A performance evaluation framework of public health distribution network for essential medicines: lessons from the select Indian states

The present work has been carried out to develop a performance evaluation framework of distribution network design in public health with specific reference to essential medicines based on six different types of public health distribution networks (PHDNs) prevalent across six Indian states. We evaluated the performance of PHDNs on the criteria of cost and service and also on the sub-criteria of cost and service by following the analytic hierarchy process. We utilized the pairwise comparison method in determining the relative importance of criteria and sub-criteria by seeking responses from several experts and subsequently evaluated the PHDNs on all sub-criteria in a 7-point Likert scale by seeking views from the same experts. Finally, we developed the “cost–service matrix,” in which cost and service have been depicted in the horizontal and vertical axes, respectively. We demonstrated the performance of six PHDNs in this matrix in terms of cost and service by plotting scores obtained by them on cost and service, respectively. The findings of the study provide rich insights to the policy planners of public health.     

A matching game framework for users clustering and resource allocation with wireless power transfer in a CR-NOMA network

This paper investigates the resource allocation in a massively deployed user cognitive radio enabled non-orthogonal multiple access (CR-NOMA) network considering the downlink scenario. The system performance deteriorates with the number of users who are experiencing similar channel characteristics from the base station (BS) in NOMA. To address this challenge, we propose a framework for maximizing the system throughput that is based on one-to-one matching game theory integrated with the machine learning technique. The proposed approach is decomposed to solve users clustering and power allocation subproblems. The selection of optimal cluster heads (CHs) and their associated cluster members is based on Gale-Shapley matching game theoretical model with the application of Hungarian method. The CHs can harvest energy from the BS and transfer their surplus power to the primary user (PU) through wireless power transfer. In return, they are allowed to access the licensed band for secondary transmission. The power allocation to the users intended for power conservation at CHs is formulated as a probabilistic constraint, which is then solved by employing the support vector machine (SVM) algorithm. The simulation results demonstrate the efficacy of our proposed schemes that enable the CHs to transfer the residual power while ensuring maximum system throughput. The effects of different parameters on the performance are also studied.     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Energy Efficient Hardware Loop Based Optimization for CGRAs

Journal of Signal Processing Systems - Research interest and industry investment in edge computing solutions have increased dramatically in recent years. Consequent quest for balanced performance,...     

Development and validation of a Re-Modified Work-Style Short Form Questionnaire for assessment of stress in medical practitioners working in Indian hospitals

Medical practitioners are unduly stressed, leading to ill health, loss of work efficiency, sometimes affecting decision-making capability. The present study was conducted with the aim to quantify the psychosocial factors that affect the medical practitioners working in Indian hospitals. This study constructed and validated Re-Modified Work-Style Short Form Questionnaire, an eight-item instrument based on work style of 108 medical practitioners comprising Indian physicians and surgeons. The re-modified tool had acceptable validity and internal consistency, which the modified one did not. Explorative factor analysis identified and labelled three factors: ‘Working through pain’, ‘Deadlines/pressure’ and ‘Self-imposed workload’. The findings of the study reveal that the mean total work style score exceeded the standardised limits ≥16, which suggests that the work style of medical practitioners working in Indian hospitals are at risk which may precipitate psychosocial stress. Factor weights was derived through Analytic Hierarchy Process to prioritise the relative importance of three potential work-style factors. The study may help to increase the preventive strategies to proactively reduce the effect of risk factors for the precipitation of stress, successfully leading to its attenuation.     

Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach

Sustainable development has become one of the leading global issues over the period of time. Currently, implementation of sustainability in supply chain has been continuously in center of attention due to introducing stringent legislations regarding environmental pollution by various governments and increasing stakeholders’ concerns toward social injustice. Unfortunately, literature is still scarce on studies considering all three dimensions (economical, environmental and social) of sustainability for the supply chain. An effective supply chain network design (SCND) is very important to implement sustainability in supply chain. This study proposes an uncertain SCND model that minimizes the total supply chain-oriented cost and determines the opening of plants, warehouses and flow of materials across the supply chain network by considering various carbon emissions and social factors. In this study, a new AHP and fuzzy TOPSIS-based methodology is proposed to transform qualitative social factors into quantitative social index, which is subsequently used in chance-constrained SCND model with an aim at reducing negative social impact. Further, the carbon emission of supply chain is estimated by considering a composite emission that consists of raw material, production, transportation and handling emissions. In the model, a carbon emission cap is imposed on total supply chain to reduce the carbon footprint of supply chain. To solve the proposed model, a code is developed in AMPL software using a nonlinear solver SNOPT. The applicability of the proposed model is illustrated with a numerical example. The sensitivity analysis examines the effects of reducing carbon footprint cap, negative social impacts and varying probability on the total cost of the supply chain. It is observed that a stricter carbon cap over supply chain network leads to opening of more plants across the supply chain. In addition, carbon footprint of supply chain is found to be decreased in certain extent with the reduction in negative social impacts from suppliers. The carbon footprint of the supply chain is found to be reduced with increasing certainty of material supply from the suppliers. The total supply chain cost is observed to be augmented with increasing probability.     

Biosynthesis of AgNPs using aqueous leaf extract of Ipomoea eriocarpa and their anti‐inflammatory effect on carrageenan‐induced paw edema in male Wistar rats

Silver nanoparticles (AgNPs) were synthesised from aqueous Ag nitrate through a simple, competent and eco‐friendly method using the leaf extract of Ipomoea eriocarpa as reducing as well as capping agent. Ultraviolet–visible absorption spectroscopy was used to confirm the formation of AgNPs which displayed the substantiation of surface plasmon bands at 425 nm. The NPs were also characterised using Fourier transformer infrared spectroscopy, X‐ray diffraction method, transmission electron microscope and zeta potential. The characterisation study confirmed the formation of AgNPs, their spherical shape and average diameter of 12.85 ± 8.65 nm. Zeta potential value of −20.5 mV suggested that the AgNPs are stable in the suspension. The aqueous extract and the AgNPs were further screened for in vivo anti‐inflammatory activity using carrageenan‐induced paw edema in male Wistar rats. The study demonstrated that the AgNPs (1 ml kg⁻¹) had a significant (p  < 0.05) anti‐edemic effect and inhibition was observed from the first hour (21.31 ± 1.34) until the sixth hour (52.67 ± 1.41), when the inhibitory effect was greatest and superior to the aqueous extract and the standard, diclofenac.Inspec keywords: silver, nanoparticles, nanofabrication, ultraviolet spectra, visible spectra, absorption coefficients, surface plasmons, Fourier transform infrared spectra, X‐ray diffraction, transmission electron microscopy, suspensions, drugs, nanomedicineOther keywords: biosynthesis, aqueous leaf extract, ipomoea eriocarpa, antiinflammatory effect, carrageenan‐induced paw edema, male Wistar rats, silver nanoparticles, aqueous nitrate, capping agent, ultraviolet‐visible absorption spectroscopy, surface plasmon band, Fourier transformer infrared spectroscopy, X‐ray diffraction, transmission electron microscopy, zeta potential, spherical shape, suspension, aqueous extract, in vivo antiinflammatory activity, antiedemic effect, inhibitory effect, diclofenac, wavelength 425 nm, size 12.85 nm to 8.65 nm, Ag     

Topical delivery of paclitaxel for treatment of skin cancer

Context: Skin cancer represents the most growing types of cancer in human and ultraviolet radiation can be cited as one of the prime factor for its occurrence. Current therapy of skin cancer suffers from numerous side effects; for effective therapy, topical application of formulation of paclitaxel (PTX) can be considered as a novel approach.

Objective: The present study is an attempt to prepare formulation of solid lipid nanoparticles (SLN) of PTX for the effective treatment of various form of skin carcinoma.

Methods: The SLN were prepared by high-speed homogenization and ultrasonication method. The prepared SLN were characterized. The optimized PTX SLN were loaded in carbopol gel. The prepared gels were evaluated for its gelling properties and finally studied for in vivo anti-cancer efficacy and histopathological study.

Results: The particle size distribution was found to be in the range of 78.82–587.8?nm. The product yield (%) was found between 60% and 66% and showed a highest entrapment efficiency of 68.3%. The in vitro release of the drug from SLN dispersion was found to be biphasic with the initial burst effect, followed by slow release. SLN-loaded gel were subjected to permeability study and the results show steady-state flux (J_ss), permeability coefficient (K_p), and enhancement ratio were significantly increased in SLN-loaded gel formulation as compared with PTX-loaded gel. The histopathological study clearly reveals the efficacy of the SLN-F3 3G in the treatment of skin cancer.

Conclusion: The experimental formulations show controlled release of PTX and thus expected to show reduce dose-related side effects.     

Challenges in Liquid‐Phase Exfoliation,Processing, and Assembly of Pristine Graphene

Recent developments in the exfoliation, dispersion, and processing of pristine graphene (i.e., non‐oxidized graphene) are described. General metrics are outlined that can be used to assess the quality and processability of various “graphene” products, as well as metrics that determine the potential for industrial scale‐up. The pristine graphene production process is categorized from a chemical engineering point of view with three key steps: i) pretreatment, ii) exfoliation, and iii) separation. How pristine graphene colloidal stability is distinct from the exfoliation step and is dependent upon graphene interactions with solvents and dispersants are extensively reviewed. Finally, the challenges and opportunities of using pristine graphene as nanofillers in polymer composites, as well as as building blocks for macrostructure assemblies are summarized in the context of large‐scale production.     

Design and Uncertainty Evaluation of a Strain Measurement System

Strain measurement is very important in various industrial applications as well as different disciplines of science and technology for direct and indirect observations of certain parameters. Designing signal conditioning circuit is always a challenging and important task for satisfactory and reliable performance of a sensor as well as the system. The design and implementation details of a signal conditioning circuit of resistive sensor (strain gauge) for strain measurement are presented in this paper. Also the important aspects in designing a signal conditioning circuit for resistive sensor are presented and a novel method for the measurement of strain is discussed. Quarter bridge configuration with AC voltage excitation is used for the measurement along with the necessary circuitry to get a suitable and measurable output DC voltage. The measurement system is calibrated using a cantilever of stainless steel and the details of calibration are presented in the paper. The uncertainty associated with the measurement system is evaluated.