Odonata of Ayer Hitam Forest Reserve, Johor, Peninsular Malaysia

Odonata records from Ayer Hitam Forest Reserve and the surrounding area in Johor, Peninsular Malaysia are presented. A total of 44 Odonata species from eight families were collected in the area in October 2012. All of these records are new to Ayer Hitam Forest Reserve. Indothemis carnitica is a new record for Malaysia

Optimal Charging of Electric Vehicles in Smart Grid: Characterization and Valley-Filling Algorithms

Electric vehicles (EVs) offer an attractive long-term solution to reduce the dependence on fossil fuel and greenhouse gas emission. However, a fleet of EVs with different EV battery charging rate constraints, that is distributed across a smart power grid network requires a coordinated charging schedule to minimize the power generation and EV charging costs. In this paper, we study a joint optimal power flow (OPF) and EV charging problem that augments the OPF problem with charging EVs over time. While the OPF problem is generally nonconvex and nonsmooth, it is shown recently that the OPF problem can be solved optimally for most practical power networks using its convex dual problem. Building on this zero duality gap result, we study a nested optimization approach to decompose the joint OPF and EV charging problem. We characterize the optimal offline EV charging schedule to be a valley-filling profile, which allows us to develop an optimal offline algorithm with computational complexity that is significantly lower than centralized interior point solvers. Furthermore, we propose a decentralized online algorithm that dynamically tracks the valley-filling profile. Our algorithms are evaluated on the IEEE 14 bus system, and the simulations show that the online algorithm performs almost near optimality ($<1$ relative difference from the offline optimal solution) under different settings.Comment: This paper is temporarily withdrawn in preparation for journal submissio

Self-Dual Conformal Supergravity and the Hamiltonian Formulation

In terms of Dirac matrices the self-dual and anti-self-dual decomposition of a conformal supergravity is given and a self-dual conformal supergravity theory is developed as a connection dynamic theory in which the basic dynamic variabes include the self-dual spin connection i.e. the Ashtekar connection rather than the triad. The Hamiltonian formulation and the constraints are obtained by using the Dirac-Bergmann algorithm. PACS numbers: 04.20.Cv, 04.20.Fy,04.65.+

Antibiotics to improve recovery following tonsillectomy: a systematic review.

OBJECTIVE: To determine if antibiotics improve recovery following tonsillectomy. STUDY DESIGN: DATA SOURCES: Electronic databases Medline, Embase, and Cochrane Controlled Trials Register were searched using relevant search terms. Additional trials, if any, were retrieved by searching the references from all identified trials, reviews, correspondences, editorials, and conference proceedings. No language restriction was applied. STUDY SELECTION: Systematic review of trials in which antibiotic was administered as a study medication intraoperatively and/or postoperatively, in children or adults undergoing tonsillectomy or adenotonsillectomy. Only randomized, placebo-controlled, double-blind trials attaining preset quality scores were included. Outcomes analyzed: 1) pain, need for analgesia, fever, halitosis, and return to normal diet and activities; 2) secondary hemorrhage using 2 parameters-significant hemorrhage (ie, warranting readmission, blood transfusion, or return to theatre for hemostasis) and total hemorrhage; and 3) adverse events. RESULTS: Five trials met the eligibility criteria. Antibiotics significantly reduced the number of subjects manifesting fever (relative risk [RR]: 0.62, 95% confidence interval [CI]: 0.45, 0.85) and duration of halitosis (-1.94 [-3.57, -0.30] days), and marginally reduced the time taken to resume normal activity (-0.63 [-1.12, -0.14] days), but had no significant effect in reducing pain scores (-0.01 [-0.60, 0.57]) or need for analgesia. Similarly, there was no significant difference in the time taken to resume normal diet or incidence of significant and total hemorrhage, although data was underpowered to detect differences for these outcomes. In the antibiotic group 4 patients developed an adverse reaction (3 cases of rash and 1 case of oropharyngeal candidiasis), while in the control group 1 patient had an adverse reaction (rash). The RR of antibiotic-related adverse events was 2.45 (0.45, 13.31). CONCLUSION: Antibiotics appear to be effective in reducing some, but not all, morbid outcomes following tonsillectomy, and may increase the risk of adverse events. Further trials are needed to better define the role of antibiotics in facilitating post-tonsillectomy recovery. EBM RATING: A-1a

Estimating Time-Varying Effective Connectivity in High-Dimensional fMRI Data Using Regime-Switching Factor Models

Recent studies on analyzing dynamic brain connectivity rely on sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously. Emerging evidence suggests state-related changes in brain connectivity where dependence structure alternates between a finite number of latent states or regimes. Another challenge is inference of full-brain networks with large number of nodes. We employ a Markov-switching dynamic factor model in which the state-driven time-varying connectivity regimes of high-dimensional fMRI data are characterized by lower-dimensional common latent factors, following a regime-switching process. It enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We consider the switching VAR to quantity the dynamic effective connectivity. We propose a three-step estimation procedure: (1) extracting the factors using principal component analysis (PCA) and (2) identifying dynamic connectivity states using the factor-based switching vector autoregressive (VAR) models in a state-space formulation using Kalman filter and expectation-maximization (EM) algorithm, and (3) constructing the high-dimensional connectivity metrics for each state based on subspace estimates. Simulation results show that our proposed estimator outperforms the K-means clustering of time-windowed coefficients, providing more accurate estimation of regime dynamics and connectivity metrics in high-dimensional settings. Applications to analyzing resting-state fMRI data identify dynamic changes in brain states during rest, and reveal distinct directed connectivity patterns and modular organization in resting-state networks across different states.Comment: 21 page

Linear Size Optimal q-ary Constant-Weight Codes and Constant-Composition Codes

An optimal constant-composition or constant-weight code of weight $w$ has linear size if and only if its distance $d$ is at least $2w-1$. When $d\geq 2w$, the determination of the exact size of such a constant-composition or constant-weight code is trivial, but the case of $d=2w-1$ has been solved previously only for binary and ternary constant-composition and constant-weight codes, and for some sporadic instances. This paper provides a construction for quasicyclic optimal constant-composition and constant-weight codes of weight $w$ and distance $2w-1$ based on a new generalization of difference triangle sets. As a result, the sizes of optimal constant-composition codes and optimal constant-weight codes of weight $w$ and distance $2w-1$ are determined for all such codes of sufficiently large lengths. This solves an open problem of Etzion. The sizes of optimal constant-composition codes of weight $w$ and distance $2w-1$ are also determined for all $w\leq 6$, except in two cases.Comment: 12 page