Search results for: customer discovery

Authors: E. O. Okan, A. Kepic, P. Williams

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Iron oxide copper gold (IOCG) deposits constitute important sources of copper and gold in Australia especially since the discovery of the supergiant Olympic Dam deposits in 1975. They are considered to be metasomatic expressions of large crustal-scale alteration events occasioned by intrusive actions and are associated with felsic igneous rocks in most cases, commonly potassic igneous magmatism, with the deposits ranging from ~2.2 –1.5 Ga in age. For the past two decades, geological, geochemical and potential methods have been used to identify the structures hosting these deposits follow up by drilling. Though these methods have largely been successful for shallow targets, at deeper depth due to low resolution they are limited to mapping only very large to gigantic deposits with sufficient contrast. As the search for ore-bodies under regolith cover continues due to depletion of the near surface deposits, there is a compelling need to develop new exploration technology to explore these deep seated ore-bodies within 1-4km which is the current mining depth range. Seismic reflection method represents this new technology as it offers a distinct advantage over all other geophysical techniques because of its great depth of penetration and superior spatial resolution maintained with depth. Further, in many different geological scenarios, it offers a greater ‘3D mapability’ of units within the stratigraphic boundary. Despite these superior attributes, no arguments for crustal scale seismic surveys have been proposed because there has not been a compelling argument of economic benefit to proceed with such work. For the seismic reflection method to be used at these scales (100’s to 1000’s of square km covered) the technical risks or the survey costs have to be reduced. In addition, as most IOCG deposits have large footprint due to its association with intrusions and large fault zones; we hypothesized that these deposits can be found by mainly looking for the seismic signatures of intrusions along prospective structures. In this study, we present two of such cases: - Olympic Dam and Vulcan iron-oxide copper-gold (IOCG) deposits all located in the Gawler craton, South Australia. Results from our 2D modelling experiments revealed that seismic reflection surveys using 20m geophones and 40m shot spacing as an exploration tool for locating IOCG deposit is possible even when hosted in very complex structures. The migrated sections were not only able to identify and trace various layers plus the complex structures but also show reflections around the edges of intrusive packages. The presences of such intrusions were clearly detected from 100m to 1000m depth range without losing its resolution. The modelled seismic images match the available real seismic data and have the hypothesized characteristics; thus, the seismic method seems to be a valid exploration tool to find IOCG deposits. We therefore propose that 2D seismic survey is viable for IOCG exploration as it can detect mineralised intrusive structures along known favourable corridors. This would help in reducing the exploration risk associated with locating undiscovered resources as well as conducting a life-of-mine study which will enable better development decisions at the very beginning.

Keywords: crustal scale, exploration, IOCG deposit, modelling, seismic surveys

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Authors: Bhargavi G. Iyer, Ojaswi Bhagat

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It is often noted that the value of a novel idea lies in its successful implementation. However, successful implementation requires the nurturing and encouragement of innovation. Nascent competitors are a true representation of innovation in any given industry. A nascent competitor is an entity whose prospective innovation poses a future threat to an incumbent dominant competitor. While a nascent competitor benefits in several ways, it is also exposed significantly and is at greater risk of facing the brunt of exclusionary practises and abusive conduct by dominant incumbent competitors in the industry. This research paper aims to explore the risks and threats faced by nascent competitors and analyse the benefits they accrue as well as the advantages they proffer to the economy; through an analytical, critical study. In such competitive market environments, a rise of the acquisitions of nascent competitors by the incumbent dominants is observed. Therefore, this paper will examine the dynamics of nascent acquisition. Further, this paper hopes to specifically delve into the role of antitrust bodies in regulating nascent acquisition. This paper also aspires to deal with the question how to distinguish harmful from harmless acquisitions in order to facilitate ideal enforcement practice. This paper proposes mechanisms of scrutiny in order to ensure healthy market practises and efficient merger control in the context of nascent acquisitions. Taking into account the scope and nature of the topic, as well as the resources available and accessible, a combination of the methods of doctrinal research and analytical research were employed, utilising secondary sources in order to assess and analyse the subject of research. While legally evaluating the Killer Acquisition theory and the Nascent Potential Acquisition theory, this paper seeks to critically survey the precedents and instances of nascent acquisitions. In addition to affording a compendious account of the legislative framework and regulatory mechanisms in the United States, the United Kingdom, and the European Union; it hopes to suggest an internationally practicable legal foundation for domestic legislation and enforcement to adopt. This paper hopes to appreciate the complexities and uncertainties with respect to nascent acquisitions and attempts to suggest viable and plausible policy measures in antitrust law. It additionally attempts to examine the effects of such nascent acquisitions upon the consumer and the market economy. This paper weighs the argument of shifting the evidentiary burden on to the merging parties in order to improve merger control and regulation and expounds on its discovery of the strengths and weaknesses of the approach. It is posited that an effective combination of factual, legal, and economic analysis of both the acquired and acquiring companies possesses the potential to improve ex post and ex ante merger review outcomes involving nascent companies; thus, preventing anti-competitive practises. This paper concludes with an analysis of the possibility and feasibility of industry-specific identification of anti-competitive nascent acquisitions and implementation of measures accordingly.

Keywords: acquisition, antitrust law, exclusionary practises merger control, nascent competitor

Procedia PDF Downloads 163

Authors: Rosilyn Sanders

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This qualitative study examined the impact of hiring people with intellectual disabilities (ID). The research questions were: What defines a disability? What accommodations are needed to ensure the success of a person with a disability? As a leader, what benefits do people with intellectual disabilities bring to the organization? What are the benefits of hiring people with intellectual disabilities in retail organizations? Moreover, how might people with intellectual disabilities contribute to the organizational culture of retail organizations? A narrative strength approach was used as a theoretical framework to guide the discussion and uncover the benefits of hiring individuals with intellectual disabilities in various retail organizations. Using qualitative interviews, the following themes emerged: diversity and inclusion, accommodations, organizational culture, motivation, and customer service. These findings put to rest some negative stereotypes and perceptions of persons with ID as being unemployable or unable to perform tasks when employed, showing instead that persons with ID can work efficiently when given necessary work accommodations and support in an enabling organizational culture. All participants were recruited and selected through various forms of electronic communication via social media, email invitations, and phone; this was conducted through the methodology of snowball sampling with the following demographics: age, ethnicity, gender, number of years in retail, number of years in management, and number of direct reports. The sample population was employed in several retail organizations throughout Arkansas and Texas. The small sample size for qualitative research in this study helped the researcher develop, build, and maintain close relationships that encouraged participants to be forthcoming and honest with information (Clow & James, 2014 ). Participants were screened to ensure they met the researcher's study; and screened to ensure that they were over 18 years of age. Participants were asked if they recruit, interview, hire, and supervise individuals with intellectual disabilities. Individuals were given consent forms via email to indicate their interest in participating in this study. Due to COVID-19, all interviews were conducted via teleconferencing (Zoom or Microsoft Teams) that lasted approximately 1 hour, which were transcribed, coded for themes, and grouped based on similar responses. Further, the participants were not privy to the interview questions beforehand, and demographic questions were asked at the end, including questions concerning age, education level, and job status. Each participant was assigned random numbers using an app called ‘The Random Number Generator ‘to ensure that all personal or identifying information of participants were removed. Regarding data storage, all documentation was stored on a password-protected external drive, inclusive of consent forms, recordings, transcripts, and researcher notes.

Keywords: diversity, positive psychology, organizational development, leadership

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Authors: Birgit A. A. Solem, Kristin Bentsen

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Scholarly attention in entrepreneurship is currently directed towards understanding entrepreneurial venture creation as a process -the journey of new economic activities from nonexistence to existence often studied through flow- or network models. To complement existing research on entrepreneurial venture creation with more interactivity-based research of organized activities, this study examines two pop-up stores as anchor events involving on-site activities of fifteen participating entrepreneurs launching their new ventures. The pop-up stores were arranged in two middle-sized Norwegian cities and contained different brand stores that brought together actors of sub-networks and communities executing venture creation activities. The pop-up stores became on-site arenas for the entrepreneurs to create, maintain, and rejuvenate their networks, at the same time as becoming venues for temporal coordination of activities involving existing and potential customers in their venture creation. In this work, we apply a conceptual framework based on frequently addressed dilemmas within entrepreneurship theory (discovery/creation, causation/effectuation) to further shed light on the broad aspect of on-site anchor event activities and their venture creation outcomes. The dilemma-based concepts are applied as an analytic toolkit to pursue answers regarding the nature of anchor event activities typically found within entrepreneurial venture creation and how these anchor event activities affect entrepreneurial venture creation outcomes. Our study combines researcher participation with 200 hours of observation and twenty in-depth interviews. Data analysis followed established guidelines for hermeneutic analysis and was intimately intertwined with ongoing data collection. Data was coded and categorized in NVivo 12 software, and iterated several times as patterns were steadily developing. Our findings suggest that core anchor event activities typically found within entrepreneurial venture creation are; a concept- and product experimentation with visitors, arrangements to socialize (evening specials, auctions, and exhibitions), store-in-store concepts, arranged meeting places for peers and close connection with municipality and property owners. Further, this work points to four main entrepreneurial venture creation outcomes derived from the core anchor event activities; (1) venture attention, (2) venture idea-realization, (3) venture collaboration, and (4) venture extension. Our findings show that, depending on which anchor event activities are applied, the outcomes vary. Theoretically, this study offers two main implications. First, anchor event activities are both discovered and created, following the logic of causation, at the same time as being experimental, based on “learning by doing” principles of effectuation during the execution. Second, our research enriches prior studies on venture creation as a process. In this work, entrepreneurial venture creation activities and outcomes are understood through pop-up stores as on-site anchor event arenas, particularly suitable for interactivity-based research requested by the entrepreneurship field. This study also reveals important managerial implications, such as that entrepreneurs should allow themselves to find creative physical venture creation arenas (e.g., pop-up stores, showrooms), as well as collaborate with partners when discovering and creating concepts and activities based on new ideas. In this way, they allow themselves to both strategically plan for- and continually experiment with their venture.

Keywords: anchor event, interactivity-based research, pop-up store, entrepreneurial venture creation

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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: Tsitsi Nyukurayi Muparari, Walter Timo De Vries, Jaap Zevenbergen

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The nature of Land administration accommodates diversity in terms of both spatial data handling activities and the expertise involved, which supposedly aims to satisfy the unpredictable demands of land data and the diverse demands of the customers arising from the land. However, it is known that strategic decisions of restructuring are in most cases repelled in favour of complex structures that strive to accommodate professional diversity and diverse roles in the field of Land administration. Yet despite of this widely accepted knowledge, there is scanty theoretical knowledge concerning the psychological methodologies that can extract the deeper perceptions from the diverse spatial expertise in order to explain the invisible control arm of the polarised reception of the ideas of change. This paper evaluates Q methodology in the context of a cadastre and land registry merger (under one agency) using the Swedish cadastral system as a case study. Precisely, the aim of this paper is to evaluate the effectiveness of Q methodology towards modelling the diverse psychological perceptions of spatial professionals who are in a widely contested decision of merging the cadastre and land registry components of Land administration using the Swedish cadastral system as a case study. An empirical approach that is prescribed by Q methodology starts with the concourse development, followed by the design of statements and q sort instrument, selection of the participants, the q-sorting exercise, factor extraction by PQMethod and finally narrative development by logic of abduction. The paper uses 36 statements developed from a dominant competing value theory that stands out on its reliability and validity, purposively selects 19 participants to do the Qsorting exercise, proceeds with factor extraction from the diversity using varimax rotation and judgemental rotation provided by PQMethod and effect the narrative construction using the logic abduction. The findings from the diverse perceptions from cadastral professionals in the merger decision of land registry and cadastre components in Sweden’s mapping agency (Lantmäteriet) shows that focus is rather inclined on the perfection of the relationship between the legal expertise and technical spatial expertise. There is much emphasis on tradition, loyalty and communication attributes which concern the organisation’s internal environment rather than innovation and market attributes that reveals customer behavior and needs arising from the changing humankind-land needs. It can be concluded that Q methodology offers effective tools that pursues a psychological approach for the evaluation and gradations of the decisions of strategic change through extracting the local perceptions of spatial expertise.

Keywords: cadastre, factor extraction, land administration merger, land registry, q-methodology, rotation

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Authors: Vesa Salminen, Esa Santakallio, Heikki Ruohomaa

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Introduction: The city of Riihimäki has decided robotics on well-being, service and industry as the main focus area on their ecosystem strategy. Robotics is going to be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, also education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The objective of this activity has been to develop education continuity from diaper age to doctorate. The main target of the development activity is to create a unique robotics study entity that enables ongoing robotics studies from preprimary education to university. The aim is also to attract students internationally and supply a skilled workforce to the private sector, capable of the challenges of the future. Methodology: Education instances (high school, second grade, Universities on all levels) in a large area of Tavastia Province have gradually directed their education programs to support this goal. On the other hand, applied research projects have been created to make proof of concept- phases on areal real environment field labs to test technology opportunities and digitalization to change business processes by applying robotic solutions. Customer-oriented applied research projects offer for students in robotics education learning environments to learn new knowledge and content. That is also a learning environment for education programs to adapt and co-evolution. New content and problem-based learning are used in future education modules. Major findings: Joint robotics education entity is being developed in cooperation with the city of Riihimäki (primary education), Syria Education (secondary education) and HAMK (bachelor and master education). The education modules have been developed to enable smooth transitioning from one institute to another. This article is introduced a case study of the change of education of wellbeing education because of digitalization and robotics. Riihimäki's Elderly citizen's service house, Riihikoti, has been working as a field lab for proof-of-concept phases on testing technology opportunities. According to successful case studies also education programs on various levels of education have been changing. Riihikoti has been developed as a physical learning environment for home care and robotics, investigating and developing a variety of digital devices and service opportunities and experimenting and learn the use of equipment. The environment enables the co-development of digital service capabilities in the authentic environment for all interested groups in transdisciplinary cooperation.

Keywords: ecosystem strategy, digitalization and robotics, education continuity, learning environment, transdisciplinary co-operation

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Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: Ved Vrat Verma, Rani Gupta, Manisha Goel

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γ-glutamyltranspeptidase (GGT: EC 2.3.2.2) is an N-terminal nucleophile hydrolase conserved in all three domains of life. GGT plays a key role in glutathione metabolism where it catalyzes the breakage of the γ-glutamyl bonds and transfer of γ-glutamyl group to water (hydrolytic activity) or amino acids or short peptides (transpeptidase activity). GGTs from bacteria, archaea, and eukaryotes (human, rat and mouse) are homologous proteins sharing >50% sequence similarity and conserved four layered αββα sandwich like three dimensional structural fold. These proteins though similar in their structure to each other, are quite diverse in their enzyme activity: some GGTs are better at hydrolysis reactions but poor in transpeptidase activity, whereas many others may show opposite behaviour. GGT is known to be involved in various diseases like asthma, parkinson, arthritis, and gastric cancer. Its inhibition prior to chemotherapy treatments has been shown to sensitize tumours to the treatment. Microbial GGT is known to be a virulence factor too, important for the colonization of bacteria in host. However, all known inhibitors (mimics of its native substrate, glutamate) are highly toxic because they interfere with other enzyme pathways. However, a few successful efforts have been reported previously in designing species specific inhibitors. We aim to leverage the diversity seen in GGT family (pathogen vs. eukaryotes) for designing specific inhibitors. Thus, in the present study, we have used DIVERGE software to identify sites in GGT proteins, which are crucial for the functional and structural divergence of these proteins. Since, type II divergence sites vary in clade specific manner, so type II divergent sites were our focus of interest throughout the study. Type II divergent sites were identified for pathogen vs. eukaryotes clusters and sites were marked on clade specific representative structures HpGGT (2QM6) and HmGGT (4ZCG) of pathogen and eukaryotes clade respectively. The crucial divergent sites within 15 A radii of the binding cavity were highlighted, and in-silico mutations were performed on these sites to delineate the role of these sites on the mechanism of catalysis and protein folding. Further, the amino acid network (AAN) analysis was also performed by Cytoscape to delineate assortative mixing for cavity divergent sites which could strengthen our hypothesis. Additionally, molecular dynamics simulations were performed for wild complexes and mutant complexes close to physiological conditions (pH 7.0, 0.1 M ionic strength and 1 atm pressure) and the role of putative divergence sites and structural integrities of the homologous proteins have been analysed. The dynamics data were scrutinized in terms of RMSD, RMSF, non-native H-bonds and salt bridges. The RMSD, RMSF fluctuations of proteins complexes are compared, and the changes at protein ligand binding sites were highlighted. The outcomes of our study highlighted some crucial divergent sites which could be used for novel inhibitors designing in a species-specific manner. Since, for drug development, it is challenging to design novel drug by targeting similar protein which exists in eukaryotes, so this study could set up an initial platform to overcome this challenge and help to deduce the more effective targets for novel drug discovery.

Keywords: γ-glutamyltranspeptidase, divergence, species-specific, drug design

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Authors: Thomas J. Bell III

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This paper explores the value of assimilating certification training within a traditional course curriculum. This innovative approach is believed to increase stakeholder value within the Computer Information System program at Texas Wesleyan University. Stakeholder value is obtained from increased job marketability and critical thinking skills that create employment-ready graduates. This paper views value as first developing the capability to earn an industry-recognized certification, which provides the student with more job placement compatibility while allowing the use of critical thinking skills in a liberal arts business program. Graduates with industry-based credentials are often given preference in the hiring process, particularly in the information technology sector. And without a pioneering curriculum that better prepares students for an ever-changing employment market, its educational value is dubiously questioned. Since certifications are trending in the hiring process, academic programs should explore the viability of incorporating certification training into teaching pedagogy and courses curriculum. This study will examine the use of the balanced scorecard across four performance dimensions (financial, customer, internal process, and innovation) to measure the stakeholder value of certification training within a traditional course curriculum. The balanced scorecard as a strategic management tool may provide insight for leveraging resource prioritization and decisions needed to achieve various curriculum objectives and long-term value while meeting multiple stakeholders' needs, such as students, universities, faculty, and administrators. The research methodology will consist of quantitative analysis that includes (1) surveying over one-hundred students in the CIS program to learn what factor(s) contributed to their certification exam success or failure, (2) interviewing representatives from the Texas Workforce Commission to identify the employment needs and trends in the North Texas (Dallas/Fort Worth) area, (3) reviewing notable Workforce Innovation and Opportunity Act publications on training trends across several local business sectors, and (4) analyzing control variables to identify specific correlations between industry alignment and job placement to determine if a correlation exists. These findings may provide helpful insight into impactful pedagogical teaching techniques and curriculum that positively contribute to certification credentialing success. And should these industry-certified students land industry-related jobs that correlate with their certification credential value, arguably, stakeholder value has been realized.

Keywords: certification exam teaching pedagogy, exam preparation, testing techniques, exam study tips, passing certification exams, embedding industry certification and curriculum alignment, balanced scorecard performance evaluation

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Authors: Kumalbeo Paul Kamani

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Marketing plays a very important role in the success of any firm since it represents the means through which a firm can reach its customers and also promotes its products and services. In fact, marketing aids the firm in identifying customers who the business can competitively serve, and tailoring product offerings, prices, distribution, promotional efforts, and services towards those customers. Unfortunately, in many firms, marketing has been reduced to merely advertisement. For effective marketing, firms must go beyond this often-limited function of advertisement. In the fashion industry in particular, marketing faces challenges due to its peculiar characteristics. Previous research for instance affirms the idiosyncrasy and peculiarities that differentiate the fashion industry from other industrial areas. It has been documented that the fashion industry is characterized seasonal intensity, short product life cycles, the difficulty of competitive differentiation, and long time for companies to reach financial stability. These factors are noted to pose obstacles to the fashion entrepreneur’s endeavours and can be the reasons that explain their low survival rates. In recent times, the fashion industry has been described as a market that is accessible market, has low entry barriers, both in terms of needed capital and skills which have all accounted for the burgeoning nature of startups. Yet as already stated, marketing is particularly challenging in the industry. In particular, areas such as marketing, branding, growth, project planning, financial and relationship management might represent challenges for the fashion entrepreneur but that have not been properly addressed by previous research. It is therefore important to assess marketing strategies of fashion firms and the factors influencing their success. This study generally sought to examine marketing strategies of fashion dealers in Ghana and their critical success factors. The study employed the quantitative survey research approach. A total of 120 fashion dealers were sampled. Questionnaires were used as instrument of data collection. Data collected was analysed using quantitative techniques including descriptive statistics and Relative Importance Index. The study revealed that the marketing strategies used by fashion apparels are text messages using mobile phones, referrals, social media marketing, and direct marketing. Results again show that the factors influencing fashion marketing effectiveness are strategic management, marketing mix (product, price, promotion etc), branding and business development. Policy implications are finally outlined. The study recommends among others that there is a need for the top management executive to craft and adopt marketing strategies that enable that are compatible with the fashion trends and the needs of the customers. This will improve customer satisfaction and hence boost market penetration. The study further recommends that the fashion industry in Ghana should seek to ensure that fashion apparels accommodate the diversity and the cultural setting of different customers to meet their unique needs.

Keywords: marketing, fashion, industry, success factors

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Chin-Chia Jane

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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

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Authors: Mao Zhaofang, Xu Yida, Fang Kan, Fu Enyuan, Zhao Zhao

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Nowadays, last-mile distribution plays an increasingly important role in the whole industrial chain delivery link and accounts for a large proportion of the whole distribution process cost. Promoting the upgrading of logistics networks and improving the layout of final distribution points has become one of the trends in the development of modern logistics. Due to the discrete and heterogeneous needs and spatial distribution of customer demand, which will lead to a higher delivery failure rate and lower vehicle utilization, last-mile delivery has become a time-consuming and uncertain process. As a result, courier companies have introduced a range of innovative parcel storage facilities, including pick-up points and lockers. The introduction of pick-up points and lockers has not only improved the users’ experience but has also helped logistics and courier companies achieve large-scale economy. Against the backdrop of the COVID-19 of the previous period, contactless delivery has become a new hotspot, which has also created new opportunities for the development of collection services. Therefore, a key issue for logistics companies is how to design/redesign their last-mile distribution network systems to create integrated logistics and distribution networks that consider pick-up points and lockers. This paper focuses on the introduction of self-pickup facilities in new logistics and distribution scenarios and the heterogeneous demands of customers. In this paper, we consider two types of demand, including ordinary products and refrigerated products, as well as corresponding transportation vehicles. We consider the constraints associated with self-pickup points and lockers and then address the location-routing problem with self-pickup facilities and heterogeneous demands (LRP-PFHD). To solve this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to minimize the total cost, which includes the facility opening cost, the variable transport cost, and the fixed transport cost. Due to the NP-hardness of the problem, we propose a hybrid adaptive large-neighbourhood search algorithm to solve LRP-PFHD. We evaluate the effectiveness and efficiency of the proposed algorithm by using instances generated based on benchmark instances. The results demonstrate that the hybrid adaptive large neighbourhood search algorithm is more efficient than MILP solvers such as Gurobi for LRP-PFHD, especially for large-scale instances. In addition, we made a comprehensive analysis of some important parameters (e.g., facility opening cost and transportation cost) to explore their impacts on the results and suggested helpful managerial insights for courier companies.

Keywords: city logistics, last-mile delivery, location-routing, adaptive large neighborhood search

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Authors: Majed Al Otaibi, Melissa Lessard-Beaudoin, Amel Loudghi, Raphael Chouinard-Watkins, Melanie Plourde, Frederic Calon, C. Alexandre Castellano, Stephen Cunnane, Helene Payette, Pierrette Gaudreau, Denis Gris, Rona K. Graham

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Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD.

Keywords: Alzheimer's disease, APOE4, cognition, caspase, brain atrophy, neurodegenerative, olfactory dysfunction

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Authors: Bianca Peterson, Tomasz J. Sańko, Carlos C. Bezuidenhout, Johnnie Van Den Berg

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Busseola fusca (Fuller) (Lepidoptera: Noctuidae), the maize stem borer, is a major pest in sub-Saharan Africa. It causes economic damage to maize and sorghum crops and has evolved non-recessive resistance to genetically modified (GM) maize expressing the Cry1Ab insecticidal toxin. Since B. fusca is a non-model organism, very little genomic information is publicly available, and is limited to some cytochrome c oxidase I, cytochrome b, and microsatellite data. The biology of B. fusca is well-described, but still poorly understood. This, in combination with its larval-specific behavior, may pose problems for limiting the spread of current resistant B. fusca populations or preventing resistance evolution in other susceptible populations. As part of on-going research into resistance evolution, B. fusca larvae were collected from Bt and non-Bt maize in South Africa, followed by RNA isolation (15 specimens) and sequencing on the Illumina HiSeq 2500 platform. Quality of reads was assessed with FastQC, after which Trimmomatic was used to trim adapters and remove low quality, short reads. Trinity was used for the de novo assembly, whereas TransRate was used for assembly quality assessment. Transcript identification employed BLAST (BLASTn, BLASTp, and tBLASTx comparisons), for which two libraries (nucleotide and protein) were created from 3.27 million lepidopteran sequences. Several transcripts that have previously been implicated in Cry toxin resistance was identified for B. fusca. These included aminopeptidase N, cadherin, alkaline phosphatase, ATP-binding cassette transporter proteins, and mitogen-activated protein kinase. MEGA7 was used to align these transcripts to reference sequences from Lepidoptera to detect mutations that might potentially be contributing to Cry toxin resistance in this pest. RSEM and Bioconductor were used to perform differential gene expression analysis on groups of B. fusca larvae challenged and unchallenged with the Cry1Ab toxin. Pairwise expression comparisons of transcripts that were at least 16-fold expressed at a false-discovery corrected statistical significance (p) ≤ 0.001 were extracted and visualized in a hierarchically clustered heatmap using R. A total of 329,194 transcripts with an N50 of 1,019 bp were generated from the over 167.5 million high-quality paired-end reads. Furthermore, 110 transcripts were over 10 kbp long, of which the largest one was 29,395 bp. BLAST comparisons resulted in identification of 157,099 (47.72%) transcripts, among which only 3,718 (2.37%) were identified as Cry toxin receptors from lepidopteran insects. According to transcript expression profiles, transcripts were grouped into three subclusters according to the similarity of their expression patterns. Several immune-related transcripts (pathogen recognition receptors, antimicrobial peptides, and inhibitors) were up-regulated in the larvae feeding on Bt maize, indicating an enhanced immune status in response to toxin exposure. Above all, extremely up-regulated arylphorin genes suggest that enhanced epithelial healing is one of the resistance mechanisms employed by B. fusca larvae against the Cry1Ab toxin. This study is the first to provide a resource base and some insights into a potential mechanism of Cry1Ab toxin resistance in B. fusca. Transcriptomic data generated in this study allows identification of genes that can be targeted by biotechnological improvements of GM crops.

Keywords: epithelial healing, Lepidoptera, resistance, transcriptome

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Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Kevin Tinkham, Ella Quigley

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Structural integrity for cladding products is a key performance parameter, especially concerning fire performance. Cladding products such as PIR-based sandwich panels are tested rigorously, in line with industrial standards. Physical fire tests are necessary to ensure the customer's safety but can give little information about critical behaviours that can help develop new materials. Numerical modelling is a tool that can help investigate a fire's behaviour further by replicating the fire test. However, fire is an interdisciplinary problem as it is a chemical reaction that behaves fluidly and impacts structural integrity. An analysis using Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is needed to capture all aspects of a fire performance test. One method is a two-way coupling analysis that imports the updated changes in thermal data, due to the fire's behaviour, to the FEA solver in a series of iterations. In light of our recent work with Tata Steel U.K using a two-way coupling methodology to determine the fire performance, it has been shown that a program called FDS-2-Abaqus can make predictions of a BS 476 -22 furnace test with a degree of accuracy. The test demonstrated the fire performance of Tata Steel U.K Trisomet product, a Polyisocyanurate (PIR) based sandwich panel used for cladding. Previous works demonstrated the limitations of the current version of the program, the main limitation being the computational cost of modelling three Trisomet panels, totalling an area of 9 . The computational cost increases substantially, with the intention to scale up to an LPS 1181-1 test, which includes a total panel surface area of 200 .The FDS-2-Abaqus program is developed further within this paper to overcome this obstacle and better accommodate Tata Steel U.K PIR sandwich panels. The new developments aim to reduce the computational cost and error margin compared to experimental data. One avenue explored is a multi-scale approach in the form of Reduced Order Modeling (ROM). The approach allows the user to include refined details of the sandwich panels, such as the overlapping joints, without a computationally costly mesh size.Comparative studies will be made between the new implementations and the previous study completed using the original FDS-2-ABAQUS program. Validation of the study will come from physical experiments in line with governing body standards such as BS 476 -22 and LPS 1181-1. The physical experimental data includes the panels' gas and surface temperatures and mechanical deformation. Conclusions are drawn, noting the new implementations' impact factors and discussing the reasonability for scaling up further to a whole warehouse.

Keywords: fire testing, numerical coupling, sandwich panels, thermo fluids

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Authors: Vincent Oghenekevbe Olughor, Olusoji Mayowa Ige

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Except for a preexisting liver disease and malnutrition, there are no predilections for low serum albumin (SA) levels in humans. At normal reference levels (4.0-6.0g/dl) SA is a universal marker for mortality and morbidity risks assessments where depletion by 1.0g/dl increases mortality risk by 137% and morbidity by 89%.It has 40 known functions contributing significantly to the sustenance of human life. A depletion in SA to <2.2g/dl, in most clinical settings worldwide, leads to loss of oncotic pressure of blood causing clinical manifestations of bipedal Oedema, in which the patients remain conscious. SA also contributes significantly to buffering of blood to a life-sustaining pH of 7.35-7.45. A drop in blood pH to <6.9 will lead to instant coma and death, which can occur after SA continues to deplete after manifestations of bipedal Oedema. In an intervention study conducted in 2014 following the discovery that “SA is depleted during malaria fever”, a Nutraceutical formulated for use as treatment adjunct to prevent SA depletions during malaria to <2.4g/dl after Efficacy testing was found to be satisfactory. There are five known types of Malaria caused by Apicomplexan parasites, Plasmodium: the most lethal being that caused by Plasmodium falciparum causing malignant tertian malaria, in which the fever was occurring every 48 hours coincides with the dumping of malaria-toxins (Hemozoin) into blood, causing contamination: blood must remain sterile. Other Apicomplexan parasites, Toxoplasma and Cryptosporidium, are opportunistic infections of HIV. Separate studies showed SA depletions in MDRTB (multidrug resistant TB), and MDRTB-HIV patients by the same mechanism discovered with malaria and such depletions will be further complicated whenever Apicomplexan parasitic infections co-exist. Both Apicomplexan parasites and the TB parasite belong to the Obligate-group of Parasites, which are parasites that replicate only inside its host; and most of them have capacities to over-consume host nutrients during parasitaemia. In MDRTB patients the body attempts repeatedly to prevent depletions in SA to critical levels in the presence of adequate nutrients and only for a while in MDRTB-HIV patients. These groups of patients will, therefore, benefit from the already tested Nutraceutical in malaria patients. The Nutraceutical bio-Powder was formulated (to BP 1988 specification) from twelve nature-based food-grade nutrients containing all dedicated nutrients for ensuring improved synthesis of Albumin by the liver. The Nutraceutical was administered daily for 38±2days in 23 children, in a prospective phase-2 clinical trial, and its impact on body weight and core blood parameters were documented at the start and end of efficacy testing period. Sixteen children who did not experience malaria-induced depletions of SA had significant SA increase; seven children who experienced malaria-induced depletions of SA had insignificant SA decrease. The Packed Cell Volume Percentage (PCV %), a measure of the Oxygen carrying capacity of blood and the amount of nutrients the body can absorb, increased in both groups. The total serum proteins (SA+ Globulins) increased or decreased within the continuum of normal. In conclusion, MDRTB and MDRTB-HIV patients will benefit from a variant of this Nutraceutical when used as treatment adjunct.

Keywords: antitrypsin-free Nutraceutical, apicomplexan parasites, no predilections for low serum albumin, toxoplasmosis

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Authors: Darko Prebežac, Josip Mikulić, Maja Šerić, Damir Krešić

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Camping tourism is recognized as a growing segment of the broader tourism industry, currently evolving from an inexpensive, temporary sojourn in a rural environment into a highly fragmented niche tourism sector. The trends among public-managed campgrounds seem to be moving away from rustic campgrounds that provide only a tent pad and a fire ring to more developed facilities that offer a range of different amenities, where campers still search for unique experiences that go above the opportunity to experience nature and social interaction. In addition, while camping styles and options changed significantly over the last years, coastal camping in particular became valorized as is it regarded with a heightened sense of nostalgia. Alongside this growing interest in the camping tourism, a demand for quality servicing infrastructure emerged in order to satisfy the wide variety of needs, wants, and expectations of an increasingly demanding traveling public. However, camping activity in general and quality of camping experience and campers’ satisfaction in particular remain an under-researched area of the tourism and consumption behavior literature. In this line, very few studies addressed the issue of quality product/service provision in satisfying nature based tourists and in driving their future behavior with respect to potential re-visitation and recommendation intention. The present study thus aims to investigate the drivers of positive and negative campsite experience using the case of Croatia. Due to the well-preserved nature and indented coastline, camping tourism has a long tradition in Croatia and represents one of the most important and most developed tourism products. During the last decade the number of tourist overnights in Croatian camps has increased by 26% amounting to 16.5 million in 2014. Moreover, according to Eurostat the market share of campsites in the EU is around 14%, indicating that the market share of Croatian campsites is almost double large compared to the EU average. Currently, there are a total of 250 camps in Croatia with approximately 75.8 thousands accommodation units. It is further noteworthy that Croatian camps have higher average occupancy rates and a higher average length of stay as compared to the national average of all types of accommodation. In order to explore the main drivers of positive and negative campsite experiences, this study uses principal components analysis (PCA) and an impact-asymmetry analysis (IAA). Using the PCA, first the main dimensions of the campsite experience are extracted in an exploratory manner. Using the IAA, the extracted factors are investigated for their potentials to create customer delight and/or frustration. The results provide valuable insight to both researchers and practitioners regarding the understanding of campsite satisfaction.

Keywords: Camping tourism, campsite, impact-asymmetry analysis, satisfaction

Procedia PDF Downloads 187

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 63

Authors: M. Arun, A. Kannan

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Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.

Keywords: acid orange 10, activated carbon, optimum adsorption conditions, statistical design

Procedia PDF Downloads 171

Authors: Christiane Paulus

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Post-Islamism assumes that the Quran should not be viewed in terms of what Lyotard identifies as a ‘meta-narrative'. However, its socio-ethical content can be viewed as critical of power discourse (Foucault). Practicing religion seems to be limited to rites and individual spirituality, taqwa. Alternatively, can we build on Muhammad Abduh's classic-modern reform and develop it through a postmodernist frame? This is the main question of this study. Through his general and vague remarks on the context of the Quran, Abduh was the first to refer to the historical and cultural distance of the text as an obstacle for interpretation. His application, however, corresponded to the modern absolute idea of authentic sharia. He was followed by Amin al-Khuli, who hermeneutically linked the content of the Quran to the theory of evolution. Fazlur Rahman and Nasr Hamid abu Zeid remain reluctant to go beyond the general level in terms of context. The hermeneutic circle, therefore, persists in challenging, how to get out to overcome one’s own assumptions. The insight into and the acceptance of the lasting ambivalence of understanding can be grasped as a postmodern approach; it is documented in Derrida's discovery of the shift in text meanings, difference, also in Lyotard's theory of différend. The resulting mixture of meanings (Wolfgang Welsch) can be read together with the classic ambiguity of the premodern interpreters of the Quran (Thomas Bauer). Confronting hermeneutic difficulties in general, Niklas Luhmann proves every description an attribution, tautology, i.e., remaining in the circle. ‘De-tautologization’ is possible, namely by analyzing the distinctions in the sense of objective, temporal and social information that every text contains. This could be expanded with the Kantian aesthetic dimension of reason (critique of pure judgment) corresponding to the iʽgaz of the Coran. Luhmann asks, ‘What distinction does the observer/author make?’ Quran as a speech from God to the first listeners could be seen as a discourse responding to the problems of everyday life of that time, which can be viewed as the general goal of the entire Qoran. Through reconstructing koranic Lifeworlds (Alfred Schütz) in detail, the social structure crystallizes the socio-economic differences, the enormous poverty. The koranic instruction to provide the basic needs for the neglected groups, which often intersect (old, poor, slaves, women, children), can be seen immediately in the text. First, the references to lifeworlds/social problems and discourses in longer koranic passages should be hypothesized. Subsequently, information from the classic commentaries could be extracted, the classical Tafseer, in particular, contains rich narrative material for reconstructing. By selecting and assigning suitable, specific context information, the meaning of the description becomes condensed (Clifford Geertz). In this manner, the text gets necessarily an alienation and is newly accessible. The socio-ethical implications can thus be grasped from the difference of the original problem and the revealed/improved order/procedure; this small step can be materialized as such, not as an absolute solution but as offering plausible patterns for today’s challenges as the Agenda 2030.

Keywords: postmodern hermeneutics, condensed description, sociological approach, small steps of reform

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Hideaki Endo, Mika Goto

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The global outbreak of the COVID-19 pandemic has seriously affected railway businesses. The number of railway passengers decreased due to the decline in the number of commuters and business travelers to avoid crowded trains and a sharp drop in inbound tourists visiting Japan. This has affected not only railway businesses but also related businesses, including hotels, leisure businesses, and retail businesses at station buildings. In 2021, the companies were divided into profitable and loss-making companies. This division suggests that railway companies, particularly loss-making companies, needed to decrease operational inefficiency. To measure the impact of COVID-19 and discuss the sustainable management strategies of railway companies, we examine the cost inefficiency of Japanese listed railway companies by applying stochastic frontier analysis (SFA) to their operational and financial data. First, we employ the stochastic frontier cost function approach to measure inefficiency. The cost frontier function is formulated as a Cobb–Douglas type, and we estimated parameters and variables for inefficiency. This study uses panel data comprising 26 Japanese-listed railway companies from 2005 to 2020. This period includes several events deteriorating the business environment, such as the financial crisis from 2007 to 2008 and the Great East Japan Earthquake of 2011, and we compare those impacts with those of the COVID-19 pandemic after 2020. Second, we identify the characteristics of the best-practice railway companies and examine the drivers of cost inefficiencies. Third, we analyze the factors influencing cost inefficiency by comparing the profiles of the top 10 railway companies and others before and during the pandemic. Finally, we examine the relationship between cost inefficiency and the implementation of efficiency measures for each railway company. We obtained the following four findings. First, most Japanese railway companies showed the lowest cost inefficiency (most efficient) in 2014 and the highest in 2020 (least efficient) during the COVID-19 pandemic. The second worst occurred in 2009 when it was affected by the financial crisis. However, we did not observe a significant impact of the 2011 Great East Japan Earthquake. This is because no railway company was influenced by the earthquake in this operating area, except for JR-EAST. Second, the best-practice railway companies are KEIO and TOKYU. The main reason for their good performance is that both operate in and near the Tokyo metropolitan area, which is densely populated. Third, we found that non-best-practice companies had a larger decrease in passenger kilometers than best-practice companies. This indicates that passengers made fewer long-distance trips because they refrained from inter-prefectural travel during the pandemic. Finally, we found that companies that implement more efficiency improvement measures had higher cost efficiency and they effectively used their customer databases through proactive DX investments in marketing and asset management.

Keywords: COVID-19 pandemic, stochastic frontier analysis, railway sector, cost efficiency

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Authors: Tamar Lin, Nufar Buchshtab, Yifat Elharar, Julian Nicenboim, Rotem Edgar, Iddo Weiner, Lior Zelcbuch, Ariel Cohen, Sharon Kredo-Russo, Inbar Gahali-Sass, Naomi Zak, Sailaja Puttagunta, Merav Bassan

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Background: Atopic dermatitis (AD) is a chronic, relapsing inflammatory skin disorder that is characterized by dry skin and flares of eczematous lesions and intense pruritus. Multiple lines of evidence suggest that AD is associated with increased colonization by Staphylococcus aureus, which contributes to disease pathogenesis through the release of virulence factors that affect both keratinocytes and immune cells, leading to disruption of the skin barrier and immune cell dysfunction. The aim of the current study is to develop a bacteriophage-based product that specifically targets S. aureus. Methods: For the discovery of phage, environmental samples were screened on 118 S. aureus strains isolated from skin samples, followed by multiple enrichment steps. Natural phages were isolated, subjected to Next-generation Sequencing (NGS), and analyzed using proprietary bioinformatics tools for undesirable genes (toxins, antibiotic resistance genes, lysogeny potential), taxonomic classification, and purity. Phage host range was determined by an efficiency of plating (EOP) value above 0.1 and the ability of the cocktail to completely lyse liquid bacterial culture under different growth conditions (e.g., temperature, bacterial stage). Results: Sequencing analysis demonstrated that the 118 S. aureus clinical strains were distributed across the phylogenetic tree of all available Refseq S. aureus (~10,750 strains). Screening environmental samples on the S. aureus isolates resulted in the isolation of 50 lytic phages from different genera, including Silviavirus, Kayvirus, Podoviridae, and a novel unidentified phage. NGS sequencing confirmed the absence of toxic elements in the phages’ genomes. The host range of the individual phages, as measured by the efficiency of plating (EOP), ranged between 41% (48/118) to 79% (93/118). Host range studies in liquid culture revealed that a subset of the phages can infect a broad range of S. aureus strains in different metabolic states, including stationary state. Combining the single-phage EOP results of selected phages resulted in a broad host range cocktail which infected 92% (109/118) of the strains. When tested in vitro in a liquid infection assay, clearance was achieved in 87% (103/118) of the strains, with no evidence of phage resistance throughout the study (24 hours). A S. aureus host was identified that can be used for the production of all the phages in the cocktail at high titers suitable for large-scale manufacturing. This host was validated for the absence of contaminating prophages using advanced NGS methods combined with multiple production cycles. The phages are produced under optimized scale-up conditions and are being used for the development of a topical formulation (BX005) that may be administered to subjects with atopic dermatitis. Conclusions: A cocktail of natural phages targeting S. aureus was effective in reducing bacterial burden across multiple assays. Phage products may offer safe and effective steroid-sparing options for atopic dermatitis.

Keywords: atopic dermatitis, bacteriophage cocktail, host range, Staphylococcus aureus

Procedia PDF Downloads 155

Authors: Sedef Sert, Paola Garrone, Marco Melacini, Alessandro Perego

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This paper is aimed at enhancing our current understanding of motivations behind corporate in-kind donations and to find out whether economic efficiency may be a major driver. Our empirical setting is consisted of surplus food recovery and donation by companies from food supply chain. This choice of empirical setting is motivated by growing attention on the paradox of food insecurity and food waste i.e. a total of 842 million people worldwide were estimated to be suffering from regularly not getting enough food, while approximately 1.3 billion tons per year food is wasted globally. Recently, many authors have started considering surplus food donation to nonprofit organizations as a way to cope with social issue of food insecurity and environmental issue of food waste. In corporate philanthropy literature the motivations behind the corporate donations for social purposes, such as altruistic motivations, enhancements to employee morale, the organization’s image, supplier/customer relationships, local community support, have been examined. However, the relationship with economic efficiency is not studied and in many cases the pure economic efficiency as a decision making factor is neglected. Although in literature there are some studies give us the clue on economic value creation of surplus food donation such as saving landfill fees or getting tax deductions, so far there is no study focusing deeply on this phenomenon. In this paper, we develop a conceptual framework which explores the economic barriers and drivers towards alternative surplus food management options i.e. discounts, secondary markets, feeding animals, composting, energy recovery, disposal. The case study methodology is used to conduct the research. Protocols for semi structured interviews are prepared based on an extensive literature review and adapted after expert opinions. The interviews are conducted mostly with the supply chain and logistics managers of 20 companies in food sector operating in Italy, in particular in Lombardy region. The results shows that in current situation, the food manufacturing companies can experience cost saving by recovering and donating the surplus food with respect to other methods especially considering the disposal option. On the other hand, retail and food service sectors are not economically incentivized to recover and donate surplus food to disfavored population. The paper shows that not only strategic and moral motivations, but also economic motivations play an important role in managerial decision making process in surplus food management. We also believe that our research while rooted in the surplus food management topic delivers some interesting implications to more general research on corporate in-kind donations. It also shows that there is a huge room for policy making favoring the recovery and donation of surplus products.

Keywords: corporate philanthropy, donation, recovery, surplus food

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Authors: Rachana Tank, Donald. M. Lyall, Kristin Flegal, Joey Ward, Jonathan Cavanagh

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Alzheimer’s research UK estimates by 2050, 2 million individuals will be living with Late Onset Alzheimer’s disease (LOAD). However, individuals experience considerable cognitive deficits and brain pathology over decades before reaching clinically diagnosable LOAD and studies have utilised gene candidate studies such as genome wide association studies (GWAS) and polygenic risk (PGR) scores to identify high risk individuals and potential pathways. This investigation aims to determine whether high genetic risk of LOAD is associated with worse brain MRI and cognitive performance in healthy older adults within the UK Biobank cohort. Previous studies investigating associations of PGR for LOAD and measures of MRI or cognitive functioning have focused on specific aspects of hippocampal structure, in relatively small sample sizes and with poor ‘controlling’ for confounders such as smoking. Both the sample size of this study and the discovery GWAS sample are bigger than previous studies to our knowledge. Genetic interaction between loci showing largest effects in GWAS have not been extensively studied and it is known that APOE e4 poses the largest genetic risk of LOAD with potential gene-gene and gene-environment interactions of e4, for this reason we  also analyse genetic interactions of PGR with the APOE e4 genotype. High genetic loading based on a polygenic risk score of 21 SNPs for LOAD is associated with worse brain MRI and cognitive outcomes in healthy individuals within the UK Biobank cohort. Summary statistics from Kunkle et al., GWAS meta-analyses (case: n=30,344, control: n=52,427) will be used to create polygenic risk scores based on 21 SNPs and analyses will be carried out in N=37,000 participants in the UK Biobank. This will be the largest study to date investigating PGR of LOAD in relation to MRI. MRI outcome measures include WM tracts, structural volumes. Cognitive function measures include reaction time, pairs matching, trail making, digit symbol substitution and prospective memory. Interaction of the APOE e4 alleles and PGR will be analysed by including APOE status as an interaction term coded as either 0, 1 or 2 e4 alleles. Models will be adjusted partially for adjusted for age, BMI, sex, genotyping chip, smoking, depression and social deprivation. Preliminary results suggest PGR score for LOAD is associated with decreased hippocampal volumes including hippocampal body (standardised beta = -0.04, P = 0.022) and tail (standardised beta = -0.037, P = 0.030), but not with hippocampal head. There were also associations of genetic risk with decreased cognitive performance including fluid intelligence (standardised beta = -0.08, P<0.01) and reaction time (standardised beta = 2.04, P<0.01). No genetic interactions were found between APOE e4 dose and PGR score for MRI or cognitive measures. The generalisability of these results is limited by selection bias within the UK Biobank as participants are less likely to be obese, smoke, be socioeconomically deprived and have fewer self-reported health conditions when compared to the general population. Lack of a unified approach or standardised method for calculating genetic risk scores may also be a limitation of these analyses. Further discussion and results are pending.

Keywords: Alzheimer's dementia, cognition, polygenic risk, MRI

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Authors: Rabindranath Bag, Surjeet Singh

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Materials in which the electrons are strongly correlated provide some of the most challenging and exciting problems in condensed matter physics today. After the discovery of high critical temperature superconductivity in layered or two-dimensional copper oxides, many physicists got attention in cuprates and it led to an upsurge of interest in the synthesis and physical properties of copper-oxide based material. The quest to understand superconducting mechanism in high-temperature cuprates, drew physicist’s attention to somewhat simpler compounds consisting of spin-chains or one-dimensional lattice of coupled spins. Low-dimensional quantum magnets are of huge contemporary interest in basic sciences as well emerging technologies such as quantum computing and quantum information theory, and heat management in microelectronic devices. Spin ladder is an example of quasi one-dimensional quantum magnets which provides a bridge between one and two dimensional materials. One of the examples of quasi one-dimensional spin-ladder compounds is Sr14Cu24O41, which exhibits a lot of interesting and exciting physical phenomena in low dimensional systems. Very recently, the ladder compound Sr14Cu24O41 was shown to exhibit long-distance quantum entanglement crucial to quantum information theory. Also, it is well known that hole-compensation in this material results in very high (metal-like) anisotropic thermal conductivity at room temperature. These observations suggest that Sr14Cu24O41 is a potential multifunctional material which invites further detailed investigations. To investigate these properties one must needs a large and high quality of single crystal. But these systems are showing incongruently melting behavior, which brings many difficulties to grow a large and quality of single crystals. Hence, we are using TSFZ (Travelling Solvent Floating Zone) method to grow the high quality of single crystals of the low dimensional magnets. Apart from this, it has unique crystal structure (alternating stacks of plane containing edge-sharing CuO2 chains, and the plane containing two-leg Cu2O3 ladder with intermediate Sr layers along the b- axis), which is also incommensurate in nature. It exhibits abundant physical phenomenon such as spin dimerization, crystallization of charge holes and charge density wave. The maximum focus of research so far involved in introducing defects on A-site (Sr). However, apart from the A-site (Sr) doping, there are only few studies in which the B-site (Cu) doping of polycrystalline Sr14Cu24O41 have been discussed and the reason behind this is the possibility of two doping sites for Cu (CuO2 chain and Cu2O3 ladder). Therefore, in our present work, the crystals (pristine and Cu-site doped) were grown by using TSFZ method by tuning the growth parameters. The Laue diffraction images, optical polarized microscopy and Scanning Electron Microscopy (SEM) images confirm the quality of the grown crystals. Here, we report the single crystal growth, magnetic and transport properties of Sr14Cu24O41 and its lightly doped variants (magnetic and non-magnetic) containing less than 1% of Co, Ni, Al and Zn impurities. Since, any real system will have some amount of weak disorder, our studies on these ladder compounds with controlled dilute disorder would be significant in the present context.

Keywords: low-dimensional quantum magnets, single crystal, spin-ladder, TSFZ technique

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Authors: Stefan Fuchs

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Against the backdrop of the proliferation of shopping malls in Japan during the last two decades, this paper presents the results of an ethnography conducted at a recently built suburban shopping mall in Western Tokyo. Through the analysis of the lived experiences of local residents, mall customers and the mall management this paper evaluates the benefits and disadvantages of the Business Improvement District (BID) model, which was implemented as urban redevelopment strategy in the area surrounding the shopping mall. The results of this research project show that while the BID model has in some respects contributed to the economic prosperity and to the perceived convenience of the area, it has led to gentrification and the redevelopment shows some deficiencies with regard to the inclusion of the elderly population as well as to the democratization of the decision-making process within the area. In Japan, shopping malls have been steadily growing both in size and number since a series of deregulation policies was introduced in the year 2000 in an attempt to push the domestic economy and to rejuvenate urban landscapes. Shopping malls have thereby become defining spaces of the built environment and are arguably important places of social interaction. Notwithstanding the vital role they play as factors of urban transformation, they have been somewhat overlooked in the research on Japan; especially with respect to their meaning for people’s everyday lives. By examining the ways, people make use of space in a shopping mall the research project presented in this paper addresses this gap in the research. Moreover, the research site of this research project is one of the few BIDs of Japan and the results presented in this paper can give indication on the scope of the future applicability of this urban redevelopment model. The data presented in this research was collected during a nine-months ethnographic fieldwork in and around the shopping mall. This ethnography includes semi-structured interviews with ten key informants as well as direct and participant observations examining the lived experiences and perceptions of people living, shopping or working at the shopping mall. The analysis of the collected data focused on recurring themes aiming at ultimately capturing different perspectives on the same aspects. In this manner, the research project documents the social agency of different groups within one communal network. The analysis of the perceptions towards the urban redevelopment around the shopping mall has shown that mainly the mall customers and large businesses benefit from the BID redevelopment model. While local residents benefit to some extent from their neighbourhood becoming more convenient for shopping they perceive themselves as being disadvantaged by changing demographics due to rising living expenses, the general noise level and the prioritisation of a certain customer segment or age group at the shopping mall. Although the shopping mall examined in this research project is just an example, the findings suggest that in future urban redevelopment politics have to provide incentives for landowners and developing companies to think of other ways of transforming underdeveloped areas.

Keywords: business improvement district, ethnography, shopping mall, urban redevelopment

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Authors: Anatoliy A. Alabugin, Nikolay K. Topuzov, Sergei V. Aliukov

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It is well known, that while we do a quantitative evaluation of the quality control of some economic processes (in particular, resource saving) with help innovation factors, there are three groups of problems: high uncertainty of indicators of the quality management, their considerable ambiguity, and high costs to provide a large-scale research. These problems are defined by the use of contradictory objectives of enhancing of the quality control in accordance with innovation factors and preservation of economic stability of the enterprise. The most acutely, such factors are felt in the countries lagging behind developed economies of the world according to criteria of innovativeness and effectiveness of management of the resource saving. In our opinion, the following two methods for reconciling of the above-mentioned objectives and reducing of conflictness of the problems are to solve this task most effectively: 1) the use of paradigms and concepts of evolutionary improvement of quality of resource-saving management in the cycle "from the project of an innovative product (technology) - to its commercialization and update parameters of customer value"; 2) the application of the so-called integrative-cyclical approach which consistent with complexity and type of the concept, to studies allowing to get quantitative assessment of the stages of achieving of the consistency of these objectives (from baseline of imbalance, their compromise to achievement of positive synergies). For implementation, the following mathematical tools are included in the integrative-cyclical approach: index-factor analysis (to identify the most relevant factors); regression analysis of relationship between the quality control and the factors; the use of results of the analysis in the model of fuzzy sets (to adjust the feature space); method of non-parametric statistics (for a decision on the completion or repetition of the cycle in the approach in depending on the focus and the closeness of the connection of indicator ranks of disbalance of purposes). The repetition is performed after partial substitution of technical and technological factors ("hard") by management factors ("soft") in accordance with our proposed methodology. Testing of the proposed approach has shown that in comparison with the world practice there are opportunities to improve the quality of resource-saving management using innovation factors. We believe that the implementation of this promising research, to provide consistent management decisions for reducing the severity of the above-mentioned contradictions and increasing the validity of the choice of resource-development strategies in terms of parameters of quality management and sustainability of enterprise, is perspective. Our existing experience in the field of quality resource-saving management and the achieved level of scientific competence of the authors allow us to hope that the use of the integrative-cyclical approach to the study and evaluation of the resulting and factor indicators will help raise the level of resource-saving characteristics up to the value existing in the developed economies of post-industrial type.

Keywords: integrative-cyclical approach, quality control, evaluation, innovation factors. economic sustainability, innovation cycle of management, disbalance of goals of development

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