The Effect of Board Structure on Shareholders’ Wealth in Small Listed Companies in Malaysia

Using content analyses, this study examines whether board structure of small listed companies influence their shareholders’ wealth. This study focuses on three elements of board structure, namely, board size, board composition and directors’ remuneration to examine the relationship between board structure and shareholders’ wealth. Shareholders’ wealth is measured by the return on investment and earnings per share. The results show that out of the three elements of board structure, board size and board composition play an important role in influencing shareholders’ wealth in small listed companies. The results support the findings in earlier studies that large number of directors and the proportion of executive directors in a board would instil better decision-making policy. The results in this study, however, did not support the contention that there is a significant relationship between the directors’ remuneration and financial performance. The results in this study complement previous studies and provide some understanding on the importance of practicing good corporate governance. Keywords: Board structure, board size, board composition, director remuneration, shareholders’ wealth, Malaysia

Recovery in cognitive motor dissociation after severe brain injury: A cohort study.

To investigate the functional and cognitive outcomes during early intensive neurorehabilitation and to compare the recovery patterns of patients presenting with cognitive motor dissociation (CMD), disorders of consciousness (DOC) and non-DOC. We conducted a single center observational cohort study of 141 patients with severe acquired brain injury, consecutively admitted to an acute neurorehabilitation unit. We divided patients into three groups according to initial neurobehavioral diagnosis at admission using the Coma Recovery Scale-Revised (CRS-R) and the Motor Behavior Tool (MBT): potential clinical CMD, [N = 105]; DOC [N = 19]; non-DOC [N = 17]). Functional and cognitive outcomes were assessed at admission and discharge using the Glasgow Outcome Scale, the Early Rehabilitation Barthel Index, the Disability Rating Scale, the Rancho Los Amigos Levels of Cognitive Functioning, the Functional Ambulation Classification Scale and the modified Rankin Scale. Confirmed recovery of conscious awareness was based on CRS-R criteria. CMD patients were significantly associated with better functional outcomes and potential for improvement than DOC. Furthermore, outcomes of CMD patients did not differ significantly from those of non-DOC. Using the CRS-R scale only; approximatively 30% of CMD patients did not recover consciousness at discharge. Our findings support the fact that patients presenting with CMD condition constitute a separate category, with different potential for improvement and functional outcomes than patients suffering from DOC. This reinforces the need for CMD to be urgently recognized, as it may directly affect patient care, influencing life-or-death decisions

Robust super-resolution depth imaging via a multi-feature fusion deep network

Three-dimensional imaging plays an important role in imaging applications where it is necessary to record depth. The number of applications that use depth imaging is increasing rapidly, and examples include self-driving autonomous vehicles and auto-focus assist on smartphone cameras. Light detection and ranging (LIDAR) via single-photon sensitive detector (SPAD) arrays is an emerging technology that enables the acquisition of depth images at high frame rates. However, the spatial resolution of this technology is typically low in comparison to the intensity images recorded by conventional cameras. To increase the native resolution of depth images from a SPAD camera, we develop a deep network built specifically to take advantage of the multiple features that can be extracted from a camera's histogram data. The network is designed for a SPAD camera operating in a dual-mode such that it captures alternate low resolution depth and high resolution intensity images at high frame rates, thus the system does not require any additional sensor to provide intensity images. The network then uses the intensity images and multiple features extracted from downsampled histograms to guide the upsampling of the depth. Our network provides significant image resolution enhancement and image denoising across a wide range of signal-to-noise ratios and photon levels. We apply the network to a range of 3D data, demonstrating denoising and a four-fold resolution enhancement of depth

Effect of root exuded specific sugars on biological nitrogen fixation and growth promotion in rice (Oryza sativa).

Biological Nitrogen Fixation (BNF) is an energy involving process. A 15N tracer study was conducted under growth chamber and glasshouse conditions to determine the effect of glucose, galactose and arabinose (common sugars found in root environments) on BNF by two diazotrophs, Rhizobium sp. Sb16 and Corynebacterium sp. Sb26, previously isolated from rice genotypes (Mayang Segumpal and MR219). Diazotrophs have preferences for specific sugar utilization and plant association. Sb16 showed high preference for galactose, and Sb26 preferred arabinose. Application of 10 mM sugar in the experimental pot (5 kg soil), either galactose or arabinose, to the respective rice genotype enhanced diazotroph population growth, N2 fixation activity and simultaneously plant growth. Mayang inoculated with Sb16 applied with galactose increased plant N concentration 4.2 +/- 0.07 %, whereby, 42 +/- 1.06 % of the N was derived from the atmosphere. About 40 +/- 1.29 % of the N concentration of MR219 inoculated with Sb26 and arabinose was obtained from BNF. The association between Mayang with Sb16 increased 195 +/- 40 % of plant biomass as compared to control, and 36 +/- 19.8 % over 60 kg ha-1 of N-fertilizer. On the other hand, the association of MR219 with Sb26 resulted in 108 +/- 37.07 % biomass increment as compared to control, and 89 +/- 22.34 % over fertilized-N in different sugar treatments. The association between the plant-diazotrophs along with sugar significantly increased photosynthetic activity. The study indicated that growth and N2 fixation activity of rice can be increased by increasing the availability of specific sugars in the rhizosphere

High-speed object detection with a single-photon time-of-flight image sensor

3D time-of-flight (ToF) imaging is used in a variety of applications such as augmented reality (AR), computer interfaces, robotics and autonomous systems. Single-photon avalanche diodes (SPADs) are one of the enabling technologies providing accurate depth data even over long ranges. By developing SPADs in array format with integrated processing combined with pulsed, flood-type illumination, high-speed 3D capture is possible. However, array sizes tend to be relatively small, limiting the lateral resolution of the resulting depth maps, and, consequently, the information that can be extracted from the image for applications such as object detection. In this paper, we demonstrate that these limitations can be overcome through the use of convolutional neural networks (CNNs) for high-performance object detection. We present outdoor results from a portable SPAD camera system that outputs 16-bin photon timing histograms with 64x32 spatial resolution. The results, obtained with exposure times down to 2 ms (equivalent to 500 FPS) and in signal-to-background (SBR) ratios as low as 0.05, point to the advantages of providing the CNN with full histogram data rather than point clouds alone. Alternatively, a combination of point cloud and active intensity data may be used as input, for a similar level of performance. In either case, the GPU-accelerated processing time is less than 1 ms per frame, leading to an overall latency (image acquisition plus processing) in the millisecond range, making the results relevant for safety-critical computer vision applications which would benefit from faster than human reaction times.Comment: 13 pages, 5 figures, 3 table