Morphometric relationships of spineless cuttlefish, Sepiella inermis (Orbigny, 1848) from Mumbai waters

The relationships of various morphometric characters with dorsal mantle length (DML) of Sepiella inermis from Mumbai waters was established. The coefficient of correlation (r²) for various morphometric characters against dorsal mantle length ranged from 0.747 to 0.942 indicating high degree of relationship among the characters compared. The regression of characteristics obtained by least squares method for S. inermis indicates that the characters have positive allometric growth

Wireless Power Transmission to a Buried Sensor in Concrete

The feasibility of sending wireless power to a buried sensor antenna within concrete was studied. a receive patch rectenna with 75.8% conversion efficiency was designed for operation at 5.7 GHz. The received DC power at the rectenna was measured within dry and wet concrete samples with various cover thicknesses and air-gaps. For the rectenna buried within 30 mm of the concrete, the received DC power was 10.37 mW, which was, about 70% of the received DC power in free-space

Prevalence of ectoparasites in farmed Pangasius hypothalamus

Of the total 240 Pangasius hypothalamus (5 - 8.7cm) fry examined during September' O1 to February'02, 80 (33.33%) were found to be infested with one or more ecroparasites irrespective of genera or groups. Seven parasitic groups were identified with the highest average prevalence of Trichodinids (55%) followed by Dacrylogyrus spp. ( 42%), Episrylis spp. (8%), Apiosoma spp. (7%) Argulus spp. (5%), Gyrodacrylus spp. (4%) and Piscicola spp. (2%) the lowest prevalent group irrespective of months. Trichodinid and Dacrylogyms spp. were recorded to be the dominating parasitic groups among the seven both in terms of monthly prevalence and severity of infestation throughout the period of investigation. The highest prevalence (60%) of ectoparasite was recorded in December and the lowest (10%) in February irrespective of groups

Optimum dietary carbohydrate to lipid ratio in stinging catfish, Heteropneustes fossilis (Bloch, 1792)

A feeding trial of 8 weeks was conducted in a static indoor rearing system to investigate the optimum carbohydrate to lipid ratio (CHO:L ratio) in stinging catfish, Heteropneustes fossilis. Five iso-nitrogenous (35% crude protein) and iso-energetic (17.06 kJ gˉ¹ gross energy (GE)) fish meal based diets with varying carbohydrate to lipid (CHO:L g/g) ratios of 0.60, 0.98, 1.53, 2.29 and 3.44 for diets 1-5, were tested, respectively. The diets containing a fixed protein to energy ratio (P:E ratio) of 20.50-mg protein kJˉ¹ GE were fed to triplicate groups of 40 fish (per 70-L tank). Fish were fed 5% of their body weight per day adjusted fortnightly. Diet 1, containing 10% carbohydrate and 17% lipids with a CHO:L ratio of 0.60 produced the poorest (p<0.05) growth rates, feed and protein efficiency. Increasing carbohydrate content in the diets to 26% concomitant with a reduction in lipid content to 11% with a CHO:L ration of 2.29 of diet 5 significantly improved (p<0.05) growth rates, feed and protein efficiency. But did not differ with diet 4, containing CHO:L ratio 2.29. A further increase in dietary carbohydrate up to 31% and a decrease in lipids levels to 9% with a CHO:L ratio ranging from 2.29 to 3.44 (diet 4-5) did not significantly improve the fish performance. Apparent net protein utilisation (ANPU) of fish fed diet 5 was higher (p<0.05) than for diets 1 and 2 but did not differ from diets 3 and 4. Higher lipid deposition (p<0.05) in whole body was observed with decreasing dietary CHO:L ratios as increasing lipid levels. Whole body protein of fish fed varying CHO:L diets did not show any discernible changes among the dietary treatments. This study revealed that H. fossilis can perform equally well on diets containing carbohydrate ranging from 26 to 31%, with 9 to 11% lipid or at CHO:L g/g ratio of 2.29-3.44

A K-Chart based implementation framework to attain lean & agile manufacturing

[EN] Lean manufacturing has always ensured production optimization by eliminating wastes, and its implementation has helped in improving the operational performance of the organization since it eliminates the bottlenecks from the processes, thus making them efficient. In lean scenarios, the focus is on “waste” elimination, but in agile manufacturing, the focus is on the ability of comprehension of changing market dynamics and the resilience. One of the major factors in the combined implementation of lean and agile approaches is inadequate planning, monitoring and lack of awareness regarding changing market trends, and this can be countered by utilizing the effective tool of K-Chart. Through a systematic literature review, the authors establish the requirement of effective planning and monitoring in the implementation of integrated lean and agile approach, concluding that K-Chart is a handy tool to adopt for their effective implementation. The result provides a new vision of lean implementation through K-Chart, whereas it provides clarity to practitioners by presenting a K-chart based implementation framework for achieving favourable results. Being a literature review the research work can be validated through a case study approach in future through a comparative analysis between various implementation techniques and K-Chart.Zaheer, S.; Amjad, M.; Rafique, M.; Khan, M. (2020). A K-Chart based implementation framework to attain lean & agile manufacturing. International Journal of Production Management and Engineering. 8(2):123-135. https://doi.org/10.4995/ijpme.2020.12935OJS12313582Abdullah, M. K., Mohd Suradi, N., Jamaluddin, N., Mokhtar, A. S., Abu Talib, A., & Zainuddin, M. F. (2006). K-chart: a tool for research planning and monitoring. J. of Quality Management And Analysis, 2(1), 123-130.Abdullah, M. K., Suradi, N. R. M., Jamaluddin, N., Mokhtar, S., Talib, A. R. A., & Zainuddin, M. F. K-chart: a tool for research planning and monitoring, 7.Abdulmalek, F. A., & Rajgopal, J. (2007). Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study. International Journal of Production Economics, 107(1), 223-236. https://doi.org/10.1016/j.ijpe.2006.09.009Abu, F., Gholami, H., Saman, M. Z. M., Zakuan, N., & Streimikiene, D. (2019). The implementation of lean manufacturing in the furniture industry: A review and analysis on the motives, barriers, challenges, and the applications. Journal of Cleaner Production, 234, 660-680. https://doi.org/10.1016/j.jclepro.2019.06.279Alfaris, M., Edikuncoro, G., Savitri, A., Yogiari, D., & Sulistio, J. (2019). A Literature Review of Sustain Enterprise Resource Planning. Paper presented at the IOP Conference Series: Materials Science and Engineering. https://doi.org/10.1088/1757-899X/598/1/012128Anand, G., & Kodali, R. (2010). Development of a framework for implementation of lean manufacturing systems. International Journal of Management Practice, 4(1), 95. https://doi.org/10.1504/IJMP.2010.029705Anvari, A., Ismail, Y., & Hojjati, S. M. H. (2011). A Study on Total Quality Management and Lean Manufacturing: Through Lean Thinking Approach. World applied sciences journal, 12(9), 1585-1596.Baker, P. (2006). Designing distribution centres for agile supply chains. International Journal of Logistics Research and Applications, 9(3), 207-221. https://doi.org/10.1080/13675560600859136Baramichai, M., Zimmers, E. W., & Marangos, C. A. (2007). Agile supply chain transformation matrix: an integrated tool for creating an agile enterprise. Supply Chain Management: An International Journal, 12(5), 334-348. https://doi.org/10.1108/13598540710776917Bhamu, J., & Singh Sangwan, K. (2014). Lean manufacturing: literature review and research issues. International Journal of Operations & Production Management, 34(7), 876-940. https://doi.org/10.1108/IJOPM-08-2012-0315Bhasin, S., & Burcher, P. (2006). Lean viewed as a philosophy. Journal of Manufacturing Technology Management, 17(1), 56-72. https://doi.org/10.1108/17410380610639506Botti, L., Mora, C., & Regattieri, A. (2017). Integrating ergonomics and lean manufacturing principles in a hybrid assembly line. Computers & Industrial Engineering, 111, 481-491. https://doi.org/10.1016/j.cie.2017.05.011Carvalho, H., Azevedo, S. G., & Cruz-Machado, V. (2012). Agile and resilient approaches to supply chain management: influence on performance and competitiveness. Logistics Research, 4(1-2), 49-62. https://doi.org/10.1007/s12159-012-0064-2Chen, J. C., Li, Y., & Shady, B. D. (2010). From value stream mapping toward a lean/sigma continuous improvement process: an industrial case study. International Journal of Production Research, 48(4), 1069-1086. https://doi.org/10.1080/00207540802484911Christian, P.H., Zimmers Jr, E.W. (1999). Age of agile manufacturing puts quality to the test. Quality Progress, 32(5), 45.Chun Wu, Y. (2003). Lean manufacturing: a perspective of lean suppliers. International Journal of Operations & Production Management, 23(11), 1349-1376. https://doi.org/10.1108/01443570310501880Constantinescu, C., Matarazzo, D., Dienes, D., Francalanza, E., & Bayer, M. (2014). Modeling of system knowledge for efficient agile manufacturing: Tool evaluation, selection and implementation scenario in SMEs. Procedia CIRP, 25, 246-252. https://doi.org/10.1016/j.procir.2014.10.035Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., & Mangini, A. M. (2012). A model for supply management of agile manufacturing supply chains. International Journal of Production Economics, 135(1), 451-457. https://doi.org/10.1016/j.ijpe.2011.08.021Duguay, C. R., Landry, S., & Pasin, F. (1997). From mass production to flexible/agile production. International Journal of Operations & Production Management, 17(12), 1183-1195. https://doi.org/10.1108/01443579710182936Elkins, D. A., Huang, N., & Alden, J. M. (2004). Agile manufacturing systems in the automotive industry. International Journal of Production Economics, 91(3), 201-214. https://doi.org/10.1016/j.ijpe.2003.07.006Elnadi, M. (2015). An innovative framework for implementing lean principles in product-service system.Fagerholm, F., Ikonen, M., Kettunen, P., Münch, J., Roto, V., & Abrahamsson, P. (2015). Performance Alignment Work: How software developers experience the continuous adaptation of team performance in Lean and Agile environments. Information and Software Technology, 64, 132-147. https://doi.org/10.1016/j.infsof.2015.01.010Gani, W., & Limam, M. (2013). On the use of the K-chart for phase II monitoring of simple linear profiles. Journal of Quality and Reliability Engineering, 2013. https://doi.org/10.1155/2013/705450Ghobadian, A., Talavera, I., Bhattacharya, A., Kumar, V., Garza-Reyes, J. A., & O'Regan, N. (2020). Examining legitimatisation of additive manufacturing in the interplay between innovation, lean manufacturing and sustainability. International Journal of Production Economics. 219, 457-468. https://doi.org/10.1016/j.ijpe.2018.06.001Ghobakhloo, M., & Azar, A. (2018). Business excellence via advanced manufacturing technology and lean-agile manufacturing. Journal of Manufacturing Technology Management, 29(1), 2-24. https://doi.org/10.1108/JMTM-03-2017-0049Goldsby, T. J., Griffis, S. E., & Roath, A. S. (2006). MODELING LEAN, AGILE, AND LEAGILE SUPPLY CHAIN STRATEGIES. Journal of Business Logistics, 27(1), 57-80. https://doi.org/10.1002/j.2158-1592.2006.tb00241.xGrewal, C. (2008). An initiative to implement lean manufacturing using value stream mapping in a small company. International Journal of Manufacturing Technology and Management, 15(3-4), 404-417. https://doi.org/10.1504/IJMTM.2008.020176Gunasekaran, A. (1998). Agile manufacturing: Enablers and an implementation framework. International Journal of Production Research, 36(5), 1223-1247. https://doi.org/10.1080/002075498193291Gunasekaran, A. (1999). Agile manufacturing: A framework for research and development. International Journal of Production Economics, 62(1-2), 87-105. https://doi.org/10.1016/S0925-5273(98)00222-9Gunasekaran, A., Lai, K., & Edwincheng, T. (2008). Responsive supply chain: A competitive strategy in a networked economy. Omega, 36(4), 549-564. https://doi.org/10.1016/j.omega.2006.12.002Gunasekaran, A., Yusuf, Y. Y., Adeleye, E. O., & Papadopoulos, T. (2018). Agile manufacturing practices: the role of big data and business analytics with multiple case studies. International Journal of Production Research, 56(1-2), 385-397. https://doi.org/10.1080/00207543.2017.1395488Gunasekaran, A., Yusuf, Y. Y., Adeleye, E. O., Papadopoulos, T., Kovvuri, D., & Geyi, D. A. G. (2019). Agile manufacturing: an evolutionary review of practices. International Journal of Production Research, 57(15-16), 5154-5174. https://doi.org/10.1080/00207543.2018.1530478Hines, P., & Rich, N. (1997). The seven value stream mapping tools. International journal of operations & production management, 17(1), 46-64. https://doi.org/10.1108/01443579710157989Immawan, T., Arkeman, Y., & Maulana, A. (2015). Sustainable supply chain management for Make To Stock-Make To Order production typology case study: batik industry in Solo Indonesia. Supply Chain Management (SSCM), 7(11).Inman, R. A., Sale, R. S., Green, K. W., & Whitten, D. (2011). Agile manufacturing: Relation to JIT, operational performance and firm performance. Journal of Operations Management, 29(4), 343-355. https://doi.org/10.1016/j.jom.2010.06.001Iskanius, P., Haapasalo, H., & Page, T. (2006). Requirements for change in a traditional industry to be competitive: transformation towards an agile supply chain. International Journal of Agile Systems and Management, 1(3), 258. https://doi.org/10.1504/IJASM.2006.010942Ismail, H. S., & Sharifi, H. (2006). A balanced approach to building agile supply chains. International Journal of Physical Distribution & Logistics Management, 36(6), 431-444. https://doi.org/10.1108/09600030610677384Jasiulewicz-Kaczmarek, M. (2013). Sustainability: Orientation in Maintenance Management: Case Study. In P. Golinska (Ed.), EcoProduction and Logistics (pp. 135-154). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-23553-5_9Jin‐Hai, L., Anderson, A. R., & Harrison, R. T. (2003). The evolution of agile manufacturing. Business Process Management Journal, 9(2), 170-189. https://doi.org/10.1108/14637150310468380Keyte, B., & Locher, D. A. (2004). The complete lean enterprise: Value stream mapping for administrative and office processes: Productivity Press. https://doi.org/10.1201/b16650Khalfallah, M., & Lakhal, L. (2020). The impact of lean manufacturing practices on operational and financial performance: the mediating role of agile manufacturing. International Journal of Quality & Reliability Management. https://doi.org/10.1108/IJQRM-07-2019-0244Khodeir, L. M., & Othman, R. (2016). Examining the interaction between lean and sustainability principles in the management process of AEC industry. Ain Shams Engineering Journal.Konecka, S. (2010). Lean and agile supply chain management concept in the aspect of risk management. LogForum, 6(4), 23-31.Koskela, L. (1992). Application of the new production philosophy to construction (72). Stanford: Stanford University. Retrieved from http://www.leanconstruction.org.uk/media/docs/Koskela-TR72.pdfKumar, S., Choudhary, A., Kumar, M., Shankar, R., & Tiwari, M. (2006). Kernel distance-based robust support vector methods and its application in developing a robust K-chart. International Journal of Production Research, 44(1), 77-96. https://doi.org/10.1080/00207540500216037Leite, M., & Braz, V. (2016). Agile manufacturing practices for new product development: industrial case studies. Journal of Manufacturing Technology Management, 27(4), 560-576. https://doi.org/10.1108/JMTM-09-2015-0073Lian, Y.-H., & Van Landeghem, H. (2007). Analysing the effects of Lean manufacturing using a value stream mapping-based simulation generator. International Journal of Production Research, 45(13), 3037-3058. https://doi.org/10.1080/00207540600791590Losonci, D., Demeter, K., & Jenei, I. (2011). Factors influencing employee perceptions in lean transformations. International Journal of Production Economics, 131(1), 30-43. https://doi.org/10.1016/j.ijpe.2010.12.022Mamat, R.C., Md Deros, B., Ab Rahman, M.N., Khalil Omar, M., Abdullah, S. (2015). Soft Lean Practices for Successful Lean Production System Implementation in Malaysia Automotive Smes: A Proposed Framework. Jurnal Teknologi, 77(27). https://doi.org/10.11113/jt.v77.6910Maqbool, Y., Rafique, M. Z., Hussain, A., Ali, H., Javed, S., Amjad, M. S., . . . Atif, M. (2019). An Implementation Framework to Attain 6R-Based Sustainable Lean Implementation-A Case Study. IEEE Access, 7, 117561-117579. https://doi.org/10.1109/ACCESS.2019.2936056Marodin, G., Frank, A. G., Tortorella, G. L., & Netland, T. (2018). Lean product development and lean manufacturing: Testing moderation effects. International Journal of Production Economics, 203, 301-310. https://doi.org/10.1016/j.ijpe.2018.07.009Martin, C., & Towill, D. R. (2000). Supply chain migration from lean and functional to agile and customised. Supply Chain Management: An International Journal, 5(4), 206-213. https://doi.org/10.1108/13598540010347334Martínez Sánchez, A., & Pérez Pérez, M. (2001). Lean indicators and manufacturing strategies. International Journal of Operations & Production Management, 21(11), 1433-1452. https://doi.org/10.1108/01443570110407436Matt, D. T., & Rauch, E. (2013). Implementation of Lean Production in Small Sized Enterprises. Procedia CIRP, 12, 420-425. https://doi.org/10.1016/j.procir.2013.09.072McCullen, P., & Towill, D. (2001). Achieving lean supply through agile manufacturing. Integrated Manufacturing Systems, 12(7), 524-533. https://doi.org/10.1108/EUM0000000006232Mejabi, O. O. (2003). Framework for a lean manufacturing planning system. International Journal of Manufacturing Technology and Management, 5(5/6), 563. https://doi.org/10.1504/IJMTM.2003.003710Metternich, J., Bechtloff, S., & Seifermann, S. (2013). Efficiency and Economic Evaluation of Cellular Manufacturing to Enable Lean Machining. Procedia CIRP, 7, 592-597. https://doi.org/10.1016/j.procir.2013.06.038Moyano‐Fuentes, J., Sacristán‐Díaz, M., & José Martínez‐Jurado, P. (2012). Cooperation in the supply chain and lean production adoption: Evidence from the Spanish automotive industry. International Journal of Operations & Production Management, 32(9), 1075-1096. https://doi.org/10.1108/01443571211265701Näslund, D. (2008). Lean, six sigma and lean sigma: fads or real process improvement methods?. Business process management journal, 14(3), 269-287. https://doi.org/10.1108/14637150810876634Nawanir, G., Kong Teong, L., & Norezam Othman, S. (2013). Impact of lean practices on operations performance and business performance: Some evidence from Indonesian manufacturing companies. Journal of Manufacturing Technology Management, 24(7), 1019-1050. https://doi.org/10.1108/JMTM-03-2012-0027Nesensohn, C. (2014). An innovative framework for assessing lean construction maturity. Liverpool John Moores University.Nordin, N., Deros, B.M., Wahab, D.A. (2010). A survey on lean manufacturing implementation in Malaysian automotive industry. International Journal of Innovation, Management and Technology, 1(4), 374.Nordin, N., Deros, B. M., Wahab, D. A., & Rahman, M. N. A. (2012). A framework for organisational change management in lean manufacturing implementation. Int. J. Services and Operations Management, 12(1), 101-117. https://doi.org/10.1504/IJSOM.2012.046676Pawlowski, K., & Pawlowski, E. (2015). Modern manufacturing practices and agile enterprise. Anticipated scope of implementation and empirical results from Polish enterprises. Procedia Manufacturing, 3, 464-471. https://doi.org/10.1016/j.promfg.2015.07.209Rafique, M. Z., Ab Rahman, M. N., Saibani, N., & Arsad, N. (2017). A systematic review of lean implementation approaches: a proposed technology combined lean implementation framework. Total Quality Management & Business Excellence, 30(3-4), 386-421. https://doi.org/10.1080/14783363.2017.1308818Rafique, M. Z., Ab Rahman, M. N., Saibani, N., Arsad, N., & Saadat, W. (2016). RFID impacts on barriers affecting lean manufacturing. Industrial Management & Data Systems, 116(8), 1585-1616. https://doi.org/10.1108/imds-10-2015-0427Rahani, A., & Al-Ashraf, M. (2012). Production flow analysis through value stream mapping: a lean manufacturing process case study. Procedia Engineering, 41, 1727-1734. https://doi.org/10.1016/j.proeng.2012.07.375Rahman, N. A. A., Sharif, S. M., & Esa, M. M. (2013). Lean Manufacturing Case Study with Kanban System Implementation. Procedia Economics and Finance, 7, 174-180. https://doi.org/10.1016/S2212-5671(13)00232-3Rahman, S., Laosirihongthong, T., & Sohal, A. S. (2010). Impact of lean strategy on operational performance: a study of Thai manufacturing companies. Journal of Manufacturing Technology Management, 21(7), 839-852. https://doi.org/10.1108/17410381011077946Rehman, A. U., Alkhatani, M., & Umer, U. (2018). Multi Criteria Approach to Measure Leanness of a Manufacturing Organization. IEEE Access, 6, 20987-20994. https://doi.org/10.1109/ACCESS.2018.2825344Robson, C., & McCartan, K. (2016). Real world research: John Wiley & Sons.Rohani, J. M., & Zahraee, S. M. (2015). Production line analysis via value stream mapping: a lean manufacturing process of color industry. Procedia Manufacturing, 2, 6-10. https://doi.org/10.1016/j.promfg.2015.07.002Rother, M., & Shook, J. (2003). Learning to see: value stream mapping to add value and eliminate muda: Lean Enterprise Institute.Sabbagh, O., Ab Rahman, M. N., Ismail, W. R., & Wan Hussain, W. M. H. (2016). Methodology implications in automotive product-service systems: a systematic literature review. Total Quality Management & Business Excellence, 28(13-14), 1632-1668. https://doi.org/10.1080/14783363.2016.1150169Sahwan, M. A., Rahman, M. N. A., & Deros, B. M. (2012). Barriers to Implement Lean Manufacturing in Malaysian Automotive Industry. Jurnal Teknologi, 59, 107-110. https://doi.org/10.11113/jt.v59.2571Salonitis, K., & Tsinopoulos, C. (2016). Drivers and barriers of lean implementation in the Greek manufacturing sector. Procedia CIRP, 57, 189-194. https://doi.org/10.1016/j.procir.2016.11.033Sartal, A., Llach, J., Vázquez, X. H., & de Castro, R. (2017). How much does Lean Manufacturing need environmental and information technologies? Journal of Manufacturing Systems, 45, 260-272. https://doi.org/10.1016/j.jmsy.2017.10.005Saunders, M., Lewis, P., & Thornhill, A. (2009). Understanding research philosophies and approaches. Research methods for business students, 4, 106-135.Saunders, M. N. (2011). Research methods for business students, 5/e: Pearson Education India.Serrano Lasa, I., Ochoa Laburu, C., & de Castro Vila, R. (2008). An evaluation of the value stream mapping tool. Business process management journal, 14(1), 39-52. https://doi.org/10.1108/14637150810849391Seth, D., & Gupta, V. (2005). Application of value stream mapping for lean operations and cycle time reduction: an Indian case study. Production Planning & Control, 16(1), 44-59. https://doi.org/10.1080/09537280512331325281Sharifi, H., & Zhang, Z. (2001). Agile manufacturing in practice ‐ Application of a methodology. International Journal of Operations & Production Management, 21(5/6), 772-794. https://doi.org/10.1108/01443570110390462Sindhwani, R., & Malhotra, V. (2017). A framework to enhance agile manufacturing system. Benchmarking: An International Journal. https://doi.org/10.1108/BIJ-09-2015-0092Singh, B., Garg, S. K., & Sharma, S. K. (2011). Value stream mapping: literature review and implications for Indian industry. The International Journal of Advanced Manufacturing Technology, 53(5-8), 799-809. https://doi.org/10.1007/s00170-010-2860-7Srichuachom, U. (2015). The impact of lean approaches to support quality developments in Thailand: an investigation of a claim of universality of lean thinking. University of Southampton.Sriparavastu, L., & Gupta, T. (1997). An empirical study of just‐in‐time and total quality management principles implementation in manufacturing firms in the USA. International Journal of Operations & Production Management, 17(12), 1215-1232. https://doi.org/10.1108/01443579710182954Sundar, R., Balaji, A. N., & Kumar, R. M. S. (2014). A Review on Lean Manufacturing Implementation Techniques. Procedia Engineering, 97, 1875-1885. https://doi.org/10.1016/j.proeng.2014.12.341Swank, C. K. (2003). The Lean Service Machine. Harvard Business Review, 9.Tao, F., & Zhang, M. (2017). Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE Access, 5, 20418-20427. https://doi.org/10.1109/ACCESS.2017.2756069TER JI-XI, J. (2013). Object Locator for People With Dementia (DEMICATOR). Universiti Teknikal Malaysia Melaka.Vonderembse, M. A., Uppal, M., Huang, S. H., & Dismukes, J. P. (2006). Designing supply chains: Towards theory development. International Journal of Production Economics, 100(2), 223-238. https://doi.org/10.1016/j.ijpe.2004.11.014Waters, C. D. J. (2007). Supply chain risk management: vulnerability and resilience in logistics. London ; Philadelphia: Kogan Page.Womack, J. P., & Jones, D. T. (1996). Beyond Toyota: How to Root Out Waste and Pursue Perfection. 13.Womack, J. P., Jones, D. T., & Roos, D. (1990). The Machine That Changed The World. New York, NY: Rawson Associates.Yadav, G., Luthra, S., Huisingh, D., Mangla, S. K., Narkhede, B. E., & Liu, Y. (2020). Development of a lean manufacturing framework to enhance its adoption within manufacturing companies in developing economies. Journal of Cleaner Production, 245, 118726. https://doi.org/10.1016/j.jclepro.2019.118726Yahaya, S.M.B. (201

Factors associated with pregnancy complications during antenatal period: an extended GEE approach

The purpose of the paper is to examine the factors affecting pregnancy complications during antenatal period of mothers. The study uses data which have been repeated over time i.e., the nature of the data is longitudinal in type. Thus the generalized estimating equation (GEE) method has been employed to identify the factors associated with the pregnancy complications which constitute binary response. The study reveals important findings. Among others, education of mothers, taking special food during pregnancy and desired index pregnancy are found to be negatively associated with pregnancy related complications i.e., lower risk of complication. Patients visit to health workers during antenatal period is positively associated with identifying the causes of pregnancy related complications. Female literacy and maternal morbidity are intertwined in an inverse relationship i.e., improving the former will reduce the latter. Educated women take better care of themselves. It improves their economic power and ensures a better social and legal status. Pregnant women should take special food in order to get rid of pregnancy related complications

Study and Design of a Capacitively Coupled Polymeric Internal Antenna

A capacitively coupled polymeric internal antenna is introduced for Bluetooth or GPS applications. Such an antenna can be easily fabricated on a flexible film substrate and attached to the inside surface of the plastic housing of a portable wireless device; such as a PDA. The proposed antenna saves critical space on the printed circuit board (PCB) and eliminates the need for a vertical contact feed. Thus manufacturing is also simplified and cost is reduced. Practical examples of utilizing such a concept for Bluetooth (2.45 GHz) and GPS (1.575 GHz) applications are provided. The antenna system requires a small coupling plate (as small as 4 by 4 mm(2)) that can be easily surface mounted on a PCB. The solution proposed provides wideband operation satisfying Bluetooth functionality with good radiation pattern and gain

Psychological impact of COVID-19 pandemic on health care workers of tertiary care hospit

Healthcare workers (HCWs) are at increased risk of mental health issues when faced with the challenges associated with pandemics. This study was conducted to assess the psychological impact of pandemic o n HCWs working in tertiary care hospitals of Khyber-Pakhtunkhwa province of Pakistan. This cross-sectional study was conducted between April & June 2020. By convenience sampling an electronic form of Goldberg General Health Questionnaire was distributed among HCWs of the private sector and public tertiary care hospitals. Data were analyzed using SPSS version 22. Inferential analysis was done. The significant level was considered at p=<0.05. Total of 186 HCWs among which 105 (56.5%) males and 81 (43.5%) females participated in the survey, a mean age of 37.6±9.28 years. The highest prevalence was found for social dysfunction 184 (97.8%) followed by somatization, 169 (92.8%). Significance of difference was found between age group and anxiety (p=0.018), specialty of HCWs with somatization and social dysfunction (p=0.041 and 0.037 respectively). Pandemic poses a significant risk for the mental health of HCWs. During pandemics at its peak, proper mental health support program, personal and family protection assurance is highly recommended for provision of quality care by HCWs

Design and analysis of strut-based lattice structure cranial implant

A specialized medical cranioplasty procedure entails the use of implants of various materials, forms, and sizes. Computational technologies such as modelling and simulation, have refined the technique for creating these implants catering to patient specific needs. Superior qualities of lattice structures have considerable usage in implants. This study mainly focuses on three distinct types of strut-based lattice structures, Octet, Diamond, and Kelvin, for constructing cranial implant models using CAD tools like Solidworks and nTopology. Titanium alloy (Ti6Al4V) is used to test the behaviour of the designed implants in two cases: impact of external force and increase in intracranial pressure. Level of porosity is compared to determine extent of porosity of these implants, as porosity is significant in osseointegration. According to the study, these lattice structures give satisfactory results and can be utilized to make the implant more porous while satisfying the load bearing capacity

Bi-allelic Variants in METTL5 Cause Autosomal-Recessive Intellectual Disability and Microcephaly

Contains fulltext : 208970.pdf (publisher's version ) (Open Access