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Volume-4 Issue-8, January 2015, ISSN:  2278-3075 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

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Xiaohong Wang, Jiayin Wang

Paper Title:

Vascularization and Adipogenesis of a Spindle Hierarchical Adipose-Derived Stem Cell/Collagen/ Alginate-PLGA Construct for Breast Manufacturing

Abstract:  The creation of vascularized adipose tissues is a subject of broad fundamental and technological interest in implantable breast manufacturing. Here, we demonstrated a simple, easy, and effective way to fabricate a spindle hierarchical poly(DL-lactic-co-glycolic acid) (PLGA) encapsulated adipose-derived stem cell (ADSC)/collagen/alginate construct with a multiple-branched vascular network using a rotational combined mould system (RCMS). Both the optimized PLGA overcoat and internal collagen/alginate hydrogel provided the ADSCs with a stable and comfortable accommodation to grow, proliferate, and differentiate. Cell viability remained at a comparatively high level during 4 weeks in vitro engagement with two groups of cell growth factor combinations. At the end of the second week, part of the cells were engaged into endothelial cells, while at the end of the fourth week more than 63% of the ADSCs were replaced by adipose cells. We envisage that this RCMS, vascularization and adipogenesis techniques will provide an enabling platform for a wide array of research and clinical applications.

Vascularization; adipogenesis; a rotational combined mould system; adipose-derived stem cells (ADSCs); collagen/alginate hydrogel


1.          Cui T, Yan Y, Zhang R, Xu M, & Wang X. (2010). Progress in development of vascularized adipose tissues. Journal of Mechanical Engineering. 46:99-104.
2.          Wang XH. (2012). Intelligent freeform manufacturing of complex organs. Artif Organs. 36: 951-961.

3.          Wang XH, Yan YN, & Zhang RJ. (2010). Recent trends and chanllenges in complex organ manufacturing. Tissue Eng Part B.;16:189-197.

4.          Wang XH, Yan YN, & Zhang RJ. (2007). Rapid prototyping as a tool for manufacturing bioartificial livers. Trends Biotechnol. 25:505-513.

5.          Wang X. (2014). Spatial effects of stem cell engagement in 3D printing constructs. J Stem Cells Res Rev & Rep. 1; 5-9.

6.          Xu YF, & Wang XH. 3D biomimetic models for drug delivery and regenerative medicine. Curr Pharm Des, in press.

7.          Liu LB, Zhou XW, Xu YF, Zhang WM, Liu C-H, & Wang XH. Controlled release of growth factors for regenerative medicine. Curr Pharm Des, in press.

8.          Radisic M, Yang LM, Boublik J, Cohen RJ, Langer R, Freed LE, & Vunjak-Novakovic G. (2004). Medium perfusion enables engineering of compact and contractile cardiac tissue. Am J Physiol Heart Circ Physiol. 286:H507-516.

9.          Colton C. (1955). Implantable biohybrid artificial organs. Cell Transplant. 4:415-436.

10.       Vunjak-Novakovic G, & Scadden DT. (2011). Biomimetic platforms for human stem cell research. Cell Stem Cell. 8:252-261.

11.       Choi NW, Cabodi M, Held B, Gleghorn JP, Bonassar LJ, & Stroock AD. (2007). Microfluidic scaffolds for tissue engineering. Nat Mater. 6:908-915.

12.       Therriault D, White SR, & Lewis JA. (2003). Chaotic mixing in three-dimensional microvascular networks fabricated by direct-write assembly. Nat Mater. 2:265-271.

13.       Yeong, W-Y, Chua C-K, Leong F-F, Chandrasekaran M, & Lee M-W. (2006). Indirect fabrication of collagen scaffold based on inkjet printing technique. Rapid Prototyping J. 12:229-337.

14.       Lim D, Kamotani Y, Cho B, Mazumder J, & Takayama S. (2003). Fabrication of microfluidics mixers and artificial vasculatures using a high-brightness diode-pumped Nd:YAG laser direct write method. Lab Chip. 3:318-323.

15.       Li SJ, Xiong Z, Wang XH, Yan YN, Liu HX, & Zhang RJ. (2009). Direct fabrication of a hybrid cell/hydrogel construct via a double-nozzle assembling technology. J Bioact Compa Polym. 24:249-264.

16.       Huang YW, He K, & Wang XH. (2013). Rapid Prototyping of a hybrid hierarchical polyurethane-cell/hydrogel onstruct for regenerative medicine. Mater Sci Eng C. 33:3220-3229.

17.       Wang XH, Yan YN, & Zhang RJ. (2010). Gelatin-based hydrogels for controlled cell assembly. In: Ottenbrite RM (ed.) Biomedical Applications of Hydrogels Handbook. New York: Springer. 269-284.

18.       Wang XH, Tuomi J, Mäkitie AA, Paloheimo K-S, Partanen J, & Yliperttula M. (2013). The integrations of biomaterials and rapid prototyping techniques for intelligent manufacturing of complex organs. In: Lazinica R (ed.) Advances in biomaterials science and applications in biomedicine. InTech. pp437-463.

19.       Wang XH, & Zhang QQ. (2011). Overview on “Chinese-Finnish workshop on biomanufacturing and evaluation techniques”. Artif Organs. 35:E191-193.

20.       Wang XH. (2013). Overview on biocompatibilities of implantable biomaterials. In: Lazinica R (ed.) Advances in biomaterials science and applications in biomedicine. InTech. 111-155.

21.       Risau W, Flamme I. & Vasculogenesis. (1995). Annu Rev Cell Dev Biol. 11:73-91.

22.       Stoppato M, Stevens HY, Carletti E, Migliaresi C, Motta A, & Guldberg RE. (2013). Effects of silk fibroin fiber incorporation on mechanical properties, endothelial cell colonization and vascularization of PDLLA scaffolds. Biomaterials. 34:4573-4581.

23.       Sahota PS, Burn JL, Heaton M, Freedlander E, Suvarna SK, Brown NJ, & Mac Neil S. (2003). Development of a reconstructed human skin model for angiogenesis. Wound Repair Regen. 11:275-284.

24.       Laschke MW, Strohe A, Scheuer C, Eglin D, Verrier S, Alini M, Pohlemann T, & Menger MD. (2009). In vivo biocompatibility and vascularization of biodegradable porous polyurethane scaffolds for tissue engineering. Acta Biomaterialia. 5:1991-2001.

25.       Kinnaird T, Stabile E, Burnett MS, Shou M, Lee CW, Barr S, Fuchs S, & Epstein SE. (2004). Local delivery of marrow-derived stromal cells augments collateral perfusion through paracrine mechanisms. Circulation. 109:1543-1549.

26.       Laschke MW, Schank TE, Scheuer C, Kleer S, Schuler S, Metzger W, Eglin D, Alini M, & Menger MD. (2013). Three-dimensional spheroids of adipose-derived mesenchymal stem cells are potent initiators of blood vessel formation in porous polyurethane scaffolds. Acta Biomaterialia. 9:6876-6884.

27.       He K, & Wang XH. (2011). Rapid prototyping of tubular polyurethane and cell/hydrogel construct. J Bioact Compat Polym. 26:363-374.

28.       Zhao XR, & Wang XH. (2013). Preparation of an adipose-derived stem cell/fibrin-poly (D, L-lactic-co-glycolic acid) construct based on a rapid prototyping technique. J Bioact Compat Polym. 28:191-203.

29.       Zhao XR, Liu LB, Wang JY, Xu YF, Zhang WM, Khang G, & Wang XH. (2014). In vitro vascularization of a combined system based on a 3D printing technique. J Tissue Eng Regen Med. DOI: 10.1002/term.1863.

30.       Bhadriraju K, & Chen CS. (2002). Engineering cellular microenvironments to improve cell-based drug testing. DDT. 7:612-620.

31.       Díaz-Prado S, Muiños-López E, Hermida-Gómez T, Fuentes-Boquete I, Esbrit P, Buján J, De Toro FJ, & Blanco FJ. (2012). Type I Collagen and heparan sulfate scaffolds support human chondrogenesis for cartilage tissue engineering. Osteoarthritis and Cartilage. 20:S271-272.

32.       Gumbiner BM. (1996). Cell adhesion: the molecular basis of tissue architecture and morphogenesis. Cell. 84:345-357.

33.       Wang XH, & Sui SC. (2011). Pulsatile culture of a poly(DL-Lactic-co-glycolic acid) sandwiched cell/hydrogel construct fabricated using a step-by-step mould/extraction methods. Artif Organs. 35:645-655.

34.       Cui TK, Yan YN, Zhang R, Liu L, Xu W, & Wang XH. (2009). Rapid prototyping a new polyurethane-collagen conduit and its Schwann cell compatibility. J Bioact Compat Polym. 24(S1):5-7.

35.       Xu W, Wang XH, Yan YN, & Zhang R. (2008). Rapid Prototyping of Polyurethane for the Creation of Vascular Systems. J Bioact Compat Polym. 23:103-114.

36.       Yan YN, Wang XH, Yin DZ, & Zhang RJ. (2007). A New Polyurethane/Heparin Vascular Graft for Small-caliber Vein Repair. J Bioact Compat Polym. 22:323-341.






A. Arunitha, T. Gunasekaran, N. Senthil Kumar, N. Senthilvel

Paper Title:

Adaptive Beam Forming Algorithms for MIMO Antenna

Abstract: MIMO antenna is a combination of multiple antenna elements. It has a signal processing capability to optimize its radiation reception pattern which automatically change in response to the signal environment. This paper provides comprehensive review on various evolutionary algorithms which are used for adaptation. The weights of the smart antenna array are adapted to maximize the output in desired direction and minimize the signals in undesired direction. Adaptive beam forming algorithm is used for track corresponding users automatically. This paper discuss about  Non-blind beam forming algorithm i.e.. Least Mean Square, and Blind beam forming algorithm i.e.. Constant Modulus Algorithm and Sample Matrix Inversion. The algorithms are simulated for MIMO environment by using MATLAB. Beam forming can be used for either radio or sound waves. It has found numerous applications in radar, sonar, seismology, wireless communication, radio astronomy, speech and biomedicine.

 Smart antenna, Beam forming, Least Mean Square, Constant Modulus Algorithm , Sample Matrix Inversion.


1.       Amara prakasa Rao, N.V.S.N.Sarma, “Adaptive Beamforming for Smart Antenna Systems” WSEAS Transactions on Communication, E-ISSN:2224-2864, Volume 13,2014.
2.       Balasem. S.S, S.K.Tiong, S. P. Koh," Beam forming Algorithms Technique by Using MVDR and LCMV, " International E-Conference on Information Technology and Applications (IECITA) 2012.

3.       L.C. Godara, Applications of Antenna Arrays to Mobile Communications. Part I: Performance Improvement, Feasibility and System considerations, Proc. IEEE, Vol.85, No.7, pp. 1031–1060.

4.       Liaqat  Ali,  Anum  Ali,  Anis-ur-Rehman, "Adaptive Beam forming  Algorithms  for  Anti-Jamming," International  Journal  of  Signal Processing, Image Processing and Pattern Recognition Vol. 4, No. 1, March. 2011.

5.       Nwalozie, V.N Okorogu, S.S Maduadichie, A. Adenola," A Simple Comparative Evaluation of Adaptive Beam forming Algorithms," in International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 7, January 2013.

6.       Ramakrishna, K.Ramanjaneyulu, "A Novel Adaptive Beam forming RLMS Algorithm for    Smart Antenna System," International Journal of Computer Applications (0975 – 8887)Volume 86 – No 5, January 2014.

7.       Shankar Ram, Susmita Das, “A Study of Adaptive Beamforming Techniques Using Smart Antenna For Mobile Communication” 2007.

8.       Shu-Hung Leung and C.F. So. Gradient-based variable forgetting factor rls algorithm in time-varying environments. Signal Processing, IEEE Transactions on, 53(8):3141 – 3150, 2005






Archana Singh Sikarwar, Denishvaran Jaya Gopal

Paper Title:

A Review on Antibiotic Drug Resistance in Escherichia Coli

Abstract:  Antibiotic drug resistance to Escherichia coli is an emerging issue for healthcare which causes public health problems and outbreak worldwide. Antibiotic resistant of E.coli can cause community and hospital acquired infections. Uses of broad spectrum antibiotics, inadequate aseptic techniques and improper infection control measures had worsen the emergence of antibiotic resistance of E.coli. Emergence of antibiotic resistant E.coli is a major challenge to healthcare provider to create newer, better and more efficient antibiotics. Infection control measures should be taken by healthcare provider to control emergence and spread of antibiotic resistant E.coli.  Further researches are needed to evaluate the available antibiotic drugs, agent and identify new drugs that can solve the issue of antibiotic resistant emergence.

  Antibiotic drug resistance, Escherichia coli, infections


1.       Aibinu IE, Peters RF, Amisu KO, Adesida SA, Ojo MO, Odugbemi T, Multidrug Resistance in E.coli 0157 Strains and the Public Health Implication. The Journal of American Science. 2007; 3(3):22-33
2.       Sharma S, Bhat GK, Shenoy S. Virulence factors and drug resistance in Escherichia coli isolated from extra intestinal infections. Indian J Med Microbiol 2007; 25:369-73.

3.       Jan N, Meshram SU, Kulkarni A. Plasmid profile analysis of multidrug resistant E. coli isolated from UTI patients of Nagpur City, India. Rom. Biotechnol. Lett. 2009; 14(5): 4635-4640.

4.       Samaha-Kfoury JN, Araj GF. Recent developments in beta lactamases and extended spectrum beta lactamases. BMJ. 2003; 327:1209-1213.

5.       Majiduddin FK, Materon IC, Palzkill TG. Molecular analysis of beta-lactamase structure and function. Int J Med Microbiol. 2002; 292(2):127-37.

6.       Al-Jasser AM. Extended-Spectrum Beta-Lactamases (ESBLs): A Global Problem. Kuwait Med J 2006, 38(3): 171-185.

7.       Lautenbach E, Patel JB, Bilker WB, Edelstein PH, Fishman NO.Extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae: risk factors for infection and impact of resistance on outcomes. Clin Infect Dis. 2001; 32(8):1162-71.

8.       Rupp ME, Fey PD. Extended spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae: considerations for diagnosis, prevention and drug treatment. Drugs. 2003; 63(4):353-65.

9.       Shah AA, Hasan F, Ahmed S, Hameed A. Extended-spectrum beta-lactamases (ESbLs): characterization, epidemiology and detection. Crit Rev Microbiol. 2004; 30(1):25-32.

10.    Colodner R. Extended-spectrum beta-lactamases: a challenge for clinical microbiologists and infection control specialists. Am J Infect Control. 2005; 33(2):104-7.

11.    Turner PJ. Extended-Spectrum b-Lactamases. CID 2005; 41:S273–5.

12.    Shah A A, Hasan F, Ahmed S, Hameed A. Extended-spectrum beta-lactamases (ESbLs): characterization, epidemiology and detection. Crit Rev Microbiol. 2004; 30(1):25-32.

13.    Tschudin-Sutter S, Frei R, Battegay M, Hoesli I, Widmer AF. ExtendedSpectrum β-Lactamase–producing Escherichia coli in Neonatal Care Unit. Emerg Infect Dis. 2010; 16(11):1758-1760.

14.    Paterson DL, Singh N, Rihs JD, Squier C, Rihs BL, Muder RR. Control of an outbreak of infection due to extended-spectrum beta-lactamase--producing Escherichia coli in a liver transplantation unit. Clin Infect Dis. 2001;33(1):126-8.

15.    Bhusal Y, Mihu CN, Tarrand JJ, Rolston KV. Incidence of Fluoroquinolone-Resistant and Extended-Spectrum β-Lactamase-Producing Escherichia coli at a Comprehensive Cancer Center in the United States. Chemotherapy. 2011; 57(4):335-338.

16.    Strausbaugh LJ, Siegel JD, Weinstein RA. Preventing Transmission of Multidrug-Resistant Bacteria in Health Care Settings: A Tale of Two Guidelines. Clin Infect Dis. 2006; 42(6):828-835

17.    Fraimow HS, Tsigrelis C. Antimicrobial Resistance in the Intensive Care Unit: Mechanism, Epidermiology, and Management of specific Resistant Pathogens. Crit Care Clin 27. 2011;27(1):163–205.

18.    Fridkin SK, Gaynes RP. Antimicrobial resistance in intensive care units. Clin Chest Med. 1999; 20(2):303-16.

19.    Wu CJ, Hsueh PR, Ko WC. A new health threat in Europe: Shiga toxin-producing Escherichia coli O104:H4 infections. J Microbiol Immunol Infect. 2011.
20.    Rasko DA, Webster DR, Sahl JW, Bashir A, Boisen N, Scheutz F, Paxinos EE, Sebra R, Chin CS, Iliopoulos D, Klammer A, Peluso P, Lee L, Kislyuk AO, Bullard J, Kasarskis A, Wang S, Eid J ,Rank D, Redman JC, Steyert SR, Frimodt-Møller J, Struve C, Petersen AM, Krogfelt KA, Nataro JP, Schadt EE, Waldor MK Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. N Engl J Med. 2011; 365(8):709-17.
21.    Outbreaks of E. coli O104:H4 infection. 2011 July [cited 2011 September 19, online].

22.    Frank C, Werber D, Cramer JP, Askar M, Faber M, Heiden MA, Bernard H, Fruth A, Prager R, Spode A, Wadl M, Zoufaly A, Jordan S, Stark K, Krause G. Epidemic Profile of Shiga-Toxin, Producing Escherichia coli O104:H4 Outbreak in Germany - Preliminary Report. N Engl J Med. 2011. 

23.    Falagas ME, Karageorgopoulos DE. Extended-spectrum beta-lactamase-producing organisms. J Hosp Infect. 2009; 73(4):345-54.

24.    Bush K, Jacoby GA. Updated functional classification of beta-lactamases. Antimicrob Agents Chemother. 2010; 54(3):969-76.





Pritesh R. Gumble, S.A. Ladhake

Paper Title:

Design of Low Power Optimized Filter Architecture using VLSI Technique

Abstract:   In the prevalence of DSP applications the weighted operations are the multiplication and accumulation. Multiplier-Accumulator (MAC) unit that consumes low power is always a means to accomplish a high concert digital signal processing system. Finite impulse response (FIR) filters are widely used in various DSP applications where signal were present with noise (e.g. data converters). Uptill many proficient techniques have been introduced for the design of low snag bit-parallel multiple constant multiplications (MCM) process which reduces the intricacy of many digital signal processing systems. On the other hand, digit-serial adder architectures present remarkable n-bit designs which process dynamic size data, since digit-serial operators hold less area and power. The purpose of this work is to design and implementation of low power optimized digital Finite impulse response (FIR) filter architecture using VLSI technique. We design and analyze 1] Direct form 2] Transpose form 3] Transpose using MCM 4] Transpose using digit serial adder 5] Transpose using MCM and digit serial adder. Experimental results shows the efficiency of the various architectures and we found best performance results of Transpose using MCM and digit serial adder design in terms of area and power. To execute this work the design is verified using Active-HDL with MATLAB and synthesis [45nm] using Synopsys.

 digit- serial adder architecture, FIR, Low Power, MAC, MCM.


1.       Keshab K. Parhi, and Ching-Yi Wang, “Digit-Serial DSP Architectures” International Conference on Application Specific Array Processors, pp.  341-351.
2.       Yun-Nan Chang, Janardhan H. Satyanarayana, and Keshab K. Parhi, “Systematic Design of High-Speed and Low-Power Digit-Serial Multipliers” IEEE Transactions On Circuits And Systems—II: Analog And Digital Signal Processing, Vol. 45, No. 12, December 1998, pp. 1585-1596.
3.       Ahmed Shahein, , Qiang Zhang, Niklas Lotze, and Yiannos Manoli, “ A Novel Hybrid Monotonic Local Search Algorithm For Fir Filter Coefficients Optimization”  IEEE Transactions On Circuits And Systems—I: Regular Papers, Vol. 59, No. 3, March 2012, pp. 616-627.
4.       Levent Aksoy and Cristiano Lazzari, Eduardo Costa, Paulo Flores and Jose Monteiro, “Optimization of Area in Digit-Serial Multiple Constant Multiplications at Gate-Level”, pp. 2737-2740.

5.       Mustafa Aktan, Arda Yurdakul, and Günhan Dündar, “An Algorithm for the Design of Low-Power Hardware-Efficient FIR Filters”, IEEE Transactions On Circuits And Systems—I: Regular Papers, Vol. 55, No. 6, July 2008, pp. 1536-1545.

6.       Levent Aksoy, Cristiano Lazzari, Eduardo Costa,  Paulo Flores, and José Monteiro, “Design Of Digit-Serial FIR Filters: Algorithms, Architectures, And A CAD Tool”, IEEE Transactions On Very Large Scale Integration (VlSI) Systems, pp. 1-14 

7.       Chi-Jui Chou, Satish Mohanakrishnan, Joseph B.Evans “Fpga Implementation Of Digital Filters” Proc. Icspat ’93

8.       Bahman Rashidi and Majid Pourormazd ” Design and implementation of low power Digital FIR Filter based on low power multipliers and adders on Xilinx FPGA ,” IEEE Publications, 2011.

9.       Pritesh R. Gumble, Dr. S.A. Ladhake “ Architecture For High Performance, Low Power Data Converter And Filter, In Deep Submicron CMOS Technology”, International Journal of Computing and Corporate Research, ISSN2249054X-V212M5-032012 Volume 2 Issue 2 March 2012.

10.    Shanthala S, S. Y. Kulkarni, “VLSI Design and Implementation of Low power MAC unit with Block Enabling Technique ,“ Eurojournals Publishing Inc.2009

11.    Nadia Khouja , Khaled Grati, Adel Ghazel ”Low Power implementation of Decimation Filters in Multistandard Radio Receiver Using optimized Multiplication–Accumulation Unit ,“,IEEE Publications, 2007.

12.    Q. F. Zhao and Y. Tadokoro, “A simple design of FIR filters wit Power-of-two coefficients,” IEEE Trans. Circuits Syst., vol. 35, no. 5.

13.    S Salivahanan, A Vallavaraj, C Gnanapriya, “ A text book of Digital Signal Processing”, Tata McGraw-Hill Publication, pp. 453-514

14.    K.K. Parhi, “VLSI digital signal processing system”.

15.    Volnei A. Pedroni, “ Circuit Design with VHDL”, PHI publication, pp. 275-303






Komal K. Maheshkar, Dhiraj G. Agrawal

Paper Title:

Campus Access Management System via RFID

Abstract: For colleges where security is vital and access to certain areas of campus must be controlled & monitored, there should be some access control system that allows college administration to manage and monitor all access points & locks centrally and remotely, allowing for auditable security & quick responses to any security breaches. Campus Access Management System (CAMS) via Radio-Frequency Identification (RFID) allows only authorized persons i.e. student, teacher or an employee to enter a particular area of the college campus. The authorized persons are provided with unique RFID Tag & its PIN code, using which they can access that area. The system is designed using Peripheral Interface Controller (PIC) Microcontroller MICROCHIP-16F877 and comprises of RFID module (Tag+Reader), Keypad for entering access code an (Liquid Crystal Display) LCD module for displaying “name” of the authorized person & a relay for opening the door for him. For an unauthorized person door remains closed and buzzer alarms with indication as “invalid card” on LCD Display [1]. The data from RFID reader is transmitted to a Centralized Remote Computer or Server located in the administrative office of the college through a RS-232 interface. The centralized server determines the authorization & access control rights. The entire program code is written in Microsoft Visual Basic 6.0 Software.

 Inductive couplings, PIC controller, RFID reader, RFID Tag.


1.       Bikramjeet waraich, “RFID-BASED SECURITY SYSTEM”, EFY (Electronics For You), pp.102-105, December 2010.
2.       K.Shrinivasa Ravi, G.H.Vrun, T. Vamsi, P. Pratuksha, “RFID Based Security System”, IJITEE (International Journal of Innovative Technology and Exploring Engineering), ISSN: 2278-3075, vol.2, issue.5, pp.132-134, April 2013.

3.       Unnati A. Patel, “Student Management System based on RFID Technology”, IJETTCS (International Journal of Emerging Trends & Technology in Computer Science), ISSN: 2278-6856, vol.2, issue. 6, pp.173-178, November – December 2013.

4.       Mandeep Kaur, Manjeet Sandhu,Neeraj Mohan and Parvinder S. Sandhu, “RFID Technology Principles,Advantages,Limitations & Its Applications”,IJCEE (International Journal of Electrical Engineering), ISSN:1793-8163,Vol.3,No.1, pp.151-157, February 2011.






A. Ali, R. Hussain, F. Kappel


Paper Title:

Resonance Effect in Dynamic of the Mathematical Model for Baroreceptor

Abstract:  The  best  known  nervous  mechanism  for  control  of  arterial  pressure  is  the baroreceptor  loop.  To  simulate  some  fundamental  regulation  processes  mathematical model  is  used  which approximate  the  short-term  behavior  of  the  baroreceptor. The most important short term properties of baroreceptor in a clear mathematical  model  is presented in [2]. This model  is  applies  in  the  dynamic  features  of  the  human  system.  The goal of our work is to see the resonance effect in the dynamic of the baroreceptor model presented in [2].

 baroreceptor, mechanism, fundamental, mathematical model.


1.       M. Scher , D. S. O. O Leary, D. D. Sheriff, Arterial baroreceptor regulation of peripheral resistance and of cardiac performance ,in "Baroreceptor Reflexes "(P. B. Persson. H. R. Kirchbeim, Eds) Springer Verlag, Berlin 1991.
2.       Urbaszek.  H.  Hutten,  and  M.  Schaldach  odell  des  menschlichen,Blutkreislaufs und  der  Herzfunktion  mit  Schwerpunkt  auf  Kurzzeitigen,  Regulationsvorgangen, Boimedizinische  Technik 36 (Erganzungsband 1) (1991), 260-261.

3.       G. N. Franz nonlinear rate sensitivity of the carotid sinus reflex as a consequence of static and dynamic nonlinearity in baroreceptor behaviour, Ann. N.Y.156 (1969)  811-824.

4.       H.Drischel,Einfuhrung in the Biokybernetik,Academie Verlag,Berlin 1973.

5.       H. M. Coleridge ,J. G. G. Coleridge, M. P. Kaufman, A, Dangel, Operational sensitivity and cute resetting of aortic Baroreceptors in dogs, circ. Res. 48(1981), 676-684.

6.       Textbook of Medical Physiology, W. B. Saunders, London 1981.






R. Hussain, A. Ali, N. Arif

Paper Title:

Stability Analysis of Mathematical Model Comparing Solute Kinetics in Low & High Hemodialysis Patients

Abstract:   This paper is about the stability analysis of model, which we have taken from “The mathematical model comparing solute kinetics in low- and high-BMI hemodialysis patients” [2]. The purpose of this study is to check the stability of three types of patients i.e small medium and large during dialysis and in between the dialysis treatment. In all cases we get the stable solution for above model presented in [2].

 Stability analysis, hemodialysis, mathematical    modeling.


1.          D. Cronin-Fine, F. Gotch, N. Levin, P. Kotanko, M.    Lysaght, A Mathematical Model Comparing Solute Kinetics in Low- and High BMI Hemodialysis Patients. Internatl. J. Artificial Organs(30)(11) (2007), 1000-1007.
2.          F. Kappel, J. Batzal , M. Bacher , and P.Kotanko A Mathematical Model Comparing Solute Kinetics in Low- and High-BMI Hemodialysis Patients, March 11, (2009).

3.          J. J. Batzal and F. Kappel and H. T. Tran and D. Schneditz, Cardiovascular and Respiratory Systems: Modeling, Analysis and Control, Siam, Philadelphia (2006).

4.          P. Hartman, A lemma in the Theory of Structural Stability of Differential Equations, Proceedings of the AMS 11(1960) 610-620.

5.          P. Howard, Analysis of ODE Models, fall 2009.

6.          P. Howard, Modelling with ODE, Available at www.math.tamu.edu~/phoward/M442.html

7.          R. Hussain, A. Ali, S.Nasar, Mathematical Model of Dialysis: Stable and Unstable Solution. Mirpur University of Science and Technology.    (Submitted paper)

8.          R. Hussain, F. Kappel, Fansan Zhu, Nathan W. Levin and Peter. Kotanko, Body Composition and Solute Kinetics in Hemodialysis Patients: A Mathematical Model.

9.          S. Beddhu and L. M. Pappas and N. Ramkumar and M. Samore, Effect of Body Size and Body Composition on Survival in Hemodialysis Patients, J Am Soc Nephrol 14 (2003),2366-2372.

10.       Schneditz, D. and Daugridas, J. T. (2001). Compartment Effect in Hemodialysis. Semin Dial, Vol. 14, No. 4, pp. (271-7).

11.       www.math.tamu.edu~/phoward/M442.html

12.       Yon-Ping Chen, 8.Phase Plane Method, NCTU Department of Electrical and Computer Engineering Senior Course <Dynamic System Analysis and Simulation>.

13.       Zachary S. Tseng 2008. Phase Plane.

14.       Ziolko, M. Pietrzyk, J. A. and Grabska- Chrzastowaska, J. (2000). Accuracy of Hemodialysis Modeling. Kidney Int, Vol. 57, No. 3, pp. (1152-63).