructure, mechanical, and corrosion behaviors of the aluminum metal matrix were reviewed, focusing on the stir casting fabrication process and usage of agro/industrial waste reinforcement particles. The results portrayed that mechanical properties like tensile strength, ultimate tensile strength, hardness, percentage of elongation, impact, and fracture toughness are highly dependent on the amount, kind, and size of reinforcing particles. Additionally, uniform distribution, wettability of reinforcement particles, and the porosity level of the resulting composite also affect the mechanical and corrosion behaviors of aluminum matrix composites. The two-step stir-casting process resulted in better wetting characteristics, a lower porosity level, and a uniform distribution of particles with proper handling of process parameters. On the other hand, the inconsistent and contradicting results on corrosion behavior regarding monolithic and hybrid aluminum matrix composites need further study.

Keywords: microstructure, mechanical behavior, corrosion, aluminum matrix composite

Procedia PDF Downloads 70