Search results for: target marketing

Authors: Farid Benkaci-Alia, Abdelhamid Neggada, Sophie Laurentb

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A new extraction method of polyphenols from honey using a biodegradable resin was developed and compared with the common commercial resin amberlite XAD2. For this purpose, three honey samples of Algerian origin were selected for the different physico-chemical and biochemical parameters study. After extraction of the target compounds by both resins, the polyphenol content was determined, the antioxidant activity was tested, and LC-MS analyses were performed for identification and quantification. The results showed that physico-chemical and biochemical parameters meet the norms of the International Honey commission, and the H1 sample seemed to be of high quality. The optimal conditions of extraction by biodegradable resin were a pH of 3, an adsorption dose of 40 g/L, a contact time of 50 min, an extraction temperature of 60°C and no stirring. The regeneration and reuse number of both resins was three cycles. The polyphenol contents demonstrated a higher extraction efficiency of biosorbent than of XAD2, especially in H1. LC-MS analyses allowed for the identification and quantification of fifteen compounds in the different honey samples extracted using both resins and the most abundant compound was 3,4,5-trimethoxybenzoic acid. In addition, the biosorbent extracts showed stronger antioxidant activities than the XAD2 extracts.

Keywords: extraction, polyphénols, biosorbent, resin amberlite, HPLC-MS

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Authors: Fatemeh Torabi, Jamal El-Den, Narumon Sriratanviriyakul

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Perpetual changes in the workplace and daily business activities bring a need for imbedding organizational knowledge sharing within the organizations’ culture, routines and processes. Organizations should adapt to the changing in the environment in order to survive. Accordingly, the management should promote a knowledge sharing culture which might result in knowledge accumulation, hence better response to these changing environmental conditions. Researchers in the field of strategy and marketing stressed that employees’, as well as the overall performance of the organization, would improve as a result of implementing a knowledge-oriented culture. The research investigated the significant impact of knowledge sharing on market response and the competitiveness of organizations. A knowledge sharing framework was developed based on current literary frameworks with additional constructs such as employees’ learning commitments, experiences and prior knowledge. Linear regression was used to analyze the relationships among dependent and independent variables. The research’s results indicated strong positive correlation between the dependent and independent variables, especially in organizational market sharing. We anticipate that this correlation would improve organizational knowledge sharing related practices and the associated knowledge entities. The research posits the introduced framework could be a solid ground for further investigations on how some organizational factors would influence the organization’s response to the market as well as on competitiveness. Final results support all hypotheses. Finding of this research show that knowledge sharing intention had the significant and positive effect on market response and competitiveness of organizations.

Keywords: knowledge management, knowledge sharing, market response, organizational competitiveness

Procedia PDF Downloads 199

Authors: Felsy J. Sandi

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There is a potential of growth in the spa industry due to the influx of domestic and international tourist coming to Sabah, Malaysia. It is a good opportunity to venture into this industry for the country’s economic future growth, and therefore, it is essential for this area to be researched. Being one of the fastest growing industries in the world, has led to enormous challenges, which need to be addressed. Malaysia is also riding with this phenomenon. The President of the Malaysian Association of Wellness and Spa stated that the misconception about the Spa industry’s image, especially amongst the elderly is the biggest challenge faced by the industry, as they perceived the spa industry is equivalent to a prostitution center. Therefore, the objective of this study is to explore the issue by analyzing whether image can be added in the theory of planned behavior to better understand the consumer’s intention to visit, in the spa context. The Theory of Planned Behavior by Ajzen, a theory or model in predicting intention, has three constructs; such as Attitude as the first construct, the second construct is Subjective Norm and the third construct is Perceived Behavioral Control. Qualitative research is used as this is an exploratory research. The site of study will be at Jari Jari Spa, located in Kota Kinabalu, the only spa in Sabah that was awarded as the Center of Excellence (CoE) by the Ministry of Tourism and Culture in Malaysia. The findings propose to provide useful information to the relevant stakeholders on ways to approach local customers to convince them to visit the spa and for spa marketers to help them develop and design effective marketing strategies. Future investigation should consider more on the perception and loyalty of the local customers.

Keywords: consumer's perception, image, local customer, spa, visit intention

Procedia PDF Downloads 261

Authors: Panupong Chanplin, Kathaleeya Chanda., Wilailuk Mepracha

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The aims of this research were twofold: 1) to brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province and 2) to study the level of tourist satisfaction towards brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province. tourist satisfaction was measured using six criteria: clear brand positioning, likeable brand personality, memorable logo, attractive color palette, professional typography and on-brand supporting graphics. The researcher utilized a probability sampling method via simple random sampling. The sample consisted of 30 tourists in the Creative Agriculture Community Enterprise. Statistics utilized for data analysis were percentage, mean, and standard deviation. The results suggest that tourist had high levels of satisfaction towards all six criteria of the brand identity design that was designed to target them. This study proposes that specifically brand identity designed of Creative Agriculture Community Enterprise could also be implemented with other real media already available on the market.

Keywords: satisfaction, brand identity, logo, creative agriculture community enterprise

Procedia PDF Downloads 235

Authors: Christiana Gauci-Sciberras

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The first language (L1) could be used in foreign language teaching and learning as a pedagogical tool to scaffold new knowledge in the target language (TL) upon linguistic knowledge that the learner already has. In a bilingual context, code-switching between the two languages usually occurs in classrooms. One of the reasons for code-switching is because both languages are used for scaffolding new knowledge. This research paper aims to find out why both the L1 (Maltese) and the L2 (English) are used in the classroom of Mandarin Chinese as a foreign language (CFL) in the bilingual context of Malta. This research paper also aims to find out the learners’ perceptions of the use of a bilingual medium of instruction. Two research methods were used to collect qualitative data; semi-structured interviews with adult learners of Mandarin Chinese and lesson observations. These two research methods were used so that the data collected in the interviews would be triangulated with data collected in lesson observations. The L1 (Maltese) is the language of instruction mostly used. The teacher and the learners switch to the L2 (English) or to any other foreign language according to the need at a particular instance during the lesson.

Keywords: Chinese, bilingual, pedagogical purpose of L1 and L2, CFL acquisition

Procedia PDF Downloads 191

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Jeremie Coullon, Robert J. Webber

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We introduce a Markov chain Monte Carlo (MCMC) sam-pler for infinite-dimensional inverse problems. Our sam-pler is based on the affine invariant ensemble sampler, which uses interacting walkers to adapt to the covariance structure of the target distribution. We extend this ensem-ble sampler for the first time to infinite-dimensional func-tion spaces, yielding a highly efficient gradient-free MCMC algorithm. Because our ensemble sampler does not require gradients or posterior covariance estimates, it is simple to implement and broadly applicable. In many Bayes-ian inverse problems, Markov chain Monte Carlo (MCMC) meth-ods are needed to approximate distributions on infinite-dimensional function spaces, for example, in groundwater flow, medical imaging, and traffic flow. Yet designing efficient MCMC methods for function spaces has proved challenging. Recent gradi-ent-based MCMC methods preconditioned MCMC methods, and SMC methods have improved the computational efficiency of functional random walk. However, these samplers require gradi-ents or posterior covariance estimates that may be challenging to obtain. Calculating gradients is difficult or impossible in many high-dimensional inverse problems involving a numerical integra-tor with a black-box code base. Additionally, accurately estimating posterior covariances can require a lengthy pilot run or adaptation period. These concerns raise the question: is there a functional sampler that outperforms functional random walk without requir-ing gradients or posterior covariance estimates? To address this question, we consider a gradient-free sampler that avoids explicit covariance estimation yet adapts naturally to the covariance struc-ture of the sampled distribution. This sampler works by consider-ing an ensemble of walkers and interpolating and extrapolating between walkers to make a proposal. This is called the affine in-variant ensemble sampler (AIES), which is easy to tune, easy to parallelize, and efficient at sampling spaces of moderate dimen-sionality (less than 20). The main contribution of this work is to propose a functional ensemble sampler (FES) that combines func-tional random walk and AIES. To apply this sampler, we first cal-culate the Karhunen–Loeve (KL) expansion for the Bayesian prior distribution, assumed to be Gaussian and trace-class. Then, we use AIES to sample the posterior distribution on the low-wavenumber KL components and use the functional random walk to sample the posterior distribution on the high-wavenumber KL components. Alternating between AIES and functional random walk updates, we obtain our functional ensemble sampler that is efficient and easy to use without requiring detailed knowledge of the target dis-tribution. In past work, several authors have proposed splitting the Bayesian posterior into low-wavenumber and high-wavenumber components and then applying enhanced sampling to the low-wavenumber components. Yet compared to these other samplers, FES is unique in its simplicity and broad applicability. FES does not require any derivatives, and the need for derivative-free sam-plers has previously been emphasized. FES also eliminates the requirement for posterior covariance estimates. Lastly, FES is more efficient than other gradient-free samplers in our tests. In two nu-merical examples, we apply FES to challenging inverse problems that involve estimating a functional parameter and one or more scalar parameters. We compare the performance of functional random walk, FES, and an alternative derivative-free sampler that explicitly estimates the posterior covariance matrix. We conclude that FES is the fastest available gradient-free sampler for these challenging and multimodal test problems.

Keywords: Bayesian inverse problems, Markov chain Monte Carlo, infinite-dimensional inverse problems, dimensionality reduction

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Authors: Tuhina-khatun, Mohamed Hanafi Musa, Mohd Rafii Yosup, Wong Mui Yun, Aktar-uz-Zaman, Mahbod Sahebi

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Suppression subtractive hybridization (SSH) method is valuable tool for identifying differentially regulated genes in disease specific or tissue specific genes important for cellular growth and differentiation. It is a widely used method for separating DNA molecules that distinguish two closely related DNA samples. SSH is one of the most powerful and popular methods for generating subtracted cDNA or genomic DNA libraries. It is based primarily on a suppression polymerase chain reaction (PCR) technique and combines normalization and subtraction in a solitary procedure. The normalization step equalizes the abundance of DNA fragments within the target population, and the subtraction step excludes sequences that are common to the populations being compared. This dramatically increases the probability of obtaining low-abundance differentially expressed cDNAs or genomic DNA fragments and simplifies analysis of the subtracted library. SSH technique is applicable to many comparative and functional genetic studies for the identification of disease, developmental, tissue specific, or other differentially expressed genes, as well as for the recovery of genomic DNA fragments distinguishing the samples under comparison.

Keywords: suppression subtractive hybridization, differentially expressed genes, disease specific genes, tissue specific genes

Procedia PDF Downloads 426

Authors: Irfan Khairi

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It is arguable that today's social media has dramatically redefined human contact, and chiefly because the platforms enable communication opportunities unprecedented. Without question, billions of individuals globally engage in the media, a reality by no means lost on businesses and social entrepreneurs desirous of generating interest in a cause, movement, or other social effort. If, however, the opportunities are immense, so too is the competition. Private persons and entrepreneurial concerns alike virtually saturate the popular sites of Facebook, Twitter, and Instagram, and most are intent on capturing as much external interest as possible. At the same time, however, the social entrepreneur possesses an advantage over the individual concerned only the social aspects of the sites, as they express interests in, and measures applicable to, important causes of which the public at large may be unaware. There is, unfortunately, no single means of assuring success in using the media outlets to generate interest. Nonetheless, a general awareness of how social media sites function, as well as the psychological elements relevant to the functioning, is necessary. It is as important to comprehend basic realities of the platforms and approaches that fail as it is to develop strategy, for the latter relies on knowledge of the former. This awareness in place, the social entrepreneur is then better enabled to determine strategy, in terms of which sites to focus upon and how to most effectively convey their message. What is required is familiarity with the online communities, with attention to the specific advantages each provides. Ultimately, today's social entrepreneur may establish a highly effective platform of promotion and engagement, provided they fully comprehend the social investment necessary for success.

Keywords: social media, marketing, e-commerce, internet business

Procedia PDF Downloads 205

Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Salma Ainine, Colin Ritchie, Tracey McFee

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Background: The societal impact of antibiotic resistance is a major public health concern. The increase in the incidence of resistant bacteria can ultimately be fatal. Objective: To analyse the appropriateness of antibiotic prescribing in Dundee Dental Hospital, ultimately improving the safety and quality of patient care. Methods: Two examiners independently cross-checked approximately fifty consecutive prescriptions, and corresponding patient case notes, for three data collection cycles between August 2014–September 2015. The Scottish Dental Clinical Effectiveness Program (SDCEP) Drug Prescribing for Dentistry guidelines was the standard utilised. The criteria: clinical justification, regime justification, and review arrangements was measured, and compared to the standard. Results: Cycle one revealed 42% of antibiotic prescriptions were appropriate. Interventions included: multiple staff meetings, an introduction of a checklist attached to the prescription pack, and production of patient leaflets explaining indications for antibiotics. Cycle two and three revealed 44%, and 30% compliance, respectively. Conclusion: The results of the audit have yet to meet target standards set out in prescribing guidelines. However, steps are being taken and change has occurred on a cultural level.

Keywords: antibiotic resistance, antibiotic stewardship, dental infection, hygiene standards

Procedia PDF Downloads 221

Authors: K. K. A. Bakhti, D. Mottet, J. Froger, I. Laffont

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Background: After a cerebrovascular accident (or stroke), many patients use excessive trunk movements to move their paretic hand towards a target (while the elbow is maintained flexed) even though they can use the upper-limb when the trunk is restrained. This phenomenon is labelled learned non-use and is known to be detrimental to neuroplasticity and recovery. Objective: The aim of this study is to quantify learned non-use of the paretic upper limb during a hand reaching task using 3D movement analysis. Methods: Thirty-four participants post supratentorial stroke were asked to reach a cone placed in front of them at 80% of their arm length. The reaching movement was repeated 5 times with the paretic hand, and then 5 times with the less-impaired hand. This sequence was first performed with the trunk free, then with the trunk restrained. Learned non-use of the upper-limb (LNUUL) was obtained from the difference of the amount of trunk compensation between the free trunk condition and the restrained trunk condition. Results: LNUUL was significantly higher for the paretic hand, with individual values ranging from 1% to 43%, and one-half of the patients with an LNUUL higher than 15%. Conclusions: Quantification of LNUUL can be used to objectively diagnose patients who need trunk rehabilitation. It can be also used for monitoring the rehabilitation progress. Quantification of LNUUL may guide upper-limb rehabilitation towards more optimal motor recovery avoiding maladaptive trunk compensation and its consequences on neuroplasticity.

Keywords: learned non-use, rehabilitation, stroke, upper limb

Procedia PDF Downloads 232

Authors: Kurotimi M. Fems, Francis D. W. Poazi, Helen Opigo

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The concepts of entrepreneurship education together with graduate entrepreneurship have taken centre stage in many countries as a 21^st century strategy for economic growth and development. Entrepreneurship education has been viewed as a pre-requisite tool for a more effective and successful business operation. This paper seeks to verify if entrepreneurship education is pre-requisite to graduate entrepreneurship, and to ascertain if such other factors as the need for achievement, competence and experience etc. also play a foundational role in the choice of a graduate becoming an entrepreneur. The scope of the research study is entrepreneurs within Yenagoa metropolis in Bayelsa state, Nigeria. The sample target is graduates engaged in entrepreneurship activities (graduates who own and run businesses). Stratified sampling technique was used and 101 responses were obtained from a total of 300 questionnaires issued. Bar chart, tables and percentages were used to analyze the collected data. The findings revealed that personality traits, situational circumstance, need for achievement and experience/competence were the foundational factors stimulating graduate entrepreneurs to engage in entrepreneurial pursuits. Of all, personality trait showed the highest score with 73 (73%) out of 101 entrepreneurs agreeing. Experience/Competence and situational circumstances followed behind with 66 (65%) and 63 (62.4%), respectively. Entrepreneurship education revealed the least score with 33 (32.3%) out of 101 participating entrepreneurs. All hope, however, is not lost, as this shows that something can be done to increase the impact of entrepreneurship education on graduate entrepreneurship.

Keywords: Creative destruction, entrepreneurs, entrepreneurship education, graduate entrepreneurship, pre-requisite

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Authors: Zijiao Chai, Wangming Li

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Under the background of increasing aging population, the situation of city endowment resources shortage gradually revealed. And many villages in the metropolitan area with the good natural ecological environment and leisure tourism base, have become one of the main destinations of urban old people for the off-site pension. This paper is based on a survey of more than ten villages which are characterized by leisure and endowment in Hangzhou metropolitan area, China. The satisfaction degree of the two main groups in the villages, dwellers, and aged visitors, is researched using the method of fuzzy comprehensive evaluation. The statistics are obtained from 535 questionnaires and qualitative interview. According to the satisfaction scores, it could be determined whether the dwellers and aged visitors have reached the equilibrium state. The equilibrium state is the development target of the villages, and it`s defined by environmentally friendly, proper for employment and pension, facilities sharing and harmonious life for each other. Furthermore, this paper comes up with some planning countermeasures in order to avoid "imbalance between dwellers and aged visitors" and obtain sustainable development while maintaining the economic benefit.

Keywords: aged visitors, balance between dwellers and aged visitors, dwellers, fuzzy comprehensive evaluation, Hangzhou metropolitan area, leisure and endowment characteristic villages

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Authors: Mehrnoosh Pirhayati

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Translation can be affected by different meta-textual factors of target context such as ideology, politics, and culture. So, the rule of fidelity, or being faithful to the source text, can be ignored by the translator. On the other hand, critical discourse analysis, derived from applied linguistics, is entered into the field of translation studies and used by scholars for revealing hidden deviations and possible roots of manipulations. This study focused on the famous Persian translation of the bestseller book, “A**hole No More,” written by XavierCrement 1990, performed by Mahmud Farjami to comparatively and critically analyze it with its corresponding English original book. The researcher applied Pirhayati’s model and framework of translation criticism at the textual and semiotic levels for this qualitative study. It should be noted that Kress and Van Leeuwen’s semiotic model, along with Machin’s model of typographical analysis, was also used at the semiotic level. The results of the comparisons and analyses indicate thatthis Persian translation of the book is affected by the factors of ideology and economics and reveal that the Islamic attitude causes the translator to employ some strategies such as substitution and deletion. Those who may benefit from this research are translation trainers, students of translation studies, critics, and scholars.

Keywords: farjami (2013), Ideology, manipulation, pirhayati's (2013) model of translation criticism, Xavier crement (1990)

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Authors: Mohammad Kargar Shouraki, Naji Yazdi, Mohsen Emami

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The environmental and social challenges have caused the organizations to put further attention and emphasis on sustainable growth and developing strategies for sustainability. Since human is both the target of development and the agent of development at the same time, one of the most important factors in the development of the sustainability strategy in organizations is the human factor. In addition, organizations have been facing the new challenge of digital transformation which impacts the human factor, meanwhile, undeniably, the human factor contributes to such transformation. Therefore, organizations are facing the challenge of digital human resource management (HRM). Thus, the present study aims to investigate how an HRM model should be so that it not only can help the consideration and of the business sustainability requirements but also can make the highest and the most appropriate positive, not destructive, utilization of the digital transformations. Furthermore, the success of the HRM regarding the two sustainability and digital transformation challenges requires dynamic human competencies, which are addressed as digital/sustainable human dynamic capabilities in this paper. The present study is conducted using a hybrid methodology consisting of the qualitative methods of meta-synthesis and content analysis and the quantitative method of interpretive-structural model (ISM). Finally, a rotatory model, including 3 approaches, 3 perspectives, and 9 dimensions, is presented.

Keywords: sustainable human resource management, digital human resource management, digital/sustainable human dynamic capabilities, talent management

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Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: M. Lizzy Madiwani, Ignatious Ncube, Evelyn Madoroba

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This study was designed to determine the distribution of pathogenic bacteria in household raised chickens and study their virulence and antibiotic profiles. For this purpose, 40 chickens were purchased from families in the Capricorn district and sacrificed for sampling. Tissues were cultured on different bacteriological media followed by biotyping using Matrix-assisted Laser Desorption Ionization-time of Flight (MALDI-TOF). Disk diffusion test was performed to determine the antibiotic susceptibility profiles of these bacteria. Out of a total of 160 tissue samples evaluated, E. coli and Salmonella were detected in these tissues. Furthermore, determination of the pathogenic E. coli and Salmonella strains at species level using primer sets that target selected genes of interest in the polymerase chain reaction (PCR) assay was employed. The invA gene, a confirmatory gene of Salmonella was detected in all the Salmonella isolates. The study revealed that there is a high distribution of Salmonella and pathogenic E. coli in these chickens. Therefore, further studies on identification at the species level are highly recommended to provide management and sanitation practices to lower this prevalence. The antimicrobial susceptibly data generated from this study can be a valuable reference to veterinarians for treating bacterial diseases in poultry.

Keywords: antimicrobial, Escherichia coli, pathogens, Salmonella

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Authors: Reem Al-Shidhani, Isabelle S. R. Storer, Michael J. Bromley, Lydia Tabernero

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Invasive fungal diseases are an increasing global health concern that contributes to the high mortality rates in immunocompromised patients. The rising of antifungal resistance severely lowers the efficacy of the limited antifungal agents available. New antifungal drugs that target new mechanisms are necessary to tackle the current shortfalls. Amongst post- modifications, phosphorylation is a predominant and an outstanding protein alteration in all eukaryotes. In fungi, protein phosphorylation plays a vital role in many signal transduction pathways, including cell cycle, cell growth, metabolism, transcription, differentiation, proliferation, and virulence. The investigation of Aspergillus fumigatus phosphatases revealed seven genes essential for viability. Inhibiting one of these phosphatases is a new interesting route to develop novel antifungal drugs. In this study, we carried out an early drug discovery process targeting oneessential phosphatase, GlcA. Here, we report the identification of new GlcA inhibitors that show antifungal activity. These important finding open a new avenue to the development of novel antifungals to expand the current narrow arsenal of clinical candidates.

Keywords: invasive fungal diseases, phosphatases, GlcA, competitive inhibitors

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Authors: M. Pena, J. Shin, H. Park

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The main objective of any engineering activity is the development of a system that fulfills the specific economic, social or environmental needs. Green growth policies, as a system, targets to satisfy two main needs: economic and environmental growth. Cities are complex systems composed of varied characteristics such as differences in socio-environmental conditions and local affordability, among others. Thus, commissioned policies are required to address these differences and to ensure green development. A more maintainable and justifiable, resource-efficient green growth can be obtained in urban areas if multi-criteria framework of policies relevant to green buildings is designed. Reason is that, this approach fits to target the differences and unique conditions of urban areas. By following the principles of axiomatic design, this paper urges to derive a framework for the application of green buildings policies in urban areas with distinctive socio-economic and environmental characteristics. Functional requirements defined as principles to ensure green growth and design parameters are identified in each set of conditions. Design matrices are constructed for each group of urban areas. Thus, the understanding of the needs and differences for each group of urban areas and the methodology to ensure green buildings is achieved.

Keywords: axiomatic design, green growth, sustainable development, urban planning

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Muhammad Fathurridho

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Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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Authors: Esra Cansever Mutlu, Muge Sennaroglu Bostan, Fatemeh Bahadori, Ebru Toksoy Oner, Mehmet S. Eroglu

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Paclitaxel is used in treatment of different cancer types mainly breast, ovarian, lung and Kaposi’s sarcoma. It is poorly soluble in water; therefore, currently used formulations tremendously show side-effects and high toxicity. Encapsulation of the drug in a nano drug carrier which causes both reducing side effects and increasing drug activity is a desired new approach for the nano-medicine to target the site of cancer. In this study, synthesis of a novel nano paclitaxel formulation made of a new amphiphilic monomer was followed by the investigation of its pharmacological properties. UV radical polymerization was carried out by using the monomer Lecithin-2-Acrylamido-2-methylpropane (L-AMPS) and the drug-spacer, to obtain sterically high stabilized, biocompatible and biodegradable phospholipid nanoparticles, in which the drug paclitaxel (Pxl) was encapsulated (NanoPxl). Particles showed high drug loading capacity (68%) and also hydrodynamic size less than 200 nm with slight negative surface charge. The drug release profile was obtained and in vitro cytotoxicity test was performed on MCF-7 cell line. Consequently, these data indicated that paclitaxel loaded Lecithin-AMPS/PCL-MAC nanoparticles can be considered as a new, safe and effective nanocarrier for the treatment of breast cancer.

Keywords: paclitaxel, nanoparticle, drug delivery, L-AMPS

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Authors: Ibrahim R. Elomari, Fin O'Flaherty, Ibrahim R. Elomari, Paul Lambert

Abstract:

Cathodic protection (CP) is a technique commonly used to arrest corrosion of steel in infrastructure. However, it is not generally used on high strength, pre-stressed tendons due to the risk of hydrogen generation, leading to possible embrittlement. This paper investigates its use in such circumstances where the applied protection potential is varied to determine if CP can be safely employed on pre-stressed tendons. Plain steel tendons measuring 5.4 mm diameter were pre-stressed in timber moulds and embedded in sand/cement mortar, formulated to represent gunite. Two levels of pre-stressing were investigated (400MPa and 1200MPa). Pre-corrosion of 0% (control), 3% and 6% target loss of cross-sectional area was applied to replicate service conditions. Impressed current cathodic protection (ICCP) was then applied to the tendons at two levels of potential to identify any effect on strength. Instant-off values up to -950mV were used for normal protection with values of -1100mV or more negative to achieve overprotection. Following the ICCP phase, the tendons were removed from the mortar, cleaned and weighed to confirm actual percentage of corrosion. Tensile tests were then conducted on the tendons. The preliminary results show the influence of normal levels and overprotection of CP on the ultimate strength of the tendons.

Keywords: pre-stressed concrete, corrosion, cathodic protection, hydrogen embrittlement

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Authors: S. Pradhan, D. Pradhan, G. Tripathy, T. Dasmohapatra

Abstract:

Suppressors of cytokine signalling (SOCS3), a newly indentified anti-apoptotic molecule is a downstream effecter of the receptor tyrosine kinase-Ras signalling pathway. Current study has uncovered that SOCS3 may have wide and imperative capacities, particularly because of its close correlation with malignant tumors. To investigate the impact of SOCS3 on MDR, we analyzed the expression of P-gp and SOCS3 by immune-histochemistry and found there was positive correlation between them. At that point we effectively interfered with RNA translation by the contamination of siRNA of SOCS3 into MCF7/ADM breast cancer cell lines through a lentivirus, and the expression of the target gene was significantly inhibited. After RNAi the drug resistance was reduced altogether and the expression of MDR1 mRNA and P-gp in MCF7/ADM cell lines demonstrated a significant decrease. Likewise the expression of P53 protein increased in a statistically significant manner (p ≤ 0.01) after RNAi exposure. Moreover, flowcytometry analysis uncovers that cell cycle and anti-apoptotic enhancing capacity of cells changed after RNAi treatment. These outcomes proposed SOCS3 may take part in breast cancer MDR by managing MDR1 and P53 expression, changing cell cycle and enhancing the anti-apoptotic ability.

Keywords: SOCS3gene, breast cancer, multidrug resistance, MDR1 gene, RNA interference

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Authors: Shalitha Jayasekara, Saluk Bawantha, Dinithi Anupama, Isuru Gunarathne, Pradeepa Bandara, Hansi De Silva

Abstract:

Dogs have been known as "man's best friend" for generations, providing friendship and loyalty to their human counterparts. However, due to people's busy lives, they are unaware of the ailments that can affect their pets. However, in recent years, mobile technologies have had a significant impact on our lives, and with technological improvements, a rule-based expert system allows the end-user to enable new types of healthcare systems. The advent of Android OS-based smartphones with more user-friendly interfaces and lower pricing opens new possibilities for continuous monitoring of pets' health conditions, such as healthy dogs, dangerous ingestions, and swallowed objects. The proposed ‘Best Bark’ Dog care and owner consultation system is a mobile application for dog owners. Four main components for dog owners were implemented after a questionnaire was distributed to the target group of audience and the findings were evaluated. The proposed applications are widely used to provide health and clinical support to dog owners, including suggesting exercise and diet plans and answering queries about their dogs. Additionally, after the owner uploads a photo of the dog, the application provides immediate feedback and a description of the dog's skin disease.

Keywords: Convolution Neural Networks, Artificial Neural Networks, Knowledgebase, Sentimental Analysis.

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Authors: Motlatso Rampedi

Abstract:

Nigeria has the fifth highest Total Fertility Rate in Sub-Saharan Africa at 5.5 children born to a woman. Some demographic research has found that there is an association between region of residence and fertility in Nigeria, with the Northern regions pertaining to high fertility and the Southern regions pertaining to low fertility levels. Even so, little attention has been given to understanding the effect of region of residence on fertility. Instead, a significant amount of research has been conducted on exploring the proximate determinants of fertility in Nigeria. The objective of this study was to test whether there is an association between region of residence and fertility in Nigeria. Using a sample size of 38 948 women aged 15-49 derived from the 2013 NDHS and the Poisson regression model for analysis, the study has found that region of residence has a significant effect on fertility. Moreover, the ANOVA test has shown that there is a socioeconomic disparity by region of residence in Nigeria. The Northern regions of Nigeria have shown to have higher levels of fertility as compared to the Southern regions. Therefore, while proximate determinants of fertility and socio-demographic characteristics of women are important, region of residence remains one of the fundamental determinants of fertility. Given these findings, it is recommended that government should not exhaust its resources or focus its fertility reduction policies and programmes at entire populations but target specific regions where fertility is most prevalent.

Keywords: high fertility, region, socioeconomic disparity, socio-demographic characteristics

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Authors: Dinesh Kumar Yadav

Abstract:

Short stories for language development are deeply rooted elsewhere in any language syllabus. Its relevance is manifold. The short stories have the power to take the students to the target culture directly from the classroom. It works as a crucial factor in enhancing language skills in different ways. This article is an outcome of an experimental study conducted for a month on the 12th graders where they were engaged in different creative and critical-thinking activities along with various tasks that ranged from knowledge level to application level. The sole purpose was to build up their confidence in speaking in the classroom as well as develop all their language skills simultaneously. With the start of the class in August 2021, the students' speaking skill and their confidence in speaking in the class was tested. The test was abruptly followed by a presentation of a short story from their culture. The students were engaged in different tasks related to the story. The PowerPoint slides, handouts with the story, and tasks on photocopy were used as tools whenever needed. A one-month class exclusively on speaking skills through sharing stories was found to be very helpful in developing confidence in the learners. The result was very satisfactory. A large number of students became responsive in the class. The proficiency level was not satisfactory; however, their effort to speak in class showed a very positive sign in language development.

Keywords: short stories, relevance, language enhancement, language proficiency

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Authors: Hagen Stosnach

Abstract:

The analytical demands on modern instruments for element analysis in food samples include the analysis of major, trace and ultra-trace essential elements as well as potentially toxic trace elements. In this study total reflection, X-ray fluorescence analysis (TXRF) is presented as an analytical technique, which meets the requirements, defined by the Association of Official Agricultural Chemists (AOAC) regarding the limit of quantification, repeatability, reproducibility and recovery for most of the target elements. The advantages of TXRF are the small sample mass required, the broad linear range from µg/kg up to wt.-% values, no consumption of gases or cooling water, and the flexible and easy sample preparation. Liquid samples like alcoholic or non-alcoholic beverages can be analyzed without any preparation. For solid food samples, the most common sample pre-treatment methods are mineralization, direct deposition of the sample onto the reflector without/with minimal treatment, mainly as solid suspensions or after extraction. The main disadvantages are due to the possible peaks overlapping, which may lower the accuracy of quantitative analysis and the limit in the element identification. This analytical technique will be presented by several application examples, covering a broad range of liquid and solid food types.

Keywords: essential elements, toxic metals, XRF, spectroscopy

Procedia PDF Downloads 128