Search results for: sustainable decision making

Authors: Balarabe Z. Ahmad, Anne-Lorène Vernay

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The emergence of electricity in Nigeria was dated back to 1896. The power plants have the potential to generate 12,522 MW of electric power. Whereas current dispatch is about 4,000 MW, access to electrification is about 60%, with consumption at 0.14 MWh/capita. The government embarked on energy reforms to mitigate energy poverty. The reform targeted the provision of electricity access to 75% of the population by 2020 and 90% by 2030. Growth of total electricity demand by a factor of 5 by 2035 had been projected. This means that Nigeria will require almost 530 TWh of electricity which can be delivered through generators with a capacity of 65 GW. Analogously, the geographical location of Nigeria has placed it in an advantageous position as the source of solar energy; the availability of a high sunshine belt is obvious in the country. The implication is that the far North, where energy poverty is high, equally has about twice the solar radiation as against southern Nigeria. Hence, the chance of generating solar electricity is 66% possible at 11850 x 103 GWh per year, which is one hundred times the current electricity consumption rate in the country. Harvesting these huge potentials may be a mirage if the entrepreneurs in the solar panel business are left with the conventional business models that are not uncertainty resilient. Currently, business entities in RE in Nigeria are uncertain of; accessing the national grid, purchasing potentials of cooperating organizations, currency fluctuation and interest rate increases. Uncertainties such as the security of projects and government policy are issues entrepreneurs must navigate to remain sustainable in the solar panel industry in Nigeria. The aim of this paper is to identify how entrepreneurial firms consider uncertainties in developing workable business models for commercializing solar energy projects in Nigeria. In an attempt to develop a novel business model, the paper investigated how entrepreneurial firms assess and navigate uncertainties. The roles of key stakeholders in helping entrepreneurs to manage uncertainties in the Nigeria RE sector were probed in the ongoing study. The study explored empirical uncertainties that are peculiar to RE entrepreneurs in Nigeria. A mixed-mode of research was embraced using qualitative data from face-to-face interviews conducted on the Solar Energy Entrepreneurs and the experts drawn from key stakeholders. Content analysis of the interview was done using Atlas. It is a nine qualitative tool. The result suggested that all stakeholders are required to synergize in developing an uncertainty resilient business model. It was opined that the RE entrepreneurs need modifications in the business recommendations encapsulated in the energy policy in Nigeria to strengthen their capability in delivering solar energy solutions to the yawning Nigerians.

Keywords: uncertainties, entrepreneurial, business model, solar-panel

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Authors: Maureen Kamau, Gulnaz Mohamoud, Adelaide Lusambili, Njeri Nyanja

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Life expectancy has increased over the last century amongst older individuals, and in particular, those 60 years and over. The World Health Organization estimates that the world's population of persons over 60 years will rise to 22 per cent by the year 2050. Ageing is associated with increasing disability, multiple chronic conditions, and an increase in the use of health services. These multiple chronic conditions are managed with polypharmacy. Polypharmacy has numerous adverse effects including non-adherence, poor compliance to the various medications, reduced appetite, and risk of fall. Studies on polypharmacy and ageing are few and poorly understood especially in low and middle - income countries. The aim of this study was to explore the knowledge, attitudes and beliefs of older people towards polypharmacy. A qualitative study of 15 patients aged 60 years and above, taking more than five medications per day were conducted at the Aga Khan University using Semi-structured in-depth interviews. Three interviews were pilot interviews, and data analysis was performed on 12 interviews. Data were analyzed using NVIVO 12 software. A thematic qualitative analysis was carried out guided by Braun and Clarke (2006) framework. Themes identified; - knowledge of their co-morbidities and of the medication that older persons take, sources of information about medicines, and storage of the medication, experiences and attitudes of older patients towards polypharmacy both positive and negative, older peoples beliefs and their coping mechanisms with polypharmacy. The study participants had good knowledge on their multiple co-morbidities, and on the medication they took. The patients had positive attitudes towards medication as it enhanced their health and well-being, and enabled them to perform their activities of daily living. There was a strong belief among older patients that the medications were necessary for their health. All these factors enhanced compliance to the multiple medication. However, some older patients had negative attitudes due to the pill burden, side effects of the medication, and stigma associated with being ill. Cost of healthcare was a concern, with most of the patients interviewed relying on insurance to cover the cost of their medication. Older patients had accepted that the medication they were prescribed were necessary for their health, as it enabled them to complete their activities of daily living. Some concerns about the side effects of the medication arose, and brought about the need for patient education that would ensure that the patients are aware of the medications they take, and potential side effects. The effect that the COVID 19 pandemic had in the healthcare of the older patients was evident by the number of the older patients avoided coming to the hospital during the period of the pandemic. The relationship with the primary care physician and the older patients is an important one, especially in LMICs such as Kenya, as many of the older patients trusted the doctors wholeheartedly to make the best decision about their health and about their medication. Prescription review is important to avoid the use of potentially inappropriate medication.

Keywords: polypharmacy, older patients, multiple chronic conditions, Kenya, Africa, qualitative study, indepth interviews, primary care

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Authors: Neha Sahu, Awantika Singh, Brijesh Kumar, K. R. Arya

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Taraxacum officinale Weber or dandelion (Asteraceae) is an important Indian traditional herb used to treat liver detoxification, digestive problems, spleen, hepatic and kidney disorders, etc. The plant is well known to possess important phenolic and flavonoids to serve as a potential source of antioxidative and chemoprotective agents. Biosynthesis of bioactive compounds through in vitro cultures is a requisite for natural resource conservation and to provide an alternative source for pharmaceutical applications. Thus an efficient and reproducible protocol was developed for in vitro biosynthesis of bioactive antioxidative compounds from leaf derived callus and in vitro regenerated cultures of Taraxacum officinale using MS media fortified with various combinations of auxins and cytokinins. MS media containing 0.25 mg/l 2, 4-D (2, 4-Dichloro phenoxyacetic acid) with 0.05 mg/l 2-iP [N6-(2-Isopentenyl adenine)] was found as an effective combination for the establishment of callus with 92 % callus induction frequency. Moreover, 2.5 mg/l NAA (α-Naphthalene acetic acid) with 0.5 mg/l BAP (6-Benzyl aminopurine) and 1.5 mg/l NAA showed the optimal response for in vitro plant regeneration with 80 % regeneration frequency and rooting respectively. In vitro regenerated plantlets were further transferred to soil and acclimatized. Quantitative variability of accumulated bioactive compounds in cultures (in vitro callus, plantlets and acclimatized) were determined through UPLC-MS/MS (ultra-performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry) and compared with wild plants. The phytochemical determination of in vitro and wild grown samples showed the accumulation of 6 compounds. In in vitro callus cultures and regenerated plantlets, two major antioxidative compounds i.e. chlorogenic acid (14950.0 µg/g and 4086.67 µg/g) and umbelliferone (10400.00 µg/g and 2541.67 µg/g) were found respectively. Scopoletin was found to be highest in vitro regenerated plants (83.11 µg/g) as compared to wild plants (52.75 µg/g). Notably, scopoletin is not detected in callus and acclimatized plants, but quinic acid (6433.33 µg/g) and protocatechuic acid (92.33 µg/g) were accumulated at the highest level in acclimatized plants as compared to other samples. Wild grown plants contained highest content (948.33 µg/g) of flavonoid glycoside i.e. luteolin-7-O-glucoside. Our data suggests that in vitro callus and regenerated plants biosynthesized higher content of antioxidative compounds in controlled conditions when compared to wild grown plants. These standardized cultural conditions may be explored as a sustainable source of plant materials for enhanced production and adequate supply of oxidative polyphenols.

Keywords: anti-oxidative compounds, in vitro cultures, Taraxacum officinale, UPLC-MS/MS

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Authors: R. S. Giraddi, C. M. Poleshi

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Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

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Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, solder joint reliability, NUDD, connectivity issues, qualifications, characterization and control

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

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Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

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Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

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Authors: Shahrukh Ahmad, Purnendu Bose

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Algal-Bacterial photobioreactors (ABPBRs) have emerged as a promising technology for sustainable biomass production and wastewater treatment. Nutrient removal is seldom done in sewage treatment plants and large volumes of wastewater which still have nutrients are being discharged and that can lead to eutrophication. That is why ABPBR plays a vital role in wastewater treatment. However, improving the efficiency of ABPBR remains a significant challenge. This study aims to enhance ABPBR efficiency by focusing on two key aspects: nutrient removal and cost-effective optimization of the light source. By integrating nutrient removal and cost analysis for light source optimization, this study proposes practical strategies for improving ABPBR efficiency. To reduce organic carbon and convert ammonia to nitrates, domestic wastewater from a 130 MLD sewage treatment plant (STP) was aerated with a hydraulic retention time (HRT) of 2 days. The treated supernatant had an approximate nitrate and phosphate values of 16 ppm as N and 6 ppm as P, respectively. This supernatant was then fed into the ABPBR, and the removal of nutrients (nitrate as N and phosphate as P) was observed using different colored LED bulbs, namely white, blue, red, yellow, and green. The ABPBR operated with a 9-hour light and 3-hour dark cycle, using only one color of bulbs per cycle. The study found that the white LED bulb, with a photosynthetic photon flux density (PPFD) value of 82.61 µmol.m-2 .sec-1 , exhibited the highest removal efficiency. It achieved a removal rate of 91.56% for nitrate and 86.44% for phosphate, surpassing the other colored bulbs. Conversely, the green LED bulbs showed the lowest removal efficiencies, with 58.08% for nitrate and 47.48% for phosphate at an HRT of 5 days. The quantum PAR (Photosynthetic Active Radiation) meter measured the photosynthetic photon flux density for each colored bulb setting inside the photo chamber, confirming that white LED bulbs operated at a wider wavelength band than the others. Furthermore, a cost comparison was conducted for each colored bulb setting. The study revealed that the white LED bulb had the lowest average cost (Indian Rupee)/light intensity (µmol.m-2 .sec-1 ) value at 19.40, while the green LED bulbs had the highest average cost (INR)/light intensity (µmol.m-2 .sec-1 ) value at 115.11. Based on these comparative tests, it was concluded that the white LED bulbs were the most efficient and costeffective light source for an algal photobioreactor. They can be effectively utilized for nutrient removal from secondary treated wastewater which helps in improving the overall wastewater quality before it is discharged back into the environment.

Keywords: algal bacterial photobioreactor, domestic wastewater, nutrient removal, led bulbs

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Authors: Mokhlisur Rahman

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The growing consensus among scientists and world leaders indicates that immediate action should be considered regarding the climate change phenomenon. However, climate change is no more a global issue but a personal one. Thus, individual participation is necessary to address such a significant issue. Studies show that individuals who perceive climate change as a personal issue are more likely to act toward it. This abstract presents augmented reality (A.R.) technology in the social media platform Facebook video advertising. The idea involves creating a video advertisement that enables users to interact with the video by navigating its features and experiencing the result uniquely and engagingly. This advertisement uses A.R. to bring changes, such as people making changes in real-life scenarios by simple clicks on the video and hearing an instant rewarding fact about their choices. The video shows three options: room, lawn, and driveway. Users select one option and engage in interaction based on while holding the camera in their personal spaces: Suppose users select the first option, room, and hold their camera toward spots such as by the windows, balcony, corners, and even walls. In that case, the A.R. offers users different plants appropriate for those unoccupied spaces in the room. Users can change the options of the plants and see which space at their house deserves a plant that makes it more natural. When a user adds a natural element to the video, the video content explains a piece of beneficiary information about how the user contributes to the world more to be livable and why it is necessary. With the help of A.R., if users select the second option, lawn, and hold their camera toward their lawn, the options are various small trees for their lawn to make it more environmentally friendly and decorative. The video plays a beneficiary explanation here too. Suppose users select the third option, driveway, and hold their camera toward their driveway. In that case, the A.R. video option offers unique recycle bin designs using A.I. measurement of spaces. The video plays audio information on anthropogenic contribution to greenhouse gas emission. IoT embeds tracking code in the video ad on Facebook, which stores the exact number of views in the cloud for data analysis. An online survey at the end collects short qualitative answers. This study helps understand the number of users involved and willing to change their behavior; It makes personalized advertising in social media. Considering the current state of climate change, the urgency for action is increasing. This ad increases the chance to make direct connections with individuals and gives a sense of personal responsibility for climate change to act

Keywords: motivations, climate, iot, personalized-advertising, action

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Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

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Authors: Mojtaba Eshraghi Arani

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The freight forwarders, who are known as the Architect of Transportation, play a vital role in the supply chain management. The package of various services which they provide has made the legal nature of freight forwarders very controversial, so that they might be qualified once as principal or carrier and, on other occasions, as agent of the shipper as the case may be. They could even be involved in the transportation process as the agent of shipping line, which makes the situation much more complicated. The courts in all countries have long had trouble in distinguishing the “forwarder as agent” from “forwarder as principal” (as it is outstanding in the prominent case of “Vastfame Camera Ltd v Birkart Globistics Ltd And Others” 2005, Hong Kong). It is not fully known that in the case of a claim against the forwarder, what particular parameter would be used by the judge among multiple, and sometimes contradictory, tests for determining the scope of the forwarder liability. In particular, every country has its own legal parameters for qualifying the freight forwarders that is completely different from others, as it is the case in France in comparison with Germany and England. The unpredictability of the courts’ decisions in this regard has provided the freight forwarders with the opportunity to impose any limitation or exception of liability while pretending to play the role of a principal, consequently making the cargo interests incur ever-increasing damage. The transportation industry needs to remove such uncertainty by unifying national laws governing freight forwarders liability. A long time ago, in 1967, The International Institute for Unification of Private Law (UNIDROIT) prepared a draft convention called “Draft Convention on Contract of Agency for Forwarding Agents Relating to International Carriage of Goods” (hereinafter called “UNIDROIT draft convention”). The UNIDROIT draft convention provided a clear and certain framework for the liability of freight forwarder in each capacity as agent or carrier, but it failed to transform to a convention, and eventually, it was consigned to oblivion. Today, after nearly 6 decades from that era, the necessity of such convention can be felt apparently. However, one might reason that the same grounds, in particular, the resistance by forwarders’ association, FIATA, exist yet, and thus it is not logical to revive a forgotten draft convention after such long period of time. It is argued in this article that the main reason for resisting the UNIDROIT draft convention in the past was pending efforts for developing the “1980 United Nation Convention on International Multimodal Transport of Goods”. However, the latter convention failed to become in force on due time in a way that there was no new accession since 1996, as a result of which the UNIDROIT draft convention must be revived strongly and immediately submitted to the relevant diplomatic conference. A qualitative method with the concept of interpretation of data collection has been used in this manuscript. The source of the data is the analysis of international conventions and cases.

Keywords: freight forwarder, revival, agent, principal, uidroit, draft convention

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Authors: T. J. O Ceallaigh

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Subject matter driven programs such as immersion programs are increasingly popular across the world. These programs have allowed for extensive experimentation in the realm of second language teaching and learning and have been at the centre of many research agendas since their inception. Even though immersion programs are successful, especially in terms of second language development, they remain complex to implement and not always as successful as what we would hope them to be. Among all the challenges these varied programs face, research indicates that the primary issue lies in the difficulty to create well-balanced programs where both content instruction and language/literacy instruction can be targeted simultaneously. Initial teacher education and professional development experiences are key drivers of successful language immersion education globally. They are critical to the supply of teachers with the mandatory linguistic and cultural competencies as well as associated pedagogical practices required to ensure learners’ success. However, there is a significant dearth of research on professional development experiences of immersion teachers. We lack an understanding of the nature of their expertise and their needs in terms of professional development as well as their perceptions of the primary challenges they face as they attempt to formulate a coherent pedagogy of integrated language and content instruction. Such an understanding is essential if their specific needs are to be addressed appropriately and thus improve the overall quality of immersion programs. This paper reports on immersion teacher perceptions of online professional development experiences that have a positive impact on their ability to facilitate language and content connections in instruction. Twenty Irish-medium immersion teachers engaged in the instructional integration of language and content in a systematic and developmental way during a year-long online professional development program. Data were collected from a variety of sources e.g., an extensive online questionnaire, individual interviews, reflections, assignments and focus groups. This study provides compelling evidence of the potential of online professional development experiences as a pedagogical framework for understanding the complex and interconnected knowledge demands that arise in content and language integration in immersion. Findings illustrate several points of access to classroom research and pedagogy and uncover core aspects of high impact online experiences. Teachers identified aspects such as experimentation and risk-taking, authenticity and relevance, collegiality and collaboration, motivation and challenge and teacher empowerment. The potential of the online experiences to foster teacher language awareness was also identified as a contributory factor to success. The paper will conclude with implications for designing meaningful and effective online CLIL professional development experiences.

Keywords: content and language integrated learning , immersion pedagogy, professional development, teacher language awareness

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Authors: Kedar J. Mahadeshwar

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Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

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Authors: Y. Roumila, D. Meziani, R. Bagtache, K. Abdmeziem, M. Trari

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Heterogeneous photocatalysis over semiconductors has proved its effectiveness in the treatment of wastewaters since it works under soft conditions. It has emerged as a promising technique, giving rise to less toxic effluents and offering the opportunity of using sunlight as a sustainable and renewable source of energy. Many compounds have been used as photocatalysts. Though synthesized ones are intensively used, they remain expensive, and their synthesis involves special conditions. We thus thought of implementing a natural material, a phosphate ore, due to its low cost and great availability. Our work is devoted to the removal of hazardous organic pollutants, which cause several environmental problems and health risks. Among them, dye pollutants occupy a large place. This work relates to the study of the photodegradation of methyl violet (MV) and rhodamine B (RhB), in single and binary systems, under UV light and sunlight irradiation. Methyl violet is a triarylmethane dye, while RhB is a heteropolyaromatic dye belonging to the Xanthene family. In the first part of this work, the natural compound was characterized using several physicochemical and photo-electrochemical (PEC) techniques: X-Ray diffraction, chemical, and thermal analyses scanning electron microscopy, UV-Vis diffuse reflectance measurements, and FTIR spectroscopy. The electrochemical and photoelectrochemical studies were performed with a Voltalab PGZ 301 potentiostat/galvanostat at room temperature. The structure of the phosphate material was well characterized. The photo-electrochemical (PEC) properties are crucial for drawing the energy band diagram, in order to suggest the formation of radicals and the reactions involved in the dyes photo-oxidation mechanism. The PEC characterization of the natural phosphate was investigated in neutral solution (Na₂SO₄, 0.5 M). The study revealed the semiconducting behavior of the phosphate rock. Indeed, the thermal evolution of the electrical conductivity was well fitted by an exponential type law, and the electrical conductivity increases with raising the temperature. The Mott–Schottky plot and current-potential J(V) curves recorded in the dark and under illumination clearly indicate n-type behavior. From the results of photocatalysis, in single solutions, the changes in MV and RhB absorbance in the function of time show that practically all of the MV was removed after 240 mn irradiation. For RhB, the complete degradation was achieved after 330 mn. This is due to its complex and resistant structure. In binary systems, it is only after 120 mn that RhB begins to be slowly removed, while about 60% of MV is already degraded. Once nearly all of the content of MV in the solution has disappeared (after about 250 mn), the remaining RhB is degraded rapidly. This behaviour is different from that observed in single solutions where both dyes are degraded since the first minutes of irradiation.

Keywords: environment, organic pollutant, phosphate ore, photodegradation

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Authors: A. Falenski, A. Kaesbohrer, M. Filter

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Introduction: Risk assessments can be performed in various ways and in different degrees of complexity. In order to assess risks associated with imported foods additional information needs to be taken into account compared to a risk assessment on regional products. The present review is an overview on currently available best practise approaches and data sources used for food import risk assessments (IRAs). Methods: A literature review has been performed. PubMed was searched for articles about food IRAs published in the years 2004 to 2014 (English and German texts only, search string “(English [la] OR German [la]) (2004:2014 [dp]) import [ti] risk”). Titles and abstracts were screened for import risks in the context of IRAs. The finally selected publications were analysed according to a predefined questionnaire extracting the following information: risk assessment guidelines followed, modelling methods used, data and software applied, existence of an analysis of uncertainty and variability. IRAs cited in these publications were also included in the analysis. Results: The PubMed search resulted in 49 publications, 17 of which contained information about import risks and risk assessments. Within these 19 cross references were identified to be of interest for the present study. These included original articles, reviews and guidelines. At least one of the guidelines of the World Organisation for Animal Health (OIE) and the Codex Alimentarius Commission were referenced in any of the IRAs, either for import of animals or for imports concerning foods, respectively. Interestingly, also a combination of both was used to assess the risk associated with the import of live animals serving as the source of food. Methods ranged from full quantitative IRAs using probabilistic models and dose-response models to qualitative IRA in which decision trees or severity tables were set up using parameter estimations based on expert opinions. Calculations were done using @Risk, R or Excel. Most heterogeneous was the type of data used, ranging from general information on imported goods (food, live animals) to pathogen prevalence in the country of origin. These data were either publicly available in databases or lists (e.g., OIE WAHID and Handystatus II, FAOSTAT, Eurostat, TRACES), accessible on a national level (e.g., herd information) or only open to a small group of people (flight passenger import data at national airport customs office). In the IRAs, an uncertainty analysis has been mentioned in some cases, but calculations have been performed only in a few cases. Conclusion: The current state-of-the-art in the assessment of risks of imported foods is characterized by a great heterogeneity in relation to general methodology and data used. Often information is gathered on a case-by-case basis and reformatted by hand in order to perform the IRA. This analysis therefore illustrates the need for a flexible, modular framework supporting the connection of existing data sources with data analysis and modelling tools. Such an infrastructure could pave the way to IRA workflows applicable ad-hoc, e.g. in case of a crisis situation.

Keywords: import risk assessment, review, tools, food import

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Ahlam Ali, Katrina Lappin, Jaine Blayney, Ken Mills

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Leukaemia is the most frequently (30%) occurring type of paediatric cancer. Of these, approximately 80% are acute lymphoblastic leukaemia (ALL) with acute myeloid leukaemia (AML) cases making up the remaining 20% alongside other leukaemias. Unfortunately, children with AML do not have promising prognosis with only 60% surviving 5 years or longer. It has been highlighted recently the need for age-specific therapies for AML patients, with paediatric AML cases having a different mutational landscape compared with AML diagnosed in adult patients. Drug Repurposing is a recognized strategy in drug discovery and development where an already approved drug is used for diseases other than originally indicated. We aim to identify novel combination therapies with the promise of providing alternative more effective and less toxic induction therapy options. Our in-silico analysis highlighted ‘cell death and survival’ as an aberrant, potentially targetable pathway in paediatric AML patients. On this basis, 83 apoptotic inducing compounds were screened. A preliminary single agent screen was also performed to eliminate potentially toxic chemicals, then drugs were constructed into a pooled library with 10 drugs per well over 160 wells, with 45 possible pairs and 120 triples in each well. Seven cell lines were used during this study to represent the clonality of AML in paediatric patients (Kasumi-1, CMK, CMS, MV11-14, PL21, THP1, MOLM-13). Cytotoxicity was assessed up to 72 hours using CellTox™ Green reagent. Fluorescence readings were normalized to a DMSO control. Z-Score was assigned to each well based on the mean and standard deviation of all the data. Combinations with a Z-Score <2 were eliminated and the remaining wells were taken forward for further analysis. A well was considered ‘successful’ if each drug individually demonstrated a Z-Score <2, while the combination exhibited a Z-Score >2. Each of the ten compounds in one well (155) had minimal or no effect as single agents on cell viability however, a combination of two or more of the compounds resulted in a substantial increase in cell death, therefore the ten compounds were de-convoluted to identify a possible synergistic pair/triple combinations. The screen identified two possible ‘novel’ drug pairing, with BCL2 inhibitor ABT-737, combined with either a CDK inhibitor Purvalanol A, or AKT/ PI3K inhibitor LY294002. (ABT-737- 100 nM+ Purvalanol A- 1 µM) (ABT-737- 100 nM+ LY294002- 2 µM). Three possible triple combinations were identified (LY2409881+Akti-1/2+Purvalanol A, SU9516+Akti-1/2+Purvalanol A, and ABT-737+LY2409881+Purvalanol A), which will be taken forward for examining their efficacy at varying concentrations and dosing schedules, across multiple paediatric AML cell lines for optimisation of maximum synergy. We believe that our combination screening approach has potential for future use with a larger cohort of drugs including FDA approved compounds and patient material.

Keywords: AML, drug repurposing, ABT-737, apoptosis

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Authors: Dimitrios Kafetzopoulos

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Nowadays, companies are more concerned with adopting their own strategies for increased efficiency and sustainability. Dynamic environments are fertile fields for developing operational changes. For this purpose, organizations need to implement an advanced management philosophy that boosts changes to companies’ operation. Changes refer to new applications of knowledge, ideas, methods, and skills that can generate unique capabilities and leverage an organization’s competitiveness. So, in order to survive and compete in the global and niche markets, companies should incorporate the adoption of operational changes into their strategy with regard to their products and their processes. Creating the appropriate culture for changes in terms of products and processes helps companies to gain a sustainable competitive advantage in the market. Thus, the purpose of this study is to investigate the role of both incremental and radical changes into operations of a company, taking into consideration not only product changes but also process changes, and continues by measuring the impact of these two types of changes on business efficiency and sustainability of Greek manufacturing companies. The above discussion leads to the following hypotheses: H1: Radical operational changes have a positive impact on firm efficiency. H2: Incremental operational changes have a positive impact on firm efficiency. H3: Radical operational changes have a positive impact on firm sustainability. H4: Incremental operational changes have a positive impact on firm sustainability. In order to achieve the objectives of the present study, a research study was carried out in Greek manufacturing firms. A total of 380 valid questionnaires were received while a seven-point Likert scale was used to measure all the questionnaire items of the constructs (radical changes, incremental changes, efficiency and sustainability). The constructs of radical and incremental operational changes, each one as one variable, has been subdivided into product and process changes. Non-response bias, common method variance, multicollinearity, multivariate normal distribution and outliers have been checked. Moreover, the unidimensionality, reliability and validity of the latent factors were assessed. Exploratory Factor Analysis and Confirmatory Factor Analysis were applied to check the factorial structure of the constructs and the factor loadings of the items. In order to test the research hypotheses, the SEM technique was applied (maximum likelihood method). The goodness of fit of the basic structural model indicates an acceptable fit of the proposed model. According to the present study findings, radical operational changes and incremental operational changes significantly influence both efficiency and sustainability of Greek manufacturing firms. However, it is in the dimension of radical operational changes, meaning those in process and product, that the most significant contributors to firm efficiency are to be found, while its influence on sustainability is low albeit statistically significant. On the contrary, incremental operational changes influence sustainability more than firms’ efficiency. From the above, it is apparent that the embodiment of the concept of the changes into the products and processes operational practices of a firm has direct and positive consequences for what it achieves from efficiency and sustainability perspective.

Keywords: incremental operational changes, radical operational changes, efficiency, sustainability

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Authors: Mustafa M. Donma, Orkide Donma

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The number of indices developed for the evaluation of obesity both in adults and pediatric population is ever increasing. These indices are also used in cases with metabolic syndrome (MetS), mostly the ultimate form of morbid obesity. Aside from anthropometric measurements, formulas constituted using these parameters also find clinical use. These formulas can be listed as two groups; being weight-dependent and –independent. Some are extremely sophisticated equations and their clinical utility is questionable in routine clinical practice. The aim of this study is to compare presently available obesity indices and find the most practical one. Their associations with MetS components were also investigated to determine their capacities in differential diagnosis of morbid obesity with and without MetS. Children with normal body mass index (N-BMI) and morbid obesity were recruited for this study. Three groups were constituted. Age- and sex- dependent BMI percentiles for morbid obese (MO) children were above 99 according to World Health Organization tables. Of them, those with MetS findings were evaluated as MetS group. Children, whose values were between 85 and 15 were included in N-BMI group. The study protocol was approved by the Ethics Committee of the Institution. Parents filled out informed consent forms to participate in the study. Anthropometric measurements and blood pressure values were recorded. Body mass index, hip index (HI), conicity index (CI), triponderal mass index (TPMI), body adiposity index (BAI), body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), waist-to-hip ratio (WHR) and waist circumference+hip circumference/2 ((WC+HC)/2) were the formulas examined within the scope of this study. Routine biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein-cholesterol (HDL-C) were performed. Statistical package program SPSS was used for the evaluation of study data. p<0.05 was accepted as the statistical significance degree. Hip index did not differ among the groups. A statistically significant difference was noted between N-BMI and MetS groups in terms of ABSI. All the other indices were capable of making discrimination between N-BMI-MO, N-BMI- MetS and MO-MetS groups. No correlation was found between FBG and any obesity indices in any groups. The same was true for INS in N-BMI group. Insulin was correlated with BAI, TPMI, CI, BRI, AVI and (WC+HC)/2 in MO group without MetS findings. In MetS group, the only index, which was correlated with INS was (WC+HC)/2. These findings have pointed out that complicated formulas may not be required for the evaluation of the alterations among N-BMI and various obesity groups including MetS. The simple easily computable weight-independent index, (WC+HC)/2, was unique, because it was the only index, which exhibits a valuable association with INS in MetS group. It did not exhibit any correlation with other obesity indices showing associations with INS in MO group. It was concluded that (WC+HC)/2 was pretty valuable practicable index for the discrimination of MO children with and without MetS findings.

Keywords: children, insulin, metabolic syndrome, obesity indices

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Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

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The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

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Authors: Celine Davis

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The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

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Authors: Md. Omar Bin Harun Khan

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The collapse of the infamous Rana Plaza, a multi-storeyed commercial building in Savar, near Dhaka, Bangladesh has brought with it a plethora of positive and negative consequences. Bangladesh being a key player in the export of clothing, found itself amidst a wave of economic upheaval following this tragic incident that resulted in numerous Bangladeshis, most of whom were factory workers. This paper compares the consequences that the country’s Ready Made Garments (RMG) sector is facing now, two years into the incident. The paper presents a comparison of statistical data from study reports and brings forward perspectives from all dimensions of Labour, Employment and Industrial Relations in Bangladesh following the event. The paper brings across the viewpoint of donor organizations and donor countries, the impacts of several initiatives taken by foreign organizations like the International Labour Organization, and local entities like the Bangladesh Garment Manufacturers and Exporters Association (BGMEA) in order to reinforce compliance and stabilize the shaky foundation that the RMG sector had found itself following the collapse. Focus of the paper remains on the stance taken by the suppliers in Bangladesh, with inputs from buying houses and factories, and also on the reaction of foreign brands. The paper also focuses on the horrific physical, mental and financial implications sustained by the victims and their families, and the consequent uproar from workers in general regarding compliance with work safety and workers’ welfare conditions. The purpose is to get across both sides of the scenario: the economic impact that suppliers / factories/ sellers/ buying houses/exporters have faced in Bangladesh as a result of complete loss of reliability on them regarding working standards; and also to cover the aftershock felt on the other end of the spectrum by the importers/ buyers, particularly the foreign entities, in terms of the sudden accountability of being affiliated with non- compliant factories. The collapse of Rana Plaza has received vast international attention and strong criticism. Nevertheless, the almost immediate strengthening of labourrights and the wholesale reform undertaken on all sides of the supply chain, evidence a move of all local and foreign stakeholders towards greater compliance and taking of precautionary steps for prevention of further disasters. The tragedy that Rana Plaza embodies served as a much-needed epiphany for the soaring RMG Sector of Bangladesh. Prompt co-operation on the part of all stakeholders and regulatory bodies now show a move towards sustainable development, which further ensures safeguarding against any future irregularities and pave the way for steady economic growth.

Keywords: economy, employment standards, Rana Plaza, RMG

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Authors: Gebreselassie Sebhatleab

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According to the Global Peace Index report (GPI, 2023), global peacefulness has deteriorated by more than 0.42%. Old and new conflicts, COVID-19, and political and cultural polarization are the main drivers of conflicts in the world. The 2022 was the deadliest year for armed conflict in the history of the GPI. In Ethiopia, over half a million people died in the Tigray war, which was the largest conflict death event since the 1994 Rwandan genocide. In total, 84 countries recorded an improvement, while 79 countries recorded a deterioration in peacefulness across the globe. The Russia-Ukraine war and its consequences were the main drivers of the deterioration in peacefulness globally. Both Russia and Ukraine are now ranked amongst the ten least peaceful countries, and Ukraine had the largest deterioration of any country in the 2023 GPI. In the same year, the global impact of violence on the economy was 17 percent, which was equivalent to 10.9% of global GDP. Besides, the brutal conflict in Tigray started in November. 2020 claimed more than half a million lives lost and displaced nearly 3 million people, along with widespread human rights violations and sexual violence has left deep damage on the population. The displaced people are still unable to return home because the western, southern and Eastern parts of Tigray are occupied by Eritrean and Amhara forces, despite the Pretoria Agreement. Currently, armed conflicts in Amhara in the Oromya regions are intensified, and human rights violations are being reported in both regions. Meanwhile, protests have been held by war-injured TDF members, IDPs and teachers in the Tigray region. Hence, the general objective of this project is to explore the challenges of peace-building processes in the border woredas of the Eastern Zone of the Tigray Region. Methodologically, the project will employ exploratory qualitative research designs to gather and analyze qualitative data. A purposive sampling technique will be applied to gather pertinent information from the key stakeholders. Open-ended interview questions will be prepared to gather relevant information about the challenges and perceptions of peacebuilding in the study area. Data will be analyzed using qualitative methods such as content analysis, narrative analysis and phenomenological analysis to deeply investigate the challenges of peace-building in the study woredas. Findings of this research project will be employed for program intervention to promote sustainable peace in the study area.

Keywords: peace building, conflcit and violence, political instability, insecurity

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Authors: Kamaran Fathulla

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Human creativity knows no bounds. More than a millennia ago humans have expressed their knowledge on cave walls and on clay artefacts. Using visuals such as diagrams and paintings have always provided us with a natural and intuitive medium for expressing such creativity. Making sense of human generated visualisation has been influenced by western scientific philosophies which are often reductionist in their nature. Theoretical frameworks such as those delivered by Peirce dominated our views of how to make sense of visualisation where a visual is seen as an emergent property of our thoughts. Others have reduced the richness of human-generated visuals to mere shapes drawn on a piece of paper or on a screen. This paper introduces an alternate framework where the centrality of human functioning is given explicit and richer consideration through the multi aspectual philosophical works of Herman Dooyeweerd. Dooyeweerd's framework of understanding reality was based on fifteen aspects of reality, each having a distinct core meaning. The totality of the aspects formed a ‘rainbow’ like spectrum of meaning. The thesis of this approach is that meaningful human functioning in most cases involves the diversity of all aspects working in synergy and harmony. Illustration of the foundations and applicability of this approach is underpinned in the case of humans use of diagramming for creative purposes, particularly within an educational context. Diagrams play an important role in education. Students and lecturers use diagrams as a powerful tool to aid their thinking. However, research into the role of diagrams used in education continues to reveal difficulties students encounter during both processes of interpretation and construction of diagrams. Their main problems shape up students difficulties with diagrams. The ever-increasing diversity of diagrams' types coupled with the fact that most real-world diagrams often contain a mix of these different types of diagrams such as boxes and lines, bar charts, surfaces, routes, shapes dotted around the drawing area, and so on with each type having its own distinct set of static and dynamic semantics. We argue that the persistence of these problems is grounded in our existing ways of understanding diagrams that are often reductionist in their underpinnings driven by a single perspective or formalism. In this paper, we demonstrate the limitations of these approaches in dealing with the three problems. Consequently, we propose, discuss, and demonstrate the potential of a nonreductionist framework for understanding diagrams based on Symbolic and Spatial Mappings (SySpM) underpinned by Dooyeweerd philosophy. The potential of the framework to account for the meaning of diagrams is demonstrated by applying it to a real-world case study physics diagram.

Keywords: SySpM, drawing style, mapping

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Authors: Ines Antunes, Andrea Massari, Concetta Bartucca

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Greenhouse gasses (GHG) role in the atmosphere has been well known since the 19th century; however, researchers have begun to relate them to climate changes only in the second half of the following century. From this moment, scientists started to correlate the presence of GHG such as CO₂ with the global warming phenomena. This has raised the awareness not only of those who were experts in this field but also of public opinion, which is becoming more and more sensitive to environmental pollution and sustainability issues. Nowadays the reduction of GHG emissions is one of the principal objectives of EU nations. The target is an 80% reduction of emissions in 2050 and to reach the important goal of carbon neutrality. Road sector is responsible for an important amount of those emissions (about 20%). The most part is due to traffic, but a good contribution is also given directly or indirectly from road construction and maintenance. Raw material choice and reuse of post-consumer plastic rather than a cleverer design of roads have an important contribution to reducing carbon footprint. Bituminous membranes can be successfully used as reinforcement systems in asphalt layers to improve road pavement performance against cracking. Composite materials coupling membranes with grids and/or fabrics should be able to combine improved tensile properties of the reinforcement with stress absorbing and waterproofing effects of membranes. Polyglass, with its brand dedicated to road construction and maintenance called Polystrada, has done more than this. The company's target was not only to focus sustainability on the final application but also to implement a greener mentality from the cradle to the grave. Starting from production, Polyglass has made important improvements finalized to increase efficiency and minimize waste. The installation of a trigeneration plant and the usage of selected production scraps inside the products as well as the reduction of emissions into the environment, are one of the main efforts of the company to reduce impact during final product build-up. Moreover, the benefit given by installing Polystrada products brings a significant improvement in road lifetime. This has an impact not only on the number of maintenance or renewal that needs to be done (build less) but also on traffic density due to works and road deviation in case of operations. During the end of the life of a road, Polystrada products can be 100% recycled and milled with classical systems used without changing the normal maintenance procedures. In this work, all these contributions were quantified in terms of CO₂ emission thanks to an LCA analysis. The data obtained were compared with a classical system or a standard production of a membrane. What it is possible to see is that the usage of Polyglass products for street maintenance and building gives a significant reduction of emissions in case of membrane installation under the road wearing course.

Keywords: CO₂ emission, LCA, maintenance, sustainability

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Authors: Ilaria Coppola, Davide Lacqua, Nadia Ranìa

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Over the past two decades, migration has gained central importance in the global landscape. Europe hosts the largest number of migrants, totaling 92.9 million people, approximately 37.4 million of whom are regular residents within the European Union's borders. Reception services and different modes of management have received increasing attention precisely because of the complexity of the phenomenon, which necessarily impacts the wider community. Indeed, opening a reception center in an area entails major challenges for that context, for the community that inhabits it, and for the people who use that service. Questioning the strategies needed to offer a functional reception service means listening to the different actors involved who daily face the difficulties involved in working in the field. Recognizing the importance of the professional figures who work closely with migrant people, each with their own specific experiences has led researchers to study and analyze the different types of reception centers and their management. This has led to the development of intervention models and best practices in various countries. However, research from this perspective is still limited, especially in Italy. From this theoretical framework, this study aims to bring out an innovative qualitative tool, such as the world café, the work experiences of 29 social workers working in shelters in the Italian context. Most of the participants were female and lived in the Northwest regions of Italy. Through this tool, the aim was to bring out and share reflections on the critical issues encountered in working in reception centers, with a view to identifying possible solutions for better management of services. The World café represents a tool used in participatory action research that promotes dialogue among participants through the sharing of reflections and ideas. In fact, from critical reflections, participants are invited to identify and share possible solutions to provide a more functional service with benefits to the entire community. Therefore, this research, through the innovative technique of the World café, aims to promote critical thinking processes that can help participants find solutions that can be introduced into their work contexts or proposed to decision-makers. Specifically, the findings shed light on several issues, including complex bureaucratic procedures, insufficient project planning, and inefficiencies in the services provided to migrants. These concerns collectively contribute to what participants perceive as a disorganized and uncoordinated system. In addition, the study explores potential solutions that promote more efficient networking practices, coordinated project management, and a more positive approach to cultural diversity. The main results obtained will be discussed with a focus on critical reflections and possible solutions identified.

Keywords: participatory action research, world café method, reception services, migration contexts, social workers, Italy

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: Ramin Tafazzoli, Rahime Zamanfashami, Amir Mohagheghzadeh

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Entrepreneurship is the driving engine of countries’ economic development and has a determinant role in the economic, social and cultural improvement of the societies. Entrepreneurship and its impact on countries’ destiny, result in the planner and policy makers’ attempts to explore and extend it in various aspects. These days, all countries follow their social capital development and human resource quality improvement to achieve the strategic national objectives, economic growth, value creation, cultural dynamism, civil excellence and social solidarity, pursuing the sustainable development based on innovation, entrepreneurial technology , knowledge management and knowledge-focused in various levels and areas. Because of the rapid economic and cultural changes in recent decades and also the emerged need for reinforcing the knowledge-based structures and wealth generation via knowledge, a convenient infrastructure is strongly required for generating science and technology. Devoting attention to entrepreneurship and training and fostering the students who have the essential abilities and skills for creating a suitable business unit, is one of the duties of each university. New expectations necessitate that universities in the development trend by way of entrepreneurship, play a prominent role. Since, higher education has an important role in training and fostering the specialist human resource in the society, attention to the academic entrepreneurship help to develop this issue better. The higher education, relying on its core mission (training and researching) be expected to help the path where exploit and apply the created capabilities and also to cause the development in the society. In this term, the higher education play an essential role to expanse and extent the entrepreneurial concepts by establishing the entrepreneurship universities. Therefore, it is necessary to constitute and establish the entrepreneurship university to solve the problems and improve the development trend. The entrepreneurial courses follow the objectives such as: informing, creating culture, entrepreneurial morality, technical knowledge, entrepreneurial skills transferring, preparing the audiences or researching, job creation, business establishing and its preservation. According to the vision 1404 of Islamic republic of Iran in which the society has to include the advanced knowledge in the field of technology and science generation and also economic growth. In this essay, we investigate the entrepreneurship concepts, entrepreneurship university characteristics, entrepreneurship organizations values, entrepreneurship education process, meanwhile paying attention to that fact which the university can play an essential role in entrepreneurs training by education, culture and science. At the end, we present some suggestion and some solution for obstacles, emphasizing on the vision.

Keywords: entrepreneurship, entrepreneur university, higher education, university

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Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

Abstract:

Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

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Authors: Mursleen Yasin, Sunil Panchal, Michelle Mak, Zhonghua Chen

Abstract:

“The use of agricultural and horticultural waste to obtain beneficial products. Thus reduce its environmental impact and help the general population.” Every year 20 billion dollars of food is wasted in the world. All the energy, resources, nutrients and metabolites are lost to the landfills as well. On farm production losses are a main issue in agriculture. Almost 25% vegetables never leave the farm because they are not considered perfect for supermarkets and treated as waste material along with the rest of the plant parts. For capsicums, this waste is 56% of the total crop. Capsicum genus is enriched with a group of compounds called capsaicinoids which are a source of spiciness of these fruits. Capsaicin and dihydrocapsaicin are the major members comprising almost 90% of this group. The major production and accumulation site is the non-edible part of fruit i.e., placenta. Other parts of the plant, like stem, leaves, pericarp and seeds, also contain these pungent compounds. Capsaicinoids are enriched with properties like analgesic, antioxidants, anti-inflammatory, antibacterial, anti-virulence anti-carcinogenic, chemo preventive, chemotherapeutic, antidiabetic etc. They are also effective in treating problems related to gastrointestinal tract, lowering cholesterol and triglycerides in obesity. The aim of the study is to develop a standardised technique for capsaicinoids extraction and to identify better nutrient treatment for fruit and capsaicinoids yield. For research 3 capsicum and 2 chilli varieties were grown in a high-tech glass house facility in Sydney, Australia. Plants were treated with three levels of nutrient treatments i.e., EC 1.8, EC 2.8 and EC 3.8 in order to check its effect on fruit yield and capsaicinoids concentration. Solvent extraction procedure is used with 75% ethanol to extract these secondary metabolites. Physiological, post-harvest and waste biomass measurement and metabolomic analysis are also performed. The results showed that EC 2.8 gave the better fruit yield of capsicums, and those fruits have the higher capsaicinoids concentration. For chillies, higher EC levels had better results than lower treatment. The UHPLC analysis is done to quantify the compounds, and a decrease in capsaicin concentration is observed with the crop maturation. The outcome of this project is a sustainable technique for extraction of capsaicinoids which can easily be adopted by farmers. In this way, farmers can help in value adding of waste by extracting and selling capsaicinoids to nutraceutical and pharmaceutical industries and also earn some secondary income from the 56% waste of capsicum crop.

Keywords: capsaicinoids, plant waste, capsicum, solvent extraction, waste biomass

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