Threat Resistant Strategy Model Design & Analysis

Strategy of Business/ Operations remained crucial aspect in modern business environment as the ever changing scenario of business compels the design to be full proof to withstand the expected & unexpected  threats which may disrupt the well planned project. Designing such a strategy which not only withstand with the known threats but may also provide scope for the indicators to implement alternative / remedy looking at the existent /nonexistent symptoms. As in ever changing Business atmosphere the organizations are expected to transform their strategy as the suggested analysis of SWOT. & other prevalent age old technique /models practiced earlier are remained no more effective alone. Also the careful /effective analysis of the stakeholders, vendors/distributors, customers & government policies provide reason to be extra cautious for full proof strategy design in Cyber Era

Explainable Depression Detection via Head Motion Patterns

While depression has been studied via multimodal non-verbal behavioural cues, head motion behaviour has not received much attention as a biomarker. This study demonstrates the utility of fundamental head-motion units, termed \emph{kinemes}, for depression detection by adopting two distinct approaches, and employing distinctive features: (a) discovering kinemes from head motion data corresponding to both depressed patients and healthy controls, and (b) learning kineme patterns only from healthy controls, and computing statistics derived from reconstruction errors for both the patient and control classes. Employing machine learning methods, we evaluate depression classification performance on the \emph{BlackDog} and \emph{AVEC2013} datasets. Our findings indicate that: (1) head motion patterns are effective biomarkers for detecting depressive symptoms, and (2) explanatory kineme patterns consistent with prior findings can be observed for the two classes. Overall, we achieve peak F1 scores of 0.79 and 0.82, respectively, over BlackDog and AVEC2013 for binary classification over episodic \emph{thin-slices}, and a peak F1 of 0.72 over videos for AVEC2013

Explainable Depression Detection via Head Motion Patterns

While depression has been studied via multimodal non-verbal behavioural cues, head motion behaviour has not received much attention as a biomarker. This study demonstrates the utility of fundamental head-motion units, termed \emph{kinemes}, for depression detection by adopting two distinct approaches, and employing distinctive features: (a) discovering kinemes from head motion data corresponding to both depressed patients and healthy controls, and (b) learning kineme patterns only from healthy controls, and computing statistics derived from reconstruction errors for both the patient and control classes. Employing machine learning methods, we evaluate depression classification performance on the \emph{BlackDog} and \emph{AVEC2013} datasets. Our findings indicate that: (1) head motion patterns are effective biomarkers for detecting depressive symptoms, and (2) explanatory kineme patterns consistent with prior findings can be observed for the two classes. Overall, we achieve peak F1 scores of 0.79 and 0.82, respectively, over BlackDog and AVEC2013 for binary classification over episodic \emph{thin-slices}, and a peak F1 of 0.72 over videos for AVEC2013

Six-membered ring systems: with O and/or S atoms

A large variety of publications involving O- and S-6-membered ring systems have appeared in 2017. The importance of these heterocyclic compounds is highlighted by the huge number of publications on the total synthesis of natural oxygen derivatives and of other communications dedicated to synthetic derivatives. Reviews on stereoselective organocatalytic synthesis of tetrahydropyrans (17EJO4666), of tetrahydropyrans and their application in total synthesis of natural products (17CSR1661), on the synthesis of the less thermodynamically stable 2,6-trans-tetrahydropyrans (17S4899), on enantioselective synthesis of polyfunctionalized pyran and chromene derivatives (17TA1462), and on enantioselective and racemic total synthesis of camptothecins, including the formation of their pyran-2-one ring (17SL1134), have appeared. Advances in the transition metal-catalyzed synthesis of pyran-2/4-ones (17TL263), N-heterocyclic carbene (NHC)-catalyzed achiral synthesis of pyran-2-one, coumarin and (thio)chromone derivatives (17OBC4731), on the synthesis and transformation of 2H-pyran-2-ones (17T2529) and 2-styrylchromones (17EJO3115) into other heterocyclic compounds, have been surveyed. The strategies to build up the tetrahydropyranyl core of brevisamide (17H(95)81) and the reactions of ketyl radicals, generated from carbonyl derivatives under transition-metal photoredox-catalyzed conditions, leading to isochromen- and chroman-type compounds (17CC13093) were disclosed. Developments in the synthesis of pentafluorosulfanyl(chromene and coumarin) derivatives (17TL4803), photoswitchable D9-tetrahydrocannabinol derivatives (17JA18206), and aminobenzopyranoxanthenes with nitrogen-containing rings (17JOC13626) have been studied.info:eu-repo/semantics/publishedVersio

Conceptual Study of Ama and its Manifestation in Various Diseases

Like the theories of Tridosha, Sapta Dhatu, and Trimalas, the concept of Agni and Ama are very unique conceived in Ayurvedic texts. The concept of Ama encompasses an almost whole spectrum of diseases mentioned in Ayurveda. In the Ayurvedic view, nearly all diseases have their origin in Ama dosha. In Ayurveda, the word Ama and Pakva are very important to understand the theories of pathology and treatment according to Ayurveda. The success or failure of the Ayurvedic Physician in treatment depends upon the understanding of two conditions, Sama and Nirama- immature and mature. In Ama dosha langhan or fasting is the general form of treatment. Even medicine is forbidden in acute conditions. As the Jathragni is already weak and struggling to digest Ama, it can’t digest the medicine, another newcomer. The interaction of Doshas, food, and medicine may cause even fatal results

Head matters : explainable human-centered trait prediction from head motion dynamics

We demonstrate the utility of elementary head-motion units termed kinemes for behavioral analytics to predict personality and interview traits. Transforming head-motion patterns into a sequence of kinemes facilitates discovery of latent temporal signatures characterizing the targeted traits, thereby enabling both efficient and explainable trait prediction. Utilizing Kinemes and Facial Action Coding System (FACS) features to predict (a) OCEAN personality traits on the First Impressions Candidate Screening videos, and (b) Interview traits on the MIT dataset, we note that: (1) A Long-Short Term Memory (LSTM) network trained with kineme sequences performs better than or similar to a Convolutional Neural Network (CNN) trained with facial images; (2) Accurate predictions and explanations are achieved on combining FACS action units (AUs) with kinemes, and (3) Prediction performance is affected by the time-length over which head and facial movements are observed

Fast-killing tyrosine amide ((S)-SW228703) with blood- and liver-stage antimalarial activity associated with the cyclic amine resistance locus (PfCARL)

Current malaria treatments are threatened by drug resistance, and new drugs are urgently needed. In a phenotypic screen for new antimalarials, we identified (S)-SW228703 ((S)-SW703), a tyrosine amide with asexual blood and liver stage activity and a fast-killing profile. Resistance to (S)-SW703 is associated with mutations in the Plasmodium falciparum cyclic amine resistance locus (PfCARL) and P. falciparum acetyl CoA transporter (PfACT), similarly to several other compounds that share features such as fast activity and liver-stage activity. Compounds with these resistance mechanisms are thought to act in the ER, though their targets are unknown. The tyramine of (S)-SW703 is shared with some reported PfCARL-associated compounds; however, we observed that strict S-stereochemistry was required for the activity of (S)-SW703, suggesting differences in the mechanism of action or binding mode. (S)-SW703 provides a new chemical series with broad activity for multiple life-cycle stages and a fast-killing mechanism of action, available for lead optimization to generate new treatments for malaria