Original Baseline Research Articles

Effects of ‘pre-fracking’ operations on ambient air quality at a shale gas exploration site in rural North Yorkshire, England

Rural observations of air quality and meteorological parameters (NOx, O3, NMHCs, SO2, PM) were made over a 2.5-year period (2016–2018) before, during and after preparations for hydraulic fracturing (fracking) at a shale gas exploration site near Kirby Misperton, North Yorkshire, England. As one of the first sites to apply for permits to carry out hydraulic fracturing, it has been subject to extensive regulatory and public scrutiny, as well as the focus for a major programme of long-term environmental monitoring. A baseline period of air quality monitoring (starting 2016) established the annual climatology of atmospheric composition against which a 20-week period of intensive activity on the site in preparation for hydraulic fracturing could be compared. During this ‘pre-operational phase’ of work in late 2017, the most significant effect was an increase in ambient NO (3-fold) and NOx (2-fold), arising from a combination of increased vehicle activity and operation of equipment on site. Although ambient NOx increased, air quality limit values for NO2 were not exceeded, even close to the well-site. Local ozone concentrations during the pre-operational period were slightly lower than the baseline phase due to titration with primary emitted NO. The activity on site did not lead to significant changes in airborne particulate matter or non-methane hydrocarbons. Hydraulic fracturing of the well did not subsequently take place and the on-site equipment was decommissioned and removed. Air quality parameters then returned to the original (baseline) climatological conditions. This work highlights the need to characterise the full annual climatology of air quality parameters against which short-term local activity changes can be compared. Based on this study, changes to ambient NOx appear to be the most significant air quality ahead of hydraulic fracturing. However, in rural locations, concentrations at individual sites are expected to be below ambient air quality limit thresholds.

The Effect of UV Illumination on the Room Temperature Detection of Vaporized Ammonium Nitrate by a ZnO Coated Nanospring-Based Sensor.

The effect of UV illumination on the room temperature electrical detection of ammonium nitrate vapor was examined. The sensor consists of a self-assembled ensemble of silica nanosprings coated with zinc oxide. UV illumination mitigates the baseline drift of the resistance relative to operation under dark conditions. It also lowers the baseline resistance of the sensor by 25% compared to dark conditions. At high ammonium nitrate concentrations (120 ppm), the recovery time after exposure is virtually identical with or without UV illumination. At low ammonium nitrate concentrations (20 ppm), UV illumination assists with refreshing of the sensor by stimulating analyte desorption, thereby enabling the sensor to return to its baseline resistance. Under dark conditions and low ammonium nitrate concentrations, residual analyte builds up with each exposure, which inhibits the sensor from returning to its original baseline resistance and subsequently impedes sensing due to permanent occupation of absorption sites.

Adversarial Adaptation From Synthesis to Reality in Fast Detector for Smoke Detection

Video smoke detection is a promising method for early fire prevention. However, it is still a challenging task for application of video smoke detection in real-world detection systems, as the limitations of smoke image samples for training and lack of efficient detection algorithm. This paper proposes a method based on two state-of-the-art fast detectors, a single-shot multi-box detector, and a multi-scale deep convolutional neural network, for smoke detection using synthetic smoke image samples. The virtual data can automatically offer rich samples with ground truth annotations. However, the learning of smoke representation in the detectors will be restricted by the appearance gap between real and synthetic smoke samples, which will cause a significant performance drop. To train a strong detector with synthetic smoke samples, we incorporate the domain adaptation into the fast detectors. A series of branches with the same structure as the detection branches are integrated into the fast detectors for domain adaptation. We design an adversarial training strategy to optimize the model of the adapted detectors, to learn a domain-invariant representation for smoke detection. The domain discrimination, domain confusion, and detection are combined in the iterative training procedure. The performance of the proposed approach surpasses the original baseline in our experiments.

QUALITY OF CROWDSOURCED RELEVANCE JUDGMENTS IN ASSOCIATION WITH LOGICAL REASONING ABILITY

Crowdsourcing has become a low-cost and scalable alternative to gather relevance assessments through crowdsourcing platforms. However, when gathering subjective human judgments, it can be challenging to enforce data quality due to the lack of vision about how judges make a decision. It is important to determine the attributes that could affect the effectiveness of crowsourced-judgments in an information retrieval systems evaluation. The purpose of the experiment that is discussed in this paper is to investigate if logical reasoning ability of the crowd workers is related to the quality of the relevant judgments produced through the crowdsource process. The study also evaluates the effect of cognitive characteristics on the quality of relevance judgment compared to the gold standard dataset. Through this experiment, a comparison study is done between the quality of the judgments obtained through the crowdsourcing process and the original baseline judgments generated by the hired experts by TREC. In the study, the systems performances were measured using both of these sets of relevance judgments to see its correlation. The experimentation reveals that quality of relevance judgments is highly correlated with the logical reasoning ability of individuals. The judgment difficulty level reported by the crowdsource workers and the confidence level claimed by the workers showed a significant correlation with the quality of the judgments. Unexpectedly though, self-reported knowledge about a given topic and demographics data have no correlation with the quality of judgments produced through crowdsourcing

Long term outcome after anti-VEGF treatment—what do we know about the impact of morphological parameters?

Despite the initial positive effect of anti-VEGF treatment in eyes with neovascular AMD (nAMD), long-term results still remain un-satisfying (1-3). Five-year outcomes from the CATT study showed a mean decline of 11 letters from the 2-year follow-up visit, and 3 letters compared to the original baseline (3).

Linking design and operation performance analysis through model calibration: Parametric assessment on a Passive House building

Efficient buildings are an essential component of sustainability and energy transitions, which represent today a techno-economic and socio-economic problem. New paradigms are emerging both for new and existing buildings (e.g. NZEBs) and passive design strategies are becoming increasingly common. However, the adoption of these strategies in mild climates has to be carefully evaluated to prevent overheating in intermediate seasons and increasing cooling loads in summer, considering also climate change scenarios. Additionally, optimistic assumptions about building technology performance are often considered and the variability of occupant comfort preferences and behaviour is generally neglected in the design phase. The research presented aims at verifying the suitability of a simple, robust and scalable calibration approach (based on multivariate linear regression) to link design and operational performance analysis transparently, using a Passive House case study building. First, the original baseline design configuration is compared with a larger spectrum of data generated by means of parametric simulation, following a Design of Experiment (DOE) approach. After that, regression models are trained first on simulation data and then progressively calibrated on measured data during a three year monitoring period. The two fundamental objectives are evaluating the robustness of design phase performance analysis through parametric simulation (i.e. detecting potentially critical assumptions) and maintaining a continuity with operation phase performance analysis (i.e. exploiting the feed-back from measured data).

Collagen fiber crimping following in vivo UVA-induced corneal crosslinking

The purpose of this study was to measure collagen fiber crimping (CFC) using nonlinear optical imaging of second harmonic generated (SHG) signals to determine the effects of UVA-riboflavin induced corneal collagen crosslinking (UVA CXL) on collagen structure. Two groups, four rabbits each, were treated in the right eye with standard UVA CXL. In vivo confocal microscopy was performed at 1, 2, and 4 weeks after treatment for the first group and up to three months for the second group to measure epithelial/stromal thickness and corneal haze during recovery. Rabbits were sacrificed at one and three months, respectively, and their corneas fixed under pressure. Regions of crosslinking were identified by the presence of collagen autofluorescence (CAF) and then collagen structure was imaged using SHG microscopy. The degree of CFC was determined by measuring the percentage difference between the length of the collagen fiber and the linear distance traveled. CFC was measured in the central anterior and posterior CXL region, the peripheral non-crosslinked region in the same cornea, and the central cornea of the non-crosslinked contralateral eye. No change in corneal thickness was detected after one month, however the stromal thickness surpassed its original baseline thickness at three months by 25.9 μm. Corneal haze peaked at one month and then began to clear. Increased CAF was detected in all CXL corneas, localized to the anterior stroma and extending to 42.4 ± 3.4% and 47.7 ± 7.6% of the corneal thickness at one and three months. There was a significant (P < 0.05) reduction in CFC in the CAF region in all eyes averaging 1.007 ± 0.006 and 1.009 ± 0.005 in one and three month samples compared to 1.017 ± 0.04 and 1.016 ± 0.06 for controls. These results indicate that there is a significant reduction in collagen crimping following UVA CXL of approximately 1%. One possible explanation for this loss of crimping could be shortening of the collagen fibers over the CXL region.

Evaluating the Link between Low Carbon Reductions Strategies and Its Performance in the Context of Climate Change: A Carbon Footprint of a Wood-Frame Residential Building in Quebec, Canada

The design and study of low carbon buildings is a major concern in a modern economy due to high carbon emissions produced by buildings and its effects on climate change. Studies have investigated (CFP) Carbon Footprint of buildings, but there remains a need for a strong analysis that measure and quantify the overall degree of GHG emissions reductions and its relationship with the effect on climate change mitigation. This study evaluates the potential of reducing greenhouse gas (GHG) emissions from the building sector by evaluating the (CFP) of four hotpots approaches defined in line with commonly carbon reduction strategies, also known as mitigation strategies. CFP framework is applied to compare the (CC) climate change impact of mitigation strategies. A multi-story timber residential construction in Quebec City (Canada) was chosen as a baseline scenario. This building has been designed with the idea of being a reference of sustainable development application in the building sector. In this scenario, the production of materials and construction (assembly, waste management and transportation) were evaluated. A CFP that covers eight actions divided in four low carbon strategies, including: low carbon materials, material minimization, reuse and recycle materials and adoption of local sources and use of biofuels were evaluated. The results of this study shows that the used of prefabricated technique in buildings is an alternative to reduce the CFP of buildings in the context of Quebec. The CC decreases per m2 floor area in baseline scenario is up to 25% than current buildings. If the benefits of low carbon strategies are included, the timber structures can generate 38% lower CC than the original baseline scenario. The investigation recommends that CO2eq emissions reduction in the design and implementation of residential constructions as climate change mitigation is perfectly feasible by following different working strategies. It is concluded that if the four strategies were implemented in current buildings they would have environmental benefits by reducing its CFP. The reuse wood wastes into production of particleboard has the greatest environmental benefit due to temporary carbon storage.

Exploiting Sparsity to Accelerate Fully Connected Layers of CNN-Based Applications on Mobile SoCs

Convolutional neural networks (CNNs) are widely employed in many image recognition applications. With the proliferation of embedded and mobile devices, such applications are becoming commonplace on mobile devices. Network pruning is a commonly used strategy to reduce the memory and storage footprints of CNNs on mobile devices. In this article, we propose customized versions of the sparse matrix multiplication algorithm to speed up inference on mobile devices and make it more energy efficient. Specifically, we propose a Block Compressed Sparse Column algorithm and a bit-representation-based algorithm (BitsGEMM) that exploit sparsity to accelerate the fully connected layers of a network on the NVIDIA Jetson TK1 platform. We evaluate the proposed algorithms using real-world object classification and object detection applications. Experiments show that performance speedups can be achieved over the original baseline implementation using cuBLAS. On object detection CNNs, an average speedup of 1.82× is obtained over baseline cuBLAS in the fully connected layer of the VGG model, whereas on classification CNNs, an average speedup of 1.51× is achieved for the fully connected layer of the pruned-VGG model. Energy consumption reduction of 43--46% is also observed due to decreased computational and memory bandwidth demands.

The impact of an educational intervention on home support workers' ability to detect early pressure ulcer damage.

To investigate the impact of an educational intervention on home support workers' ability to detect early pressure ulcer damage. A repeated measure design was employed to quantify the effectiveness of an educational intervention, consisting of one pre-test and two post-tests. Education was provided to home support workers and this was followed by an assessment of their ability to correctly classify 20 photographs detailing varying stages of skin damage severity. At the baseline (pre-education), 58% of the photographs were classified correctly. At post-test 1, 55% of the photographs were classified correctly. In post-test 2 this increased to 58%, achieving the original baseline scores. There was a moderate negative relationship between pre-training and post-test 2 scores (r=-0.44; n=27; p=0.02). The educational intervention has been shown not to have a statistically significantly positive effect on home support workers' ability to detect early pressure ulcer damage. The moderate negative relationship between pre-training and post-test 2 scores concur with the aforementioned qualitative findings, and similarly indicate behaviour associated with individuals experiencing difficulty comprehending new health terms.

Revisiting the long-run energy mix with the global energy market model (GEM)

The objective of this paper is to estimate the long-run energy mix—i.e., the combination of resources including solids, liquids, and gases that will satisfy energy demand to the year 2040—with a Global Energy Market model (GEM). The GEM first provides a close match of the historical energy mix dating back to 1850 and is then used to make forecasts for the future. Originally developed in 2007, the model was used at that time to project the energy mix to the year 2030. The original findings from 2007 introduced a “2030 1/3 forecast,” indicating that solids, liquids, and gases would each occupy a third of the energy market in 2030. After further disaggregating the categories, it was found that liquids, mostly oil, would experience a declining market share by 2030 while natural gas would see a rapid rise. The solids’ share, mostly coal, was relatively flat by that time. This paper uses the most recent statistics of the last 10 years on consumption of different energy sources to verify the accuracy of the original GEM baseline scenario carried out in 2007. Once the results are proven reasonable, the scenario’s time horizon is extended to the year 2040—a limit in which outcomes can be reasonably conceptualized and quantified. Our findings show continued penetration of natural gas in the energy mix—a result consistent with efforts to reduce carbon emissions. In reality, that outcome will be contingent on the enactment of policies that encourage the development, transportation, and consumption of gas.

The impact of an educational intervention on Home Support Workers' ability to detect pressure ulcer damage

Introduction: Internationally, pressure ulcers remain a significant health care problem (NPUAP, EPUAP and PPPIA, 2014). Skin assessment is an essential component in pressure ulcer prevention, however, there is evidence to suggest that patients may not always receive the correct level of care to maintain their skin integrity (Samuriwo, 2010). Home Support Workers are directly involved in patient care, and they have a pivotal role to play in skin assessment (Athlin et al, 2010). All health care workers require education to fulfil this role. Aim & Objective: To investigate the impact of an educational intervention on Home Support Workers’ ability to detect early pressure ulcer damage. Method: A repeated measure design was employed to quantify the effectiveness of an educational intervention, consisting of one pre-test and two post-tests. This was followed by a workshop, tasked with reflecting on the educational intervention. To capture participant issues following the educational intervention, words used by them were recorded, as they represented the terms and language used to articulate their main concerns and affirmations. Outcomes: Education was provided to Home Support Workers and this was followed by an assessment of their ability to correctly classify 20 photographs detailing varying stages of skin damage severity. At the baseline (pre-education), 58% of the photographs were classified correctly. The post-test 1 results were lower, with 55% of the photographs being classified correctly. In post-test 2 findings, results increased to 58%, achieving the original baseline scores. There was a moderate negative relationship between pre-training and post-test 2 scores (r=-.44; n=27; p=0.02). Conclusion: The educational intervention has been shown not to have a statistically significant positive effect on Home Support Workers’ ability to detect early pressure ulcer damage. The moderate negative relationship between pre-training and post-test 2 scores and can be principally explained by low health literacy among the participants. The workshop group findings exposed educational issues relating to participant ability to understand theoretical health concepts. These difficulties were fundamentally linked to low health literacy among the participants.

M3L: Multi-modality mining for metric learning in person re-Identification

Learning a scene-specific distance metric from labeled data is critical for person re-identification. Most of the earlier works in this area aim to seek a linear transformation of the feature space such that relevant dimensions are emphasized while irrelevant ones are discarded in a global sense. However, when training data exhibit multi-modality transitions, the globally learned metric would deviate from the correct metrics learned from each modality. In this study, we propose a multi-modality mining approach for metric learning (M3L) to automatically discover multiple modalities of illumination changes by exploring the shift-invariant property in log-chromaticity space, and then learn a sub-metric for each modality to maximally reduce the bias derived from metric learning model with global sense. The experiments on the challenging VIPeR dataset and the fusion dataset VIPeR&PRID 450S have validated the effectiveness of the proposed method with an average improvement of 2–7% over original baseline methods.

Long-term follow-up on patients treated for abdominal fat using a selective contactless radiofrequency device.

The aim of this study was to evaluate how abdominal circumferential reduction achieved after using a noninvasive radiofrequency device (BTL Vanquish, BTL Industries Inc., Boston, MA) evolves over a 4-year period. This is a follow-up on patients who were treated in our practice for abdominal fat in an earlier published multicenter prospective study. Patients were recalled for biometric data collection 4years (±60days) after the last treatment. Body and weight measurements were compared to the historical data. Digital images of the treated area were taken. Independent panelists were asked to recognize the original baseline images from the 4-year follow-up images. The evaluation encompasses 13 subjects. In the original study, these patients lost on average 5.88±4.14cm of waist circumference (P<.001) while losing on average 1.29kg. After 4years, the same subjects had an average reduction of 4.42±2.85cm (P<.001) compared to the baseline, while gaining on average 0.50kg. In both cases, the waist change was statistically independent of the weight change (P<.01). The patients preserved on average 75.2% of the original body contouring effect after 4years as measured by circumference. None of the patients grew in circumference when compared to the baseline. Reviewers recognized the baseline patient images from the follow-up patient images in 82.1% cases. No long-term side effects were observed that would relate to the treatments. In the study group, patients with ordinary weight changes preserved most of the original waist reduction after 4years.

Sediment geochronology for bar-built estuaries subject to flood deposition and erosion: A robust multiproxy approach across an estuarine zone

This paper presents a contiguous late Anthropocene 210Pb sediment geochronology and a late Anthropocene flood/fire event geochronology for an estuary subject to flood deposition and erosion. The procedure used multiple proxies to identify and evaluate flood facies overlying regions of erosion. Reconstructions of the original baseline sediments were undertaken for the major 210Pb geochronological methods. Only the lower estuary core site, which was deficient in inventory of excess 210Pb of baseline sediments, over the expected atmospheric supply for, was chosen to calculate the total amount of erosion. Erosion, as both cumulative mass and thickness, was then proportioned across flood events, relative to the size of the Rp index flood signal. The Rp index is the product of a simple stepwise thermogravimetric procedure. The flood geochronology was constructed by correlating the relative magnitudes of pivotal floods from an existing 100-year rainfall/river flow model and correlations in peak sediment char content outside of the flood facies with contemporary fire records. Overall, it was determined that 210Pb sediment isotope tomography gave the closest convergence with flood and fire events over those of the constant rate of supply and constant initial concentration methods. The agreement signified that around 40% of the original baseline accretion (25 cm) had been eroded by floods over the last 83 years and that there was possibly considerably more erosion at the upper site, which led to the loss of two flood facies.

Impact of Cataract Surgery during Treatment with Ranibizumab in Patients with Diabetic Macular Edema

To determine how best-corrected visual acuity (BCVA) was affected by cataract surgery in patientswith diabetic macular edema (DME) who were treated with ranibizumab during the RIDE/RISE phaseIIItrials. Post hoc analysis of data from RIDE and RISE, 2 phase III, parallel, randomized, multicenter, double-masked trials (clinicaltrials.gov identifiers, NCT00473382 and NCT00473330). Patients with DME (N= 759) who were randomized 1:1:1 to monthly intravitreal ranibizumab 0.3 mg or 0.5 mg, or sham injections for 24 months. Patient records in the electronic RIDE/RISE study database were examined for cataract surgeries using the terms "cataract extraction," "cataract removal," "cataract surgery," "lens implant," and "lensectomy." The last study visit immediately before cataract surgery served as the redefined baseline to examine subsequent BCVA changes. The t test was performed to compare times to cataract surgery for the sham and pooled ranibizumab groups. Mean change in BCVA from redefined baseline to 1, 2, and 3 months (±15 days) after surgery. Among study eyes that underwent cataract surgery, mean BCVA at original study baseline was 54.6 letters in the pooled ranibizumab arms and 56.6 letters in the sham arm (approximate Snellen equivalent 20/80). At the redefined presurgery baseline, mean BCVA was 54.2 letters for the pooled ranibizumab group and 46.6 letters for the sham-treated study eyes. Compared with the redefined baseline, at 1 month after surgery, mean BCVA changes were+10.6 letters for ranibizumab-treated patients and+10.3 letters for sham-treated patients. Compared with the original baseline, at 1 month after surgery, on average, ranibizumab-treated study eyesexperienced mean BCVA improvement (+11.3 letters), whereas sham-treated eyes (-0.5 letters) and felloweyes (+1.8 and+1.7 letters for ranibizumab and sham, respectively) had a mean BCVA similar to the original baseline. In patients undergoing ranibizumab treatment for DME and who had cataract surgery, an average of 2 lines of vision were gained from the last visit before surgery to 1 month after surgery.

Recruitment and retention of child welfare workers in longitudinal research: Successful strategies from the Florida Study of Professionals for Safe Families

Longitudinal panel studies are effective strategies to assess the personal impact of child welfare work, as well as employment outcomes of workers over time. However, longitudinal studies encounter obstacles such as disproportionate attrition that threaten the validity of findings. This paper provides an overview of the Florida Study of Professionals for Safe Families (FSPSF), a 5-year longitudinal panel study of newly hired workers into the child welfare workforce. The purpose of this paper is three-fold: 1) describe the study methodology and recruitment and retention techniques for the FSPSF; 2) illustrate Estrada and colleagues' Tailored Panel Management framework (2014) through FSPSF methodological decisions; and 3) provide guidance and time estimates of key tasks for those interested in undertaking similar projects, with a particular focus on electronic data collection and communication strategies. Initial results are excellent – 84% of all eligible workers completed baseline surveys (n=1,451). At Wave 2 (6 months), 81% of those workers were retained, with preliminary findings of 84% retention of the original baseline respondents at Wave 3 (12 months).

Performance assessment of peat rail subgrade before and after mass stabilization

Railway tracks over peat subgrades can experience large ground deformations, increased pore-water pressures, formation of pumping holes, and pumping of fines during the passage of trains, which can lead to accelerated track deterioration and risk of derailment. One approach to mitigate these issues is to improve the subgrade stiffness using mass stabilization, which involves mixing a binding agent, such as cement, into a soil to improve its physical properties. This paper describes the development and use of a method to calculate trackbed modulus to quantify the improvement due to mass stabilization at a site with peat subgrade. Track modulus was calculated using in-service freight trains by measuring track displacements using digital image correlation and wheel loads from a nearby wheel impact load detector. Because of the voids that existed between the rail, sleepers, and ballast it was found that using displacements of the ballast crib to calculate the trackbed modulus, instead of the overall track modulus using rail or sleeper displacements, provided a way to quantify the improvement of the subgrade that was not affected by the presence of voids. The results indicate the post-rehabilitation trackbed modulus was double the original baseline value for the track section, indicating that mass stabilization can be an effective rehabilitation strategy to improve the stiffness of problematic peat subgrades.

Optimism bias within the project management context

PurposeOne of the major challenges for any project is to prepare and develop an achievable baseline schedule and thus set the project up for success, rather than failure. The purpose of this paper is to explore and investigate research outputs in one of the major causes, optimism bias, to identify problems with developing baseline schedules and analyse mitigation techniques and their effectiveness recommended by research to minimise the impact of this bias.Design/methodology/approachA systematic quantitative literature review was followed, examining Project Management Journals, documenting the mitigation approaches recommended and then reviewing whether these approaches were validated by research.FindingsOptimism bias proved to be widely accepted as a major cause of unrealistic scheduling for projects, and there is a common understanding as to what it is and the effects that it has on original baseline schedules. Based upon this review, the most recommended mitigation method is Flyvbjerg’s “Reference class,” which has been developed based upon Kahneman’s “Outside View”. Both of these mitigation techniques are based upon using an independent third party to review the estimate. However, within the papers reviewed, apart from the engineering projects, there has been no experimental and statistically validated research into the effectiveness of this method. The majority of authors who have published on this topic are based in Europe.Research limitations/implicationsThe short-listed papers for this review referred mainly to non-engineering projects which included information technology focussed ones. Thus, on one hand, empirical research is needed for engineering projects, while on the other hand, the lack of tangible evidence for the effectiveness of methods related to the alleviation of optimism bias issues calls for greater research into the effectiveness of mitigation techniques for not only engineering projects, but for all projects.Originality/valueThis paper documents the growth within the project management research literature over time on the topic of optimism bias. Specifically, it documents the various methods recommended to mitigate the phenomenon and highlights quantitatively the research undertaken on the subject. Moreover, it introduces paths for further research.

Impact of intervention on awareness of biomedical waste disposal among medical students

Background :The proper management of biomedical waste has become a worldwide humanitarian topic today. Hazards of poor management of biomedical waste have aroused the concern world over, especially in the light of its far-reaching effects on human, health and the environment. With this milieu, this interventional study was carried out on medical students aimed at assessing and creating the awareness of knowledge of Biomedical Waste Management (BMWM) among Second year MBBS Students. Methods : Multiple-choice-Question(MCQ) based Questionnaire was administered to the students. This was followed by a lecture on Biomedical Waste Management.The same MCQ based Questionnaire was administered to the students immediately after the lecture and after one month.The questions in the test were based on Four domains-“Existence of Biomedical Waste rules”, “Categories of Waste”, “Different colour codes used” and “Waste disposal methods” Mean scores were calculated for the entire tests as well as for these domains. Results: Mean scores in pre-lecture test indicated that awareness of Biomedical Waste Management amongst medical students was quite low.Mean scores were higher in post lecture test and post one month test, indicating that the knowledge of the various aspects of biomedical waste management significantly improved after the lecture conducted by the investigator of the study However, the knowledge did not sustain after one month, though it was still higher than the original baseline level. Friedman test and Wilcoxon signed rank tests were used to prove the statistical significance. Conclusion: This study shows that early sensitisation about BMWM in Second MBBS students who are future doctors will improve awareness of BMWM. Repeated sensitisation is needed for the knowledge levels to sustain. DOI: 10.21276/APALM.1251