Taxonomic revision of Garcinia section Garcinia (Clusiaceae)

Species of Garcinia sect. Garcinia are typically understorey trees in rain forest and are distributed from eastern India to Malesia. A taxonomic revision of Garcinia section Garcinia (Clusiaceae) has resulted in the recognition of 13 species, two of which have three varieties each. Several species are excluded from Garcinia section Garcinia, reported as insufficiently known, or reduced to synonymy. Five species, G. acuticosta, G. discoidea, G. exigua, G. ochracea and G. sangudsangud, and two varieties, G. diospyrifolia var. minor and G. mangostana var. borneensis, are newly described. Morphological characters that are important for sectional delimitation are terminally attached inflorescences of simple cymes, stamen bundles 4 or 4-angled, and fruits with a smooth surface. Species limits are defined on the basis of a combination of characters of the male flower (i.e. shape of stamens, presence of pistillode), type of fruit, and characters of the leaf (shape and size, venation pattern and glandular lines)

Zingiber zerumbet (L.) Smith: A Review of Its Ethnomedicinal, Chemical, and Pharmacological Uses

Zingiber zerumbet Sm., locally known to the Malay as “Lempoyang,” is a perennial herb found in many tropical countries, including Malaysia. The rhizomes of Z. zerumbet, particularly, have been regularly used as food flavouring and appetizer in various Malays' cuisines while the rhizomes extracts have been used in Malay traditional medicine to treat various types of ailments (e.g., inflammatory- and pain-mediated diseases, worm infestation and diarrhea). Research carried out using different in vitro and in vivo assays of biological evaluation support most of these claims. The active pharmacological component of Z. zerumbet rhizomes most widely studied is zerumbone. This paper presents the botany, traditional uses, chemistry, and pharmacology of this medicinal plant

Adaptive memory-based single distribution resampling for particle filter

The restrictions that are related to using single distribution resampling for some specific computing devices’ memory gives developers several difficulties as a result of the increased effort and time needed for the development of a particle filter. Thus, one needs a new sequential resampling algorithm that is flexible enough to allow it to be used with various computing devices. Therefore, this paper formulated a new single distribution resampling called the adaptive memory size-based single distribution resampling (AMSSDR). This resampling method integrates traditional variation resampling and traditional resampling in one architecture. The algorithm changes the resampling algorithm using the memory in a computing device. This helps the developer formulate a particle filter without over considering the computing devices’ memory utilisation during the development of different particle filters. At the start of the operational process, it uses the AMSSDR selector to choose an appropriate resampling algorithm (for example, rounding copy resampling or systematic resampling), based on the current computing devices’ physical memory. If one chooses systematic resampling, the resampling will sample every particle for every cycle. On the other hand, if it chooses the rounding copy resampling, the resampling will sample more than one of each cycle’s particle. This illustrates that the method (AMSSDR) being proposed is capable of switching resampling algorithms based on various physical memory requirements. The aim of the authors is to extend this research in the future by applying their proposed method in various emerging applications such as real-time locator systems or medical applications

Graphical user interface for wireless patient monitoring system using zigbee communication

Nowadays, heart related diseases are on the rise situation. In Malaysia, the proportion of patients is increasing day by day but the number of doctor and nurse slightly different situation. For this reason, the new propose graphical user interface for wireless patient monitoring system is proposed in order to help doctors and nurses to monitor their patient wirelessly for 24 hours by using a designated proposed device. This system runs as prototype to minimize the costing issue in the hospital. This system consists of software and hardware. Visual Basic Net 2010 software is used to design the graphical user interface (GUI) and Peripheral Interface Controller (PIC) 16F877A microcontroller is used as the hardware to implement the whole proposed system. This system is can be divided into three parts. There are three stages that involved in completing the system. The first is developing a program for the microcontroller, the second is transmitting the data from microcontroller to the personal computer (PC) using XBee module and the third is designing the GUI. In conclusion, the proposed GUI for wireless patient monitoring system facilitated the doctor and nurse in monitoring the patient and increased the efficiency of patient monitoring. For the future recommendation

Effect of fibre coating and geometry on the tensile properties of hybrid carbon nanotube coated carbon fibre reinforced composite

Hierarchically structured hybrid composites are ideal engineered materials to carry loads and stresses due to their high in-plane specific mechanical properties. Growing carbon nanotubes (CNTs) on the surface of high performance carbon fibres (CFs) provides a means to tailor the mechanical properties of the fibre-resin interface of a composite. The growth of CNT on CF was conducted via floating catalyst chemical vapor deposition (CVD). The mechanical properties of the resultant fibres, carbon nanotube (CNT) density and alignment morphology were shown to depend on the CNT growth temperature, growth time, carrier gas flow rate, catalyst amount, and atmospheric conditions within the CVD chamber. Carbon nanotube coated carbon fibre reinforced polypropylene (CNT-CF/PP) composites were fabricated and characterized. A combination of Halpin-Tsai equations, Voigt-Reuss model, rule of mixture and Krenchel approach were used in hierarchy to predict the mechanical properties of randomly oriented short fibre reinforced composite. A fractographic analysis was carried out in which the fibre orientation distribution has been analyzed on the composite fracture surfaces with Scanning Electron Microscope (SEM) and image processing software. Finally, the discrepancies between the predicted and experimental values are explained. (C) 2013 Elsevier Ltd. All rights reserved

Mitochondrial barcodes of dragonflies and damselflies originated from Taman Negara Endau Rompin, Johor, Malaysia

Dragonflies and damselflies (Odonates) are important biological indicators in freshwater ecosystems. However, identification among Odonates is often challenging due to their similar morphological features. Therefore, the incorporation of morphological identification by taxonomists and validation using mitochondrial barcodes such as cytochrome c oxidase subunit I (COI) can be a more reliable approach to enhance the accuracy in species identification. In this study, four COI barcodes for Malaysian dragonflies (Neurothemis fluctuans) and damselflies (Neurobasis chinensis, Aristocypha fenestrella and Sundacypha petiolata) were generated. Three of the generated barcodes (D2 COI, D4 COI and D5 COI) supported the species identified by taxonomists meanwhile D3 COI deduced that the damselfly species was misidentified due to the very similar morphology between the same genus of damselfly. All of the COI barcodes are now available in the GenBank with the accession numbers of MT266926.1 (D2 COI), MT266925.1 (D3 COI), MT269676.1 (D4 COI) and MT266924.1 (D5 COI)

Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study

This is the final version. Available on open access from MDPI via the DOI in this recordCephalexin (CFX) residues in the environment represent a major threat to human health worldwide. Herein we investigate the use of novel approaches in deep learning in order to understand the mechanisms and optimal conditions for the sorption of cephalexin in water onto an acidic pretreated jackfruit peel adsorbent (APJPA). The interaction between the initial concentration of CFX (10–50 mg/100 mL), APJAP dosage (3–10 mg/100 mL), time (10–60 min), and the pH (4–9), was simulated using the one-factor-at-a-time method. APJPA was characterized by FESEM images showing that APJPA exhibits a smooth surface devoid of pores. FTIR spectra confirmed the presence of -C-O, C–H, C=C, and -COOH bonds within the APJPA. Maximum removal was recorded with 6.5 mg/100 mL of APJAP dosage, pH 6.5, after 35 min and with 25 mg/100 mL of CFX, at which the predicted and actual adsorption were 96.08 and 98.25%, respectively. The simulation results show that the dosage of APJAP exhibits a high degree of influence on the maximum adsorption of CFX removal (100%) between 2 and 8 mg dose/100 mL. The highest adsorption capacity of APJAP was 384.62 mg CFX/g. The simulation for the effect of pH determined that the best pH for the CFX adsorption lies between pH 5 and 8.Ministry of Higher Education Malaysia (MOHE)Royal SocietyKing Saud University, Riyadh, Saudi Arabi

VULNERABILITY MAPPING AND ANALYSIS: AN IMPLEMENTATION IN GEOHAZARD AREAS IN SABAH

Vulnerability identifies the element-at-risk as well as the evaluation of their relationships with the hazard. The relationships relate the landslide potential damages over a specific element-at-risk. Vulnerability can be defined as the degree of loss to a given element-at-risk or set of elements at risk resulting from the occurrence of a natural phenomenon of a given magnitude and expressed on a scale from 0 (no damage) to 1 (total damage). In this study, the landslide vulnerability mapping and analysis were made on two element-at-risks namely buildings and roads. Based on field observations, building and road construction materials have been classified into 22 and 5 construction materials respectively. The field visits were made on specific areas based on candidate buildings and roads as chosen during the landslide exposure analysis and mapping. The vulnerability values for these element-at-risks were expressed using expert opinion. Four experts have been interviewed with separate sessions. The experts were also supplied with local information on the landslides occurrences and photos of element-at-risk in Kundasang and Kota Kinabalu. The vulnerability matrices were combined based on the weighted average approach, in which higher weight was assigned to panel with local expert (landslides and damage assessment), wide experience in landslide vulnerability analysis, hazard and risk mapping. Finally, the vulnerability maps were produced for Kundasang and Kota Kinabalu with spatial resolution of 25 cm. These maps were used for the next step i.e. landslide risk mapping and analysis

GEOSPATIAL APPROACH FOR LANDSLIDE ACTIVITY ASSESSMENT AND MAPPING BASED ON VEGETATION ANOMALIES

Remote sensing has been widely used for landslide inventory mapping and monitoring. Landslide activity is one of the important parameters for landslide inventory and it can be strongly related to vegetation anomalies. Previous studies have shown that remotely sensed data can be used to obtain detailed vegetation characteristics at various scales and condition. However, only few studies of utilizing vegetation characteristics anomalies as a bio-indicator for landslide activity in tropical area. This study introduces a method that utilizes vegetation anomalies extracted using remote sensing data as a bio-indicator for landslide activity analysis and mapping. A high-density airborne LiDAR, aerial photo and satellite imagery were captured over the landslide prone area along Mesilau River in Kundasang, Sabah. Remote sensing data used in characterizing vegetation into several classes of height, density, types and structure in a tectonically active region along with vegetation indices. About 13 vegetation anomalies were derived from remotely sensed data. There were about 14 scenarios were modeled by focusing in 2 landslide depth, 3 main landslide types with 3 landslide activities by using statistical approach. All scenarios show that more than 65% of the landslides are captured within 70% of the probability model indicating high model efficiency. The predictive model rate curve also shows that more than 45% of the independent landslides can be predicted within 30% of the probability model. This study provides a better understanding of remote sensing data in extracting and characterizing vegetation anomalies induced by hillslope geomorphology processes in a tectonically active region in Malaysia