Search results for: rapid identification

Authors: Sidra Pervez, Afsheen Aman, Shah Ali Ul Qader

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The importance of attaining an optimum performance of an enzyme is often a question of devising an effective method for its immobilization. Cross-linked enzyme aggregate (CLEAs) is a new approach for immobilization of enzymes using carrier free strategy. This method is exquisitely simple (involving precipitation of the enzyme from aqueous buffer followed by cross-linking of the resulting physical aggregates of enzyme molecules) and amenable to rapid optimization. Among many industrial enzymes, amyloglucosidase is an important amylolytic enzyme that hydrolyzes alpha (1→4) and alpha (1→6) glycosidic bonds in starch molecule and produce glucose as a sole end product. Glucose liberated by amyloglucosidase can be used for the production of ethanol and glucose syrups. Besides this amyloglucosidase can be widely used in various food and pharmaceuticals industries. For production of amyloglucosidase on commercial scale, filamentous fungi of genera Aspergillus are mostly used because they secrete large amount of enzymes extracellularly. The current investigation was based on isolation and identification of filamentous fungi from genus Aspergillus for the production of amyloglucosidase in submerged fermentation and optimization of cultivation parameters for starch saccharification. Natural isolates were identified as Aspergillus niger KIBGE-IB36, Aspergillus fumigatus KIBGE-IB33, Aspergillus flavus KIBGE-IB34 and Aspergillus terreus KIBGE-IB35 on taxonomical basis and 18S rDNA analysis and their sequence were submitted to GenBank. Among them, Aspergillus fumigatus KIBGE-IB33 was selected on the basis of maximum enzyme production. After optimization of fermentation conditions enzyme was immobilized on CLEA. Different parameters were optimized for maximum immobilization of amyloglucosidase. Data of enzyme stability (thermal and Storage) and reusability suggested the applicability of immobilized amyloglucosidase for continuous saccharification of starch in industrial processes.

Keywords: aspergillus, immobilization, industrial processes, starch saccharification

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Authors: Samiyah Tasleem, Muhammad Abdul Haq, Syed Baqir Shyum Naqvi, Muhammad Abid Husnain, Sajjad Haider Naqvi

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The objective of the present study was: a) to investigate the antimicrobial activity of honey samples of different floral sources of Pakistan, b) to recover the phenolic acids in them as a possible contributing factor of antimicrobial activity. Six honey samples from different floral sources, namely: Trachysperm copticum, Acacia species, Helianthus annuus, Carissa opaca, Zizyphus and Magnifera indica were used. The antimicrobial activity was investigated by the disc diffusion method against eight freshly isolated clinical isolates (Staphylococci aureus, Staphylococci epidermidis, Streptococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumonia, Escherichia coli, Proteus vulgaris and Candida albicans). Antimicrobial activity of honey was compared with five commercial antibiotics, namely: doxycycline (DO-30ug/mL), oxytetracycline (OT-30ug/mL), clarithromycin (CLR–15ug/mL), moxifloxacin (MXF-5ug/mL) and nystatin (NT – 100 UT). The fractions responsible for antimicrobial activity were extracted using ethyl acetate. Solid phase extraction (SPE) was used to recover the phenolic acids of honey samples. Identification was carried out via High-Performance Liquid Chromatography (HPLC). The results indicated that antimicrobial activity was present in all honey samples and found comparable to the antibiotics used in the study. In the microbiological assay, the ethyl acetate honey extract was found to exhibit a very promising antimicrobial activity against all the microorganisms tested, indicating the existence of phenolic compounds. Six phenolic acids, namely: gallic, caffeic, ferulic, vanillic, benzoic and cinnamic acids were identified besides some unknown substance by HPLC. In conclusion, Pakistani honey samples showed a broad spectrum antibacterial and promising antifungal activity. Identification of six different phenolic acids showed that Pakistani honey samples are rich sources of phenolic compounds that could be the contributing factor of antimicrobial activity.

Keywords: Pakistani honey, antimicrobial activity, Phenolic acids eg.gallic, caffeic, ferulic, vanillic, benzoic and cinnamic acids

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Authors: Adjebli Ahmed, Messis Abdelaziz, Ayeche Riad, Tighilet Karim, Talbi Melissa, Smaili Yanis, Lehri Mokrane, Louardiane Mustapha

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Colorectal cancer is one of the most common types of cancer worldwide, and its incidence has been increasing in recent years. Data and fecal samples from colorectal cancer patients were collected at the Amizour Public Hospital's oncology department (Bejaia, Algeria). Microbiological and cohort study were conducted at the Biological Engineering of Cancers laboratory at the Faculty of Medicine of the University of Bejaia. All the data showed that patients aged between 50 and 70 years were the most affected by colorectal cancer, while the age categories of [30-40] and [40-50] were the least affected. Males were more likely to be at risk of contracting colorectal cancer than females. The most common types of colorectal cancer among the studied population were sigmoid cancer, rectal cancer, transverse colon cancer, and ascending colon cancer. The hereditary factor was found to be more dominant than other risk factors. Bacterial identification revealed the presence of certain pathogenic and opportunistic bacterial genera, such as E. coli, K. pneumoniae, Shigella sp, and Streptococcus group D. These results led us to conclude that dysbiosis of the intestinal microbiome is strongly present in colorectal cancer patients at the EPH of Amizour.

Keywords: microbiome, colorectal cancer, risk factors, bacterial identification

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Prince Suka Neekia Momta, Rita Iheoma Achonyeulo

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Ant Tracking seismic attribute applied over 4-seconds seismic volume revealed structural features triggered by clay diapirism, growth fault development, rapid deltaic sedimentation and intense drilling. The attribute was extracted on vertical seismic sections and time slices. Mega tectonic structures such as growth faults and clay diapirs are visible on vertical sections with obscured minor lineaments or fractures. Fractures are distinctively visible on time slices yielding recognizable patterns corroborating established geologic models. This model seismic attribute enabled the understanding of fluid flow characteristics and production responses. Three structural patterns recognized in the field include: major growth faults, minor faults or lineaments and network of fractures. Three growth faults mapped on seismic section form major deformation bands delimiting the area into three blocks or depocenters. The growth faults trend E-W, dip down-to-south in the basin direction, and cut across the study area. The faults initiating from about 2000ms extended up to 500ms, and tend to progress parallel and opposite to the growth direction of an upsurging diapiric structure. The diapiric structures form the major deformational bands originating from great depths (below 2000ms) and rising to about 1200ms where series of sedimentary layers onlapped and pinchout stratigraphically against the diapir. Several other secondary faults or lineaments that form parallel streaks to one another also accompanied the growth faults. The fracture networks have no particular trend but form a network surrounding the well area. Faults identified in the study area have potentials for structural hydrocarbon traps whereas the presence of fractures created a fractured-reservoir condition that enhanced rapid fluid flow especially water. High aquifer flow potential aided by possible fracture permeability resulted in rapid decline in oil rate. Through the application of Ant Tracking attribute, it is possible to obtain detailed interpretation of structures that can have direct influence on oil and gas production.

Keywords: seismic, attributes, production, structural

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Authors: Jingyuan Hu, Zhandong Liu

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CRISPR genome editing technology has transformed molecular biology by accurately targeting and altering an organism’s DNA. Despite the state-of-art precision of CRISPR genome editing, the imprecise mutation outcome and off-target effects present considerable risk, potentially leading to unintended genetic changes. Targeted deep sequencing, combined with bioinformatics sequence alignment, can detect such unwanted mutations. Nevertheless, the classical method, Needleman-Wunsch (NW) algorithm may produce false alignment outcomes, resulting in inaccurate mutation identification. The key to precisely identifying CRISPR-induced mutations lies in determining optimal parameters for the sequence alignment algorithm. Hidden Markov models (HMM) are ideally suited for this task, offering flexibility across CRISPR systems by leveraging forward-backward algorithms for parameter estimation. In this study, we introduce CRISPR-HMM, a statistical software to precisely call CRISPR-induced mutations. We demonstrate that the software significantly improves precision in identifying CRISPR-induced mutations compared to NW-based alignment, thereby enhancing the overall understanding of the CRISPR gene-editing process.

Keywords: CRISPR, HMM, sequence alignment, gene editing

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Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Sara Seyfi

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DDT and petroleum contamination in coastal sand alters the physical and mechanical properties of contaminated soils. This article aims to understand the effects of DDT pollution on the geotechnical characteristics of sand groups, including sand, silty sand, and clay sand. First, the studies conducted on the topic of the article will be reviewed. In the initial stage of the tests, this article deals with the identification of the used sands (sand, silty sand, clay sand) by FTIR, µ-XRF and SEM methods. Then, the geotechnical characteristics of these sand groups, including density, permeability, shear strength, compaction, and plasticity, are investigated using a sand cone, head permeability test, Vane shear test, strain gauge penetrometer, and plastic limit test. Sand groups are artificially contaminated with petroleum substances with 1, 2, 4, 8, 10, 12% by weight. In a separate experiment, amounts of 2, 4, 8, 12, 16, 20 mg/liter of DDT were added to the sand groups. Geotechnical characteristics and identification analysis are performed on the contaminated samples. In the final tests, the mentioned amounts of oil pollution and DDT are simultaneously added to the sand groups, and identification and measurement processes are carried out. The results of the tests showed that petroleum contamination had reduced the optimal moisture content, permeability, and plasticity of all samples. Except silty sand’s plasticity, which petroleum increased it by 1-4% and decreased it by 8-12%. The dry density of sand and clay sand increased, but that of silty sand decreased. Also, the shear strength of sand and silty sand increased, but that of clay sand decreased. DDT contamination increased the maximum dry density and decreased the permeability of all samples. It also reduced the optimum moisture content of the sand. The shear resistance of silty sand and clayey sand decreased, and plasticity of clayey sand increased, and silty sand decreased. The simultaneous effect of petroleum and DDT pollution on the maximum dry density of sand and clayey sand has been synergistic, on the plasticity of clayey sand and silty sand, there has been antagonism. This process has caused antagonism of optimal sand content, shear strength of silty sand and clay sand. In other cases, the effect of synergy or antagonism is not observed.

Keywords: DDT contamination, geotechnical characteristics, petroleum contamination, sand

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Authors: Iftikhar Ahmad, Abulhakim Almajid

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Alumina (Al2O3) is an attractive structural ceramic however; brittleness turns Al2O3 down for advanced applications. Development of multi-phase phase ceramics systems is promising to curtail the brittleness and the incorporation of strong/elastic graphene, as third phase, into dual phase (Al2O3-SiC) is striking for mechanical upgrading purpose. Thin graphene nanosheets (GNS) were prepared by thermal exfoliation process and reinforced into dual phase ceramic system. The hybrid nanocomposite was consolidated by novel HF-IH (high-frequency induction heating) sintering furnace at 1500 °C under 50 MPa in vacuum conditions. Structural features and grain size of the resulting nanocomposite were analyzed by SEM and TEM whilst the mechanical properties were assessed by microhardness and nanoindentation techniques. The fracture toughness of the hybrid nanocomposites was appraised by direct crack measurement method. Electron microscopic investigations confirmed the preparation of thin (< 10 nm) graphene nanosheets (GNS). HF-IH sintering route condensed the three-phase (GNS-Al2O3-SiC) hybrid nanocomposite system to > 99% relative densities. SEM of the hybrid nanocomposites fractured surfaces revealed even distribution of the nanocomposite constituents and changed in fracture-mode. Structurally, 88% grain reduction into hybrid nanocomposite was also obtained. Mechanically, enhanced fracture toughness (50%) and hardness (53%) were also achieved for hybrid nanocomposites were attained against bench marked monolithic Al2O3.

Keywords: alumina, graphene, hybrid nanocomposites, rapid sintering

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Authors: Claudia Carbajal, Jija Dutt, Smriti Pahwa, Sumukhi Vaid, Karishma Vats

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ASER Centre, the research and assessment arm of Pratham Education Foundation sees measurement as the first stage of action. ASER uses primary research to push and give empirical foundations to policy discussions at a multitude of levels. At a household level, common citizens use a simple assessment (a floor-level test) to measure learning across rural India. This paper presents the evidence on the applicability of an ASER approach to the health sector. A citizen-led assessment was designed and executed that collected information from young mothers with children up to a year of age. The pilot assessments were rolled-out in two different models: Paid surveyors and student volunteers. The survey covered three geographic areas: 1,239 children in the Jaipur District of Rajasthan, 2,086 in the Rae Bareli District of Uttar Pradesh, and 593 children in the Bhuj Block in Gujarat. The survey tool was designed to study knowledge of health-related issues, daily practices followed by young mothers and access to relevant services and programs. It provides insights on behaviors related to infant and young child feeding practices, child and maternal nutrition and supplementation, water and sanitation, and health services. Moreover, the survey studies the reasons behind behaviors giving policy-makers actionable pathways to improve implementation of social sector programs. Although data on health outcomes are available, this approach could provide a rapid annual assessment of health issues with indicators that are easy to understand and act upon so that measurements do not become an exclusive domain of experts. The results give many insights into early childhood health behaviors and challenges. Around 98% of children are breastfed, and approximately half are not exclusively breastfed (for the first 6 months). Government established diet diversity guidelines are met for less than 1 out of 10 children. Although most households are satisfied with the quality of drinking water, most tested households had contaminated water.

Keywords: citizen-led assessment, rapid health assessment, Infant and Young Children Feeding, water and sanitation, maternal nutrition, supplementation

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Authors: Haixu Yu, Wenhui Cao

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Tailoring Large Language Models (LLMs) to perform legal reasoning has been a popular trend in the study of AI and law. Researchers have mainly employed two methods to unlock the potential of LLMs, namely by finetuning the LLMs to expand their knowledge of law and by restructuring the prompts (In-Context Learning) to optimize the LLMs’ understanding of the legal questions. Although claiming the finetuning and renovated prompting can make LLMs more competent in legal reasoning, most state-of-the-art studies show quite limited improvements of practicability. In this paper, drawing on the study of the complexity and low interpretability of legal texts, we propose a prompting strategy based on the Chain of Thought (CoT) method. Instead of merely instructing the LLM to reason “step by step”, the prompting strategy requires the tested LLM to identify the ambiguity in the questions as the first step and then allows the LLM to generate corresponding answers in line with different understandings of the identified terms as the following step. The proposed prompting strategy attempts to encourage LLMs to "interpret" the given text from various aspects. Experiments that require the LLMs to answer “case analysis” questions of bar examination with general LLMs such as GPT 4 and legal LLMs such as LawGPT show that the prompting strategy can improve LLMs’ ability to better understand complex legal texts.

Keywords: ambiguity-identification, prompt, large language model, legal text understanding

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Authors: I. S. R. Butswat, D. Zahraddeen

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This study identified and described some skill-based and necessity-driven entrepreneurship in animal agriculture (AA). AA is an integral segment of the world food industry, and provides a good and rapid source of income. The contribution of AA to the Sub-Saharan economy is quite significant, and there are still large opportunities that remain untapped in the sector. However, it is imperative to understand, simplify and package the various components of AA in order to pave way for rapid wealth creation, poverty eradication and women empowerment programmes in sub-Saharan Africa and other developing countries. The entrepreneurial areas of AA highlighted were animal breeding, livestock fattening, dairy production, poultry farming, meat production (beef, mutton, chevon, etc.), rabbit farming, wool/leather production, animal traction, animal feed industry, commercial pasture management, fish farming, sport animals, micro livestock production, private ownership of abattoirs, slaughter slabs, animal parks and zoos, among others. This study concludes that reproductive biotechnology such as oestrous synchronization, super-/multiple ovulation, artificial insemination and embryo transfer can be employed as a tool for improvement of genetic make-up of low-yielding animals in terms of milk, meat, egg, wool, leather production and other economic traits that will necessitate sustainable job and wealth creations.

Keywords: animal, agriculture, entreprenurship, wealth

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Authors: Raj Kumar, Navjyoti Dhingra

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Academic libraries are the hubs in which knowledge is a major resource and the performances of these knowledge in terms of adding and delivering value to their users depend upon their ability and effectiveness in engendering, arranging, managing, and using this knowledge. Developments in Information and Communication Technology’s (ICT), the libraries have been incorporated at the electronic edge to facilitate a rapid transfer of information on a global scale. Web2.0 refers to the development of online services that encourage collaboration, communication and information sharing. Web 2.0 reflects changes in how one can use the web rather than describing any technical or structural change. Libraries provide manifold channels of Information access to its e-users. The rapid expansion of tools, formats, services and technologies has presented many options to unfold Library Collection. Academic libraries must develop ways and means to meet their user’s expectations and remain viable. Web 2.0 tools are the first step on that journey. Web 2.0 has been widely used by the libraries to promote functional services like access to catalogue or for external activities like information or photographs of library events, enhancement of usage of library resources and bringing users closer to the library. The purpose of this paper is to provide a reconnaissance of Web 2.0 tools for enhancing library services in India. The study shows that a lot of user-friendly tools can be adopted by information professionals to effectively cater to information needs of its users. The authors have suggested a roadmap towards a revitalized future for providing various information opportunities to techno-savvy users.

Keywords: academic libraries, change management, social media, Web 2.0

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Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Ngoc Trung Ngo, Buddhima Indraratna, Cholachat Rujikiathmakjornr

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For several hundred years, the design of railway tracks has practically remained unchanged. Traditionally, rail tracks are placed on a ballast layer due to several reasons, including economy, rapid drainage, and high load bearing capacity. The primary function of ballast is to distributing dynamic track loads to sub-ballast and subgrade layers, while also providing lateral resistance and allowing for rapid drainage. Upon repeated trainloads, the ballast becomes fouled due to ballast degradation and the intrusion of fines which adversely affects the strength and deformation behaviour of ballast. This paper presents the use of three-dimensional discrete element method (DEM) in studying the shear behaviour of the fouled ballast subjected to direct shear loading. Irregularly shaped particles of ballast were modelled by grouping many spherical balls together in appropriate sizes to simulate representative ballast aggregates. Fouled ballast was modelled by injecting a specified number of miniature spherical particles into the void spaces. The DEM simulation highlights that the peak shear stress of the ballast assembly decreases and the dilation of fouled ballast increases with an increase level of fouling. Additionally, the distributions of contact force chain and particle displacement vectors were captured during shearing progress, explaining the formation of shear band and the evolutions of volumetric change of fouled ballast.

Keywords: railway ballast, coal fouling, discrete element modelling, discrete element method

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Authors: Umar Rehman, Holly Roy, K. T. Tsang, D. S. Jeyaretna, W Singleton, B. Fisher, P. A. Glew, J. Greig, Peter C. Whitfield

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Introduction: A brain abscess is a life-threatening condition, carrying significant mortality. It requires rapid identification and treatment. Management involves a combination of antibiotics and surgery. The aim of the current study was to identify common bacteria responsible for cerebral abscesses as well as the long term functional and neurological outcomes of patients following treatment in a retrospective series at a single UK neurosurgical centre. Methodology: We analysed patients that had received a diagnosis of 'cerebral abscess' or 'subdural empyema' between June 2002 and June 2018. This was done in the form of a retrospective review. The search resulted in a total of 180 patients; with 37 patients being excluded (spinal abscess, below 18 or non-abscess related admissions). Data were collected from medical case notes including information about demographics, comorbidities, immunosuppression, presentation, size/location of lesions, pathogens, treatment, and outcomes. Results: In total, we analysed 143 patients between the ages of 18-90. Focal neurological deficit and headaches were seen in 84% and 68% of patients respectively. 108 positive brain cultures were seen; with the largest proportion, 59.2% being gram-positive cocci, with strep intermedius being the most common pathogen identified in 13.9% of patients. Of the patients with positive blood cultures (n=11), 72.7% showed the same organism both in the blood and on the brain cultures. Long term outcomes (n=72) revealed that 48% of patients seizure-free without requiring anti-epileptics, 51.3% of patients had full recovery of their neurological symptoms. There was a mortality rate of 13.9% in the series. Conclusion: In conclusion, the largest bacterial cause of abscess within our population was due to gram-positive cocci. The majority of the patient demonstrated full neurological recovery with close to half of patients not requiring anti-epileptics following discharge.

Keywords: bacteria, cerebral abscess, long term outcome, neurological deficit

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Muneeba Butt

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One of the most important physical evidence which leaves suspects at the crime scene is footprints. Analysis of footprints, which can provide useful information for personal identification, is helpful in crime scene investigation. For the current study, 200 samples collected (144 male and 56 female) from Pakistani population with a consent form. The footprints were collected by using black ink with an ink pad. The entire samples were photographed, and then the magnifying glass was used for visualization of individual characteristics including detail of toes, humps, phalange mark, and flat foot cracks in footprint patterns. The descriptive results of individualizing characteristics features were presented in tabular form with respective frequency and percentage. In the result in the male population, the prevalence of tibialis type (T-type) is highest. In the female population, the prevalence of midularis type (M-type) is highest. Humps on the first toe are more found in the male population rather than other humps. In the female population, humps on the third toe are more found rather than other humps. In the male population, the prevalence of phalange mark by toe 1 is highest followed by toe 3, toe 5, toe 2, toe 4 and in female population the prevalence of phalange mark by toe 1 is highest followed by toe 5, 4, 3 and 2. Creases marks are found highest in male population as compared to the female population.

Keywords: foot prints, toes, humps, cracks

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Authors: Niki K. Burns, James R. Pearson, Paul G. Stevenson, Xavier A. Conlan

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In Australian state Victoria, synthetic cannabinoids have recently been made illegal under an amendment to the drugs, poisons and controlled substances act 1981. Identification of synthetic cannabinoids in popular brands of ‘incense’ and ‘potpourri’ has been a difficult and challenging task due to the sample complexity and changes observed in the chemical composition of the cannabinoids of interest. This study has developed analytical methodology for the targeted extraction and determination of synthetic cannabinoids available pre-ban. A simple solvent extraction and solid phase extraction methodology was developed that selectively extracted the cannabinoid of interest. High performance liquid chromatography coupled with UV‐visible and chemiluminescence detection (acidic potassium permanganate and tris (2,2‐bipyridine) ruthenium(III)) were used to interrogate the synthetic cannabinoid products. Mass spectrometry and nuclear magnetic resonance spectroscopy were used for structural elucidation of the synthetic cannabinoids. The tris(2,2‐bipyridine)ruthenium(III) detection was found to offer better sensitivity than the permanganate based reagents. In twelve different brands of herbal incense, cannabinoids were extracted and identified including UR‐144, XLR 11, AM2201, 5‐F‐AKB48 and A796‐260.

Keywords: electrospray mass spectrometry, high performance liquid chromatography, solid phase extraction, synthetic cannabinoids

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

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

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

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: time series modelling, stochastic processes, ARIMA model, Karkheh river

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Authors: Zuliani Mahmood, Thirumulu Ponnuraj Kannan, Yean Yean Chan, Salahddin A. Al-Hudhairy

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Caries is the most common childhood disease which develops due to disturbances in the physiological equilibrium in the dental plaque resulting in demineralization of tooth structures. Plaque and dentine samples were collected from three different tooth surfaces representing caries progression (intact, over carious lesion and dentine) in children with early childhood caries (ECC, n=36). In caries free (CF) children, plaque samples were collected from sound tooth surfaces at baseline and after one year (n=12). The genomic DNA was extracted from all samples and subjected to 16S rRNA PCR amplification. The end products were cloned into pCR®2.1-TOPO® Vector. Five randomly selected positive clones collected from each surface were sent for sequencing. Identification of the bacterial clones was performed using BLAST against GenBank database. In the ECC group, the frequency of Lactobacillus sp. detected was significantly higher in the dentine surface (p = 0.031) than over the cavitated lesion. The highest frequency of bacteria detected in the intact surfaces was Fusobacterium nucleatum subsp. polymorphum (33.3%) while Streptococcus mutans was detected over the carious lesions and dentine surfaces at a frequency of 33.3% and 52.7% respectively. Fusobacterium nucleatum subsp. polymorphum was also found to be highest in the CF group (41.6%). Follow up at the end of one year showed that the frequency of Corynebacterium matruchotii detected was highest in those who remained caries free (16.6%), while Porphyromonas catoniae was highest in those who developed caries (25%). In conclusion, Streptococcus mutans and Porphyromonas catoniae are strongly associated with caries progression, while Lactobacillus sp. is restricted to deep carious lesions. Fusobacterium nucleatum subsp. polymorphum and Corynebacterium matruchotii may play a role in sustaining the healthy equilibrium in the dental plaque. These identified bacteria show promise as potential biomarkers in diagnosis which could help in the management of dental caries in children.

Keywords: early childhood caries, genotypic identification, oral bacteria, 16S rRNA

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

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

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

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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Authors: Laura G. Caixeta, Maico R. Severino

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One of the biggest challenges that the industries find nowadays is to incorporate sustainability practices into its operations. The Green Supply Chain Management (GSCM) concept assists industries in such incorporation. For the full application of this concept is important that enterprises of a same supply chain have the GSCM practices coordinated among themselves. Note that this type of analyses occurs on the context of developed countries and sectors considered big impactors (as automotive, mineral, among others). The propose of this paper is to analyze as the GSCM concepts are applied on the Brazilian animal nutrition industries. The method used was the Case Study. For this, it was selected a supply chain relationship composed by animal nutrition products manufacturer (Enterprise A) and its supplier of animal waste, such as blood, viscera, among others (Enterprise B). First, a literature review was carried out to identify the main GSCM practices. Second, it was done an individual analysis of each one selected enterprise of the application of GSCM concept. For the observed practices, the coordination of each practice in this supply chain was studied. And, it was developed propose of GSCM applications for the practices no observed. The findings of this research were: a) the systematization of main GSCM practices, as: Internal Environment Management, Green Consumption, Green Design, Green Manufacturing, Green Marketing, Green Packaging, Green Procurement, Green Recycling, Life Cycle Analysis, Consultation Selection Method, Environmental Risk Sharing, Investment Recovery, and Reduced Transportation Time; b) the identification of GSCM practices on Enterprise A (7 full application, 3 partial application and 3 no application); c) the identification of GSCM practices on Enterprise B (2 full application, 2 partial application and 9 no application); d) the identification of how is the incentive and the coordination of the GSCM practices on this relationship by Enterprise A; e) proposals of application and coordination of the others GSCM practices on this supply chain relationship. Based on the study, it can be concluded that its possible apply GSCM on animal nutrition industries, and when occurs the motivation on the application of GSCM concepts by a supply chain echelon, these concepts are deployed for the others supply chain echelons by the coordination (orchestration) of the first echelon.

Keywords: animal nutrition industries, coordination, green supply chain management, supply chain management, sustainability

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Authors: Sonia Bautista Carrascosa, Carlos Renedo Sanchez

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The effect of a rapid drawdown is a classical scenario to be considered in slope stability under submerged conditions. This situation arises when totally or partially submerged slopes experience a descent of the external water level and is a typical verification to be done in a dam engineering discipline, as reservoir water levels commonly fluctuate noticeably during seasons and due to operational reasons. Although the scenario is well known and predictable in general, site conditions can increase the complexity of its assessment and external factors are not always expected, can cause a reduction in the stability or even a failure in a slope under a rapid drawdown situation. The present paper describes and discusses the interaction between two different infrastructures, a dam and a highway, and the impact on the stability of a natural rock slope overlaid by the north abutment of a viaduct of the A-44 Highway due to the rapid drawdown of the Rules Dam, in the province of Granada (south of Spain). In the year 2011, with both infrastructures, the A-44 Highway and the Rules Dam already constructed, delivered and under operation, some movements start to be recorded in the approximation embankment and north abutment of the Guadalfeo Viaduct, included in the highway and developed to solve the crossing above the tail of the reservoir. The embankment and abutment were founded in a low-angle natural rock slope formed by grey graphic phyllites, distinctly weathered and intensely fractured, with pre-existing fault and weak planes. After the first filling of the reservoir, to a relative level of 243m, three consecutive drawdowns were recorded in the autumns 2010, 2011 and 2012, to relative levels of 234m, 232m and 225m. To understand the effect of these drawdowns in the weak rock mass strength and in its stability, a new geological model was developed, after reviewing all the available ground investigations, updating the geological mapping of the area and supplemented with an additional geotechnical and geophysical investigations survey. Together with all this information, rainfall and reservoir level evolution data have been reviewed in detail to incorporate into the monitoring interpretation. The analysis of the monitoring data and the new geological and geotechnical interpretation, supported by the use of limit equilibrium software Slide2, concludes that the movement follows the same direction as the schistosity of the phyllitic rock mass, coincident as well with the direction of the natural slope, indicating a deep-seated movement of the whole slope towards the reservoir. As part of these conclusions, the solutions considered to reinstate the highway infrastructure to the required FoS will be described, and the geomechanical characterization of these weak rocks discussed, together with the influence of water level variations, not only in the water pressure regime but in its geotechnical behavior, by the modification of the strength parameters and deformability.

Keywords: monitoring, rock slope stability, water drawdown, weak rock

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Authors: Marisol Rodriguez-Duarte, Aide Saenz-Galindo, Carolina Flores-Gallegos, Raul Rodriguez-Herrera, Juan Ascacio-Valdes

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The plant known as tarbush (Fluorensia cernua) is a plant originating in northern Mexico, mainly in the states of Coahuila, Durango, San Luis Potosí, Zacatecas and Chihuahua. It is a branched shrub that belongs to the family Asteraceae, has oval leaves of 6 to 11 cm in length and also has small yellow flowers. In Mexico, the tarbush is a very appreciated plant because it has been used as a traditional medicinal agent, for the treatment of gastrointestinal diseases, skin infections and as a healing agent. This plant has been used mainly as an infusion. Due to its traditional use, the content and type of phytochemicals present in the plant are currently unknown and are responsible for its biological properties, so its recovery and identification is very important because the compounds that it contains have relevant applications in the field of food, pharmaceuticals and medicine. The objective of this work was to determine the best extraction condition of phytochemical compounds (mainly polyphenolic compounds) from the leaf using ultrasound/microwave assisted extraction (U/M-AE). To reach the objective, U/M-AE extractions were performed evaluating three mass/volume ratios (1:8, 1:12, 1:16), three ethanol/water solvent concentrations (0%, 30% and 70%), ultrasound extraction time of 20 min and 5 min at 70°C of microwave treatment. All experiments were performed using a fractional factorial experimental design. Once the best extraction condition was defined, the compounds were recovered by liquid column chromatography using Amberlite XAD-16, the polyphenolic fraction was recovered with ethanol and then evaporated. The recovered polyphenolic compounds were quantified by spectrophotometric techniques and identified by HPLC/ESI/MS. The results obtained showed that the best extraction condition of the compounds was using a mass/volume ratio of 1:8 and solvent ethanol/water concentration of 70%. The concentration obtained from polyphenolic compounds using this condition was 22.74 mg/g and finally, 16 compounds of polyphenolic origin were identified. The results obtained in this work allow us to postulate the Mexican plant known as tarbush as a relevant source of bioactive polyphenolic compounds of food, pharmaceutical and medicinal interest.

Keywords: U/M-AE, tarbush, polyphenols, identification

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Authors: Ridwan Dewayanto Rusli

Abstract:

We show how prisoner's dilemma-type competition problems can be mitigated through rapid platform diversification and ecosystem expansion. We analyze a ride-hailing company in Southeast Asia, Gojek, whose network grew to more than 170 million users comprising consumers, partner drivers, merchants, and complementors within a few years and has already achieved higher contribution margins than ride-hailing peers Uber and Lyft. Its ecosystem integrates ride-hailing, food delivery and logistics, merchant solutions, e-commerce, marketplace and advertising, payments, and fintech offerings. The company continues growing its network of complementors and App developers, expanding content and gaining critical mass in consumer data analytics and advertising. We compare the company's growth and diversification trajectory with those of its main international rivals and peers. The company's rapid growth and future potential are analyzed using Cusumano's (2012) Staying Power and Six Principles, Hax and Wilde's (2003) and Hax's (2010) The Delta Model as well as Santos' (2016) home-market advantages frameworks. The recently announced multi-billion-dollar merger with one of Southeast Asia's largest e-commerce majors lends additional support to the above arguments.

Keywords: ride-hailing, prisoner's dilemma, platform and ecosystem strategy, digital applications, diversification, home market advantages, e-commerce

Procedia PDF Downloads 91