Ancient mtDNA from the extinct Indian cheetah supports unexpectedly deep divergence from African cheetahs

Abstract: The Indian cheetah was hunted to extinction by the mid-20th century. While analysis of 139 bp of mitochondrial DNA (mtDNA) has confirmed that the Indian cheetah was part of the Asiatic subspecies (Acinonyx jubatus venaticus), the detailed relationships between cheetah populations remains unclear due to limited genetic data. We clarify these relationships by studying larger fragments of cheetah mtDNA, both from an Indian cheetah museum specimen and two African cheetah, one modern and one historic, imported into India at different times. Our results suggest that the most recent common ancestor of cheetah mtDNA is approximately twice as ancient as currently recognised. The Indian and Southeast African (Acinonyx jubatus jubatus) cheetah mtDNA diverged approximately 72 kya, while the Southeast and Northeast African (Acinonyx jubatus soemmeringii) cheetah mtDNA diverged around 139 kya. Additionally, the historic African cheetah sampled from India proved to have an A. j. jubatus haplotype, suggesting a hitherto unrecognised South African route of cheetah importation into India in the 19th century. Together, our results provide a deeper understanding of the relationships between cheetah subspecies, and have important implications for the conservation of A. j. venaticus and potential reintroduction of cheetahs into India

Ancient mtDNA from the extinct Indian cheetah supports unexpectedly deep divergence from African cheetahs

Abstract: The Indian cheetah was hunted to extinction by the mid-20th century. While analysis of 139 bp of mitochondrial DNA (mtDNA) has confirmed that the Indian cheetah was part of the Asiatic subspecies (Acinonyx jubatus venaticus), the detailed relationships between cheetah populations remains unclear due to limited genetic data. We clarify these relationships by studying larger fragments of cheetah mtDNA, both from an Indian cheetah museum specimen and two African cheetah, one modern and one historic, imported into India at different times. Our results suggest that the most recent common ancestor of cheetah mtDNA is approximately twice as ancient as currently recognised. The Indian and Southeast African (Acinonyx jubatus jubatus) cheetah mtDNA diverged approximately 72 kya, while the Southeast and Northeast African (Acinonyx jubatus soemmeringii) cheetah mtDNA diverged around 139 kya. Additionally, the historic African cheetah sampled from India proved to have an A. j. jubatus haplotype, suggesting a hitherto unrecognised South African route of cheetah importation into India in the 19th century. Together, our results provide a deeper understanding of the relationships between cheetah subspecies, and have important implications for the conservation of A. j. venaticus and potential reintroduction of cheetahs into India

Schools and skills of critical thinking for urban design

© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. This paper explores possible ways in which urban design can engage with critical thinking and critical theory. After a brief explanation of the terms, with particular attention to the Frankfurt School of thought, it provides various answers to the question as to whether urban design is critical or not. One categorization applied to planning critical theory is then used to explain the potential for employing critical theories in urban design. Critical thinking skills are then argued to be helpful for enriching the literature of urban design in order to achieve better practice. The conclusion is that urban design can benefit from critical creativity, which is an embodiment of critical thinking within the limits imposed onto creativity. In this paper, the ways in which urban design can engage with both critical theory and with critical thinking are explored in order to achieve better critical creativity in the field

Enhancing Crop Insurance in India

The broad structure of Modified National Agricultural Insurance Scheme (mNAIS), the main crop insurance program in India, is technically sound and appropriate in the context of India. The NAIS is based on an indexed approach, where average crop yield of an insurance unit, or IU, (i.e., block) is the index used. The insurance is mandatory for all farmers that borrow from financial institutions, though insurance cover is also available to non-borrowers. The actual yield of the insured crop (as measured by crop cutting experiments) in the IU is compared to the threshold yield. If the former is lower than the latter, all insured farmers in the IU are eligible for the same rate of indemnity payout. Individual crop insurance will have been prohibitively expensive, or even impossible, in a country such as India with so many small and marginal farms. Further, the method of using an 'area based approach' has several other merits and, most importantly, it mitigates moral hazard and adverse selection. This report offers detailed analysis of a number of technical and operational issues which should be addressed if mNAIS is to be implemented. GOI is to be complemented on its bold vision of the future of agriculture insurance through modifying NAIS, an action which, if well implemented, has the potential for significant economic and political economy gains. The policy note World Bank (2010) supported this vision and offered specific policy recommendations for mNAIS, with reference to the Joint Group report (2004). This technical report is intended as a complement to World Bank (2010) and also to the previous technical report World Bank (2007a), by offering detailed technical analysis of a number of issues that will be critical to the success of mNAIS

A Critical Evaluation of Vibrational Stark Effect (VSE) Probes with the Local Vibrational Mode Theory

Over the past two decades, the vibrational Stark effect has become an important tool to measure and analyze the in situ electric field strength in various chemical environments with infrared spectroscopy. The underlying assumption of this effect is that the normal stretching mode of a target bond such as CO or CN of a reporter molecule (termed vibrational Stark effect probe) is localized and free from mass-coupling from other internal coordinates, so that its frequency shift directly reflects the influence of the vicinal electric field. However, the validity of this essential assumption has never been assessed. Given the fact that normal modes are generally delocalized because of mass-coupling, this analysis was overdue. Therefore, we carried out a comprehensive evaluation of 68 vibrational Stark effect probes and candidates to quantify the degree to which their target normal vibration of probe bond stretching is decoupled from local vibrations driven by other internal coordinates. The unique tool we used is the local mode analysis originally introduced by Konkoli and Cremer, in particular the decomposition of normal modes into local mode contributions. Based on our results, we recommend 31 polyatomic molecules with localized target bonds as ideal vibrational Stark effect probe candidates

Application of Artificial Intelligence and Machine Learning in Chemistry

In the last four years, I have been exposed to various topics in scientific research under the supervision of Dr. Kraka in the CATCO group. Numerous involved chemistry projects were undertaken to gain an understanding of the basic laws of nature involving vibrational spectroscopy, molecular acidity, and catalysts based on transition metals for halogen chemistry. The insights from computational chemistry were then applied to model and predict various complicated problems in chemistry via artificial intelligence. With the help of classical artificial intelligence, the non-covalent interactions governing the properties of proteins and water properties were analyzed. Significant improvements were made in the field of drug discovery by the development of methods such as SSnet: to predict protein-ligand affinities, and CFGenNet: to generate novel drug candidates based on protein\u27s history of interaction and towards solving a notorious quantum chemistry problem i.e. transition state prediction for small molecules by modeling TS-GAN: a generative model for guess transition state prediction. SSnet was further utilized to predict potential drugs for SARS-COV-2. Thus, it is evident that artificial intelligence holds strong potential in solving centuries-old complicated chemistry problems