Foraging Behavior of Swainson\u27s Thrushes (Catharus ustulatus) During Spring Migration through Arkansas

Foraging behavior of Swainson’s Thrushes on spring migration was studied in western Arkansas in the spring of 2013 and 2014. Observations were made in two forested field sites, one of them urban and the other suburban. The former had a significantly higher woody stem area (cm2) than the latter. For each foraging observation, the following three parameters were noted: Foraging Stratum (Ground, Shrub, Sapling, Sub canopy, and Canopy); Foraging Substrate (Ground/Litter, Herb, Foliage, Bark, and Air); and Foraging Maneuver (Glean, Probe, Dive/Glean, Hover, Jump Hover, and Hawking). We tested the hypotheses that these foraging variables differed significantly between the urban and suburban sites, and between the two years. These hypotheses were rejected for all three parameters. The consolidated data from both the sites and years revealed that a significantly higher proportion (67%) of the observations were on the Ground stratum, compared to the Shrub (13.7%) and Sapling strata (13%). Similarly, a significantly higher proportion (66%) of the foraging substrate used was Ground/Litter, followed by Foliage (16.7%) and Bark (15.8%). Gleaning was the most common foraging maneuver used (71.5%), and was significantly higher than Probing (12.3%) and Dive Gleaning (8.4%)

ADAPTIVE EXPERIMENTAL DESIGN FOR OPTIMIZING COMBINATORIAL STRUCTURES

Many real-world scientific and engineering problems can be framed as instances of adaptive experimental design, wherein a sequence of experiments is chosen sequentially, with each choice informed by the outcomes of previous trials. The objective of this sequential decision-making process is to efficiently achieve a specific goal or learn about an unknown quantity of interest. Different goals lead to distinct instantiations of adaptive experimental design. For instance, in active learning, the aim is to iteratively select data points to be labeled, with the goal of learning a predictor from a hypothesis class that achieves the highest accuracy with the fewest labeled instances. Similarly, in bandit problems, the learner repeatedly chooses an arm from a set of available options, aiming to maximize their cumulative reward over time. In this dissertation, we focus on another important instantiation of adaptive experimental design: expensive black-box optimization over combinatorial spaces. In this setting, the goal is to identify the optimal design/configuration within a large design space consisting of discrete or hybrid structures, where the evaluation of each design/configuration is expensive. For example, in material design, we are commonly interested in searching the space of materials for a desired property while minimizing the total resource-cost of physical lab experiments for their evaluation. Remarkably, a large number of scientific discovery or an engineering design problems including biological sequence design, nanoporous materials design, molecule design, and manycore systems design can be cast as an instantiation of this problem where exploring large design spaces in order to find optimal configurations under the constraint of expensive evaluations is a common theme.Bayesian optimization (BO) is an effective framework for tackling the challenge of expensive black-box optimization. In spite of the huge successes of BO, current approaches focus primarily on continuous spaces and there is little principled work on combinatorial search spaces. Unlike continuous spaces, combinatorial spaces come with many unique challenges such as difficulty of defining a general representation, non-smoothness, etc. which require specialized treatment of different types of structures (sequences, graphs, permutations etc). In this thesis, we explore and address the challenges of this new problem space and develop a series of new methods and approaches for Bayesian optimization over combinatorial spaces. We develop novel Gaussian process based surrogate models for a wide variety of combinatorial inputs (for e.g. fixed-sized sequences, high-dimensional sequences, hybrid inputs containing a mixture of continuous and discrete parameters, varying sized graphs, and permutations.) and effective search strategies to search over such large spaces. Experimental results on a wide variety of synthetic and real-world benchmarks derived from science and engineering applications demonstrate the effectiveness of these methods and their significant impact on accelerating engineering design and scientific discovery processes

Dhamma, Buddhism & Ashoka : An Analytical Study

King Ashoka was the greatest emperor of the Mauryan dynasty. He was great protection of Buddhism, art and architecture. This article is about to cover the life of King Ashoka, how he follows and spreads the teachings of Buddhism and dhamma. There were many great emperors in Indian history who inscribed their names in the golden letters of history and Ashoka was one of those rulers. Many writers have analyzed the life and career of King Ashoka but this article tries to analyze how he (Ashoka) started his career and achieved success. It also emphasizes the law of King Ashoka and the protection of art and architecture in his area. This article also seeks to discuss the protection of King Ashoka’s Buddhism. He sent his own son and girl to Srilanka to spread Buddhism

Impact Of Cyber Crime On The Society During Lockdown Period

The aim of this paper is to analyse the impact of cyber-crime on the society during the period of lockdown. The concept of cyber-crime and the new hacks to extract money from the citizens and how it has impacted the common people at large is explored. The result from this study shows that computer and internet is a potent platform for the criminals and how it has impacted the lives of the people in a negative way. The discussions are made from the findings and the paper addresses how the internet and computer can be utilised properly in a safe and secured way adopting various precautions and measures to secure the usage and on the other hand increasing the awareness on how not to be trapped in any kind of web by criminals in the cyber world

Ecology and Conservation of Shrubland Bird Communities in the Eastern Ghats of Indi

Anthropogenic disturbance, in its multiple facets represents a major threat to biodiversity and habitat quality. Consequently, extensive research is guided towards understanding anthropogenic disturbance and their effects on wildlife for development of wildlife management plans. However, for development of effective wildlife management plans it is imperative that we understand the habitat use and preference by local fauna along with effects of anthropogenic presence. In this dissertation, I studied the habitat usage and preferences of Shrubland birds in the Eastern Ghats of India during the pre-monsoon and post monsoon seasons. Eastern Ghats show a marked difference from pre-monsoon season to post-monsoon season thereby affecting the habitat use by birds depending upon various vegetational characteristics identified in this study. I also studied the dependence of local community on the forest products, impact of goats and sheep on forest structure. When juxtaposed with Land Use and Land Change (LULC) patterns these changes in habitat usage, anthropogenic effects it will help in predicting future habitat usage patterns in the face of climate change. This dissertation answers the following questions: 1) Do birds select a habitat based on vegetational structure or floral composition? 2) Is there any association between plant species and bird assemblages? 3) What is the structural preference of a bird assemblages? 4)How has LULC changed over five years owing to drought? 5)Effect of anthropogenic presence on habitat structure

Facilitating Supplies of Digital Transformation: Data Sharing and Data Culture

Digital transformation is similar to magic wand. However, human intelligence can’t be overtaken by technology. We are basically working on creating tech skilled workforce. Best organizations primarily focus on culture to come in tune with technology. They avoid sweeping changes and ham-handed approach. The transition requires more time and energy. Digital transformation is happening but in siloed manner. If digital transformation is equipped with the data sharing and data culture we can achieve the true potential immersed in it. Digital transformation is gateway to success

Enhanced sensitivity with thickness optimization of ZnO based acetone sensor

Zinc oxide (ZnO) thin film based acetone gas sensor has been studied with variation of sensing layer thickness towards 500 ppm of acetone. The effect of thickness variation of the sensing layer on the structural, surface morphological, optical and gas sensing properties of ZnO thin film has been studied. A significant increase from 7.19 to 63 in the sensing response has been observed with bare ZnO thin film for the samples with an optimised thickness of 410 nm at an optimised operating temperature of 320 ᵒC. This study conducts the variations in structural, optical and the gas sensing characteristics while varying the thickness of ZnO based thin films for an acetone gas sensor. Further, the study concludes with an optimised thickness as 410 nm for an oxidizing gas

Excess Volumes of Mixing of Cl– and Br– with Na+ and K+ at 308.15 K in Aqueous Dioxane Mixed Solvent

Excess volumes of mixing for six possible binary combinations of solutions of NaCl, KCl, NaBr and KBr have been determined at constant ionic strengths of 1.000 and 2.000 mol kg–1 at 308.15 K using a dilatometer in a water +1,4-dioxane mixed solvent system. Pitzer’s ion interaction model has been utilized to obtain binary and triplet interaction parameters, i.e. θV and ψV. The data were also analysed in the light of the Friedman model. Data are dependent on the nature of the common ion and do not support the cross square rule (CSR). The  deviation from the CSR increased with increasing ionic strength and is considered to arise from the appreciable contribution of triplet interactions and preferential solvation of the ions and ion-clusters in the mixed solvent system.KEYWORDS: Excess volumes of mixing, Friedman model, Pitzer model, cross square rule

Annealing temperature optimization for highly sensitive ZnO based acetone gas sensor

The present research is related to the effect of temperature on the crystallinity for zinc oxide (ZnO) thin film based acetone sensor fabricated via sol-gel method. One of the critical parameters for a gas sensor is the annealing temperature of thin films which directly influences the crystallinity of a material and hence its structural properties. Thus, the present study shows the effects of annealing temperature variation over the properties related to the gas sensing behaviour for the sensor. The structural and optical properties with surface morphology have been analysed for the prepared samples. The response characteristics of the ZnO films with a thickness of 410 nm for the acetone vapour has been determined for the temperature range from 180 °C to 360 °C and the annealing temperature variation has been studied from 450 °C to 750 °C. The optimal operating temperature has been found to be 320 °C while the optimal annealing temperature as reflected by the results is 650 °C