Evaluation of carrot varieties for morphological traits, yield attributes and nutritional profile in Bhaktapur, Nepal

Carrot is an important root vegetable and commonly used as a snack, part of salads, cooked in curries and used in making pickles. A research was carried out to evaluate the performance of different carrot varieties for their morphological traits, yield attributing characters and nutritional parameters from Feb 2023 to June 2023 at Thimi Municipality-2, Bhaktapur. There were five carrot varieties such as Nepa Dream, Red Champion, Sigma, SK3, and New Kuroda. The experimental design was Randomized Complete Block Design with four replications. Results showed that there were significant differences in growth parameters, morphological characters, and nutrient composition. Nepa Dream showed the greatest root length (25.24 cm), weight (100.25 g), total yield (27.48 t/ha), βcarotenoid (12.34 mg/100 g), dry matter (12.35%) and TSS (11.25 ºBrix). New Kuroda had the maximum plant length (78.17 cm). The results of the current study showed that varieties differed significantly for morphological traits, yield attributes and other nutritional aspects. Nepa Dream was found to be the appropriate variety in terms of yield, TSS, β-carotene and dry matter content for growing at Thimi, Bhaktapur, Nepal. Among other varieties, SK3 seemed to be the promising for its overall traits and so it needs to be further tested over multiple seasons and locations

Exploration of Erasure-Coded Storage Systems for High Performance, Reliability, and Inter-operability

With the unprecedented growth of data and the use of low commodity drives in local disk-based storage systems and remote cloud-based servers has increased the risk of data loss and an overall increase in the user perceived system latency. To guarantee high reliability, replication has been the most popular choice for decades, because of simplicity in data management. With the high volume of data being generated every day, the storage cost of replication is very high and is no longer a viable approach. Erasure coding is another approach of adding redundancy in storage systems, which provides high reliability at a fraction of the cost of replication. However, the choice of erasure codes being used affects the storage efficiency, reliability, and overall system performance. At the same time, the performance and interoperability are adversely affected by the slower device components and complex central management systems and operations. To address the problems encountered in various layers of the erasure coded storage system, in this dissertation, we explore the different aspects of storage and design several techniques to improve the reliability, performance, and interoperability. These techniques range from the comprehensive evaluation of erasure codes, application of erasure codes for highly reliable and high-performance SSD system, to the design of new erasure coding and caching schemes for Hadoop Distributed File System, which is one of the central management systems for distributed storage. Detailed evaluation and results are also provided in this dissertation

ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model

Compute Express Link (CXL) emerges as a solution for wide gap between computational speed and data communication rates among host and multiple devices. It fosters a unified and coherent memory space between host and CXL storage devices such as such as Solid-state drive (SSD) for memory expansion, with a corresponding DRAM implemented as the device cache. However, this introduces challenges such as substantial cache miss penalties, sub-optimal caching due to data access granularity mismatch between the DRAM cache and SSD memory , and inefficient hardware cache management. To address these issues, we propose a novel solution, named ICGMM, which optimizes caching and eviction directly on hardware, employing a Gaussian Mixture Model (GMM)-based approach. We prototype our solution on an FPGA board, which demonstrates a noteworthy improvement compared to the classic Least Recently Used (LRU) cache strategy. We observe a decrease in the cache miss rate ranging from 0.32% to 6.14%, leading to a substantial 16.23% to 39.14% reduction in the average SSD access latency. Furthermore, when compared to the state-of-the-art Long Short-Term Memory (LSTM)-based cache policies, our GMM algorithm on FPGA showcases an impressive latency reduction of over 10,000 times. Remarkably, this is achieved while demanding much fewer hardware resources.This paper is accepted by DAC202

Novel Electrochemical Measurements on Nanoparticle Ensembles and Actual Single Nanoparticle

The research work in this dissertation is focused on the study of the semiconductor nanoparticles (NPs) for photo conversion of light into electricity. Semiconductor nanoparticles are used not only for photo conversion but also in medicine, environmental pollution removal, material preparations, cosmetics, etc. The main goal of this work is to establish a protocol to capture and study the reaction kinetics of the single semiconductor NP. We have studied cadmium selenide (CdSe) quantum dots and TiO2 NPs suspended in a neat methanol solution as a model system where the methanol gets photooxidized into formaldehyde. The methanol oxidation to formaldehyde is a two-electron process. The particles of quantum dots get agglomerated under illumination which is evident by the current size of the photocurrent obtained in the scale > 1 pA. This observation is also consistent with the stability of the particles in methanol suspension under constant illumination and the collision frequency. We have detected formaldehyde, the product of photooxidation of methanol by FTIR, and quantified the formaldehyde by ESI-MS. We also studied the change in temperature in the vicinity of the ultramicroelectrode (UME) under constant laser illumination. It is very important to study the change in temperature because it can have a significant effect on electron transfer rate. In the last chapter, we studied TiO2 NPs suspended in methanol solution by nano-impact study under laser illumination. The particles were spiked into the solution after turning on the laser and were captured on the UME which was evident by the current steps in i-t traces. We further carried out the surface modification of the electrode and captured an actual single particle of TiO2

Thermodynamic evaluation of a gas turbine in python programming language and comparison of the procedure and the results with the existing MATLAB model

Diese Arbeit bezieht sich auf die systematische und strukturierte Simulation einer Gasturbine in der Python Programmiersprache. Nach kurzer Einführung in der Python Programmiersprache werden an jeder Komponente der Gasturbine thermodynami-schen Eigenschaften der Fluide berechnet sowie die Energie bilanziert. Abschließend werden die Vorgehensweise und die Ergebnisse mit der vorhandenen MATLAB-Be-rechung verglichen.The thesis relates to the systematic and structural simulation of a gas turbine in python programming language. After a small introduction in the python programming lan-gaue, thermodynamic properties of the gases will be calculated, and energy will be balanced. Finally, the python procedure and results of the calculation will be com-pared with the MATLAB one demonstrating the difference between the each method

Collective effects in Single Molecule Magnets

Single molecule magnets (SMMs), such as Mn12-acetate, are composed of transition metal ions and consists of identical molecules with large ground-state spin (S = 10) and a strong uniaxial anisotropy (65 K). Below about 3 K, Mn12-acetate exhibits magnetic hysteresis with steps at specific values of longitudinal magnetic field due to resonant quantum tunneling between spin up and down projections along the easy axis. The intermolecular exchange interactions between spins on molecules are quite small and spins are considered to be independent and non-interacting. However, the molecules do interact with each other both through magnetic dipolar interactions and through the lattice (e.g. phonons). I have investigated collective effects in SMMs due to these intermolecular interactions. In the thesis I will present experiments that explored magnetic ordering due to magnetic dipole interactions in Mn12-acetate and Mn12-acetate-MeOH. I will also present exper- iments on the onset of magnetic de agration in Mn12-acetate due to a thermal instability. The magnetic ordering studies involved investigating the effect of transverse fields on the susceptibility of single crystals of Mn12-acetate and Mn12-acetate- MeOH. Transverse fields increase quantum spin uctuations that suppress long- range order. However, the suppression of the Curie temperature by transverse fields in Mn12-acetate is far more rapid than predicted by the Transverse-Field Ising Ferromagnetic Model (TFIFM) and instead agrees with the predictions of the Random-Field Ising Ferromagnet Model. It appears that solvent disorder in Mn12-acetate gives rise to a distribution of random-fields that further suppress long-range order. Subsequent studies on Mn12-acetate-MeOH, with the same spin and similar lattice constants but without solvent disorder as Mn12-acetate, agrees with the TFIFM. The magnetic de agration studies involved studying the instability that leads to the ignition of magnetic deflagration in a thermally driven Mn 12-acetate crystal. When spins prepared in a metastable state reverse, Zeeman energy is released that diffuses away. In some circumstances, the heat released cannot be compensated by thermal diffusion, resulting in an instability that gives rise to a front of rapidly reversing spins traveling through the crystal. We observed a sharp crossover from relaxation driven by heat diffusion to a self-sustained reversal front that propagates at a constant subsonic speed

Sinkhole susceptibility mapping in Marion County, Florida: Evaluation and comparison between analytical hierarchy process and logistic regression based approaches

AbstractSinkholes are the major cause of concern in Florida for their direct role on aquifer vulnerability and potential loss of lives and property. Mapping sinkhole susceptibility is critical to mitigating these consequences by adopting strategic changes to land use practices. We compared the analytical hierarchy process (AHP) based and logistic regression (LR) based approaches to map the areas prone to sinkhole activity in Marion County, Florida by using long-term sinkhole incident report dataset. For this study, the LR based model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.8 compared to 0.73 with the AHP based model. Both models performed better when an independent future sinkhole dataset was used for validation. The LR based approach showed a low presence of sinkholes in the very low susceptibility class and low absence of sinkholes in the very high susceptibility class. However, the AHP based model detected sinkhole presence by allocating more area to the high and very high susceptibility classes. For instance, areas susceptible to very high and high sinkhole incidents covered almost 43.4% of the total area under the AHP based approach, whereas the LR based approach allocated 20.7% of the total area to high and very high susceptibility classes. Of the predisposing factors studied, the LR method revealed that closeness to topographic depression was the most important factor for sinkhole susceptibility. Both models classified Ocala city, a populous city of the study area, as being very vulnerable to sinkhole hazard. Using a common test case scenario, this study discusses the applicability and potential limitations of these sinkhole susceptibility mapping approaches in central Florida.</jats:p