Antimicrobial Diterpenes: Recent Development From Natural Sources

Antimicrobial resistance has been posing an alarming threat to the treatment of infectious diseases over the years. Ineffectiveness of the currently available synthetic and semisynthetic antibiotics has led the researchers to discover new molecules with potent antimicrobial activities. To overcome the emerging antimicrobial resistance, new antimicrobial compounds from natural sources might be appropriate. Secondary metabolites from natural sources could be prospective candidates in the development of new antimicrobial agents with high efficacy and less side effects. Among the natural secondary metabolites, diterpenoids are of crucial importance because of their broad spectrum of antimicrobial activity, which has put it in the center of research interest in recent years. The present work is aimed at reviewing recent literature regarding different classes of natural diterpenes and diterpenoids with significant antibacterial, antifungal, antiviral, and antiprotozoal activities along with their reported structure–activity relationships. This review has been carried out with a focus on relevant literature published in the last 5 years following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 229 diterpenoids from various sources like plants, marine species, and fungi are summarized in this systematic review, including their chemical structures, classification, and significant antimicrobial activities together with their reported mechanism of action and structure–activity relationships. The outcomes herein would provide researchers with new insights to find new credible leads and to work on their synthetic and semisynthetic derivatives to develop new antimicrobial agents

How Vulnerable are Bangladesh’s Indigenous People to Climate Change?

This paper compares the vulnerabilities to climate change and climate variability of the indigenous people with the Bengali population of Bangladesh. It distinguishes between (a) individual vulnerabilities that are related to an individual’s capability to adapt to climate change and; (b) spatial vulnerabilities, that is, vulnerabilities that are related to the location of a person (like the exposure to climate change-induced disasters). While an individual’s capability to adapt to climate change is determined by many factors, some relatively simple approximation is to look at poverty, landlessness, and illiteracy. Spatial vulnerabilities are reviewed by looking at drought hazard maps, flood hazard maps, landslide hazard maps, and cyclone hazard maps. Hence, the paper compares levels of poverty, landlessness, illiteracy, and the more direct though also more subjective exposures to increased droughts, floods, landslides, and cyclones across the two population groups. The paper concludes with some broad suggestions on adaptation strategies of indigenous people as well as suggestions for policy interventions to reduce climate change-induced vulnerabilities for indigenous people in the Chittagong Hill Tracts (CHT).Bangladesh, climate change, vulnerability

Computing Covers Using Prefix Tables

An \emph{indeterminate string} $x = x[1..n]$ on an alphabet $\Sigma$ is a sequence of nonempty subsets of $\Sigma$; $x$ is said to be \emph{regular} if every subset is of size one. A proper substring $u$ of regular $x$ is said to be a \emph{cover} of $x$ iff for every $i \in 1..n$, an occurrence of $u$ in $x$ includes $x[i]$. The \emph{cover array} $\gamma = \gamma[1..n]$ of $x$ is an integer array such that $\gamma[i]$ is the longest cover of $x[1..i]$. Fifteen years ago a complex, though nevertheless linear-time, algorithm was proposed to compute the cover array of regular $x$ based on prior computation of the border array of $x$. In this paper we first describe a linear-time algorithm to compute the cover array of regular string $x$ based on the prefix table of $x$. We then extend this result to indeterminate strings.Comment: 14 pages, 1 figur

Inferring an Indeterminate String from a Prefix Graph

An \itbf{indeterminate string} (or, more simply, just a \itbf{string}) \s{x} = \s{x}[1..n] on an alphabet $\Sigma$ is a sequence of nonempty subsets of $\Sigma$. We say that \s{x}[i_1] and \s{x}[i_2] \itbf{match} (written \s{x}[i_1] \match \s{x}[i_2]) if and only if \s{x}[i_1] \cap \s{x}[i_2] \ne \emptyset. A \itbf{feasible array} is an array \s{y} = \s{y}[1..n] of integers such that \s{y}[1] = n and for every $i \in 2..n$, \s{y}[i] \in 0..n\- i\+ 1. A \itbf{prefix table} of a string \s{x} is an array \s{\pi} = \s{\pi}[1..n] of integers such that, for every $i \in 1..n$, \s{\pi}[i] = j if and only if \s{x}[i..i\+ j\- 1] is the longest substring at position $i$ of \s{x} that matches a prefix of \s{x}. It is known from \cite{CRSW13} that every feasible array is a prefix table of some indetermintate string. A \itbf{prefix graph} \mathcal{P} = \mathcal{P}_{\s{y}} is a labelled simple graph whose structure is determined by a feasible array \s{y}. In this paper we show, given a feasible array \s{y}, how to use \mathcal{P}_{\s{y}} to construct a lexicographically least indeterminate string on a minimum alphabet whose prefix table \s{\pi} = \s{y}.Comment: 13 pages, 1 figur

Multiphoton excitations in vibrational rotational states of diatomic molecules in intense electromagnetic field

A theory is presented and a calculational procedure is outlined for evaluating transition amplitudes of multiphoton excitations of vibrational-rotational levels in diatomic molecules. This theory can be utilized in studying behavior of molecules in intense electromagnetic fields

Algorithms to Compute the Lyndon Array

We first describe three algorithms for computing the Lyndon array that have been suggested in the literature, but for which no structured exposition has been given. Two of these algorithms execute in quadratic time in the worst case, the third achieves linear time, but at the expense of prior computation of both the suffix array and the inverse suffix array of x. We then go on to describe two variants of a new algorithm that avoids prior computation of global data structures and executes in worst-case n log n time. Experimental evidence suggests that all but one of these five algorithms require only linear execution time in practice, with the two new algorithms faster by a small factor. We conjecture that there exists a fast and worst-case linear-time algorithm to compute the Lyndon array that is also elementary (making no use of global data structures such as the suffix array)