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Introduction: Emerging resistance in microorganisms is a matter of great concern in health care setups. Bacterial isolate and AMR pattern changes from place to place and time to time. Unprofessional use of antibiotics has resulted in an increasing burden of antibiotic resistance. This study focused over the aerobic bacteriological profile and antibiotic resistance pattern in pus isolates. Materials and Methods: A retrospective study was carried out from June, 2020 to May 2021. 1174 pus samples collected during the study period were included. The samples were cultured on Blood and MacConkey agar. After aerobic incubation at 37°C for 18-24 hrs, organisms were identified by biochemical reactions, gram staining and antibiotic susceptibility was tested by Kirby Bauer disc diffusion method. Result: Among the total 1174 pus samples, 712 (60.6%) were male and 462 (39.3%) were females. 857(72.9%) samples showed positive results. Among them, Staphylococcus aureus was the most common isolate followed by Escherichia coli, Pseudomonas spp. and Klebsiella spp. The sensitivity of Staphylococcus aureus was highest with Vancomycin and Linezolid, whereas Enterobacterales and Pseudomonas were sensitive with Piperacillin tazobactam. Conclusion: Increasing resistance always poses a challenge in treating infections. The development of resistant strains of pathogens can be limited by the judicious use of antibiotics. This study shows the infecting bacterial isolates and their antibiogram from this area. Keywords: Pus, antimicrobial resistance, bacterial isolates.

Background: Hepatitis B(HBV) is one of the most important occupational hazards among the medical student and healthcare workers(HCW's) due to risk of exposure to infected bodily fluids and blood. This study aimed to assess status of HBV vaccination and factors affecting anti-HBs titres levels for HBV in HCW and medical students. Material and Method: It was a prospective, descriptive and cross sectional study done at the Department of Microbiology, DRPGMC Kangra at Tanda(H.P). Randomly 215 HCW’s and medical students were taken in the study who fulfilled the inclusion criteria. Results: Total of 215 subjects were included in the study. Males were 89 and females were 126. 182 subjects were vaccinated and 33 were unvaccinated for hepatitis B. Out of 182 vaccinated 137 were completely vaccinated. Significant correlation was seen with decrease in antibody titers with gender, duration of vaccination and smoking. Conclusion: Vaccination should be mandatory for every HCW and medical student entering the health institutions. The factors affecting the antibody titers must be evaluated and antibody titers must be reviewed from time to time. The need for a booster dose can be made mandatory at least for healthcare professionals. Keywords: Hepatitis B virus, Vaccination, Antibody titers, HCW.

Land use controversies often dog the construction of hydroelectric projects. Many important projects are battling in the tribunals because of Geo-environmental concerns. The paucity of scientific studies objectively investigating the litigations further aggravates the unsolvability of the disputes. The Sawra-Kuddu Hydroelectric project, India, became a subject of litigation when project affected persons filed a suit in the National Green Tribunal questioning the sustainability of the built environment. The litigants petitioned that the additional adit's blasting vibrations can trigger the landslide of slip zone, and Thana village situated above it. The petitioners further claimed that vibrations had cracked the houses. They also asserted degradation in the apple cultivation due to tunnel construction. The tribunal took a stern note of the petition and banned the construction activities. The tribunal further ruled that a scientific investigation must be conducted to ascertain the cause of petitioners' claims. The study results revealed that the vibrations originating from adit excavation are insignificant and cannot destabilize the slip zone. The high fluctuation of annual rainfall and tectonic strain were deemed responsible for the differential settlement of foundations and cracks in the houses. The horticulture study indicated that the physiological processes of apple crops were normal. The study's findings convinced the tribunal, and construction activities were resumed, resulting in the disputed 111 MW project's commissioning. Many run-of-the-river hydroelectric projects in the world are battling similar litigations addressed in the present study. A similar objective methodology is a need for the hour to resolve other hydroelectric projects' sustainability issues. The study findings will pave the path for the swift resolution of land disputes related to similar projects.

Boulder blasting is a different process from conventional bench blasting. Fly-rock produced in boulder blasting is a major safety concern due to the presence of 360° free-face which may result into excessive throw of the fragments radially up to 900 m distance causing accidents. Many researchers have attempted to predict the fly-rock using empirical and soft computing tools in bench blasting. But, there is paucity of literature to predict the extent of fly-rock in boulder blasting. Machine learning techniques are frequently used in bench blasting to predict ground vibrations, air overpressure, fly-rocks, but it has been rarely used in boulder blasting. In this study, an attempt has been made to use Classification and Regression Trees (CART) technique to predict the fly-rock distance in boulder blasting. Multiple linear regression (MLR) technique has been used to compare the results obtained by the CART technique. Sixty-one boulder blasting events were monitored while excavating the accident-prone slope areas of Konkan Railways. The performance of the developed models using both the techniques has been evaluated using the coefficients of determination (R2) and root-mean-square error (RSME) values. The results indicate that CART model (R2 = 0.9555 and RMSE = 1.141) provides better output than MLR model. This paper suggests the use of CART technique in boulder blasting, which will be useful in execution at sensitive locations to predict and control the fly-rock distance.

Many cases of derailments, train accidents and traffic interruptions due to the slope failure and rockfall have been reported in the past on Konkan Railway trackline because of unstable rock slopes. The authorities installed stability enhancement measures such as wire netting, rock bolting and shotcreting which were found insufficient. The failed geotechnical measures prompted authorities to excavate the unstable slopes. Rock blasting is generally not preferred for the excavation of slopes along the transportation route. Stabilisation and widening of slopes by blasting need closure of the route for a considerable time. Discontinuing traffic on Konkan Railway route was undesirable as it connects two important port cities Mumbai and Mangalore. The paper presents an innovative directional controlled blasting (DCB) technique for excavating three unstable slopes (i.e. cuttings) in hilly terrain without disturbing the traffic. New empirical formulae for small geometry blasting to estimate burden and throw have been developed. A unique sequence of firing and excavation with powder factor varying between 0.04 and 0.39 kg/m3 irrespective of the actual free face was used for rock blasting. The process controlled the throw of blasted material over the track and resulted in a smooth and stable wall. The slope angle has been changed from 80 to 82° to 45–47° and probability of wedge, planar and toppling failures was eliminated. About 100 such accident-prone slopes (52 km cumulative length, 7% of total route) situated at discrete locations along Konkan Railway route were stabilised using the technique. No incident of rockfall and slope failures along these slopes has been observed after the stabilisation.

The present study compares three different techniques (decision tree, artificial neural network and multivariate regression analysis) for predicting blast-induced ground vibrations in some Indian tunnelling projects. The performance of these models was also compared to site-specific conventional predictor equations. A database consisting of 137 vibration records was randomly divided into training and testing sets for model generation. Eight input parameters (total charge, tunnel cross-section, maximum charge per delay, number of holes, hole diameter, distance from blasting face, hole depth and charge per hole) were selected for model development using bivariate correlation analysis. Results indicated that the decision tree is best suited for predicting vibrations. The decision tree further suggested that the intensity of near-field ground vibrations is mainly affected by total charge fired in a round, whereas the intensity of far-field vibrations is governed by maximum charge per delay and charge per hole. Conventional ground vibration predictors and machine learning techniques such as neural networks do not depict the relationship between input and output parameters. However, the present study substantiates that the decision tree can be a good tool for precise prediction of ground vibrations. Further, the decision tree can classify and relate different blast design parameters for refining blast designs to control ground vibrations on sites.

Ground vibration induced by rock blasting is an unavoidable effect that may generate severe damages to structures and living communities. Peak particle velocity (PPV) is the key predictor for ground vibration. This study aims to develop a model to predict PPV in opencast mines. Two machine-learning techniques, including multivariate adaptive regression splines (MARS) and classification and regression tree (CART), which are easy to implement by field engineers, were investigated. The models were developed using a record of 1001 real blast-induced ground vibrations, with ten (10) corresponding blasting parameters from 34 opencast mines/quarries from India and Benin. The suitability of one technique over the other was tested by comparing the outcomes with the support vector regression (SVR) algorithm, multiple linear regression, and different empirical predictors using a Taylor diagram. The results showed that the MARS model outperformed other models in this study with lower error (RMSE = 0.227) and R2 of 0.951, followed by SVR (R2 = 0.87), CART (R2 = 0.74) and empirical predictors. Based on the large-scale cases and input variables involved, the developed models should lead to better representative models of high generalization ability. The proposed MARS model can easily be implemented by field engineers for the prediction of blasting vibration with reasonable accuracy.

BACKGROUND: Urinary tract infections (UTI) are one of the commonest community acquired and nosocomial infections encountered by clinicians in developing countries like India.Untreated UTI may lead to recurrence, renal scarring and renal failure. UTI is most often treated by empirical broad spectrum antibiotics.The main aim of this study was to identify the organism isolated from the urine and determine its antimicrobial resistance pattern so as to provide data for reference which may be of epidemiological and clinical importance regarding widespread multidrug resistance among uropathogens. MATERIAL AND METHODS: This study was conducted in the Department of Microbiology at DRPGMC Kangra at Tanda (Himachal Pradesh), India. Atotal of 3101 urine samples were collected from patients during a period of one and half year from April 2019 to September 2019.The urine samples were then cultured using a standard loop containing 0.01 ml of urine on CLED and MacConkey agar. The inoculated plates were incubated aerobically at 37°C for 18–24 hrs. Antimicrobial susceptibility was done on Mueller hinton agar plates that were incubated aerobically at 37°C for 18–24 hrs as per CLSI guidelines. RESULT: A total of 3101 clean catch samples were received in the Department of Microbiology,. Out of these only 640(20.64%) samples show signicant bacterial count. Among 640 samples with signicant bacterial count 178(27.81%) were from male and 462(72.19%) were from female patients.The common isolated Gram Negative bacteria were E. coli (68.3%) followed by Klebsiella spp. (11.7%). Susceptibility was seen in majority with fosfomycin, imipenem and nitrofurantoin. CONCLUSION: Escherichia coli remained the predominant isolate among enterobacterales and gram negative organisms, more commonly in females. Regular antimicrobial susceptibility is required to be carried out to see the current pattern of susceptibili

BACKGROUND: Urinary tract infections (UTI) are one of the most frequent clinical bacterial infections in women. They are at higher risk to acquire UTI during pregnancy. The emergence and spread of antimicrobial resistance is a cause of increasing concern. Thus, knowledge of local antimicrobial susceptibility patterns of common uropathogens is essential for empiric therapy of UTIs. Retrospective study was conducted in the Department of Microbiology of DRPGM MATERIALS AND METHODS: C Kangra at Tanda. Study was conducted for the period of one years ie. from July 2020 to June 202. Urine samples were collected and sent to the laboratory for identication and antimicrobial susceptibility of bacterial isolates. RESULTS: During the 12-month study period, out of the 1266 samples screened, 977(77.2%) were sterile, 224(17.698%) samples showed signicant growth of >10฀CFU/ml and 65(5.1%) were contaminanst or insignicant growth, which were excluded from the study. E. coli alone accounted for 66.9% of the urinary isolates followed by Klebsiella spp 12.9%. Among the Gram-positive cocci, Enterococcus isolated from a single sample and Methicillin resistant staphylococcus aureus were seen in two urine samples. Signicantly high susceptibility was seen with fosfomycin(90%) and nitrofurantoin(84%). Resistance was quite high against the noroxacin(30.3%) and cefazolin(17.8%). The susceptibility patterns seen in our study see CONCLUSION: m to suggest that it is necessary to obtain sensitivity reports before initiation of antibiotic therapy in cases of suspected UTI

Background: Hepatitis B(HBV) is a blood borne virus and it is one of the most important occupational hazards among healthcare workers (HCWs) & Medical students. This study aimed to measure the anti-HBs titres and to assess the seroprevalence of Hepatitis B in HCW and medical students. It was a prospective,descriptive and cross sectional hospital base Material and method: d study. Medical students and healthcare workers who had received all three doses of hepatitis B vaccination were included in the study. A total of 200 subjects , aged between 18 and Result: 62 years were taken. 182 were vaccinated and 18 were unvaccinated. 85 were males and 115 females. Seroprevalence of Hepatitis B was nil. Antibody titres were >100mIU/ml in 51.6% , 10-100mIU/ml in 16.4% &

Norovirus is one of the leading causes of gastroenteritis, acute vomiting, intense diarrhoea, acute pain in the stomach, high fever, headaches, and body pain. Conventional methods of detection gave us very promising results but had disadvantages such as low sensitivity, cost ineffectiveness, reduced specificity and selectivity, etc. Therefore, biosensors can be a viable alternative device which can overcome all setbacks associated with the conventional method. An electrochemical sensor based on oxidized graphitic carbon nitride (Ox-g-C3N4) modified electrochemical paper-based analytical device (ePAD) was fabricated for the detection of norovirus DNA. The synthesized Ox-g-C3N4 nanosheets were characterized by field emission scanning electron microscopy (FESEM), X-ray Diffraction (XRD), UV-Vis spectroscopy and X-Ray Photoelectron Spectroscopy. The capture probe DNA (PDNA) modified electrodes were characterized by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). These two characterization techniques were also employed to find the optimal scan rate, response time and temperature of the fabricated sensor. The fabricated biosensor showed a limit of detection (LOD) of 100 fM. Furthermore, the specificity of the reported biosensor was affirmed by testing the response of capture probe DNA with oxidized graphitic carbon nitride (PDNA/Ox-g-C3N4) modified ePAD on the introduction of a non-complimentary DNA. The fabricated ePAD sensor is easy to fabricate, cost effective and specific, and requires a minimum analysis time of 5 s.

This paper talks about the wavelet thresholding algorithm for image denoising. Any data, either in the form of signals, or images contains more noise than informations. To make sense out of it, it needs denoising. For that, this paper explains algorithm that makes active use of wavelet thresholding to achieve maximum denoising. For statistical analysis matlab software is used as it comes with wavelet thresholding application. This is then used to process standard lenna image to obtain haar wavelet transform for three levels of decomposition of image. On the contrary daubechies wavelet transform is also applied to the same sample image of lenna. Using Haar Wavelet for image compression has a little bifurcation in Retained Energy and Number of Zeros along x axis. On the other hand Daubechies Wavelet compression with global thresholding on decomposition level 4 for standard image of lenna yields different trend lines between Retained Energy and Number of Zeros. Its applications vastly covers all medias such as image, video, signals, etc. to achieve maximum information. With advances in image denoising, space can be utilized more appropriately as user can be able to save space in his personal devices like mobile phones, laptops, etc. With this user can be able to use or access that free space in order to upload more data, or use it for his computational use. Keywords: Image Denoising, Thresholding, Wavelet Transform

Disposal of industrial waste is a worldwide problem. Additionally, the non-biodegradable nature of these wastes further increases severity of the problem. The shortage of land to accommodate the waste landfills, increased transportation cost and other associated problems have forced industries to search for other viable alternatives. Moreover, over-exploitation of natural resources by the construction industry has led to their depletion. Thus, the construction industry is compelled to look for other economic and sustainable substitutes for conventional raw materials (river sand, natural aggregates) and cement. Past studies suggest that waste of discarded rubber tyres, silica fume, glass, slag, pond ash, bottom ash, metakaolin, stone etc. can effectively replace a part or the whole of conventional materials used for concreting. Recycling of these wastes as construction material can be a sustainable practice. However, the green concrete so produced needs to satisfy certain parameters for its applicability. In recent years, studies have claimed that waste from dimensional stone industry can be effectively recycled into concrete, a practice certainly benefiting the stone as well as construction industries. This paper reviews the applicability of dimensional stone waste in concrete. The effect of stone waste substitution on workability, strength and durability parameters such as permeability, chloride migration, porosity, water absorption, carbonation, acid and sulphate resistance have been reviewed in the paper. It is suggested to investigate in-detail the durability of concrete containing dimensional stone waste to establish the same as popular construction material.

The excessive consumption of river sand as a construction material has led to its acute scarcity. Researchers across the globe have attempted to utilize waste of copper slag, rubber tyre, recycled glass, pond ash, foundry sand, plastic, stone etc. as a partial or complete substitute of river sand in concrete. The present study investigates the feasibility of using granite cutting waste (GCW) as a partial substitute of river sand in high strength concrete based on strength, durability & microstructural attributes. Eighteen concrete mixes were cast at 0.30, 0.35 and 0.40 water cement ratios (w/c) by substituting 0%, 10%, 25%, 40%, 55% and 70% river sand by GCW. The concrete mixes were tested for compressive, flexural strength, abrasive resistance, permeability, water absorption, carbonation, corrosion and microstructure; changes in morphology and hydration were also studied. Test results suggested that 25–40% river sand can be substituted by the GCW with a favourable influence on the investigated parameters. The optimum amount of GCW to be used in concrete depends significantly upon water-cement ratio of concrete.

Extractive and mining operations are one of the largest waste producing streams in the world. In general, mining operation is accompanied with the production of stone and slurry wastes. Suc...

Konkan Railway has many unstable slopes along the 741 km long route from Roha to Thokur in the states of Maharashtra, Goa and Karnataka in India. Frequent cases of boulder fall, slope failure and landslide used to occur on the track during the rainy season. Such cases have resulted in several severe train accidents, traffic interruptions, loss of lives and assets. Hence the Konkan Railway Corporation deployed several geotechnical measures such as wire-netting, retaining wall, rock bolting and shotcreting for stability enhancement. However, none of these measures proved effective and accidents continued. Finally, the Konkan Railway Corporation decided to redesign the cut-slopes using blasting. Excavation of hard rock for its removal without damaging the existing track (2– 3 m away from the slope) and disrupting the traffic, was a daunting task. An unplanned blast would have resulted in the closure of the route for hours. The present study explains the method in which entire cutting was redesigned by formation of 5 to 2 m wide berms at an interval of 6 m bench height from rail track level using novel direction controlled blasting technique. Further, stability of the cut-slope, before and after exacavation, has been determined using kinematic analysis and 3D numerical modelling. Similar technique can be adopted to widen or stabilize an active transportation route in hills.

Big Data is a fascinating subject to various businesses and industries. As every day, more and more data input happens at an astounding rate, managing and making sense out of the raw, heterogeneous, diverse, and variable data is itself a task much head heating. This paper presents a framework for Big data solutions in automated systems using cloud infrastructure its application. More than 8 exabytes of data is generated every day due to automatically generated data over the internet. The social networks, mobile devices, emails, blogs, video, forums, banking transaction and other consumer interaction, are now driving the need to store and explore this daily expanding Big Data. It concerns large volume, complex or unstructured data which are growing from multiple autonomous sources. During past years education and skill building through online portals has increased very much, this provides many opportunities for better understanding the minds of students for providing better correlations and real-time analysis. This paper integrates automated systems with cloud computing techniques to discover important insights for big data.

Depletion of natural resources and emission of carbon dioxide are the major factors associated with cement production. Also, conventional concrete often fails to prevent the ingress of moisture and aggressive ions adequately. The concern for concrete durability surfaced globally by the time the structures built with high grade concretes started yielding to distress. Several materials such as fly ash, metakaolin, silica fume, stone waste, rubber tyre, slag, wollastonite etc. which are either industrial wastes or natural minerals, have been examined to make durable concrete. Among the various admixtures studied in the past, the effect of wollastonite on concrete has not been investigated in detail. Wollastonite is a calcium meta-silicate (CaSiO3) mineral with particles similar to cement particles by size. In the present investigation, eighteen concrete mixes at three w/b ratios (0.45, 0.50 and 0.55) were prepared, by substituting Portland cement with wollastonite at varying replacement levels (0–25%). Substitution of 10–15% cement by wollastonite resulted in improved strength and durability of concrete. SEM and MIP results indicated that substitution of cement by wollastonite upto 15% reduced porosity and densified the concrete microstructure.