Affective problems and decline in cognitive state in older adults: a systematic review and meta-analysis

Evidence suggests that affective problems, such as depression and anxiety, increase risk for late-life dementia. However, the extent to which affective problems influence cognitive decline, even many years prior to clinical diagnosis of dementia, is not clear. The present study systematically reviews and synthesises the evidence for the association between affective problems and decline in cognitive state (i.e. decline in non-specific cognitive function) in older adults. An electronic search of PubMed, PsycInfo and ScienceDirect was conducted to identify studies of the association between depression and anxiety separately and decline in cognitive state. Key inclusion criteria were prospective, longitudinal designs with a minimum follow-up period of one year. Data extraction and methodological quality assessment using the STROBE checklist were conducted independently by two raters. A total of 34 studies (n=71,244) met eligibility criteria, with 32 studies measuring depression (n=68,793), and 5 measuring anxiety (n=4,698). A multi-level meta-analysis revealed that depression assessed as a binary predictor (OR=1.36, 95% CIs: 1.05-1.76, p=.02) or a continuous predictor (B=-0.008, 95% CIs: -0.015, -0.002, p=.012; OR=0.992, 95% CIs: 0.985-0.998) was significantly associated with decline in cognitive state. The number of anxiety studies were insufficient for meta-analysis and are instead described in a narrative review. Results of the present study improve current understanding of the temporal nature of the association between affective problems and decline in cognitive state. They also suggest that cognitive function need to be monitored closely in individuals with affective disorders, as these individuals may be at a particular risk of greater cognitive decline

Packet Size Optimization for Cognitive Radio Sensor Networks Aided Internet of Things

Cognitive Radio Sensor Networks (CRSN) is state of the art communication paradigm for power constrained short range data communication. It is one of the potential technology adopted for Internet of Things (IoT) and other futuristic Machine to Machine (M2M) based applications. Many of these applications are power constrained and delay sensitive. Therefore, CRSN architecture must be coupled with different adaptive and robust communication schemes to take care of the delay and energy-efficiency at the same time. Considering the tradeoff that exists in terms of energy efficiency and overhead delay for a given data packet length, it is proposed to transmit the physical layer payload with an optimal packet size (OPS) depending on the network condition. Furthermore, due to the cognitive feature of CRSN architecture overhead energy consumption due to channel sensing and channel handoff plays a critical role. Based on the above premises, in this paper we propose a heuristic exhaustive search based Algorithm-1 and a computationally efficient suboptimal low complexity Karuh-Kuhn- Tucker (KKT) condition based Algorithm-2 to determine the optimal packet size in CRSN architecture using variable rate m-QAM modulation. The proposed algorithms are implemented along with two main cognitive radio assisted channel access strategies based on Distributed Time Slotted-Cognitive Medium Access Control (DTS-CMAC) and Centralized Common Control Channel based Cognitive Medium Access Control (CC-CMAC) and their performances are compared. The simulation results reveals that proposed Algorithm-2 outperforms Algorithm-1 by a significant margin in terms of its implementation time. For the exhaustive search based Algorithm-1 the average time consumed to determine OPS for a given number of cognitive users is 1.2 seconds while for KKT based Algorithm-2 it is of the order of 5 to 10 ms. CC-CMAC with OPS is most efficient in terms of overall energy consumption but incurs more delay as compared to DTS-CMAC with OPS scheme

Packet Size Optimization for Multiple Input Multiple Output Cognitive Radio Sensor Networks aided Internet of Things

The determination of Optimal Packet Size (OPS) for Cognitive Radio assisted Sensor Networks (CRSNs) architecture is non-trivial. State of the art in this area describes various complex techniques to determine OPS for CRSNs. However, it is observed that under high interference from the surrounding users, it is not possible to determine a feasible optimal packet size of data transmission under the simple point-to-point CRSN network topology. This is contributed primarily due to the peak transmit power constraint of the cognitive nodes. To address this specific challenge, this paper proposes a Multiple Input Multiple Output based Cognitive Radio Sensor Networks (MIMO-CRSNs) architecture for futuristic technologies like Internet of Things (IoT) and machine-to-machine (M2M) communications. A joint optimization problem is formulated taking into account network constraints like the overall end to end latency, interference duration caused to the non-cognitive users, average BER and transmit power.We propose our Algorithm-1 based on generic exhaustive search technique blue to solve the optimization problem. Furthermore, a low complexity suboptimal Algorithm-2 based on solving classical Karush-Kuhn-Tucker (KKT) conditions is proposed. These algorithms for MIMO-CRSNs are implemented in conjunction with two different channel access schemes. These channel access schemes are Time Slotted Distributed Cognitive Medium Access Control denoted as MIMO-DTS-CMAC and CSMA/CA assisted Centralized Common Control Channel based Cognitive Medium Access Control denoted as MIMO-CC-CMAC. Simulations reveal that the proposed MIMO based CRSN network outperforms the conventional point-to-point CRSN network in terms of overall energy consumption. Moreover, the proposed Algorithm-1 and Algorithm2 shows perfect match and the implementation complexity of Algorithm-2 is much lesser than Algorithm-1. Algorithm-1 takes almost 680 ms to execute and provides OPS value for a given number of users while Algorithm- 2 takes 4 to 5 ms on an average to find the optimal packet size for the proposed MIMO-CRSN framework

Absence of bimodal peak spacing distribution in the Coulomb blockade regime

Using exact diagonalization numerical methods, as well as analytical arguments, we show that for the typical electron densities in chaotic and disordered dots the peak spacing distribution is not bimodal, but rather Gaussian. This is in agreement with the experimental observations. We attribute this behavior to the tendency of an even number of electrons to gain on-site interaction energy by removing the spin degeneracy. Thus, the dot is predicted to show a non trivial electron number dependent spin polarization. Experimental test of this hypothesis based on the spin polarization measurements are proposed.Comment: 13 pages, 3 figures, accepted for publication in PRL - a few small change

Proposal to Search for Heavy Neutral Leptons at the SPS

A new fixed-target experiment at the CERN SPS accelerator is proposed that will use decays of charm mesons to search for Heavy Neutral Leptons (HNLs), which are right-handed partners of the Standard Model neutrinos. The existence of such particles is strongly motivated by theory, as they can simultaneously explain the baryon asymmetry of the Universe, account for the pattern of neutrino masses and oscillations and provide a Dark Matter candidate. Cosmological constraints on the properties of HNLs now indicate that the majority of the interesting parameter space for such particles was beyond the reach of the previous searches at the PS191, BEBC, CHARM, CCFR and NuTeV experiments. For HNLs with mass below 2 GeV, the proposed experiment will improve on the sensitivity of previous searches by four orders of magnitude and will cover a major fraction of the parameter space favoured by theoretical models. The experiment requires a 400 GeV proton beam from the SPS with a total of 2x10^20 protons on target, achievable within five years of data taking. The proposed detector will reconstruct exclusive HNL decays and measure the HNL mass. The apparatus is based on existing technologies and consists of a target, a hadron absorber, a muon shield, a decay volume and two magnetic spectrometers, each of which has a 0.5 Tm magnet, a calorimeter and a muon detector. The detector has a total length of about 100 m with a 5 m diameter. The complete experimental set-up could be accommodated in CERN's North Area. The discovery of a HNL would have a great impact on our understanding of nature and open a new area for future research

Evaluation of stable and non shattering isabgol cultivar - Gujarat isabgol 4

Isabgol growing area was surveyed during 2009-10 and selected genotypes were evaluated in preliminary evaluation trial (PET) during 2010-13 and in large scale varietal trial (LSVT) during 2013-15. It was found that JI-09-21 recorded better growth and yield characters and yield over check Gujarat Isabgol 3. The JI-09-21 did not shatter much even after water dripping and recommended for cultivation as Gujarat Isabgol 4

In-beam spectroscopy of medium- and high-spin states in 133^{133}Ce

Medium and high-spin states in $^{133}$Ce were investigated using the $^{116}$Cd($^{22}$Ne, $5n$) reaction and the Gammasphere array. The level scheme was extended up to an excitation energy of $\sim22.8$ MeV and spin 93/2 . Eleven bands of quadrupole transitions and two new dipole bands are identified. The connections to low-lying states of the previously known, high-spin triaxial bands were firmly established, thus fixing the excitation energy and, in many cases, the spin parity of the levels. Based on comparisons with cranked Nilsson-Strutinsky calculations and tilted axis cranking covariant density functional theory, it is shown that all observed bands are characterized by pronounced triaxiality. Competing multiquasiparticle configurations are found to contribute to a rich variety of collective phenomena in this nucleus.Comment: 20 pages, 11 figure