Auditors switching in the relationship between corporate governance and financial performances - evidence from Malaysian Public Listed Companies (PLCs)

Due to the corporate scandals in the business world, corporate governance is big concern and becomes an alarming issue. Bursa Malaysia required all PLCs to have corporate disclosures in order to cultivate sound corporate governance, meanwhile auditors act as watchdogs in ensuring the disclosures. However, auditor switching is evident and disorder of auditor switching often takes place in Malaysia. Thus, this paper seeks to empirically investigate the association between corporate governance, auditor switching, and financial performance of Malaysian PLCs. Secondary data on a total number of 100 PLCs from years 2009 to 2013 are used. The results reveal that separation of position for BOD chairman and CEO as well as large board size lead to better overseeing of the management on behalf of shareholders, which drives the firm performance. Surprisingly, independent directors do not definitely lead to good firm performance, especially when they do not play their role properly. When there is CEO/chairman duality, tendency of auditor switching is low due to a long-tenure relationship with auditor. A high powered structure in Malaysia that concentrates on top-down relationship prompts no objection from board members and independent directors when a less crucial decision such as auditor switching decision is made. Auditors as the mediator play significant roles between corporate governance and financial performance since they provide creditability and greater assurance to investors. Therefore, this paper has vital implications and gives insight for government to emphasize the auditors’ roles as agents for ensuring impacts on the association between corporate governance and financial performance

Early detection of mild cognitive impairment with in-home sensors to monitor behavior patterns in community-dwelling senior citizens in Singapore: Cross-sectional feasibility study

Singapore Management University; National Medical Research Council’s Healthcare Research Scholarshi

Consumer intention to use QR code

This study examines how the users' perception of QR code affects their attitude towards QR code, particularly in the context of Malaysian local university students. Next, the study examines the relationship between their attitude towards QR code and their intention to use the QR code. Empirical analysis via multiple regression analysis affirmed that PIQ influences PU and PSQ influences PEoU. Additionally, both PU and PEoU influences the attitude of users, which leads to the influence of attitude towards the user's intention to use to QR code. The functionality of QR codes can be utilized by business entities to serve for their company and create revenue. However, the companies must modify the content of the QR code application according to the minimum requirements and perception of the users. The results of this research offer essential guidelines for companies to tailor the information of their campaigns to the users' preferences. Next, future researches can utilize the proposed theoretical framework to exploit the potentials of QR code in the marketing field

Time for a new language for asthma control : Results from REALISE Asia

Acknowledgments: This study was supported and funded by Mundipharma Pte Ltd. Online survey and statistical analysis were performed by Pei-Li Teh, Rachel Howard, Tsin-Li Chua, and Jie Sun of Research Partnership Pte Ltd. Medical writing support was provided by Sen-Kwan Tay of Research2Trials Clinical Solutions Pte Ltd.Peer reviewedPublisher PD

Metabarcoding mosquitoes: MinION sequencing of bulk samples gives accurate species profiles for vector surveillance (Culicidae)

Mosquitoes (Family: Culicidae) are dominant vectors of pathogens, and their surveillance has been incorporated into major disease control programs worldwide. However, routine, species-level identification of mosquitoes is often a bottleneck for management, and Next Generation Sequencing (NGS) platforms and DNA metabarcoding can revolutionize this process. MinION nanopore technologies promise on-site sequencing and rapid sample processing rates ideal for time-sensitive biosurveillance. Here, we benchmark the results of DNA metabarcoding on the MinION against the Illumina MiSeq platform, which is known for its higher sequencing accuracy. We used metazoan COI mini-barcode primers to carry out DNA metabarcoding of mosquito bulk samples caught during a real vector survey, then compared the mosquito species profiles recovered on each sequencing platform. We also tested the influence of using different trap lures, storage methods, and pooling different specimen body parts on the number of species recovered. We report that mosquito species-level identifications were highly congruent between MinION and Illumina (93% overlap). We also find that CO2 gas cylinders outperformed biogenic CO2 sources significantly, by two-fold. Notably, we demonstrated the feasibility of detecting zoonotic reservoirs and pathogen signals from mosquito bulk samples. We present the first use of DNA metabarcoding on the MinION for vector surveillance and discuss future applications

Adaptive route optimization for mobile robot navigation using evolutionary algorithm

As technologies are advancing, demand for an intelligent mobile robot also increases. In autonomous robot design, the main problem faced by researchers is the path planning of mobile robot. Various kind of path planning algorithm was introduced in the past, but no algorithm has absolute superior towards the others algorithm. Classical methods like artificial potential field, grid search, and visual method have been easily overtaken by artificial intelligence due to its adaptability and ability to learn from the past mistakes or experience. For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. However, the performance of ACO is highly dependent on the selection of its parameters. In this paper, the proposed adaptive ACO introduced two different ants, namely abnormal ant and random ant into the normal ACO to increase its global search ability and reduce the high convergence rate of ACO. Conventional ACO and adaptive ACO are compared in this paper and the results showed that adaptive ACO has better performance than conventional ACO in path planning

Exploration of genetic algorithm in network coding for wireless sensor networks

Wireless network comprises of multiples nodes that work together to form a network. Each node in a wireless network communicates with one another by disseminating information packet among them. Source node and destination node are often far apart from each other, thus the information packet has to be transmitted to intermediate node(s) before it is able to be relayed to its destination. Network coding is introduced to combine several packets from different sources and broadcast the combined packet to several destinations in single transmission time slot. Each destination is capable to extract the intended information by decoding from a common packet. In short, network coding improves the throughput for wireless and wired networks but also causes side effects such as complexity of packets management and increases delay for coding opportunity. Hence, genetic algorithm is used to optimize the resources for network coding. Genetic algorithm will search for optimum routes to the destination according to the desired throughput with a desired multicast rate. In this paper, genetic algorithm is further enhanced in searching of optimum route for a packet. The simulation results show the enhanced genetic algorithm can adapt to various situations with different topologies with a better throughput and energy consumption compared to the store-and-forward method used in conventional wireless sensor network

A genetic algorithm for management of coding resources in VANET

This project aims to improve the throughput, energy consumption and overhead of vehicular ad hoc network (VANET) by optimising the network coding (NC) using Genetic Algorithm (GA). VANET shows a promising technology as it could enhance the traffic efficiency and promote traffic safety on the road systems. The conventional store-and-forward transmission protocol used in the intermediate node(s) simply stores the received packet and then send at a later time to the destination. However, the rapid changing in VANET topology has made the conventional store-and-forward approach inefficient to meet the throughput and reliability demand posed by VANET. Hence, NC is proposed to perform additional functions on the packet in the source or intermediate node(s). However, the chances to perform NC in wireless network is highly unlikely if the packet is not transmit to the potential NC node. Therefore, GA based network routing (GANeR) is embedded into network to search for shortest path from the source to the destination. It showed that the developed GANER in this work provides a better route with coding opportunities and reduces energy consumption in the network. The total energy consumed by GANER is 5.6% fewer than NC in wireless network transmission and forwarding structure (COPE)

HYBRID SIMULATION NETWORK FOR VEHICULAR AD HOC NETWORK (VANET)

Intelligent Transportation Systems (ITS) plays a vital role in providing different means of traffic management and enables users to be better informed of traffic condition, promoting safer, coordinated and efficient use of transport network. Vehicular Ad Hoc Network (VANET) shows promising reliability and validity in ITS. But, it poses challenges to researchers in designing protocol specifically for VANET as the deployment of VANET in real world will incur high cost. Therefore, simulation and non-physical testbed implementation have been widely adopted by the VANET research community in the development and assessment of the new or improved system and protocol of VANET. This paper presents a viable simulation platform for network development. Besides, a code cast or better known as network coding, a data packet transmission method has been developed and introduced into VANET protocol using the presented platform to assess and determine the potential of the introduced simulation platform

Prenatal selective serotonin reuptake inhibitor (SSRI) exposure induces working memory and social recognition deficits by disrupting inhibitory synaptic networks in male mice

Selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed antidepressant drugs in pregnant women. Infants born following prenatal exposure to SSRIs have a higher risk for behavioral abnormalities, however, the underlying mechanisms remains unknown. Therefore, we examined the effects of prenatal fluoxetine, the most commonly prescribed SSRI, in mice. Intriguingly, chronic in utero fluoxetine treatment impaired working memory and social novelty recognition in adult males. In the medial prefrontal cortex (mPFC), a key region regulating these behaviors, we found augmented spontaneous inhibitory synaptic transmission onto the layer 5 pyramidal neurons. Fast-spiking interneurons in mPFC exhibited enhanced intrinsic excitability and serotonin-induced excitability due to upregulated serotonin (5-HT) 2A receptor (5-HT2AR) signaling. More importantly, the behavioral deficits in prenatal fluoxetine treated mice were reversed by the application of a 5-HT2AR antagonist. Taken together, our findings suggest that alterations in inhibitory neuronal modulation are responsible for the behavioral alterations following prenatal exposure to SSRIs