Lower Bounds for Shoreline Searching With 2 or More Robots

Searching for a line on the plane with $n$ unit speed robots is a classic online problem that dates back to the 50's, and for which competitive ratio upper bounds are known for every $n\geq 1$. In this work we improve the best lower bound known for $n=2$ robots from 1.5993 to 3. Moreover we prove that the competitive ratio is at least $\sqrt{3}$ for $n=3$ robots, and at least $1/\cos(\pi/n)$ for $n\geq 4$ robots. Our lower bounds match the best upper bounds known for $n\geq 4$, hence resolving these cases. To the best of our knowledge, these are the first lower bounds proven for the cases $n\geq 3$ of this several decades old problem.Comment: This is an updated version of the paper with the same title which will appear in the proceedings of the 23rd International Conference on Principles of Distributed Systems (OPODIS 2019) Neuchatel, Switzerland, July 17-19, 201

Taurine as a biomarker for aging: A new avenue for translational research

The physiologic and irreversible process of ageing is accompanied by a wide range of structural and functional shifts at multiple different levels. It is also suggested that variations in the blood concentrations of metabolites, hormones, and micronutrients may play a role in the ageing process. Recently, Singh et al. 1,2 investigated a study on Taurine shortage as a driver and biomarker of ageing and its impact on a healthy lifespan.2 They further proposed that functional abnormalities in numerous organs associated with age-related illnesses have been linked to early-life Taurine insufficiency. Taurine deficiency in the elderly and the possible benefits of Taurine supplements One of the reasons for decreasing Taurine concentration is the loss of endogenous synthesis, which may contribute to the decrease in Taurine levels seen in the elderly. While it was previously believed that the liver was responsible for most Taurine synthesis in humans, new research suggests that other organs or common intermediates may play a larger role. The authors experimented with and analysed a life-span examination of various organisms, for example, mice to assess the impacts of Taurine supplementation. They also analysed after the administration of oral Taurine supplementation in conjunction with other interventions using multi-omics data sets (RNA sequencing, metabolomics etc.) across different species

Spatiotemporal fluctuations of olfactory stimuli and its detection by an optical method

Olfactory processing in the mammalian brain is a highly dynamic process, yet most of the olfaction experiments have been studied primarily with static stimuli. Odors in the natural environment are transported by turbulent flow of air or water. Natural odorants have fluctuations in concentration and it changes rapidly with time. These rapid fluctuations may pose some challenges to identifying an odor; on the other hand, the variation itself may provide important clues about the odor source. The goal of this thesis project was to create a similar odorant environment like the rapid odor fluctuations encountered in nature – to meet this goal; we built an odor delivery and optical odor detection system. We combine visible smoke with invisible odorant to make the odorant detectable using two high sensitivity CCD line cameras. Initial tests of the system were carried out to determine the plausibility of its use in future experiments. Based on observed and quantified fluctuations of smoke and odorants, we conclude that the system is a promising tool for studying olfaction with naturalistic odorant fluctuations

The limit of human intelligence

In 1998, Fields medalist Stephen Smale [S. Smale, Mathematical problems for the next century, The mathematical Intelligencer, 20(2) (1998), 7-15] proposed his famous eighteen problems to the mathematicians of this century. The statement of his eighteenth problem is very simple but very important. He asked "What are the limits of intelligence, both artificial and human?". In this paper, we prove that human intelligence is limitless. Moreover, we provide justifications to state that artificial intelligence has limitations. Thus, human intelligence will always remain superior to artificial intelligence. Moreover, we provide justifications to conclude the limitations of artificial intelligence

Design and Detection of Controller Manipulation Attack on RIS Assisted Communication

In this paper, we introduce a new attack called controller manipulation attack (CMA) on a Reconfigurable Intelligent Surface (RIS) assisted communication system between a transmitter and a receiver. An attacker has the capability to manipulate the RIS controller and modify the phase shift induced by the RIS elements. The goal of the attacker is to minimize the data rate at the receiver, subject to a constraint on the attack detection probability at the receiver. We consider a number of attack detection models: (i) composite hypothesis testing based attack detection in a given fading block for known channel gains, (ii) sequential quickest detection of CMA in a given fading block for known channel gains, (iii) nonparametric hypothesis test to detect CMA for unknown channel gains over a fading block, and (iv) signal-to-noise-ratio (SNR) moment based detection over possibly multiple fading blocks. In the first case, a simple energy detector turns out to be uniformly most powerful (UMP). In the second case, simplification of the standard CUSUM test and its performance bounds are obtained. In the third case, non-parametric Kolmogorov-Smirnov test is further simplified to a simple per-sample double threshold test. The attack against these three detectors are designed via novel optimization formulations and semidefinite relaxation based solutions. In the fourth case, we consider threshold detection using moments of SNR; various SNR moments under no attack are obtained analytically for large RIS and then used to formulate the attack design problem as a linear program. Finally, numerical results illustrate the performance and trade-offs associated with the attack schemes, and also demonstrate their efficacy.Comment: 16 pages, 3 figures, 6 tables and appendix from A to

Cerebrospinal fluid metabolomes of treatment-resistant depression subtypes and ketamine response:a pilot study

Depression is a disorder with variable presentation. Selecting treatments and dose-finding is, therefore, challenging and time-consuming. In addition, novel antidepressants such as ketamine have sparse optimization evidence. Insights obtained from metabolomics may improve the management of patients. The objective of this study was to determine whether compounds in the cerebrospinal fluid (CSF) metabolome correlate with scores on questionnaires and response to medication. We performed a retrospective pilot study to evaluate phenotypic and metabolomic variability in patients with treatment-resistant depression using multivariate data compression algorithms. Twenty-nine patients with treatment-resistant depression provided fasting CSF samples. Over 300 metabolites were analyzed in these samples with liquid chromatography-mass spectrometry. Chart review provided basic demographic information, clinical status with self-reported questionnaires, and response to medication. Of the 300 metabolites analyzed, 151 were present in all CSF samples and used in the analyses. Hypothesis-free multivariate analysis compressed the resultant data set into two dimensions using Principal Component (PC) analysis, accounting for ~ 32% of the variance. PC1 accounted for 16.9% of the variance and strongly correlated with age in one direction and 5-methyltetrahydrofolate, homocarnosine, and depression and anxiety scores in the opposite direction. PC2 accounted for 15.4% of the variance, with one end strongly correlated with autism scores, male gender, and cognitive fatigue scores, and the other end with bipolar diagnosis, lithium use, and ethylmalonate disturbance. This small pilot study suggests that complex treatment-resistant depression can be mapped onto a 2-dimensional pathophysiological domain. The results may have implications for treatment selection for depression subtypes