78 research outputs found
Microevolution of <i>Neisseria lactamica</i> during prolonged colonisation of the nasopharynx
No full textCarriage of Neisseria lactamica occurs naturally at high frequency in infants and low frequency in young adults. There is an inverse epidemiological relationship between N. lactamica carriage and disease caused by Neisseria meningitidis (meningococcus). Serogroup B meningococci remain the dominant cause of invasive meningococcal disease in the developed world and have frustrated the production of polysaccharide-conjugate vaccines. While two, recombinant, OMV based vaccines (Richmond et al., 2012; Vernikos and Medini, 2014) have been created and elicit immunological responses, they are less effective on infants (one of the groups most at risk of IMD) and have limited effect on meningococcal carriage and subsequently, on herd immunity. A human experimental challenge study in which healthy, young adult volunteers were inoculated with N. lactamica Y92-1009 showed that carriage of N. lactamica both displaced and inhibited reacquisition of wild type N. meningitidis, and although rare, co-colonization of the two species was also observed in a small number of cases (Deasy et al., 2015). This study provided the opportunity to investigate whether there is a genomic basis for N. lactamica’s effect on meningococcal carriage as the mechanism for this interaction remains unknown. Secondly, the use of whole genome sequencing, paired with mutation analysis via the breseq pipeline (Barrick et al., 2014) will comment on the mutability of N. lactamica, a potential bacterial medicine, during 6 months of in vivo, human challenge. Thirdly, this allows us to track the within-host microevolution of an identically administered commensal Neisseria spp. over the course of 6 months of carriage (chapter 5).Isolates obtained from individuals who were co-colonised by N. meningitidis and N. lactamica for a prolonged period were examined for evidence of the effect of recombination (r/m) as well as loci affected by it (chapter 6). In addition to the majority of volunteers who solo carried N. lactamica Y92-1009. Recombination was determined for; volunteers in which inoculated N. lactamica was the sole Neisseria spp. detected, seven, artificially inoculated, N. lactamica/meningococcal co-carriers and two extra volunteers who were naturally co-colonised. Using ClonalFrameML (Didelot and Wilson, 2015), we detected minimal homologous recombination events among N. lactamica Y92-1009 and no examples of interspecific allele transferred with co-colonising meningococci. In contrast, we found evidence of a dynamic, interspecific relationship and a number of recombination events occurring among co-colonised volunteers with naturally acquired Neisseria.A separate, short term clinical trial utilizing multiple colony sampling (chapter 4) examined the difference in mutational profiles of longitudinal samples N. lactamica strain Y92-1009 sourced from in vitro conditions versus in vivo conditions over one month. Larger numbers of SNPs, nonsense and recurring mutations were observed among the in vitro cohort and the quantity/diversity of phase variable mutations was more pronounced among the in vivo cohort. Chapters 4 and 5 are supported by a highly-accurate reference genome. The sequencing, assembly, annotation and characterisation of the first complete N. lactamica Y92-1009 genome is described in chapter 3 (Pandey et al., 2017). This chapter also revealed the presence of a large but uncharacterised prophage sequence in the strain. The very first example of a species encompassing, pan genomic analysis of N. lactamica (chapter 7) revealed that N. lactamica Y92-1009 possess fewer unique genes/alleles than other members of the species with no virulence factors detected among the results.In conclusion, the N. lactamica Y92-1009 genome is a self-curated system with plastic elements that (like other Neisseria spp.) could facilitate rapid changes in expression via its phase variable elements. However, it appears to have remained genetically stable during the 6-month course of carriage in human volunteers. Demonstrating little recombination, no interspecific gene transfer with co-colonising meningococci and an average mutation rate for a Neisseria species. While efforts need to be made to improve the acquisition and retention of carriage, N. lactamica appears to be a safe, naturally competent, potential bacterial therapeutic, capable of a broadspectrum reduction of meningococcal carriage.<br/
Responding to 4G telecom pricing war: ignore, accommodate or retaliate, Emerald Emerging Markets Case Studies, Vol. 8 Issue: 2
No full textImproved Modified Chaotic Invasive Weed Optimization Approach to Solve Multi-Target Assignment for Humanoid Robot
No full textThe paper presents an improved modified chaotic invasive weed optimization (IMCIWO) approach for solving a multi-target assignment for humanoid robot navigation. MCIWO is improved by utilizing the Bezier curve for smoothing the path and replaces the conventional split lines. In order to efficiently determine subsequent locations of the robot from the present location on the provided terrain, such that the routes to be specifically generated for the robot are relatively small, with the shortest distance from the barriers that have been generated using the IMCIWO approach. The MCIWO approach designed the path based on obstacles and targets position which is further smoothened by the Bezier curve. Simulations are performed which is further validated by real-time experiments in WEBOT and NAO robot respectively. They show good effectiveness with each other with a deviation of under 5%. Ultimately, the superiority of the developed approach is examined with existing techniques for navigation, and findings are substantially improved
Mobile robot navigation in unknown static environments using ANFIS controller
No full textSummaryNavigation and obstacle avoidance are the most important task for any mobile robots. This article presents the Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for mobile robot navigation and obstacle avoidance in the unknown static environments. The different sensors such as ultrasonic range finder sensor and sharp infrared range sensor are used to detect the forward obstacles in the environments. The inputs of the ANFIS controller are obstacle distances obtained from the sensors, and the controller output is a robot steering angle. The primary objective of the present work is to use ANFIS controller to guide the mobile robot in the given environments. Computer simulations are conducted through MATLAB software and implemented in real time by using C/C++ language running Arduino microcontroller based mobile robot. Moreover, the successful experimental results on the actual mobile robot demonstrate the effectiveness and efficiency of the proposed controller
Development of an autonomous vision sensor-actuator-based circumferential seam path tracker welding machine/device for LPG cylinders
No full textThis paper presents an autonomous vision sensor-actuator-based circumferential seam path tracker welding machine/device for LPG (Liquefied Petroleum Gas) cylinders. The machine or device is designed to avoid various hazardous health issues that are found in the workers due to unfavorable working conditions during the welding process because of high temperature, dangerous fumes, and a large amount of luminous flux in the workstation. This machine involves a pneumatic holder to hold the cylindrical workpiece inside a metallic body frame. When the cylindrical workpiece rotates in a pneumatic holder, some amount of deflection arises due to the improper arrangement of fixtures and cylinders. It is not easy to overcome this deflection in fixtures, and due to this, the welding process is not done correctly. The undercut and overcut errors can also be found due to the improper shape of fixtures and cylinders. Therefore, the box setup is designed to cope with this problem, and the box contains an RGB (Red Green Blue) camera, LED (Light Emitting Diode), and an ultrasonic sensor. The box is installed in front of the welding torch to capture the image of the seam path of the workpiece. Firstly, the image is created with the help of a LED fitted inside the box. The LED creates the shadow of the joggle joint of the cylindrical workpiece. The camera captures that shadow. After capturing the image of shadow, the centroid of the seam path (represented by shadow) of the cylindrical workpiece is traced. It is sent to the Raspberry Pi microcontroller, and the data of the image is stored in the memory of the microcontroller for further processing. According to the position of the centroid coordinate, the microcontroller sends the control commands to the microstep driver of the stepper motor to follow this centroid coordinate. By this, the torch is controlled, and the welding process is done autonomously. The experimental setup is made, and the autonomous welding process is performed in many cylinders. Moreover, after performing autonomous welding process in the cylinder, the high-pressure bursting test (which is basically done by cylinder manufacturer industries) is performed to verify the effectiveness and efficiency of the welding joints. In the bursting test result, it is found that the cylinder is burst in a longitudinal direction, which verifies the effectiveness and efficiency of the obtained circumferential joggle joint
Lube oil life prediction for heavy earth moving machinery (HEMM): A machine learning approach
No full textEvaluating lubricant life is crucial for maintaining equipment reliability and preventing failures. Conventional methods often depend on original equipment manufacturer recommendations for lubricant changes, which may result in the premature disposal of operationally effective lubricants, leading to economic costs and degrading overall efficiency. The chemical properties of these samples are evaluated by calculating multiple parameters such as total acid number, total base number, oxidation index, soot level, and water contamination. In addition, rheological properties through viscosity index analysis and the tribological properties via friction-wear analysis are determined. In this study, an artificial neural network (ANN) (a four-layer perceptron) and an adaptive neuro-fuzzy inference system (ANFIS) are applied to predict oil conditions based on multiple calculated parameters. Performance and comparison of these advanced mathematical models are evaluated using statistical indices. Overall, the artificial intelligence (AI)-powered approach proved effective in predicting lubricant life for HEMM. Among the AI models, the ANN model demonstrated particularly strong performance, with a correlation coefficient of 0.99 compared to 0.98 for the ANFIS model. Implementing the ANN model could lead to a potential 19% reduction in current engine oil expenses, which would lower operating costs and decrease environmental impact by reducing the frequency of oil disposal.</p
Embodied energy and associated carbon emission of key building materials in Nepal
No full textThe number of concrete buildings in Nepal increased by 23.90 percent within the last decade. Life Cycle Assessment (LCA) of the buildings shows that Cement, Brick and Reinforcement steel are the three major building materials which account for about half of the total life cycle energy use and emission from the building materials. However, there is no national database for energy use and emissions from these building materials in Nepal. So, the study aims to evaluate energy use and its associated emissions in the production of these materials using the LCA framework and guidelines from ISO 14040: 2006 and ISO 14044: 2006. The data from embodied energy is based on the energy audits of 26 cement industries, 21 metal industries, and 27 brick industries sampled across the country. The study shows that the production of one tonne of cement accounts for 6051.07 MJ energy and is responsible for 739.49 kgCO2-eq.; the production of 1000 pieces of standard size burnt brick from fixed chimney bull trench kiln accounts for 4124.56 MJ energy and 502.89 kgCO2-eq. emission; and the production of one tonne of reinforcement steel accounts for 26,033.14 MJ energy and 2565.5 kgCO2-eq emission. The major source of energy and emission in building material production is coal. A shift in energy sources from coal to hydroelectricity would reduce the energy-related emissions from the materials production. Also replacing high emission construction materials with locally available natural materials like stone, wood and bamboo could minimize the emissions from the built environment. © The Author(s) 2025.Article; Export Date: 11 May 2025; Cited By: 1; Correspondence Address: A. Ghimire; Environmental Engineering and Management, Asian Institute of Technology, Pathum Thani, 12120, Thailand; email: [email protected]</p
Intrapreneurship and career advancement: Investigating the role of intrapreneurship in facilitating career growth and development
No full textIntrapreneurship is increasingly recognized as a crucial driver of organizational innovation and employee career advancement. This chapter explores the role of intrapreneurship in facilitating career growth, examining key drivers such as supportive culture, resource availability, and calculated risk-taking. It highlights strategies for enhancing intrapreneurship, including fostering collaboration, recognizing achievements, and leveraging emerging trends. Future trends discussed include the impact of digital transformation, remote and hybrid work environments, and the growing focus on sustainability. Case studies demonstrate successful intrapreneurial initiatives and their impact on career development. The chapter concludes by emphasizing the importance of continuous learning and adaptability in navigating the evolving landscape of intrapreneurship
Dynamic Path Planning for Autonomous Mobile Robot using Minimum Fuzzy Rule Based Controller with Avoidance of Moving Obstacles
No full textAnalysis of Hybrid Technique for Motion Planning of Humanoid NAO
No full textThe navigation of a humanoid robot is essential because it is the basic requirement of any assigned task. Singly used motion planning techniques may take a long path to reach the target and increase the computational cost. Therefore, in this article, a hybrid controller is employed in the humanoid NAO for motion planning assignment. The Eagle strategy (ES) with Ant colony optimization (ACO) is introduced in this article for evaluating precise steering angles for humanoid robots as they traverse a route from a reference point to a target point. This enables the robot to achieve its specific target more quickly by avoiding barriers and obtaining the minimal global direction. The hybridized ES-ACO approach is critical in determining precise steering angles to escape obstacles. The details of terrain are obtained using vision and ultrasonic sensors, which also include the barriers ranges to the ES as an input variable. The ES's input parameters are the barrier ranges from the NAO in front, left, and right directions, and the technique's output variable is the precise steering angle. The designed controller is tested in both a simulation and an experimental setting with a variety of obstacles. The outcomes of both simulation and experimental conditions are compared, and a strong correlation is identified in those with the fewest deviations
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