Search results for: integrative design process

Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Mir Afzal

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Introduction: Pakistan is a country with an ever-increasing population of largely diverse ethnic, cultural, religious and sectarian divisions. Whereas diversity is seen as a strength in many societies, in Pakistan, it has become a source of conflict and more a weakness than a strength due to lack of understanding and divisions based on ethnic, cultural, political, religious, and sectarian branding. However, amid conflicts and militancy across the country, the rural, mountainous communities in the Northern Areas of Pakistan enjoy not only peace and harmony but also a continuous process of social and economic transformation supported by strong civil society institutions. These community-based institutions have organized the rural, mountainous people of diverse ethnic and religious backgrounds into village organizations, women organizations, and Local Support Organizations engaged in self-help development and peace building in the region. The Study and its Methodology: A qualitative study was conducted in one district of the Northern Pakistan to explore the contributions of the civil society institutions (CSIs) and community-based organizations to uplifting the educational and socio-economic conditions of the people with an ultimate aim of developing a thriving, peaceful and pluralistic society in this mountainous region. The study employed an eclectic set of tools, including interviews, focused group discussions, observations of CSIs’ interventions, and analysis of documents, to generate rich data on the overall role and contributions of CSIs in promoting peace and pluralism in the region. Significance of the Study: Common experiences and empirical studies reveal that such interventions by CSIs have not only contributed to the socio-economic, educational, health and cultural development of these regions but these interventions have really transformed the rural, mountainous people into organized and forward looking communities. However, how such interventions have contributed to promoting pluralism and appreciation for diversity in these regions had been an unexplored but significant area. Therefore this qualitative research study funded by the Higher Education Commission of Pakistan was carried out by the Aga Khan University Institute for Educational Development to explore the role and contributions of CSIs in promoting peace and pluralism and appreciations for diversity in one district of Northern Pakistan which is home to people of different ethnic, religious, cultural and social backgrounds. Findings and Conclusions: The study has a comprehensive list of findings and conclusions covering various aspects of CSIs and their contributions to the transformation and peaceful co-existence of rural communities in the regions. However, this paper discusses only four major contributions of CSIs, namely enhancing economic capacity, community mobilization and organization, increasing access and quality of education, and building partnerships. It also discusses the factors influencing the role of CSIs, the issues, implications, and recommendations for CSIs, policy makers, donors and development agencies, and researchers. The paper concludes that by strengthening strong networks of CSIs and community based organizations, Pakistan will not only uplift its socio-economic attainments but it will also be able to address the critical challenges of terrorism, sectarianism, and other divisions and conflicts in its various regions.

Keywords: civil society, Pakistan, peace, rural

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Authors: Rana Mohamed, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Bio-fabrication is a multidisciplinary research field that combines several principles, fabrication techniques, and protocols from different fields. The open-source-software movement is a movement that supports the use of open-source licenses for some or all software as part of the broader notion of open collaboration. Additive manufacturing is the concept of 3D printing, where it is a manufacturing method through adding layer-by-layer using computer-aided designs (CAD). There are several types of AM system used, and they can be categorized by the type of process used. One of these AM technologies is Digital light processing (DLP) which is a 3D printing technology used to rapidly cure a photopolymer resin to create hard scaffolds. DLP uses a projected light source to cure (Harden or crosslinking) the entire layer at once. Current applications of DLP are focused on dental and medical applications. Other developments have been made in this field, leading to the revolutionary field 3D bioprinting. The open-source movement was started to spread the concept of open-source software to provide software or hardware that is cheaper, reliable, and has better quality. Objective: Modification of desktop 3D printer into 3D bio-printer and the integration of DLP technology and bio-fabrication to produce an antibacterial dental model. Method: Modification of a desktop 3D printer into a 3D bioprinter. Gelatin hydrogel and sodium alginate hydrogel were prepared with different concentrations. Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum were extracted, and extractions were selected on different levels (Powder, aqueous extracts, total oils, and Essential oils) prepared for antibacterial bioactivity. Agar well diffusion method along with the E. coli have been used to perform the sensitivity test for the antibacterial activity of the extracts acquired by Zingiber officinale, Syzygium aromaticum, and Allium sativum. Lastly, DLP printing was performed to produce several dental models with the natural extracted combined with hydrogel to represent and simulate the Hard and Soft tissues. Result: The desktop 3D printer was modified into 3D bioprinter using open-source software Marline and modified custom-made 3D printed parts. Sodium alginate hydrogel and gelatin hydrogel were prepared at 5% (w/v), 10% (w/v), and 15%(w/v). Resin integration with the natural extracts of Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum was done following the percentage 1- 3% for each extract. Finally, the Antimicrobial dental model was printed; exhibits the antimicrobial activity, followed by merging with sodium alginate hydrogel. Conclusion: The open-source movement was successful in modifying and producing a low-cost Desktop 3D Bioprinter showing the potential of further enhancement in such scope. Additionally, the potential of integrating the DLP technology with bioprinting is a promising step toward the usage of the antimicrobial activity using natural products.

Keywords: 3D printing, 3D bio-printing, DLP, hydrogel, antibacterial activity, zingiber officinale, syzygium aromaticum, allium sativum, panax ginseng, dental applications

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Simon J. Wilde, David M. Herold, Michael J. Bryant

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Social media networks have become the hotbed for advertising activities due mainly to their increasing consumer/user base and, secondly, owing to the ability of marketers to accurately measure ad exposure and consumer-based insights on such networks. More than half of the world’s population (4.8 billion) now uses social media (60%), with 150 million new users having come online within the last 12 months (to June 2022). As the use of social media networks by users grows, key business strategies used for interacting with these potential customers have matured, especially social media advertising. Unlike other traditional media outlets, social media advertising is highly interactive and digital channel specific. Social media advertisements are clearly targetable, providing marketers with an extremely powerful marketing tool. Yet despite the measurable benefits afforded to businesses engaged in social media advertising, recent controversies (such as the relationship between Facebook and Cambridge Analytica in 2018) have only heightened the role trust and privacy play within these social media networks. Using a web-based quantitative survey instrument, survey participants were recruited via a reputable online panel survey site. Respondents to the survey represented social media users from all states and territories within Australia. Completed responses were received from a total of 258 social media users. Survey respondents represented all core age demographic groupings, including Gen Z/Millennials (18-45 years = 60.5% of respondents) and Gen X/Boomers (46-66+ years = 39.5% of respondents). An adapted ADTRUST scale, using a 20 item 7-point Likert scale, measured trust in social media advertising. The ADTRUST scale has been shown to be a valid measure of trust in advertising within traditional media, such as broadcast media and print media, and, more recently, the Internet (as a broader platform). The adapted scale was validated through exploratory factor analysis (EFA), resulting in a three-factor solution. These three factors were named reliability, usefulness and affect, and the willingness to rely on. Factor scores (weighted measures) were then calculated for these factors. Factor scores are estimates of the scores survey participants would have received on each of the factors had they been measured directly, with the following results recorded (Reliability = 4.68/7; Usefulness and Affect = 4.53/7; and Willingness to Rely On = 3.94/7). Further statistical analysis (independent samples t-test) determined the difference in factor scores between the factors when age (Gen Z/Millennials vs. Gen X/Boomers) was utilized as the independent, categorical variable. The results showed the difference in mean scores across all three factors to be statistically significant (p<0.05) for these two core age groupings: (1) Gen Z/Millennials Reliability = 4.90/7 vs. Gen X/Boomers Reliability = 4.34/7; (2) Gen Z/Millennials Usefulness and Affect = 4.85/7 vs Gen X/Boomers Usefulness and Affect = 4.05/7; and (3) Gen Z/Millennials Willingness to Rely On = 4.53/7 vs Gen X/Boomers Willingness to Rely On = 3.03/7. The results clearly indicate that older social media users lack trust in the quality of information conveyed in social media ads when compared to younger, more social media-savvy consumers. This is especially evident with respect to Factor 3 (Willingness to Rely On), whose underlying variables reflect one’s behavioral intent to act based on the information conveyed in advertising. These findings can be useful to marketers, advertisers, and brand managers in that the results highlight a critical need to design ‘authentic’ advertisements on social media sites to better connect with these older users in an attempt to foster positive behavioral responses from within this large demographic group – whose engagement with social media sites continues to increase year on year.

Keywords: social media advertising, trust, older consumers, internet studies

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Authors: Sricheta Chowdhury

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To require a woman to choose between her work and her personal life is the most acute form of discrimination that can be meted out against her. No woman should be given a choice to choose between her motherhood and her career at Bar, yet that is the most detrimental discrimination that has been happening in Indian Bar, which no one has questioned so far. The falling number of women in practice is a reality that isn’t garnering much attention given the sharp rise in women studying law but is not being able to continue in the profession. Moving from a colonial misogynist whim to a post-colonial “new-age construct of Indian woman” façade, the policymakers of the Indian Judiciary have done nothing so far to decolonize itself from its rudimentary understanding of ‘equality of gender’ when it comes to the legal profession. Therefore, when Indian jurisprudence was (and is) swooning to the sweeping effect of transformative constitutionalism in the understanding of equality as enshrined under the Indian Constitution, one cannot help but question why the legal profession remained out of brushing effect of achieving substantive equality. The Airline industry’s discriminatory policies were not spared from criticism, nor were the policies where women’s involvement in any establishment serving liquor (Anuj Garg case), but the judicial practice did not question the stereotypical bias of gender and unequal structural practices until recently. That necessitates the need to examine the existing Bar policies and the steps taken by the regulatory bodies in assessing the situations that are in favor or against the purpose of furthering women’s issues in present-day India. From a comparative feminist point of concern, South Africa’s pro-women Bar policies are attractive to assess their applicability and extent in terms of promoting inclusivity at the Bar. This article intends to tap on these two countries’ potential in carving a niche in giving women an equal platform to play a substantive role in designing governance policies through the Judiciary. The article analyses the current gender composition of the legal profession while endorsing the concept of substantive equality as a requisite in designing an appropriate appointment process of the judges. It studies the theoretical framework on gender equality, examines the international and regional instruments and analyses the scope of welfare policies that Indian legal and regulatory bodies can undertake towards a transformative initiative in re-modeling the Judiciary to a more diverse and inclusive institution. The methodology employs a comparative and analytical understanding of doctrinal resources. It makes quantitative use of secondary data and qualitative use of primary data collected for determining the present status of Indian women legal practitioners and judges. With respect to quantitative data, statistics on the representation of women as judges and chief justices and senior advocates from their official websites from 2018 till present have been utilized. In respect of qualitative data, results of the structured interviews conducted through open and close-ended questions with retired lady judges of the higher judiciary and senior advocates of the Supreme Court of India, contacted through snowball sampling, are utilized.

Keywords: gender, higher judiciary, legal profession, representation, substantive equality

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Authors: Naresh Kumar, Savita Kumari, Naresh Kochhar

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The objective of the study was to assess the role of mineralogy and subsurface structure on water quality of Tosham, Malani Igneous Suite (MIS), Western Rajasthan, India. MIS is the largest (55,000 km2) A-type, anorogenic and high heat producing acid magmatism in the peninsular India and owes its origin to hot spot tectonics. Apart from agricultural and industrial wastes, geogenic activities cause fluctuations in quality parameters of water resources. Twenty water samples (20) selected from Tosham and surrounding areas were analyzed for As, Pb, B, Al, Zn, Fe, Ni using Inductive coupled plasma emission and F by Ion Chromatography. The concentration of As, Pb, B, Ni and F was above the stipulated level specified by BIS (Bureau of Indian Standards IS-10500, 2012). The concentration of As and Pb in surrounding areas of Tosham ranged from 1.2 to 4.1 mg/l and from 0.59 to 0.9 mg/l respectively which is higher than limits of 0.05mg/l (As) and 0.01 mg/l (Pb). Excess trace metal accumulation in water is toxic to humans and adversely affects the central nervous system, kidneys, gastrointestinal tract, skin and cause mental confusion. Groundwater quality is defined by nature of rock formation, mineral water reaction, physiography, soils, environment, recharge and discharge conditions of the area. Fluoride content in groundwater is due to the solubility of fluoride-bearing minerals like fluorite, cryolite, topaz, and mica, etc. Tosham is comprised of quartz mica schist, quartzite, schorl, tuff, quartz porphyry and associated granites, thus, fluoride is leached out and dissolved in groundwater. In the study area, Ni concentration ranged from 0.07 to 0.5 mg/l (permissible limit 0.02 mg/l). The primary source of nickel in drinking water is leached out nickel from ore-bearing rocks. Higher concentration of As is found in some igneous rocks specifically containing minerals as arsenopyrite (AsFeS), realgar (AsS) and orpiment (As2S3). MIS consists of granite (hypersolvus and subsolvus), rhyolite, dacite, trachyte, andesite, pyroclasts, basalt, gabbro and dolerite which increased the trace elements concentration in groundwater. Nakora, a part of MIS rocks has high concentration of trace and rare earth elements (Ni, Rb, Pb, Sr, Y, Zr, Th, U, La, Ce, Nd, Eu and Yb) which percolates the Ni and Pb to groundwater by weathering, contacts and joints/fractures in rocks. Additionally, geological setting of MIS also causes dissolution of trace elements in water resources beneath the surface. NE–SW tectonic lineament, radial pattern of dykes and volcanic vent at Nakora created a way for leaching of these elements to groundwater. Rain water quality might be altered by major minerals constituents of host Tosham rocks during its percolation through the rock fracture, joints before becoming the integral part of groundwater aquifer. The weathering process like hydration, hydrolysis and solution might be the cause of change in water chemistry of particular area. These studies suggest that geological relation of soil-water horizon with MIS rocks via mineralogical variations, structures and tectonic setting affects the water quality of the studied area.

Keywords: geochemistry, groundwater, malani igneous suite, tosham

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Authors: Grâce Chidikofan, François Pinta, A. Benoist, G. Volle, J. Valette

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Statement of the Problem: biomass gasification systems may be relevant for decentralized power generation from recoverable agricultural and wood residues available in rural areas. In recent years, many systems have been implemented in all over the world as especially in Cambodgia, India. Although they have many positive effects, these systems can also affect the environment and human health. Indeed, during the process of biomass gasification, black wastewater containing tars are produced and generally discharged in the local environment either into the rivers or on soil. However, in most environmental assessment studies of biomass gasification systems, the impact of these releases are underestimated, due to the difficulty of identification of their chemical substances. This work deal with the analysis of the environmental impacts of tars from wood gasification in terms of human toxicity cancer effect, human toxicity non-cancer effect, and freshwater ecotoxicity. Methodology: A Life Cycle Assessment (LCA) approach was adopted. The inventory of tars chemicals substances was based on experimental data from a downdraft gasification system. The composition of six samples from two batches of raw materials: one batch made of tree wood species (oak+ plane tree +pine) at 25 % moisture content and the second batch made of oak at 11% moisture content. The tests were carried out for different gasifier load rates, respectively in the range 50-75% and 50-100%. To choose the environmental impacts assessment method, we compared the methods available in SIMAPRO tool (8.2.0) which are taking into account most of the chemical substances. The environmental impacts for 1kg of tars discharged were characterized by ILCD 2011+ method (V.1.08). Findings Experimental results revealed 38 important chemical substances in varying proportion from one test to another. Only 30 are characterized by ILCD 2011+ method, which is one of the best performing methods. The results show that wood species or moisture content have no significant impact on human toxicity noncancer effect (HTNCE) and freshwater ecotoxicity (FWE) for water release. For human toxicity cancer effect (HTCE), a small gap is observed between impact factors of the two batches, either 3.08E-7 CTUh/kg against 6.58E-7 CTUh/kg. On the other hand, it was found that the risk of negative effects is higher in case of tar release into water than on soil for all impact categories. Indeed, considering the set of samples, the average impact factor obtained for HTNCE varies respectively from 1.64 E-7 to 1.60E-8 CTUh/kg. For HTCE, the impact factor varies between 4.83E-07 CTUh/kg and 2.43E-08 CTUh/kg. The variability of those impact factors is relatively low for these two impact categories. Concerning FWE, the variability of impact factor is very high. It is 1.3E+03 CTUe/kg for tars release into water against 2.01E+01 CTUe/kg for tars release on soil. Statement concluding: The results of this study show that the environmental impacts of tars emission of biomass gasification systems can be consequent and it is important to investigate the ways to reduce them. For environmental research, these results represent an important step of a global environmental assessment of the studied systems. It could be used to better manage the wastewater containing tars to reduce as possible the impacts of numerous still running systems all over the world.

Keywords: biomass gasification, life cycle analysis, LCA, environmental impact, tars

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Authors: L. Kutateldze, T. Urushadze, R. Khvedelidze, N. Zakariashvili, I. Khokhashvili, T. Sadunishvili

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Microbial cellulase/xylanase have shown their potential application in various industries including pulp and paper, textile, laundry, biofuel production, food and feed industry, brewing, and agriculture. Extremophilic micromycetes and their enzymes that are resistant to critical values of temperature and pH, and retaining enzyme activity for a long time are of great industrial interest. Among strains of microscopic fungi from the collection of S. Durmishidze Institute of Biochemistry and Biotechnology, strains isolated from different ecological niches of Southern Caucasus-active producers of cellulase/xylanase have been selected by means of screening under deep cultivation conditions. Extremophilic micromycetes and their enzymes that are resistant to critical values of temperature and pH, and retaining enzyme activity for a long time are of great industrial interest. Among strains of microscopic fungi from the collection of S. Durmishidze Institute of Biochemistry and Biotechnology, strains isolated from different ecological niches of Southern Caucasus-active producers of cellulase/xylanase have been selected by means of screening under deep cultivation conditions. Representatives of the genera Aspergillus, Penicillium and Trichoderma are outstanding by relatively high activities of these enzymes. Among the producers were revealed thermophilic strains, representatives of the genus Aspergillus-Aspergillus terreus, Aspergillus versicolor, Aspergillus wentii, also strains of Sporotrichum pulverulentum and Chaetomium thermophile. As a result of optimization of cultivation media and conditions, activities of enzymes produced by the strains have been increased by 4 -189 %. Two strains, active producers of cellulase/xylanase – Penicillium canescence E2 (mesophile) and Aspergillus versicolor Z17 (thermophile) were chosen for further studies. Cellulase/xylanase enzyme preparations from two different genera of microscopic fungi Penicillium canescence E2 and Aspergillus versicolor Z 17 were obtained with activities 220 U/g /1200 U/g and 125 U/g /940 U/g, correspondingly. Main technical characteristics were as follows: the highest enzyme activities were obtained for mesophilic strain Penicillium canescence E2 at 45-500C, while almost the same enzyme activities were fixed for the thermophilic strain Aspergillus versicolor Z 17 at temperature 60-65°C, exceeding the temperature optimum of the mesophile by 150C. Optimum pH of action of the studied cellulase/xylanases from mesophileic and thermophilic strains were similar and equaled to 4.5-5.0 It has been shown that cellulase/xylanase technical preparations from selected strains of Penicillium canescence E2 and Aspergillus versicolor Z17 hydrolyzed cellulose of untreated wheat straw to reducible sugars by 46-52%, and to glucose by 22-27%. However the thermophilic enzyme preparations from the thermophilic A.versicolor strains conducted the process at 600C higher by 100C as compared to mesophlic analogue. Rate of hydrolyses of the pretreated substrate by the same enzyme preparations to reducible sugars and glucose conducted at optimum for their action 60 and 500C was 52-61% and 29-33%, correspondingly. Thus, maximum yield of glucose and reducible sugars form untreated and pretreated wheat straw was achieved at higher temperature (600C) by enzyme preparations from thermophilic strain, which gives advantage for their industrial application.

Keywords: cellulase/xylanase, cellulose hydrolysis, microscopic fungi, thermophilic strain

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Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

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Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

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Authors: Yujie Yuan, Yiyang Fan, Hong Fan

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Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.

Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1

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Authors: Anna Bjällmark, Victoria Persson, Bodil Karlsson, May Bazzi

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Introduction: Interventional radiology (IR) is a continuously growing discipline that allows minimally invasive treatments of various medical conditions. The IR environment is, in several ways, comparable to the complex and accident-prone operation room (OR) environment. This implies that the IR environment may also be associated with various types of risks related to the work process and communication in the team. Patient safety is a central aspect of healthcare and involves the prevention and reduction of adverse events related to patient care. To maintain patient safety, it is crucial to build a safety culture where the staff are encouraged to report events and incidents that may have affected patient safety. It is also important to continuously evaluate the staff´s attitudes to patient safety. Despite the increasing number of IR procedures, research on the staff´s view regarding patients is lacking. Therefore, the main aim of the study was to describe and compare the IR team members' attitudes to patient safety. The secondary aim was to evaluate whether the WHO safety checklist was routinely used for IR procedures. Methods: An electronic survey was distributed to 25 interventional units in Sweden. The target population was the staff working in the IR team, i.e., physicians, radiographers, nurses, and assistant nurses. A modified version of the Safety Attitudes Questionnaire (SAQ) was used. Responses from 19 of 25 IR units (44 radiographers, 18 physicians, 5 assistant nurses, and 1 nurse) were received. The respondents rated their level of agreement for 27 items related to safety culture on a five-point Likert scale ranging from “Disagree strongly” to “Agree strongly.” Data were analyzed statistically using SPSS. The percentage of positive responses (PPR) was calculated by taking the percentage of respondents who got a scale score of 75 or higher. The respondents rated which corresponded to response options “Agree slightly” or “Agree strongly”. Thus, average scores ≥ 75% were classified as “positive” and average scores < 75% were classified as “non-positive”. Findings: The results indicated that the IR team had the highest factor scores and the highest percentages of positive responses in relation to job satisfaction (90/94%), followed by teamwork climate (85/92%). In contrast, stress recognition received the lowest ratings (54/25%). Attitudes related to these factors were relatively consistent between different professions, with only a few significant differences noted (Factor score: p=0.039 for job satisfaction, p=0.050 for working conditions. Percentage of positive responses: p=0.027 for perception of management). Radiographers tended to report slightly lower values compared to other professions for these factors (p<0.05). The respondents reported that the WHO safety checklist was not routinely used at their IR unit but acknowledged its importance for patient safety. Conclusion: This study reported high scores concerning job satisfaction and teamwork climate but lower scores concerning perception of management and stress recognition indicating that the latter are areas of improvement. Attitudes remained relatively consistent among the professions, but the radiographers reported slightly lower values in terms of job satisfaction and perception of the management. The WHO safety checklist was considered important for patient safety.

Keywords: interventional radiology, patient safety, safety attitudes questionnaire, WHO safety checklist

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Authors: Claude Nsobya, Alice Moncaster, Karen Potter, Jed Ramsay

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The shift in Flood Risk Governance (FRG) has moved away from traditional approaches that solely relied on centralized decision-making and structural flood defenses. Instead, there is now the adoption of integrated flood risk management measures that involve various actors and stakeholders. This new approach emphasizes people-centered approaches, including adaptation and learning. This shift to a diversity of FRG approaches has been identified as a significant factor in enhancing resilience. Resilience here refers to a community's ability to withstand, absorb, recover, adapt, and potentially transform in the face of flood events. It is argued that if the FRG merely focused on the conventional 'fighting the water' - flood defense - communities would not be resilient. The move to these people-centered approaches also implies that communities will be more involved in FRG. It is suggested that effective flood risk governance influences resilience through meaningful community involvement, and effective community engagement is vital in shaping community resilience to floods. Successful community participation not only uses context-specific indigenous knowledge but also develops a sense of ownership and responsibility. Through capacity development initiatives, it can also raise awareness and all these help in building resilience. Recent Flood Risk Management (FRM) projects have thus had increasing community involvement, with varied conceptualizations of such community engagement in the academic literature on FRM. In the context of overland floods, there has been a substantial body of literature on Flood Risk Governance and Management. Yet, groundwater flooding has gotten little attention despite its unique qualities, such as its persistence for weeks or months, slow onset, and near-invisibility. There has been a little study in this area on how successful community involvement in Flood Risk Governance may improve community resilience to groundwater flooding in particular. This paper focuses on a case study of a flood risk management project in the United Kingdom. Buckinghamshire Council is leading Project Groundwater, which is one of 25 significant initiatives sponsored by England's Department for Environment, Food and Rural Affairs (DEFRA) Flood and Coastal Resilience Innovation Programme. DEFRA awarded Buckinghamshire Council and other councils 150 million to collaborate with communities and implement innovative methods to increase resilience to groundwater flooding. Based on a literature review, this paper proposes a new paradigm for effective community engagement in Flood Risk Governance (FRG). This study contends that effective community participation can have an impact on various resilience capacities identified in the literature, including social capital, institutional capital, physical capital, natural capital, human capital, and economic capital. In the case of social capital, for example, successful community engagement can influence social capital through the process of social learning as well as through developing social networks and trust values, which are vital in influencing communities' capacity to resist, absorb, recover, and adapt. The study examines community engagement in Project Groundwater using surveys with local communities and documentary analysis to test this notion. The outcomes of the study will inform community involvement activities in Project Groundwater and may shape DEFRA policies and guidelines for community engagement in FRM.

Keywords: flood risk governance, community, resilience, groundwater flooding

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Authors: Michael Picard

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This proposal offers to shed light on the changing legal geography of the global waste economy. Global waste recycling has become a multi-billion-dollar industry. NASDAQ predicts the emergence of a worldwide 1,296G$ waste management market between 2017 and 2022. Underlining this evolution, a new generation of preferential waste-trade agreements has emerged in the Pacific. In the last decade, Japan has concluded a series of bilateral treaties with Asian countries, and most recently with China. An agreement between Tokyo and Beijing was formalized on 7 May 2008, which forged an economic partnership on waste transfer and mining. The agreement set up International Recycling Zones, where certified recycling plants in China process industrial waste imported from Japan. Under the joint venture, Chinese companies salvage the embedded value from Japanese industrial discards, reprocess them and send them back to Japanese manufacturers, such as Mitsubishi and Panasonic. This circular economy is designed to convert surplus garbage into surplus value. Ever since the opening of Sino-Japanese eco-parks, millions of tons of plastic and e-waste have been exported from Japan to China every year. Yet, quite unexpectedly, China has recently closed its waste market to imports, jeopardizing Japan’s billion-dollar exports to China. China notified the WTO that, by the end of 2017, it would no longer accept imports of plastics and certain metals. Given China’s share of Japanese waste exports, a complete closure of China’s market would require Japan to find new uses for its recyclable industrial trash generated domestically every year. It remains to be seen how China will effectively implement its ban on waste imports, considering the economic interests at stake. At this stage, what remains to be clarified is whether China's ban on waste imports will negatively affect the recycling trade between Japan and China. What is clear, though, is the rapid transformation in the legal geography of waste mining in East-Asia. For decades, East-Asian waste trade had been tied up in an ‘ecologically unequal exchange’ between the Japanese core and the Chinese periphery. This global unequal waste distribution could be measured by the Environmental Stringency Index, which revealed that waste regulation was 39% weaker in the Global South than in Japan. This explains why Japan could legally export its hazardous plastic and electronic discards to China. The asymmetric flow of hazardous waste between Japan and China carried the colonial heritage of international law. The legal geography of waste distribution was closely associated to the imperial construction of an ecological trade imbalance between the Japanese source and the Chinese sink. Thus, China’s recent decision to ban hazardous waste imports is a sign of a broader ecological shift. As a global economic superpower, China announced to the world it would no longer be the planet’s junkyard. The policy change will have profound consequences on the global circulation of waste, re-routing global waste towards countries south of China, such as Vietnam and Malaysia. By the time the Berlin Conference takes place in May 2018, the presentation will be able to assess more accurately the effect of the Chinese ban on the transboundary movement of waste in Asia.

Keywords: Asia, ecological unequal exchange, global waste trade, legal geography

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Authors: Irakli Gamkrelidze, David Shengelia, Giorgi Chichinadze, Tamara Tsutsunava, Giorgi Beridze, Tamara Tsamalashvili, Ketevan Tedliashvili, Irakli Javakhishvili

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The Caucasus is situated between the Eurasian and Africa-Arabian plates and represents a component of the Mediterranean (Alpine-Himalayan) collision belt. The Loki crystalline massif crops out within one of the terranes of the Caucasus – Baiburt-Sevanian terrane. By the end of 2018, a digital geological map (1:50 000) of the Loki massif was compiled. The presented map is of great importance for the region since there is no large-scale geological map which reflects the present standards of the geological study of the massif up to the last time. The existing State Geological Map of the Loki massif is very outdated. A new map drown by using GIS (Geographic Information System) technology is loaded with multi-informative details that include: specified contours of geological units and separate tectonic scales, key mineral assemblages and facies of metamorphism, temperature conditions of metamorphism, ages of metamorphism events and the massif rocks, genetic-geodynamic types of magmatic rocks. Explanatory note, attached to the map includes the large specter of scientific information. It contains characterization of the geological setting, composition and petrogenetic and geodynamic models of the massif formation. To create a geological map of the Loki crystalline massif, appropriate methodologies were applied: a sampling of rocks, GIS technology-based mapping of geological units, microscopic description of the material, composition analysis of rocks, microprobe analysis of minerals and a new interpretation of obtained data. To prepare a digital version of the map the appropriated activities were held including the creation of a common database. Finally, the design was created that includes the elaboration of legend and the final visualization of the map. The results of the study presented in the explanatory note are given below. The autochthonous gneissose quartz diorites of normal alkalinity and sub-alkaline gabbro-diorites included in them belong to different phases of magmatism. They represent “igneous” granites corresponding to mixed mantle-crustal type granites. Four tectonic plates of the allochthonous metamorphic complex–Lower Gorastskali, Sapharlo–Lok-Jandari, Moshevani, and Lower Gorastskali differ from each other by structure and degree of metamorphism. The initial rocks of these plates are formed in different geodynamic conditions and during the Early Bretonian orogeny while overthrusting due to tectonic compression they form a thick tectonic sheet. The Lower Gorastskali overthrust sheet is a fragment of ophiolitic association corresponding to the Paleotethys oceanic crust. The protolith of the ophiolitic complex basites corresponds to the tholeiitic series of basalts. The Sapharlo–Lok-Jandari overthrust sheet is metapelites, metamorphosed in conditions of greenschist facies of regional metamorphism. The regional metamorphism of Moshevani overthrust sheet crystalline schists quartzites corresponds to a range from greenschist to hornfels facies. The “mélange” is built of rock fragments and blocks of above-mentioned overthrust sheets. Sub-alkaline and normal alkaline post-metamorphic granites of the Loki crystalline massif belong to “igneous” and rarely to “sialic” and “anorogenic” types of granites.

Keywords: digital geological map, 1:50 000 scale, crystalline massif, the caucasus

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Authors: Daniela Velichová

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Plenty of ideas on how to adopt active learning methods in education are available nowadays. Mathematics is a subject where the active involvement of students is required in particular in order to achieve desirable results regarding sustainable knowledge and deep understanding. The present article is based on the outcomes of an Erasmus+ project DrIVE-MATH, that was aimed at developing a novel and integrated framework to teach maths classes in engineering courses at the university level. It is fundamental for students from the early years of their academic life to have agile minds. They must be prepared to adapt to their future working environments, where enterprises’ views are always evolving, where all collaborate in teams, and relations between peers are thought for the well-being of the whole - workers and company profit. This reality imposes new requirements on higher education in terms of adaptation of different pedagogical methods, such as project-based and active-learning methods used within the course curricula. Active learning methodologies are regarded as an effective way to prepare students to meet the challenges posed by enterprises and to help them in building critical thinking, analytic reasoning, and insight to the solved complex problems from different perspectives. Fostering learning-by-doing activities in the pedagogical process can help students to achieve learning independence, as they could acquire deeper conceptual understanding by experimenting with the abstract concept in a more interesting, useful, and meaningful way. Clear information about learning outcomes and goals might help students to take more responsibility for their learning results. Active learning methods implemented by the project team members in their teaching practice, eduScrum and Jigsaw in particular, proved to provide better scientific and soft skills support to students than classical teaching methods. EduScrum method enables teachers to generate a working environment that stimulates students' working habits and self-initiative as they become aware of their responsibilities within the team, their own acquired knowledge, and their abilities to solve problems independently, though in collaboration with other team members. This method enhances collaborative learning, as students are working in teams towards a common goal - knowledge acquisition, while they are interacting with each other and evaluated individually. Teams consisting of 4-5 students work together on a list of problems - sprint; each member is responsible for solving one of them, while the group leader – a master, is responsible for the whole team. A similar principle is behind the Jigsaw technique, where the classroom activity makes students dependent on each other to succeed. Students are divided into groups, and assignments are split into pieces, which need to be assembled by the whole group to complete the (Jigsaw) puzzle. In this paper, analysis of students’ perceptions concerning the achievement of deeper conceptual understanding in mathematics and the development of soft skills, such as self-motivation, critical thinking, flexibility, leadership, responsibility, teamwork, negotiation, and conflict management, is presented. Some new challenges are discussed as brought by introducing active learning methods in the basic mathematics courses. A few examples of sprints developed and used in teaching basic maths courses at technical universities are presented in addition.

Keywords: active learning methods, collaborative learning, conceptual understanding, eduScrum, Jigsaw, soft skills

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Authors: Heejin Song

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Employing a critical action research approach that rejects essentialist onto-epistemological orientations to research in English language teaching (ELT) and interrogates the hegemonic relations in the knowledge construction and reconstruction processes, this study illuminates how an action research-informed pedagogical practice can transform the English for academic purposes (EAP) teaching to be more culturally and linguistically inclusive and critically oriented for English language learners’ advancement in academic literacies skills. More specifically, this paper aims to showcase the action research-informed pedagogical innovations that emphasize multilingual learners’ multiliteracies engagement and experiential education-oriented learning to facilitate the development of learners’ academic literacies, intercultural communicative competence, and inclusive global citizenship in the context of Canadian university EAP classrooms. The pedagogical innovations through action research embarked in response to growing discussions surrounding pedagogical possibilities of plurilingualism in ELT and synchronous online teaching. The paper is based on two iterations of action research over the pandemic years between 2020 and 2022. The data includes student work samples, focus group interviews, anonymous surveys, teacher feedback and comments on student work and teaching reflections. The first iteration of the action research focused on the affordances of multimodal expressions in individual learners’ academic endeavors for their literacy skills development through individual online activities such as ‘my language autobiography,’ ‘multimodal expression corner’ and public speeches. While these activities help English language learners enhance their knowledge and skills of English-spoken discourses, these tasks did not necessarily require learners’ team-based collaborative endeavors to complete the assigned tasks. Identifying this area for improvement in the instructional design, the second action research cycle/iteration emphasized collaborative performativity through newly added performance/action-based innovative learning tasks, including ‘situational role-playing’, ‘my cooking show & interview’, and group debates in order to provide learners increased opportunities to communicate with peers who joined the class virtually from different parts of the world and enhance learners’ intercultural competence through various strategic and pragmatic communicative skills to collaboratively achieve their shared goals (i.e., successful completion of the given group tasks). The paper exemplifies instances wherein learners’ unique and diverse linguistic and cultural strengths were amplified, and critical literacies were further developed through learners’ performance-oriented multiliteracies engagement. The study suggests that the action research-informed teaching practice that advocates for collaborative multiliteracies engagement serves to facilitate learners’ activation of their existing linguistic and cultural knowledge and contributes to the development of learners’ academic literacy skills. Importantly, the study illuminates that such action research-informed pedagogical initiatives create an inclusive space for learners to build a strong sense of connectedness as global citizens with increased intercultural awareness in their community of language and cultural practices, and further allow learners to actively participate in the construction of ‘collaborative relations of power’ with their peers.

Keywords: action research, EAP, higher education, multiliteracies

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Ram Sharma, Esha Chatterjee, Santosh Kumar Guru, Kunal Nepali

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A tractable anti-lung cancer agent was identified via the installation of a Ring C expanded synthetic analogue of the alkaloid vasicinone [7,8,9,10-tetrahydroazepino[2,1-b] quinazolin-12(6H)-one (TAZQ)] as a surface recognition part in the HDAC inhibitory three-component model. Noteworthy to mention that the candidature of TAZQ was deemed suitable for accommodation in HDAC inhibitory pharmacophore as per the results of the fragment recruitment process conducted by our laboratory. TAZQ was pinpointed through the fragment screening program as a synthetically flexible fragment endowed with some moderate cell growth inhibitory activity against the lung cancer cell lines, and it was anticipated that the use of the aforementioned fragment to generate hydroxamic acid functionality (zinc-binding motif) bearing HDAC inhibitors would boost the antitumor efficacy of TAZQ. Consistent with our aim of applying epigenetic targets to the treatment of lung cancer, a strikingly potent anti-lung cancer scaffold (compound 6) was pinpointed through a series of in-vitro experiments. Notably, the compounds manifested a magnificent activity profile against KRAS and EGFR mutant lung cancer cell lines (IC50 = 0.80 - 0.96 µM), and the effects were found to be mediated through preferential HDAC6 inhibition (IC50 = 12.9 nM). In addition to HDAC6 inhibition, the compounds also elicited HDAC1 and HDAC3 inhibitory activity with an IC50 value of 49.9 nM and 68.5 nM, respectively. The HDAC inhibitory ability of compound 6 was also confirmed from the results of the western blot experiment that revealed its potential to decrease the expression levels of HDAC isoforms (HDAC1, HDAC3, and HDAC6). Noteworthy to mention that complete downregulation of the HDAC6 isoform was exerted by compound 6 at 0.5 and 1 µM. Moreover, in another western blot experiment, treatment with hydroxamic acid 6 led to upregulation of H3 acK9 and α-Tubulin acK40 levels, ascertaining its inhibitory activity toward both the class I HDACs and Class II B HDACs. The results of other assays were also encouraging as treatment with compound 6 led to the suppression of the colony formation ability of A549 cells, induction of apoptosis, and increase in autophagic flux. In silico studies led us to rationalize the results of the experimental assay, and some key interactions of compound 6 with the amino acid residues of HDAC isoforms were identified. In light of the impressive activity spectrum of compound 6, a pH-responsive nanocarrier (hyaluronic acid-compound 6 nanoparticles) was prepared. The dialysis bag approach was used for the assessment of the nanoparticles under both normal and acidic circumstances, and the pH-sensitive nature of hyaluronic acid-compound 6 nanoparticles was confirmed. Delightfully, the nanoformulation was devoid of cytotoxicity against the L929 mouse fibroblast cells (normal settings) and exhibited selective cytotoxicity towards the A549 lung cancer cell lines. In a nutshell, compound 6 appears to be a promising adduct, and a detailed investigation of this compound might yield a therapeutic for the treatment of lung cancer.

Keywords: HDAC inhibitors, lung cancer, scaffold, hyaluronic acid, nanoparticles

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Authors: Amandeep Kaur

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Farming is one of the most influential traditions which started around 10000 BC and has revolutionized human civilization. It is believed that farming originated at a separate location. Thus it has a great impact on local culture, which in turn gave rise to diversified farming practices. Farming activities are influenced by the culture of a particular region or community as local people have their own knowledge and belief system about soil and crops. With the inception of the Green Revolution, 'a high tech machinery model' in Punjab, various traditional farming methods and techniques changed. The present research concentrates on the local knowledge of farmers and local farming systems from an anthropological perspective. In view of the prevailing agrarian crisis in Punjab, this research is focused on farmer’s experiences and their perception regarding farming practices. Thus an attempt has to be made to focus on the local knowledge, perception, and experience of farmers for eco-friendly and sustainable agricultural development. Farmers voices are used to understand the relationship between farming practices and socio-cultural life of farmers in Faridkot district, Punjab. The research aims to comprehend the nature of changes taking place in the socio-cultural life of people with the development of capitalism and agricultural modernization. The study is based on qualitative methods of ethnography in Sarawan village of Faridkot District. Inferences drawn from in-depth case studies collected from 60 agricultural households lead to the concept of the process of diffusion, innovation, and adoption of farming technology, a variety of crops and the dissemination of agricultural skills regarding various cultural farming practices. The data is based on random sampling; the respondents were both males and females above the age of 18 years to attain a holistic understanding across the generations. A Quasi-participant observation related to lifestyle, the standard of living, and various farming practices performed by them were done. Narratives derived from the fieldwork depicts that farmers usually oppose the restrictions imposed by the government on certain farming practices, especially ban on stubble burning. This paper presents the narratives of farmers regarding the dissemination of awareness about the use of new varieties of seeds, technology, fertilizers, pesticides, etc. The study reveals that farming systems have developed in ways reflecting the activities and choices of farmers influenced by environmental, socio-cultural, economic, and political situations. Modern farming practices have forced small farmers into debt as farmers feel pride in buying new machinery. It has also led to the loss of work culture and excessive use of drugs among youngsters. Even laborers did not want to work on the land with cultivating farmers primarily for social and political reasons. Due to lack of proper marketing of crops, there is a continuum of the wheat-rice cycle instead of crop diversification in Punjab. Change in the farming system also affects the social structure of society. Agricultural modernization has commercialized the socio-cultural relations in Punjab and is slowly urbanizing the rural landscape revolutionizing the traditional social relations to capitalistic relations.

Keywords: agricultural modernization, capitalism, farming practices, narratives

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Seema Kothari, Dinesh Panday

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An observed correlation of the reaction rates with the changes in the nature of substituent present on one of the reactants often reveals the nature of transition state. Selective oxidation of organic compounds under non-aqueous media is an important transformation in synthetic organic chemistry. Inorganic chromates and dichromates being drastic oxidant and are generally insoluble in most organic solvents, a number of different chromium (VI) derivatives have been synthesized. Benzimidazolium dichromate (BIDC) is one of the recently reported Cr(VI) reagents which is neither hygroscopic nor light sensitive being, therefore, much stable. Not many reports on the kinetics of the oxidations by BIDC are seemed to be available in the literature. In the present investigation, the kinetics and mechanism of benzyl alcohol (BA) and a number of para- and meta-substituted benzyl alcohols by benzimidazolium dichromate (BIDC), in dimethyl sulphoxide, is reported. The reactions were followed spectrophotometrically at 364 nm by monitoring the decrease in [BIDC] for up to 85-90% reaction, the temperature being constant. The observed oxidation product is the corresponding benzaldehyde. The reactions were of first order with respect to each the alcohol and BIDC. The reactions are catalyzed by proton, and the dependence is of the form: kobs = a + b[H+]. The reactions thus follow both, an acid-dependent and acid-independent paths. The oxidation of [1,1 2H2]benzyl alcohol exhibited the presence of a substantial kinetic isotope effect ( kH/kD = 6.20 at 298 K ). This indicated the cleavage of a α-C-H bond in the rate-determining step. An analysis of the temperature dependence of the deuterium isotope effect showed that the loss of hydrogen proceeds through a concerted cyclic process. The rate of oxidation of BA was determined in 19 organic solvents. An analysis of the solvent effect by Swain’s equation indicated that though both the anion and cation-solvating powers of the solvent contribute to the observed solvent effect, the role of cation-solvation is major. The rates of the para and meta compounds, at 298 K, failed to exhibit a significant correlation in terms of Hammett or Brown's substituent constants. The rates were then subjected to analyses in terms of dual substituent parameter (DSP) equations. The rates of oxidation of the para-substituted benzyl alcohols show an excellent correlation with Taft's σI and σRBA values. However, the rates for the meta-substituted benzyl alcohols show an excellent correlation with σI and σR0. The polar reaction constants are negative indicating an electron-deficient transition state. Hence the overall mechanism is proposed to involve the formation of a chromate ester in a fast pre-equilibrium and then a decomposition of the ester in a subsequent slow step via a cyclic concerted symmetrical transition state, involving hydride-ion transfer, leading to the product. The first order dependence on alcohol may be accounted in terms of the small value of the formation constant of the ester intermediate. An another reaction mechanism accounting the acid-catalysis involve the formation of a protonated BIDC prior to formation of an ester intermediate which subsequently decomposes in a slow step leading to the product.

Keywords: benzimidazolium dichromate, benzyl alcohols, correlation analysis, kinetics, oxidation

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Authors: Amberly Brigden, Ali Heawood, Emma C. Anderson, Richard Morris, Esther Crawley

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Background: Paediatric chronic fatigue syndrome (CFS)/myalgic encephalomyelitis (ME) is characterised by persistent, disabling fatigue. Health services see patients below the age of 12. This age group experience high levels of disability, with low levels of school attendance, high levels of fatigue, anxiety, functional disability and pain. CFS/ME interventions have been developed for adolescents, but the developmental needs of younger children suggest treatment should be tailored to this age group. Little is known about how intervention should be delivered to this age group, and further work is needed to explore this. Qualitative research aids patient-centered design of health intervention. Methods: Five to 11-year-olds and their parents were recruited from a specialist CFS/ME service. Semi-structured interviews explored the families’ experience of the condition and perspectives on treatment. Interactive and arts-based methods were used. Interviews were audio-recorded, transcribed and analysed thematically. Qualitative Results: 14 parents and 7 children were interviewed. Early analysis of the interviews revealed the importance of the social-ecological setting of the child, which led to themes being developed in the context of Systems Theory. Theme one relates to the level of the child, theme two the family system, theme three the organisational and societal systems, and theme four cuts-across all levels. Theme1: The child’s capacity to describe, understand and manage their condition. Younger children struggled to describe their internal experiences, such as physical symptoms. Parents felt younger children did not understand some concepts of CFS/ME and did not have the capabilities to monitor and self-regulate their behaviour, as required by treatment. A spectrum of abilities was described; older children (10-11-year-olds) were more involved in clinical sessions and had more responsibility for self-management. Theme2: Parents’ responsibility for managing their child’s condition. Parents took responsibility for regulating their child’s behaviour in accordance with the treatment programme. They structured their child’s environment, gave direct instructions to their child, and communicated the needs of their child to others involved in care. Parents wanted their child to experience a 'normal' childhood and took steps to shield their child from medicalization, including diagnostic labels and clinical discussions. Theme3: Parental isolation and the role of organisational and societal systems. Parents felt unsupported in their role of managing the condition and felt negative responses from primary care health services and schools were underpinned by a lack of awareness and knowledge about CFS/ME in younger children. This sometimes led to a protracted time to diagnosis. Parents felt that schools have the potential important role in managing the child’s condition. Theme4: Complexity and uncertainty. Many parents valued specialist treatment (which included activity management, physiotherapy, sleep management, dietary advice, medical management and psychological support), but felt it needed to account for the complexity of the condition in younger children. Some parents expressed uncertainty about the diagnosis and the treatment programme. Conclusions: Interventions for younger children need to consider the 'systems' (family, organisational and societal) involved in the child’s care. Future research will include interviews with clinicians and schools supporting younger children with CFS/ME.

Keywords: chronic fatigue syndrome (CFS)/myalgic encephalomyelitis (ME), pediatric, qualitative, treatment

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Authors: Azeem Tariq, Stephane De Tourdonnet, Lars Stoumann Jensen, Reiner Wassmann, Bjoern Ole Sander, Quynh Duong Vu, Trinh Van Mai, Andreas De Neergaard

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Rice growing area is increasing to meet the food demand of increasing population. Mostly, rice is growing on lowland, small landholder fields in most part of the world, which is one of the major sources of greenhouse gases (GHG) emissions from agriculture fields. The strategies such as, altering water and residues (carbon) management practices are assumed to be essential to mitigate the GHG emissions from flooded rice system. The actual implementation and potential of these measures on small farmer fields is still challenging. A field study was conducted on red river delta in Northern Vietnam to identify the potential challenges and barriers to the small rice farmers for implementation of climate smart rice practices. The objective of this study was to develop and access the feasibility of climate smart rice prototypes under actual farmer conditions. Field and scientific oriented framework was used to meet our objective. The methodological framework composed of six steps: i) identification of stakeholders and possible options, ii) assessment of barrios, drawbacks/advantages of new technologies, iii) prototype design, iv) assessment of mitigation potential of each prototype, v) scenario building and vi) scenario assessment. A farm survey was conducted to identify the existing farm practices and major constraints of small rice farmers. We proposed the two water (pre transplant+midseason drainage and early+midseason drainage) and one straw (full residue incorporation) management option keeping in views the farmers constraints and barriers for implementation. To test new typologies with existing prototypes (midseason drainage, partial residue incorporation) at farmer local conditions, a participatory field experiment was conducted for two consecutive rice seasons at farmer fields. Following the results of each season a workshop was conducted with stakeholders (farmers, village leaders, cooperatives, irrigation staff, extensionists, agricultural officers) at local and district level to get feedbacks on new tested prototypes and to develop possible scenarios for climate smart rice production practices. The farm analysis survey showed that non-availability of cheap labor and lacks of alternatives for straw management influence the small farmers to burn the residues in the fields except to use for composting or other purposes. Our field results revealed that application of early season drainage significantly mitigates (40-60%) the methane emissions from residue incorporation. Early season drainage was more efficient and easy to control under cooperate manage system than individually managed water system, and it leads to both economic (9-11% high rice yield, low cost of production, reduced nutrient loses) and environmental (mitigate methane emissions) benefits. The participatory field study allows the assessment of adaptation potential and possible benefits of climate smart practices on small farmer fields. If farmers have no other residue management option, full residue incorporation with early plus midseason drainage is adaptable and beneficial (both environmentally and economically) management option for small rice farmers.

Keywords: adaptation, climate smart agriculture, constrainsts, smallholders

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Authors: Sara J. Mills, Sally Howell

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The field of special education has long struggled to bridge the research to practice gap. There is ample evidence from research of effective strategies for students with special needs, but these strategies are not routinely implemented in schools in ways that yield positive results for students. In recent years, the field of special education has turned its focus to implementation science. That is, discovering effective methods of implementing evidence-based practices in school settings. Teacher training is a critical factor in implementation. This study aimed to successfully implement Schema-Based Instruction (SBI) for math problem solving in four classrooms in a special primary school serving students with language deficits, including students with Autism Spectrum Disorders (ASD) and Intellectual Disabilities (ID). Using an action research design that allowed for adjustments and modification to be made over the year-long study, two cohorts of teachers across the school were trained and supported in six-week learning cycles to implement SBI in their classrooms. The learning cycles included a one-day training followed by six weeks of one-on-one or team coaching and three fortnightly cohort group meetings. After the first cohort of teachers completed the learning cycle, modifications and adjustments were made to lesson materials in an attempt to improve their effectiveness with the second cohort. Fourteen teachers participated in the study, including master special educators (n=3), special education instructors (n=5), and classroom assistants (n=6). Thirty-one students participated in the study (21 boys and 10 girls), ranging in age from 5 to 12 years (M = 9 years). Twenty-one students had a diagnosis of ASD, 20 had a diagnosis of mild or moderate ID, with 13 of these students having both ASD and ID. The remaining students had diagnosed language disorders. To evaluate the effectiveness of the implementation approach, both student and teacher data was collected. Student data included pre- and post-tests of math word problem solving. Teacher data included fidelity of treatment checklists and pre-post surveys of teacher attitudes and efficacy for teaching problem solving. Finally, artifacts were collected throughout the learning cycle. Results from cohort 1 and cohort 2 revealed similar outcomes. Students improved in the number of word problems they answered correctly and in the number of problem-solving steps completed independently. Fidelity of treatment data showed that teachers implemented SBI with acceptable levels of fidelity (M = 86%). Teachers also reported increases in the amount of time spent teaching problem solving, their confidence in teaching problem solving and their perception of students’ ability to solve math word problems. The artifacts collected during instruction indicated that teachers made modifications to allow their students to access the materials and to show what they knew. These findings are in line with research that shows student learning can improve when teacher professional development is provided over an extended period of time, actively involves teachers, and utilizes a variety of learning methods in classroom contexts. Further research is needed to evaluate whether these gains in teacher instruction and student achievement can be maintained over time once the professional development is completed.

Keywords: implementation science, mathematics problem solving, research-to-practice gap, schema based instruction

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Authors: Sarah Hazelwood, Janice Hay

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Methoxyflurane is an inhaled analgesic administered via a disposable inhaler, which has been used in Australia for 40 years for the management of pain in children & adults. However, there is a lack of data for methoxyflurane as a frontline analgesic medication within the emergency department (ED). This study will investigate the usefulness of methoxyflurane in a private inner-city ED. The study concluded that the inclusion of all key stakeholders in the prescribing, administering & use of this new process led to comprehensive uptake & vastly positive outcomes for consumer & health professionals. Method: A 12-week prospective pilot study was completed utilizing patients presenting to the ED in pain (numeric pain rating score > 4) that fit the requirement of methoxyflurane use (as outlined in the Australian Prescriber information package). Nurses completed a formatted spreadsheet for each interaction where methoxyflurane was used. Patient demographics, day, time, initial numeric pain score, analgesic response time, the reason for use, staff concern (free text), & patient feedback (free text), & discharge time was documented. When clinical concern was raised, the researcher retrieved & reviewed patient notes. Results: 140 methoxyflurane inhalers were used. 60% of patients were 31 years of age & over (n=82) with 16% aged 70+. The gender split; 51% male: 49% female. Trauma-related pain (57%) saw the highest use of administration, with the evening hours (1500-2259) seeing the greatest numbers used (39%). Tuesday, Thursday & Sunday shared the highest daily use throughout the study. A minimum numerical pain score of 4/10 (n=13, 9%), with the ranges of 5 - 7/10 (moderate pain) being given by almost 50% of patients. Only 3 instances of pain scores increased post use of methoxyflurane (all other entries showed pain score < initial rating). Patients & staff noted obvious analgesic response within 3 minutes (n= 96, 81%, of administration). Nurses documented a change in patient vital signs for 4 of the 15 patient-related concerns; the remaining concerns were due to “gagging” on the taste, or “having a coughing episode”; one patient tried to leave the department before the procedure was attended (very euphoric state). Upon review of the staff concerns – no adverse events occurred & return to therapeutic vitals occurred within 10 minutes. Length of stay for patients was compared with similar presentations (such as dislocated shoulder or ankle fracture) & saw an average 40-minute decrease in time to discharge. Methoxyflurane treatment was rated “positively” by > 80% of patients – with remaining feedback related to mild & transient concerns. Staff similarly noted a positive response to methoxyflurane as an analgesic & as an added tool for frontline analgesic purposes. Conclusion: Methoxyflurane should be used on suitable patient presentations requiring immediate, short term pain relief. As a highly portable, non-narcotic avenue to treat pain this study showed obvious therapeutic benefit, positive feedback, & a shorter length of stay in the ED. By partnering with key stake holders, this study determined methoxyflurane use decreased work load, decreased wait time to analgesia, and increased patient satisfaction.

Keywords: analgesia, benefits, emergency, methoxyflurane

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Authors: S. MacDougall-Davis, S. Wysling, R. Willmore

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Background: The application of good non-technical skills, also known as crew resource management (CRM), is central to the delivery of safe, effective healthcare. The authors have been running remote trauma courses for over 10 years, primarily focussing on developing participants’ CRM in time-critical, high-stress clinical situations. The course has undergone an iterative process over the past 10 years. We employ a number of experiential learning techniques for improving CRM, including small group workshops, military command tasks, high fidelity simulations with reflective debriefs, and a ‘flipped classroom’, where participants are asked to create their own simulations and assess and debrief their colleagues’ CRM. We created a randomised simulation study to assess the impact of our course on UK medical students’ CRM, both at an individual and a teams level. Methods: Sixteen students took part. Four clinical scenarios were devised, designed to be of similar urgency and complexity. Professional moulage effects and experienced clinical actors were used to increase fidelity and to further simulate high-stress environments. Participants were block randomised into teams of 4; each team was randomly assigned to one pre-course simulation. They then underwent our 5 day remote trauma CRM course. Post-course, students were re-randomised into four new teams; each was randomly assigned to a post-course simulation. All simulations were videoed. The footage was reviewed by two independent CRM-trained assessors, who were blinded to the before/after the status of the simulations. Assessors used the internationally validated team emergency assessment measure (TEAM) to evaluate key areas of team performance, as well as a global outcome rating. Prior to the study, assessors had scored two unrelated scenarios using the same assessment tool, demonstrating 89% concordance. Participants also completed pre- and post-course questionnaires. Likert scales were used to rate individuals’ perceived NTS ability and their confidence to work in a team in time-critical, high-stress situations. Results: Following participation in the course, a significant improvement in CRM was observed in all areas of team performance. Furthermore, the global outcome rating for team performance was markedly improved (40-70%; mean 55%), thus demonstrating an impact at Level 4 of Kirkpatrick’s hierarchy. At an individual level, participants’ self-perceived CRM improved markedly after the course (35-70% absolute improvement; mean 55%), as did their confidence to work in a team in high-stress situations. Conclusion: Our study demonstrates that with a short, cost-effective course, using easily reproducible teaching sessions, it is possible to significantly improve participants’ CRM skills, both at an individual and, perhaps more importantly, at a teams level. The successful functioning of multi-disciplinary teams is vital in a healthcare setting, particularly in high-stress, time-critical situations. Good CRM is of paramount importance in these scenarios. The authors believe that these concepts should be introduced from the earliest stages of medical education, thus promoting a culture of effective CRM and embedding an early appreciation of the importance of these skills in enabling safe and effective healthcare.

Keywords: crew resource management, non-technical skills, training, simulation

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Authors: José Silvestre Mendoza Figueroa, Anders Kvarnheden, Jesús Méndez Lozano, Edgar Antonio Rodríguez Negrete, Manuel Soriano García

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Agroindustrial plants such as cereals and pseudo cereals offer a substantial source of biomacromolecules, as they contain large amounts per tissue-gram of proteins, polysaccharides and lipids in comparison with other plants. In particular, Amaranthus hypochondriacus seeds have high levels of proteins in comparison with other cereal and pseudo cereal species, which makes the plant a good source of bioactive molecules such as peptides. Geminiviruses are one principal class of pathogens that causes important economic losses in crops, affecting directly the development and production of the plant. One such virus is the Tomato yellow leaf curl virus (TYLCV), which affects mainly Solanacea family plants such as tomato species. The symptoms of the disease are curling of leaves, chlorosis, dwarfing and floral abortion. The aim of this work was to get peptides derived from enzymatic hydrolysis of globulins and albumins from amaranth seeds with specific recognition of the replication origin in the TYLCV genome, and to test the antiviral activity on host plants with the idea to generate a direct control of this viral infection. Globulins and albumins from amaranth were extracted, the fraction was enzymatically digested with papain, and the aromatic peptides fraction was selected for further purification. Six peptides were tested against the replication origin (OR) using affinity assays, surface resonance plasmon and fluorescent titration, and two of these peptides showed high affinity values to the replication origin of the virus, dissociation constant values were calculated and showed specific interaction between the peptide Ampep1 and the OR. An in vitro replication test of the total TYLCV DNA was performed, in which the peptide AmPep1 was added in different concentrations to the system reaction, which resulted in a decrease of viral DNA synthesis when the peptide concentration increased. Also, we showed that the peptide can decrease the complementary DNA chain of the virus in Nicotiana benthamiana leaves, confirming that the peptide binds to the OR and that its expected mechanism of action is to decrease the replication rate of the viral genome. In an infection assay, N. benthamiana plants were agroinfected with TYLCV-Israel and TYLCV-Guasave. After confirming systemic infection, the peptide was infiltrated in new infected leaves, and the plants treated with the peptide showed a decrease of virus symptoms and viral titer. In order to confirm the antiviral activity in a commercial crop, tomato plants were infected with TYLCV. After confirming systemic infection, plants were infiltrated with peptide solution as above, and the symptom development was monitored 21 days after treatment, showing that tomato plants treated with peptides had lower symptom rates and viral titer. The peptide was also tested against other begomovirus such as Pepper huasteco yellow vein virus (PHYVV-Guasave), showing a decrease of symptoms in N. benthamiana infected plants. The model of direct biochemical control of TYLCV infection shown in this work can be extrapolated to other begomovirus infections, and the methods reported here can be used for design of antiviral agrochemicals for other plant virus infections.

Keywords: agrochemical screening, antiviral, begomovirus, geminivirus, peptides, plasmon, TYLCV

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Authors: Atefeh Salehipoor

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: 1. Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. 2. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. 3. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. 4. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. 5. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. 6. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension

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