Identifying opportunities and obstacles for the use of solar energy in commercial office buildings in the northeastern region of united states

The aim of this research was to find the existing challenges to and opportunities for the use of solar energy, in commercial office buildings in the northeastern region of the United States. Although solar energy is an abundant source of energy, it is still not the number one source of energy when compared to other renewable sources of energy. This research explored some of the hindrances or hurdles associated with it and any new opportunities available. The research tried to analyze the various solar energy utilization strategies or other renewable energy strategies employed in a Leadership in Energy and Environmental Design (LEED) certified building and the motivation behind them. Throughout this research study different initiatives, progress and future outlook related to the goal are discussed. Case studies that included surveys or in-depth interviews were conducted along with extensive literature review for this research study. LEED Certified green buildings located in the northeastern region of the United States were selected for the case studies. The case studies included buildings where solar energy was actively utilized and where solar energy was not utilized. The information collected from the case studies, surveys and interviews were used for further analysis and drawing conclusions for this research. Though the idea to use solar energy in buildings has been discussed in the past decades, recent years have witnessed factors that have brought increased focus on the use of alternative energy, including solar energy. The research underlines the importance of aspects such as financial viability, government initiatives or incentives and environmental benefits or concerns. The results of this research present the current opportunities and challenges for solar energy utilization in commercial buildings, which may be of interest to individuals or research institutions, industry or government

Improving the accuracy and efficiency of bird song analysis with machine learning based event detection

Ornithology is an exciting field with novel research emerging everyday. Researchers in bioacoustics often spend hours within the wilderness recording bird calls to analyze later in their lab. The burden of sifting through hours of audio recordings from the field continues to remain a time-consuming and manual task, despite the inherent value of such research. In this work, we investigate the ability of a mobile application to provide an accelerated method for ornithologists to upload acoustic field recordings for analysis. Driven by recent advancements in technology, there is a growing need for innovative solutions that can streamline this research process. Our proposed solution integrates machine learning algorithms with bioacoustic signal processing with the goal of accelerating the process of analyzing hours of field recordings. In this thesis, we focus on the integration of future machine learning algorithms into an event detection pipeline. This larger project involves three separate parts: (1) the user interface and back end architecture developed by a small team of students for the Oregon State CS 46x capstone series, (2) an event detection algorithm completed as a synergistic extension of the capstone, and (3) a machine learning system developed as part of a graduate thesis. Together, these projects integrate to enhance the accuracy and efficiency of bioacoustic event detection by leveraging machine intelligence with deep learning. Furthermore, we evaluate the performance of these approaches using real-world datasets and discuss our approach in the context of traditional event detection techniques. This research project contributes valuable insights into the feasibility and effectiveness of integrating machine learning algorithms into a cloud-based acoustic event detection pipeline and highlights the potential benefits of this integration for various applications to expedite time-consuming bioacoustic research processes.Key Words: audio processing, bioacoustics, bird song, event detection, databas

CYBER SECURITY SOLUTIONS FOR DLMS METERS USING GSM/GPRS TECHNOLOGY

The Smart meters are used in the areas of generation, transmission, distribution and consumption. The capabilities of smart meter systems and grid networks, such as distributed intelligence and broadband capabilities can greatly enhance efficiency and reliability, but they may also create much new vulnerability if not deployed with the appropriate security controls. Much of the technology currently in use by the meters are outdated and in many cases unreliable. A system architecture implementing should recognize security threats and capture events that result not from external threats but from internal mistakes, with human error being a more common occurrence. An effective security approach enhances reliability because some security failures might be people failures, while others might be equipment failures, might be due to natural causes or might be deliberate. A simple perimeter defense is not sufficient; monitoring, both for events and physical actions, is required to bring the benefits of smart meters with minimal risk to this vital part of the infrastructure of modern life

Production of Pectinase from Bacillus sonorensis MPTD1

U radu je ispitanaproizvodnja pektinaze na podlozi s agarom s pomoću sedam sojeva bakterija izoliranih iz pokvarenog voća i povrća. Najučinkovitiji soj, MPTD1, identificiran je kao soj bakterije Bacillus sonorensis. Primjenom Plackett-Burman i Box-Behnken statističkih planova optimirani su različiti parametri, te je utvrđeno da udjeliekstrakta kvasca, K2HPO4,NaNO3i KCl te vrijeme inkubacije negativno utječu na proizvodnju pektinaze. Najveća postignuta aktivnost enzima bila je 2,43 (μM/mL)/min. U ovom je radu po prvi put opisana proizvodnja pektinaze s pomoću bakterije Bacillus sonorensis.Seven isolates from spoiled fruits and vegetables were screened for pectinase produc¬tion using pectin agar plates and the most efficient bacterial strain, MPTD1, was identified as Bacillus sonorensis. Optimisation of various process parameters was done using Plack¬ett-Burman and Box-Behnken designs and it was found that parameters like yeast extract, K2HPO4, incubation time, NaNO3 and KCl have a negative impact on pectinase production. Parameters like pH and MgSO4 and pectin mass fractions have a positive impact on pecti¬nase production. The maximum obtained enzyme activity was 2.43 (μM/mL)/min. This is the first report on pectinase production by Bacillus sonorensis

A coherent feed-forward loop drives vascular regeneration in damaged aerial organs of plants growing in a normal developmental context

Aerial organs of plants, being highly prone to local injuries, require tissue restoration to ensure their survival. However, knowledge of the underlying mechanism is sparse. In this study, we mimicked natural injuries in growing leaves and stems to study the reunion between mechanically disconnected tissues. We show that PLETHORA (PLT) and AINTEGUMENTA (ANT) genes, which encode stem cell-promoting factors, are activated and contribute to vascular regeneration in response to these injuries. PLT proteins bind to and activate the CUC2 promoter. PLT proteins and CUC2 regulate the transcription of the local auxin biosynthesis gene YUC4 in a coherent feed-forward loop, and this process is necessary to drive vascular regeneration. In the absence of this PLT-mediated regeneration response, leaf ground tissue cells can neither acquire the early vascular identity marker ATHB8, nor properly polarise auxin transporters to specify new venation paths. The PLT-CUC2 module is required for vascular regeneration, but is dispensable for midvein formation in leaves. We reveal the mechanisms of vascular regeneration in plants and distinguish between the wound-repair ability of the tissue and its formation during normal development.Peer reviewe

Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017

Background To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and inequality between districts within the states. Methods We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5 × 5 km grid estimates, using all accessible data from various surveys with subnational geographical information. The states were categorised into three groups using their Socio-demographic Index (SDI) levels calculated as part of the Global Burden of Disease Study based on per capita income, mean education and fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using coefficient of variation (CV). We projected the prevalence of CGF indicators for the districts up to 2030 based on the trends from 2000 to 2017 to compare with the NNM 2022 targets for stunting and underweight, and the WHO/UNICEF 2030 targets for stunting and wasting. We assessed Pearson correlation coefficient between two major national surveys for district-level estimates of CGF indicators in the states. Findings The prevalence of stunting ranged 3.8-fold from 16.4% (95% UI 15.2–17.8) to 62.8% (95% UI 61.5–64.0) among the 723 districts of India in 2017, wasting ranged 5.4-fold from 5.5% (95% UI 5.1–6.1) to 30.0% (95% UI 28.2–31.8), and underweight ranged 4.6-fold from 11.0% (95% UI 10.5–11.9) to 51.0% (95% UI 49.9–52.1). 36.1% of the districts in India had stunting prevalence 40% or more, with 67.0% districts in the low SDI states group and only 1.1% districts in the high SDI states with this level of stunting. The prevalence of stunting declined significantly from 2010 to 2017 in 98.5% of the districts with a maximum decline of 41.2% (95% UI 40.3–42.5), wasting in 61.3% with a maximum decline of 44.0% (95% UI 42.3–46.7), and underweight in 95.0% with a maximum decline of 53.9% (95% UI 52.8–55.4). The CV varied 7.4-fold for stunting, 12.2-fold for wasting, and 8.6-fold for underweight between the states in 2017; the CV increased for stunting in 28 out of 31 states, for wasting in 16 states, and for underweight in 20 states from 2000 to 2017. In order to reach the NNM 2022 targets for stunting and underweight individually, 82.6% and 98.5% of the districts in India would need a rate of improvement higher than they had up to 2017, respectively. To achieve the WHO/UNICEF 2030 target for wasting, all districts in India would need a rate of improvement higher than they had up to 2017. The correlation between the two national surveys for district-level estimates was poor, with Pearson correlation coefficient of 0.7 only in Odisha and four small north-eastern states out of the 27 states covered by these surveys. Interpretation CGF indicators have improved in India, but there are substantial variations between the districts in their magnitude and rate of decline, and the inequality between districts has increased in a large proportion of the states. The poor correlation between the national surveys for CGF estimates highlights the need to standardise collection of anthropometric data in India. The district-level trends in this report provide a useful reference for targeting the efforts under NNM to reduce CGF across India and meet the Indian and global targets. Keywords Child growth failureDistrict-levelGeospatial mappingInequalityNational Nutrition MissionPrevalenceStuntingTime trendsUnder-fiveUndernutritionUnderweightWastingWHO/UNICEF target

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016