Studies on the essential oil of Anemopsis Californica

The roots and rhizomes of Anemopsis Californica (Nutt.) Hook and Arn. (family Saururaceae) have been used by the early Spanish Americans and Indians to treat a variety of ailments. The plant is commonly known as Yerba del Mansa, Yerba Mansa, or Manza. We decided to investigate the essential oil of Anemopsis Californica in greater detail. The results of our investigation to date are included and described in this thesis

Characterization of Intermetallic Precipitates in Ni-Base Alloys by Non-destructive Techniques

The present industrial scenario requires all engineering structure to be designed considering stability of several parameters at the operating conditions (e.g. Temperature, pressure, resistance to mechanical and surface degradation). Choice of materials for any engineering component should be such that it operates safely for reliable function, without failure during in-service, giving optimum component life. Due to scarcity of various resources and cost of manufacturing, regular maintenance and evaluation of structural integrity at every stage of production is necessary. Non-destructive techniques (NDT), along with modern computational facility help in non-intrusive investigation of the component at regular intervals of the operating stages for many critical applications. This will result in increment of designed component life and also help in maximizing utilization of natural resources

Causative Cyberattacks on Online Learning-based Automated Demand Response Systems

Power utilities are adopting Automated Demand Response (ADR) to replace the costly fuel-fired generators and to preempt congestion during peak electricity demand. Similarly, third-party Demand Response (DR) aggregators are leveraging controllable small-scale electrical loads to provide on-demand grid support services to the utilities. Some aggregators and utilities have started employing Artificial Intelligence (AI) to learn the energy usage patterns of electricity consumers and use this knowledge to design optimal DR incentives. Such AI frameworks use open communication channels between the utility/aggregator and the DR customers, which are vulnerable to \textit{causative} data integrity cyberattacks. This paper explores vulnerabilities of AI-based DR learning and designs a data-driven attack strategy informed by DR data collected from the New York University (NYU) campus buildings. The case study demonstrates the feasibility and effects of maliciously tampering with (i) real-time DR incentives, (ii) DR event data sent to DR customers, and (iii) responses of DR customers to the DR incentives

Political Economy of International Climate Finance: Navigating Decisions in PPCR and SREP

This working paper explores how countries can build their own 'climate finance readiness' by understanding their internal political economy and use that understanding to steer consensus-based decisions on climate finance investments. For climate finance to be effective, national leaders must build shared commitments. This involves considering the arguments, incentives and power dynamics at play to ensure priorities are more equitable and representative of a broader group of stakeholders. Doing so will also help to reduce the risk of implementation delays. This paper uses case studies from Bangladesh, Ethiopia and Nepal to explore how narratives and incentives within the political economy drive climate investment outcomes under the Pilot Programme for Climate Resilience (PPCR) and the Scaling up Renewable Energy Programme (SREP). It draws from broader analysis of the discourses around these investments, including 80 interviews with government; multilateral development banks (MDBs) and other stakeholders

MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid Operation

This paper examines the feasibility of demand-side cyberattacks on power grids launched via internet-connected high-power EV Charging Stations (EVCSs). By distorting power grid frequency and voltage, these attacks can trigger system-wide outages. Our case study focuses on Manhattan, New York, and reveals that such attacks will become feasible by 2030 with increased EV adoption. With a single EVCS company dominating Manhattan, compromising a single EVCS server raises serious power grid security concerns. These attacks can overload power lines and trip over-frequency (OF) protection relays, resulting in a power grid blackout. This study serves as a crucial resource for planning authorities and power grid operators involved in the EV charging infrastructure roll-out, highlighting potential cyberthreats to power grids stemming from high-power EVCSs.Comment: This paper is accepted for publication in the proceeding of IEEE ISGT NA 2024 in Washington DC, US

Variability for growth and yield traits in single cross hybrids of maize (Zea mays L.)

Saabunud / Received 29.09.2021 ; Aktsepteeritud / Accepted 18.11.2021 ; Avaldatud veebis / Published online 18.11.2021 ; Vastutav autor / Corresponding author: Jiban Shrestha [email protected] single-cross hybrids of maize were evaluated in a randomized complete block design with three replications to investigate genetic variability and correlation among growth and yield traits at Khumaltar, Lalitpur, Nepal from March 13 to September 05, 2021. The hybrids were grouped into four clusters using Euclidean Average Linkage method. The cluster analysis showed the presence of genetic variability in the evaluated hybrids. The maximum distance between cluster centroids (194.28) was found between cluster 2 and cluster 4, indicating genetic dissimilarity. Grain yield had the maximum values of phenotypic coefficient of variation (PCV) (35.02%), followed by ear height (17.82%) and plant height (12.22%). Similarly, grain yield had the maximum values of genotypic coefficient of variation (GCV) (26.24%) followed by the number of kernel rows/cob (8.77%) and days to 50% silking (8.72%). Days to 50% silking and days to 50% tasseling had the highest values of heritability (86%) followed by cob diameter (84%) and no. of kernel rows in cob (68%). The leaf area per plant had the maximum values of genetic advance (GA) (74.87 cm2), followed by plant height (27.80 cm) and days to 50% silking (9.66 days). Similarly, the maximum values of genetic advance as percent of the mean (GAM) was found for grain yield (40.50%) followed by days to 50% silking (16.70%) and days to 50% tasseling (16.17%). The hybrids namely KWM-91 × KWM-93 produced the maximum values of grain yield (9.99 t ha–1) followed by KWM-93 × KWM-91 (9.63 t ha–1) and KWM-92 × KWM-93 (9.40 t ha–1). Grain yield showed positive and significant phenotypic correlation with days to 50% silking (r = 0.41), days to 50% tasseling (r = 0.39), plant height (r = 0.37), cob diameter (r = 0.49) and the number of kernel rows in cob (r = 0.38). Therefore, utilization of present genetic variability along with indirect selection for traits having significant association with grain yield, high heritability and GAM could aid in the improvement of maize productivity

Effects of Storage Structures and Moisture Contents on Seed Quality Attributes of Quality Protein Maize

The study was aimed to examine the effects of various storage structures and moisture contents on seed quality attributes of quality protein maize seed. The quality protein maize (QPM-1) seed was tested in conventional seed storage containers (Fertilizer sack and earthen pot) and the improved hermetic ones (Metal bin, Super grain bag, and Purdue Improved Crop Storage (PICS) bag) at Seed Science and Technology Division, Khumaltar, Nepal during February, 2015 to January 2016. Ten treatments comprising 5 storage devices in two moisture regimes (11% and 9%) replicated thrice and laid out in Completely Randomized Design (CRD). Data on temperature, relative humidity (RH), germination, electrical conductivity (EC), seed moisture content (MC) were collected bimonthly. The conventional containers were found liable to the external environmental condition whereas the hermetic structures observed with controlled RH level below 40% in all combinations. Electrical conductivity (EC) for seed vigor showed that hermetic containers provide higher seed vigor than the conventional ones. Up to 4 months all treatments were found statistically at par for germination. A significant difference was observed in each treatment after 4 months where PICS bag & Super grain bag showed best germination followed by metal bin while fertilizer bag & earthen-pot showed poorer and poorest germination respectively till one year. Almost all treatments with lower MC showed better results than the treatments with higher MC. A negative correlation (R2=69.7%) was found between EC and Germination. All six figures from 2 to 12 months on MC showed statistically different where hermetic plastic bags were found maintaining MC as initial whereas MC of fertilizer bags and earthen pot was spiked than the basal figure. The finding evidenced that the hermetic containers and low MC are the seed storage approaches for retaining the quality of seed even in an ambient environmental condition for more than a year

EBBIOT: A Low-complexity Tracking Algorithm for Surveillance in IoVT Using Stationary Neuromorphic Vision Sensors

In this paper, we present EBBIOT-a novel paradigm for object tracking using stationary neuromorphic vision sensors in low-power sensor nodes for the Internet of Video Things (IoVT). Different from fully event based tracking or fully frame based approaches, we propose a mixed approach where we create event-based binary images (EBBI) that can use memory efficient noise filtering algorithms. We exploit the motion triggering aspect of neuromorphic sensors to generate region proposals based on event density counts with >1000X less memory and computes compared to frame based approaches. We also propose a simple overlap based tracker (OT) with prediction based handling of occlusion. Our overall approach requires 7X less memory and 3X less computations than conventional noise filtering and event based mean shift (EBMS) tracking. Finally, we show that our approach results in significantly higher precision and recall compared to EBMS approach as well as Kalman Filter tracker when evaluated over 1.1 hours of traffic recordings at two different locations.Comment: 6 pages, 5 figure