Browsing by Author "Dinesh Kumar"

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A Bacteriophage Microgel Effectively Treats the Multidrug-Resistant Acinetobacter baumannii Bacterial Infections in Burn Wounds
(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Deepa Dehari; Aiswarya Chaudhuri; Dulla Naveen Kumar; Rohit Patil; Mayank Gangwar; Sonam Rastogi; Dinesh Kumar; Gopal Nath; Ashish Kumar Agrawal
Multidrug-resistant (MDR) Acinetobacter baumannii (A. baumannii) is one of the major pathogens present in burn wound infections. Biofilm formation makes it further challenging to treat with clinically available antibiotics. In the current work, we isolated the A. baumannii-specific bacteriophages (BPABΦ1), loaded into the chitosan microparticles followed by dispersion in gel, and evaluated therapeutic efficacy against MDR A. baumannii clinical strains. Isolated BPABΦ1 were found to belong to the Corticoviridae family, with burst size 102.12 ± 2.65 PFUs per infected host cell. The BPABΦ1 loaded chitosan microparticles were evaluated for quality attributes viz. size, PDI, surface morphology, in vitro release, etc. The developed formulation exhibited excellent antibiofilm eradication potential in vitro and effective wound healing after topical application. © 2023 by the authors.
A Bacteriophage-Loaded Microparticle Laden Topical Gel for the Treatment of Multidrug-Resistant Biofilm-Mediated Burn Wound Infection
(Springer Science and Business Media Deutschland GmbH, 2023) Deepa Dehari; Aiswarya Chaudhuri; Dulla Naveen Kumar; Meraj Anjum; Rajesh Kumar; Akshay Kumar; Dinesh Kumar; Gopal Nath; Ashish Kumar Agrawal
Klebsiella pneumoniae is regarded as one of the most profound bacteria isolated from the debilitating injuries caused by burn wounds. In addition, the multidrug resistance (MDR) and biofilm formation make treating burn patients with clinically available antibiotics difficult. Bacteriophage therapy has been proven an effective alternative against biofilm-mediated wound infections caused by MDR bacterial strains. In the current study, the bacteriophage (BPKPФ1) against MDR Klebsiella pneumoniae was isolated and loaded into the chitosan microparticles (CHMPs), which was later incorporated into the Sepineo P 600 to convert into a gel (BPKPФ1-CHMP-gel). BPKPФ1 was characterized for lytic profile, morphological class, and burst size, which revealed that the BPKPФ1 belongs to the family Siphoviridae. Moreover, BPKPФ1 exhibited a narrow host range with 128 PFU/host cell of burst size. The BPKPФ1-loaded CHMPs showed an average particle size of 1.96 ± 0.51 μm, zeta potential 32.16 ± 0.41 mV, and entrapment efficiency in the range of 82.44 ± 1.31%. Further, the in vitro antibacterial and antibiofilm effectiveness of BPKPФ1-CHMPs-gel were examined. The in vivo potential of the BPKPФ1-CHMPs-gel was assessed using a rat model with MDR Klebsiella pneumoniae infected burn wound, which exhibited improved wound contraction (89.22 ± 0.48%) in 28 days with reduced inflammation, in comparison with different controls. Data in hand suggest the potential of bacteriophage therapy to be developed as personalized therapy in case of difficult-to-treat bacterial infections. Graphical abstract: [Figure not available: see fulltext.]. © 2023, The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.
A Blockchain Framework for Efficient Resource Allocation in Edge Computing
(Institute of Electrical and Electronics Engineers Inc., 2024) Gaurav Baranwal; Dinesh Kumar; Amit Biswas; Ravi Yadav
Edge computing provides low-latency computing services. Since Edge computing Service Providers (ESPs) are competitors, mutual distrust and distrust towards the platform may exist if a centralized resource allocation platform is used. To address trust issues, we propose a blockchain framework for resource allocation in edge computing that ensures decentralization and transparency in resource allocation. We also offer a novel consensus mechanism for the framework, Proof of Efficient Resource Allocation (PoERA), where ESPs compete to give the best solution to the resource allocation problem to become the leader and earn rewards. The framework addresses the trust issue, single-point failure, and the biased nature of the centralized platform. PoERA includes a novel self-stabilizing leader election algorithm, ensuring no forking, final consensus and consistency, which is lacking in most existing works. The work encourages the participation of both leader and non-leader ESPs by rewarding them based on the quality of their solutions. We perform CAP theorem analysis, demonstrating that Consistency (C) and Availability (A) are more important for the proposed framework than Partition tolerance (P). We conduct experiments to show that the work ensures decentralization, fair competition, and fair reward distribution to miners, eventually improving resource allocation in edge computing. © 2004-2012 IEEE.
A comparative study of traditional and kullback-leibler divergence of survival functions estimators for the parameter of lindley distribution
(Austrian Statistical Society, 2019) Sultan Parveen; Sanjay Kumar Singh; Umesh Singh; Dinesh Kumar
A new point estimation method based on Kullback-Leibler divergence of survival functions (KLS), measuring the distance between an empirical and prescribed survival functions, has been used to estimate the parameter of Lindley distribution. The simulation studies have been carried out to compare the performance of the proposed estimator with the corresponding Least square (LS), Maximum likelihood (ML) and Maximum product spacing (MPS) methods of estimation. © 2019, Austrian Statistical Society. All rights reserved.
A computational solution of a phase-change material in the presence of convection under the most generalized boundary condition
(Elsevier Ltd, 2020) Vikas Chaurasiya; Dinesh Kumar; K.N. Rai; Jitendra Singh
This article presents a mathematical model describing inward melting process of a phase change material in the presence of convection under the most generalized boundary condition. It is assumed that the material within a container have different geometrical configuration like circular cylinder or sphere. All thermophysical properties of the solid and liquid regions are assumed to be homogeneous. Initially, we convert the mathematical model into an initial value problem in the form of vector matrix representation using a finite difference technique. Two numerical methods; the operational matrix of integration for Bessel functions and finite element Legendre wavelet Galerkin method, are applied to solve the initial value problem. Thus, the obtained results from both methods analyzed for constant (or time depending) temperature or constant (or time depending) heat flux. The whole study is presented in dimensionless form. The effect of Stefan number, Peclet number, Kirpichev number and Biot number on dimensionless temperature profile and dimensionless moving front are illustrated graphically. © 2020 Elsevier Ltd
A Mathematical Model for Hyperbolic Space-fractional Bioheat Transfer during Thermal Therapy
(Elsevier Ltd, 2015) P. Kumar; Dinesh Kumar; K.N. Rai
In this paper, we have developed a hyperbolic space-fractional bioheat transfer model based on the single-phase-lagging constitutive relation. The numerical solution of the present problem has been done using fractional backward finite difference scheme and Legendre wavelet Galerkin approach. The effect of fractional parabolic and hyperbolic bioheat transfer model on temperature profile within living biological tissues has been studied and compared with their respective standard cases. Numerical results are presented graphically in both standard and anomalous case for different values of parameters. © 2015 The Authors.
A Multi-Criteria Framework for Smart Parking Recommender System
(Institute of Electrical and Electronics Engineers Inc., 2020) Gaurav Baranwal; Dinesh Kumar; Deo Prakash Vidyarthi
Parking has become a real challenge in cities, especially in metros, due to exponential increase in number of vehicles. A significant amount of time wasted in locating the parking space results in traffic congestion, pollution and fuel consumption. Recommending parking spot is an important service towards intelligent transportation system. Evolution in Internet of Things (IoT), Fog and Cloud Computing, and Sensor technologies can be better utilized to explore parking details such as parking occupancy, traffic congestion in parking path etc. in real time and an efficient and effective Parking Recommender System (PRS) can be designed. Parkers may have different expectations from PRS such as walking distance between the destination and the parking spot, pricing, safety etc. Therefore, a personalized recommender system is warranted in which a parker specifies its preference to various quality parameters related to parking. Considering parkers as human being, uncertainty in decision making over the preference cannot be ruled out. This work proposes a framework for multiple quality parameters/criteria based smart parking spot recommender system. It also provides various quality parameters, related to parking, to help parkers to express their need which helps in recommendation. As the boundaries between the parametric values are not crisp, fuzzy logic is utilized in parking recommender method to handle the uncertainty in human decision making. A case study, along with sensitivity analysis, demonstrates the effectiveness of the proposed model. © 2020 IEEE.
A new asymmetric loss function for estimation of any parameter
(DAV College, 2020) Dinesh Kumar; Pawan Kumar; Pradip Kumar; Umesh Singh; Prashant Kumar Chaurasia
A new asymmetric loss function which is suitable for estimation of location as well as scale and other parameters has been introduced. To check the superiority of the proposed loss function over some existing and exploited loss functions such as squared error loss function (SELF), general entropy loss function (GELF), LINEX loss function and Logarithmic-SELF (LSELF), we have calculated the Bayes estimators of the parameterθ of exponential distribution under SELF, GELF, LINEX loss function, Logarithmic- SELF (LSELF) and the proposed exponential squared error loss function (ESELF) for complete sample from the exponential distribution. A data set has been considered to show its application to the real problems. The simulation study is carried out to compare the performance of Bayes estimators in terms of their posterior risks. © 2020 DAV College. All rights reserved.
A new lifetime distribution: Some of its statistical properties and application
(Natural Sciences Publishing, 2018) Dinesh Kumar; Umesh Singh; Sanjay Kumar Singh; Prashant Kumar Chaurasia
In the present paper, a new lifetime distribution has been introduced by the use of Minimum Guarantee transformation as suggested by Kumar et al. (2017). For the purpose, Lindley distribution is considered as a baseline distribution. Some of the statistical properties of this distribution has been studied and classical estimators like maximum likelihood estimator (MLE), least square estimator (LSE) and maximum product of spacing estimator (MPSE) has been obtained and their performance is carried out through simulation study. Further, a real data has been taken to show its application in the real scenario. ©2018 NSP Natural Sciences Publishing Cor.
A new species of magnimyiolia shiraki (Diptera: Tephritidae: Trypetinae) and new records of acanthonevrini from India
(Magnolia Press, 2015) Shakti Kumar Singh; K.J. David; Dinesh Kumar; V.V. Ramamurthy
A new species of the subfamily Trypetinae, Magnimyiolia perennifascia Singh & David, sp. nov. (Trypetini) is described from India. Two species of subfamily Phytalmiinae, Ectopomyia baculigera Hardy and Ptilona conformis Zia (Acantho-nevrini) are recorded for the first time from India. An updated key to Oriental species of Magnimyiolia Shiraki is provided. Copyright © 2015 Magnolia Press.
A novel 12.6-kDa protein of leishmania donovani for the diagnosis of Indian visceral leishmaniasis
(2011) Dinesh Kumar; Subodh Kumar; Jaya Chakravarty; Shyam Sundar
Background: For the diagnosis of visceral leishmaniasis (VL), rK39 antigen-based rapid test is widely used. Unfortunately, up to 32% healthy individuals from endemic region test positive with this antigen. There is an urgent need to search for a more specific antigen with sensitivity similar to rK39. Methods: We identified a Leishmania donovani-specific 12.6-kDa (BHUP3) soluble promastigote antigen through sensitive western blot technique. The identified protein was partially purified from sodium dodecyl sulfate-polyacrylamide gel electrophoresis and the antigenic response of eluted protein was determined by western blot with different groups of individual sera. The diagnostic potential was further validated by enzyme-linked immunosorbent assay using serum of 100 VL patients, 93 nonendemic healthy control individuals, 110 endemic healthy control individuals, and 110 disease control individuals. Further, it was characterized by two-dimensional gel electrophoresis followed by matrix-assisted laser desorption/ionization-time-of-flight analysis. Results: On blotting, antibody against this protein was recognized by all (9/9) VL patient's sera, but it was absent in every control group (nonendemic healthy control and endemic healthy control). Sensitivity of the enzyme-linked immunosorbent assay was 88% (89/101), whereas the specificity for endemic healthy, nonendemic healthy, and different disease groups were 96% (106/110), 100% (93/93), and 97% (107/110), respectively. The two-dimensional gel electrophoresis showed a single spot, and matrix-assisted laser desorption/ionization-time-of-flight analysis revealed that it is a 113-amino-acid-long putative uncharacterized protein of 12.6-kDa anamorsin homolog matched completely with Leishmania major (GenBank accession number: Q4QIS1). Conclusion: Despite marginally lower sensitivity of BHUP3, excellent specificity warrants its further development as a tool for diagnosis of VL. © Copyright 2011, Mary Ann Liebert, Inc.
A numerical study on dual-phase-lag model of bio-heat transfer during hyperthermia treatment
(Elsevier Ltd, 2015) P. Kumar; Dinesh Kumar; K.N. Rai
The success of hyperthermia in the treatment of cancer depends on the precise prediction and control of temperature. It was absolutely a necessity for hyperthermia treatment planning to understand the temperature distribution within living biological tissues. In this paper, dual-phase-lag model of bio-heat transfer has been studied using Gaussian distribution source term under most generalized boundary condition during hyperthermia treatment. An approximate analytical solution of the present problem has been done by Finite element wavelet Galerkin method which uses Legendre wavelet as a basis function. Multi-resolution analysis of Legendre wavelet in the present case localizes small scale variations of solution and fast switching of functional bases. The whole analysis is presented in dimensionless form. The dual-phase-lag model of bio-heat transfer has compared with Pennes and Thermal wave model of bio-heat transfer and it has been found that large differences in the temperature at the hyperthermia position and time to achieve the hyperthermia temperature exist, when we increase the value of τT. Particular cases when surface subjected to boundary condition of 1st, 2nd and 3rd kind are discussed in detail. The use of dual-phase-lag model of bio-heat transfer and finite element wavelet Galerkin method as a solution method helps in precise prediction of temperature. Gaussian distribution source term helps in control of temperature during hyperthermia treatment. So, it makes this study more useful for clinical applications. © 2015 Elsevier Ltd.
A review on integrated design and application of stimuli-responsive ZIF-8 metal-organic frameworks for breast cancer theranostics
(Elsevier B.V., 2025) Akshay Kumar Jha; Sanchit Arora; Rohan Chand Sahu; Dinesh Kumar; S. Kumar Singh; Ashish Kumar Kumar Agrawal
Breast cancer continues to be a predominant cause of death among women globally, necessitating the development of more effective and targeted treatment strategies. While current therapies have shown efficacy, they are often associated with notable adverse effects and inadequate tumor targeting. This review explores the potential of stimuli-responsive zeolitic imidazole framework-8 (ZIF-8) metal-organic frameworks (MOFs) in the treatment of breast cancer. Composed of zinc ions and imidazolate linkers, ZIF-8’s structure offers pH-sensitive degradation, making it ideal for precise medication delivery in the acidic tumor microenvironment. We investigate various synthesis methods and emphasize the advantages of ZIF-8 in enhancing drug bioavailability and precision targeting. The stimuli-responsive properties of ZIF-8 MOFs—such as responsiveness to pH, light, temperature, ultrasound, redox conditions, and enzymes—enable controlled and site-specific drug release. Furthermore, we examine the integration of ZIF-8 MOFs with existing breast cancer therapies and their applications in diagnostics and imaging. Consideration is also given to the biocompatibility of ZIF-8 to ensure safe and effective clinical use. This review article offers a comprehensive analysis of the function of stimuli-responsive ZIF-8 MOFs in transforming breast cancer therapy and facilitating novel treatment approaches. © 2025 The Authors
A study on DPL model of heat transfer in bi-layer tissues during MFH treatment
(Elsevier Ltd, 2016) Dinesh Kumar; P. Kumar; K.N. Rai
In this paper, dual-phase-lag bioheat transfer model subjected to Fourier and non-Fourier boundary conditions for bi-layer tissues has been solved using finite element Legendre wavelet Galerkin method (FELWGM) during magnetic fluid hyperthermia. FELWGM localizes small scale variation of solution and fast switching of functional bases. It has been observed that moderate hyperthermia temperature range (41-46 °C) can be better achieved in spherical symmetric coordinate system and treatment method will be independent of the Fourier and non-Fourier boundary conditions used. The effect of phase-lag times has been observed only in tumor region. FCC FePt magnetic nano-particle produces more effective treatment with respect to other magnetic nano-particles. The effect of variability of magnetic heat source parameters (magnetic induction, frequency, diameter of magnetic nano-particles, volume fractional of magnetic nano-particles and ligand layer thickness) has been investigated. The physical property of these parameters has been described in detail during magnetic fluid hyperthermia (MFH) treatment and also discussed the clinical application of MFH in Oncology. © 2016 Elsevier Ltd.
A study on red potato peel (Solanum tuberosum L. cv. Red Holland): characterization, composition and formulation of tablet using different drying techniques
(Springer, 2025) Divya Tripathi; Muskan Kumari; Anil Kumar Chauhan; Dinesh Kumar; Madhukiran R. Dhondale
Potato peels are one of the most under-utilized wastes which can be highly beneficial to mankind. The red potato peel powder was prepared by using tray drying and vacuum-oven drying method. The proximate analysis of red potato peel powder was conducted followed by its characterization which includes FT-IR, XRD, TGA, DSC, and SEM. Bioactive compounds were then extracted from the peel using ultrasound-assisted extraction. The qualitative estimation for tray-dried potato peel powder and vacuum-oven potato peel powder suggested that the drying techniques have a substantial effect on the bioactive compounds. The values obtained for total phenolic content (TPC), total flavonoid content (TFC) and DPPH for both samples showed that red potato peel powder is a rich source of antioxidants. The pre-compression properties results indicated that neither of the potato peel powders exhibited ‘Excellent’ flow characteristics. However, the addition of croscarmellose sodium improved the flow characteristics, making it feasible to create a tablet from the peel itself. This study highlights the potential of potato peels, a waste product, as a source of valuable bioactive compounds. Thus, it can be utilized in formulation of functional foods and nutraceuticals; promoting sustainability and value addition in the food processing industry. © Association of Food Scientists & Technologists (India) 2024.
A study on thermal damage during hyperthermia treatment based on DPL model for multilayer tissues using finite element Legendre wavelet Galerkin approach
(Elsevier Ltd, 2016) Dinesh Kumar; K.N. Rai
Hyperthermia is a process that uses heat from the spatial heat source to kill cancerous cells without damaging the surrounding healthy tissues. Efficacy of hyperthermia technique is related to achieve temperature at the infected cells during the treatment process. A mathematical model on heat transfer in multilayer tissues in finite domain is proposed to predict the control temperature profile at hyperthermia position. The treatment technique uses dual-phase-lag model of heat transfer in multilayer tissues with modified Gaussian distribution heat source subjected to the most generalized boundary condition and interface at the adjacent layers. The complete dual-phase-lag model of bioheat transfer is solved using finite element Legendre wavelet Galerkin approach. The present solution has been verified with exact solution in a specific case and provides a good accuracy. The effect of the variability of different parameters such as lagging times, external heat source, metabolic heat source and the most generalized boundary condition on temperature profile in multilayer tissues is analyzed and also discussed the effective approach of hyperthermia treatment. Furthermore, we studied the modified thermal damage model with regeneration of healthy tissues as well. For viewpoint of thermal damage, the least thermal damage has been observed in boundary condition of second kind. The article concludes with a discussion of better opportunities for future clinical application of hyperthermia treatment. © 2016 Elsevier Ltd
A Survey on Auction based Approaches for Resource Allocation and Pricing in Emerging Edge Technologies
(Springer Science and Business Media B.V., 2022) Dinesh Kumar; Gaurav Baranwal; Deo Prakash Vidyarthi
The advancements in sensing technologies, smart devices, wearable gadgets, and communication paradigm enable the vision of the internet of things, smart city, virtual and augmented reality, pervasive healthcare, to name a few. These applications have strict requirements of low latency delivery, high data rate, and instant response. To support this, various new technologies, such as fog computing, mobile edge computing, cloudlet, Micro, and Nano centers, mini and micro clouds, etc., have emerged. The entire set of emerging edge computing paradigms are commonly referred as "edge technologies" in which computational resources and storage are closer to the user/terminal devices somewhere between the device and the cloud data center. The edge technologies aim to deliver computing services with minimal delay by reducing the downward and upward time and data traffic volume. Like cloud service providers, edge service providers are emerging, and a market of edge computing resources has been created. Therefore, Auction theory, a subfield of Economics, is being widely applied for the allocation of resources in emerging edge technologies. This work presents a comprehensive survey on auction-based resource allocation and pricing approaches in emerging edge technologies. An overview of edge technologies and auction theory is given, followed by a thorough review and comparison of the existing auction-based approaches applied in edge technologies for resource allocation and pricing in terms of economic properties. Various open research issues have been deliberated to set the future research direction at the end. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
A survey on nature-inspired techniques for computation offloading and service placement in emerging edge technologies
(Springer, 2022) Dinesh Kumar; Gaurav Baranwal; Yamini Shankar; Deo Prakash Vidyarthi
Internet of Things (IoT) aims to make an environment more innovative and productive by connecting physical things to the internet. Processing generated data from IoT devices and actuation warranted in real-time requires computational infrastructure near the edge to get the outcome without delay. Emerging edge technologies such as Fog computing, Multi-Access Edge Computing, and Cloudlet provide computing resources near the edge, i.e. closer to the IoT devices, where devices can place their services/applications or offload their computational job for processing. The utilization of computing resources provided by emerging edge technologies addresses the issue of delay in the outcome and increases the battery life of IoT devices/End-user devices. Computational resources provided by the edge technologies, i.e. edge/fog nodes, can be heterogeneous, dynamic and mobile. Therefore, service placement and computation offloading on edge/fog nodes are challenging issues, and the problem to finding the best suitable fog/edge nodes is NP-Hard. Nature-inspired algorithms provide robust solutions to NP-Hard problems. Nowadays, nature-inspired algorithms have been widely applied for resource allocation for service placement and computation offloading in emerging edge technologies. In this work, we provide a detailed study on the applications of nature-inspired algorithms in emerging edge computing domains. We provide an overview of emerging edge technologies, related quality parameters and nature-inspired algorithms followed by the basic formulation of service placement and computation offloading in emerging edge computing systems. In this work, we classify the works in emerging edge computing applying nature-inspired algorithms into two categories: works related to service placement and works related to offloading. We provide a thorough review and comparison of the existing nature-inspired approaches in each category. We discuss various open issues at the end to set future research directions. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
A Survey on Spot Pricing in Cloud Computing
(Springer New York LLC, 2018) Dinesh Kumar; Gaurav Baranwal; Zahid Raza; Deo Prakash Vidyarthi
Amazon offers spot instances to cloud customers using an auction-like mechanism. These instances are dynamically priced and offered at a lower price with less guarantee of availability. Observing the popularity of Amazon spot instances among the cloud users, research has intensified on defining the users’ and providers’ behavior in the spot market. This work presents an exhaustive survey of spot pricing in cloud ecosystem. An insight into the Amazon spot instances and its pricing mechanism has been presented for better understanding of the spot ecosystem. Spot pricing and resource provisioning problem, modeled as a market mechanism, is discussed from both computational and economics perspective. A significant amount of important research papers related to price prediction and modeling, spot resource provisioning, bidding strategy designing etc. are summarized and categorized to evaluate the state of the art in the context. All theoretical frameworks, developed for cloud spot market, are illustrated and compared in terms of the techniques and their findings. Finally, research gaps are identified and various economic and computational challenges in cloud spot ecosystem are discussed as a guide to the future research. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.
A truthful combinatorial double auction-based marketplace mechanism for cloud computing
(Elsevier Inc., 2018) Dinesh Kumar; Gaurav Baranwal; Zahid Raza; Deo Prakash Vidyarthi
Designing market-based mechanism that benefits both the cloud customer and cloud provider in a cloud market is a fundamental but complex problem. Double auction is one such mechanism to allocate resources that prevents monopoly and is used to design an unbiased optimal market strategy for cloud market. This work proposes a truthful combinatorial double auction mechanism for allocation and pricing of computing resources in cloud. For resource allocation, utilitarian social welfare maximization problem is formulated using Integer Linear Programming (ILP) and a near optimal solution is obtained using Linear Programming based padded method. For payment, truthful and novel schemes are designed for both customers and providers. Moreover, the proposed mechanism is individual rational, computationally tractable, weakly budget-balance and asymptotic efficient. Performance evaluation and comparative study exhibit that the proposed mechanism is effective on various performance metrics such as utilitarian social welfare, total utility, customers’ satisfaction, providers’ revenue and hence is applicable in real cloud environments. © 2018 Elsevier Inc.