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This paper considers an infinite-buffer batch-service queue with Markovian arrival process, generally distributed and batch-size-dependent service time. We obtain a bivariate vector generating function of queue length and server content distribution at departure epoch of a batch. The complete joint distribution of queue length, server content and phase of the arrival process at departure epoch is extracted in terms of roots of the associated characteristic equation. By employing these probability vectors we also perceive the joint distribution at arbitrary and pre-arrival epochs. Our analytic procedure and results are demonstrated using some numerical examples for phase-type as well as deterministic service time distributions with high and low values of model parameters. The occurrence of multiple roots are also investigated in case of phase-type service time distribution. Finally, we also investigate the influence of correlation of the arrival process on the behavior of the system performance.

With the evolution of internet, there has been increased interest in the use of computer-communication networks and digital communication systems. But unusual events, like virus attack, that often results in abrupt change in the state of the system poses a major threat to these systems. The occurrence of a virus may cause immediate removal of some elements (packets) from the system. Such type of situations can be well represented as discrete-time catastrophe model where interruptions due to various types of virus attacks are referred to as catastrophe. In this paper we study a discrete-time catastrophe model in which population grows according to batch Bernoulli process and catastrophes occur according to discrete-time renewal process. When a catastrophe occurs, an element (individual or packet) of the population survives with probability p or dies with probability 1-p. The analysis of the model has been done using supplementary variable technique and steady-state probability generating function of the distribution of population size at post-catastrophe, arbitrary and pre-catastrophe epochs are obtained under late arrival system with delayed access. In order to make the model more useful for practitioners, a step-wise computing process for evaluation of distribution of population size at various epochs for commonly used inter-catastrophe time distributions viz. geometric, deterministic and arbitrary are given. We also present recursive formulae to compute factorial moments of the population size at various epochs. Further to study the effect of critical model parameters, numerical results and some graphs are included.

This paper considers a single-server queueing model in which the customers are served in batches of varying size depending on predetermined thresholds as well as available inventory. There is a finite buffer for the inventory and the service of every customer requires an inventory item. An ( s ,  S ) -type inventory system is used for the models considered in this paper. Initially, the model is studied in detail using the matrix-analytic method by assuming all the underlying random variables to be exponentially distributed. Thereafter, an outline of the model in a more general set up is also presented. Due to complexity of the model when more general assumptions are made on the underlying random variables, simulation is opted after a satisfactory validation with the analytic counterpart of the exponential model. Finally, some illustrative numerical examples are also presented to accomplish our analysis.

During the COVID-19 pandemic, huge interstitial lung disease (ILD) lung images have been captured. It is high time to develop the efficient segmentation techniques utilized to separate the anatomical structures and ILD patterns for disease and infection level identification. The effectiveness of disease classification directly depends on the accuracy of initial stages like preprocessing and segmentation. This paper proposed a hybrid segmentation algorithm designed for ILD images by taking advantage of superpixel and K-means clustering approaches. Segmented superpixel images adapt the better irregular local and spatial neighborhoods that are helpful to improving the performance of K-means clustering-based ILD image segmentation. To overcome the limitations of multiclass belongings, semiadaptive wavelet-based fusion is applied over selected K-means clusters. The performance of the proposed SPFKMC was compared with that of 3-class Fuzzy C-Means clustering (FCM) and K-Means clustering in terms of accuracy, Jaccard similarity index, and Dice similarity coefficient. The SPFKMC algorithm gives an accuracy of 99.28%, DSC 98.72%, and JSI 97.87%. The proposed Fused Clustering gives better results as compared to traditional K-means clustering segmentation with wavelet-based fused cluster results.

Any event that results in sudden change of the normal functioning of a system may be thought of as a catastrophe. Stochastic processes involving catastrophes have very rich application in modeling of a dynamic population in areas of ecology, marketing, queueing theory, etc. When the size of the population reduces abruptly as a whole, due to a catastrophe, it is termed as the total catastrophe. However, in many real-life circumstances the catastrophes have a mild influence on the population and have a sequential effect on the individuals. This paper presents a discrete-time catastrophic model in which the catastrophes occur according to renewal process, and it eliminates each individual of the population in sequential order with probability p until the one individual survives or the entire population wipes out. The individuals arrive according to the discrete-time Markovian arrival process. Using the supplementary variable technique, we obtain the steady-state vector generating function (VGF) of the population size at various epochs. Further using the inversion method of VGF, the population size distribution is expressed in terms of the roots of the associated characteristic equation. We further give a detailed computational procedure by considering inter-catastrophe time distributions as discrete phase-type as well as arbitrary. Finally, a few numerical results in form of tables and graphs are presented. Moreover, the impact of the correlation of arrival process on the mean population size is also investigated.

Streptococcus pneumoniae (SP) infections cause morbidity and mortality among children worldwide. Hence India introduced 13-valent pneumococcal conjugate vaccine (PCV-13) in 2017 in a phased manner. The primary objective of this study was to assess the proportion of healthy children having nasopharyngeal colonization (NP) with SP. Secondary objective was to determine prevalent serotype of SP among the PCV13 vaccinated and non-vaccinated children. This cross-sectional study was conducted in 4 hospitals of Lucknow District, Northern India. Three hundred healthy children (2–59 months) were recruited between July and August 2019 from vaccination-clinics of hospitals. NP specimen was cultured using 5% sheep blood agar plate containing gentamicin. Pneumococcal isolates were identified by optochin sensitivity and bile-solubility tests. Serotyping was done using Quellung Method. Of the 300 healthy children, 56.7% (170/300) were males and 59.3% (181/300) had received at least one dose of PCV13 vaccine. The NP carriage rate of SP among healthy children was 37.7% (113/300). Vaccine serotypes were found in 33.3% (22/66) in PCV vaccinated children and 48.9% (23/47) in non-vaccinated children (p 0.09). Common vaccine serotypes that isolated were: 18C, 19A, 19F, 23F, 3, 4, 6A, 6B, 9 V. Thus more than one-third of healthy children had NP colonization with SP. Adjusting for age, there was a trend for significant reduction in vaccine serotypes in the NP with one doses versus two or more doses (ptrend = 0.04).

► MIP provides long-term protection as compared to BCG against tuberculosis. ► Improved granulomatous immune response in MIP-group during chronic infection. ► Higher early protective Th1 immune response after M.tb infection in MIP-group. ► MIP-aerosol induced local lung as well as systemic protective immune response. ► MIP is safe and more effective in live form, causes no untoward reaction. Tuberculosis kills two million people each year. As the current vaccine BCG fails to prevent adult cases of TB, an improved vaccine and/or vaccination strategy is urgently needed to combat TB. Previously we reported the higher protective efficacy of Mycobacterium indicus pranii (MIP), formerly known as Mycobacterium w (M.w) as compared to BCG in murine model of TB. In this study we further evaluated the protective efficacy of MIP in guinea pig model of TB. Modulation of post infection immune response was analyzed in the lungs of MIP immunized and control groups. We found reduced bacterial loads, improved pathology and organized granulomatous response at different post infection time points in the MIP-immunized group as compared to the BCG-immunized group. Combined results suggest that MIP-immunization results in heightened protective Th1 response as compared to BCG group, early after infection with M.tb and a balanced Th1 versus immunosuppressive response at late chronic stage of infection. The study demonstrates the higher antigen presenting cells function both inside the granuloma as well as in the single cell suspension of the lung in the MIP-immunized group. We further demonstrate that live MIP is safe to use in vivo as we observed quick clearance of MIP from the body and no untoward reaction was found. Aerosol route of immunization provided higher protection. Further this study provides evidence that MIP-immunization gives significantly better long term protection as compared to BCG against TB.

Studies have shown the bactericidal potential of econazole and clotrimazole against Mycobacterium tuberculosis under in vitro and ex vivo conditions along with their synergism with conventional antituberculosis drugs. These molecules were also found to be effective against different multidrug resistant (MDR) M. tuberculosis isolates in vitro. Hence the present study was designed to evaluate the in vivo antimycobacterial potential of moxifloxacin and econazole alone and in combination against multidrug resistant tuberculosis (MDR-TB) in a mice model. Mice were infected with 2.5×10 [7] bacilli of MDR strain of M. tuberculosis by aerosol route of infection. After four weeks of infection, chemotherapy was started orally by moxifloxacin 8.0 mg/kg body wt and econazole 3.3 mg/kg alone and in combination, as well as with four first line anti-tuberculosis drugs as a positive control. The animals were sacrificed and the lungs and spleen were excised under aspetic conditions. The tissues were homogenized with sterile normal saline, an aliquot of the homogenate was plated on Middlebrook 7H11 agar supplemented with oleate albumin dextrose catalase (OADC) and incubated at 37°C for four weeks. The number of visible and individual colonies were counted. The first line anti-tuberculosis drugs (RIF+INH+EMB+PZA) after eight weeks of therapy had no impact as the bacillary load in lungs and spleens remained unchanged. However, econazole, moxifloxacin alone as well as in combination significantly reduced the bacillary load in lungs as well as in spleens of MDR-TB bacilli infected mice. Co-administration of the two drugs (econazole and moxifloxacin) to MDR-TB strain JAL-7782 infected mice exhibited additive effect, the efficacy of the drugs in combination being higher as compared with ECZ or MOX alone. These results were substantiated by histopathological studies. This study suggests the utility of econazole for the treatment of MDR tuberculosis and warrants further work in this direction.

PurposeTuberculosis (TB) chemotherapy witnesses some major challenges such as poor water-solubility and bioavailability of drugs that frequently delay the treatment. In the present study, an attempt to enhance the aqueous solubility of rifampicin (RMP) was made via co-polymeric nanoparticles approach. HPMA (N-2-hydroxypropylmethacrylamide)-PLGA based polymeric nanoparticulate system were prepared and evaluated against Mycobacterium tuberculosis (MTB) for sustained release and bioavailability of RMP to achieve better delivery.MethodologyHPMA-PLGA nanoparticles (HP-NPs) were prepared by modified nanoprecipitation technique, RMP was loaded in the prepared NPs. Characterization for particle size, zeta potential, and drug-loading capacity was performed. Release was studied using membrane dialysis method.ResultsThe average particles size, zeta potential, polydispersity index of RMP loaded HPMA-PLGA-NPs (HPR-NPs) were 260.3 ± 2.21 nm, −6.63 ± 1.28 mV, and 0.303 ± 0.22, respectively. TEM images showed spherical shaped NPs with uniform distribution without any cluster formation. Entrapment efficiency and drug loading efficiency of HPR-NPs were found to be 76.25 ± 1.28%, and 26.19 ± 2.24%, respectively. Kinetic models of drug release including Higuchi and Korsmeyer-peppas demonstrated sustained release pattern. Interaction studies with human RBCs confirmed that RMP loaded HP-NPs are less toxic in this model than pure RMP with (p < 0.05).ConclusionsThe pathogen inhibition studies revealed that developed HPR-NPs were approximately four times more effective with (p < 0.05) than pure drug against sensitive Mycobacterium tuberculosis (MTB) stain. It may be concluded that HPR-NPs holds promising potential for increasing solubility and bioavailability of RMP.