Knowledge management of flood disaster in social media

Social media sites are playing a significant role in rapid propagation of information when disasters occur. This effective communication platform is a great useful tool for emergency management agencies during all phases of disaster management life cycle which is prevention, preparedness, response, and recovery. Effective knowledge management is promising to improve organizational and personal performance. It has been widely recognized that information and communication technologies may contribute to knowledge management if they can be suitably utilized. Thus, this study is carried out to identify the utilization of knowledge management processes for flood disaster management in social media. Quantitative method is chosen for collecting data in this research

Blending big data analytics : review on challenges and a recent study

With the collection of massive amounts of data every day, big data analytics has emerged as an important trend for many organizations. These collected data can contain important information that may be key to solving wide-ranging problems, such as cyber security, marketing, healthcare, and fraud. To analyze their large volumes of data for business analyses and decisions, large companies, such as Facebook and Google, adopt analytics. Such analyses and decisions impact existing and future technology. In this paper, we explore how big data analytics is utilized as a technique for solving problems of complex and unstructured data using such technologies as Hadoop, Spark, and MapReduce. We also discuss the data challenges introduced by big data according to the literature, including its six V's. Moreover, we investigate case studies of big data analytics on various techniques of such analytics, namely, text, voice, video, and network analytics. We conclude that big data analytics can bring positive changes in many fields, such as education, military, healthcare, politics, business, agriculture, banking, and marketing, in the future. © 2013 IEEE

Draft Genome Sequence of Candida pseudohaemulonii Isolated from the Blood of a Neutropenic Patient

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Blending big data analytics: review on challenges and a recent study

With the collection of massive amounts of data every day, big data analytics has emerged as an important trend for many organizations. These collected data can contain important information that may be key to solving wide-ranging problems, such as cyber security, marketing, healthcare, and fraud. To analyze their large volumes of data for business analyses and decisions, large companies, such as Facebook and Google, adopt analytics. Such analyses and decisions impact existing and future technology. In this paper, we explore how big data analytics is utilized as a technique for solving problems of complex and unstructured data using such technologies as Hadoop, Spark, and MapReduce. We also discuss the data challenges introduced by big data according to the literature, including its six V’s. Moreover, we investigate case studies of big data analytics on various techniques of such analytics, namely, text, voice, video, and network analytics. We conclude that big data analytics can bring positive changes in many fields, such as education, military, healthcare, politics, business, agriculture, banking, and marketing, in the future

Potassium fertilisation reduced late embryogenesis abundant (LEA) gene expression in Malaysian rice (MR220) under water stress condition

The application of potassium fertiliser might mitigate water stress effects in developing rice, thus influencing Late Embryogenesis Abundant (LEA) gene expression and growth in the plant tissue. This study was conducted to examine LEA gene expression in its drought tolerance mechanisms and the growth of Malaysian Rice (MR220) when exposed to water stress and potassium fertilisation. Three treatments were developed, namely the control (CF; Continuously flooding + 80 kg K2O/ha), water stress under standard potassium fertilisation (WS; Water Stress 25 days + 80 kg K2O/ha) and water stress under high potassium fertilisation (WSK; Water Stress 25 days + 120 kg K2O/ha). The plant growth and yield components were measured for each treatment with randomly tagged plant by 3 replicates. The result showed that LEA gene expression on WSK was 36% less than on WS, thus indicating that the application of additional potassium fertilisation on MR220 rice might mitigate the water stress effect imposed on this plant. The study showed that high LEA gene expression in WS was accompanied by a reduction in plant growth and yield performance, such as plant tillers, height, number of leaves and grain yield compared to the control and WSK. © 2019 the Author(s)

Shading effects on leaf gas exchange, leaf pigments and secondary metabolites of polygonum minus huds., an aromatic medicinal herb

The growing demand for high value aromatic herb Polygonum minus-based products have increased in recent years, for its antioxidant, anticancer, antimicrobial, and anti-inflammatory potentials. Although few reports have indicated the chemical profiles and antioxidative effects of Polygonum minus, no study has been conducted to assess the benefits of micro-environmental manipulation (different shading levels) on the growth, leaf gas exchange and secondary metabolites in Polygonum minus. Therefore, two shading levels (50%:T2 and 70%:T3) and one absolute control (0%:T1) were studied under eight weeks and 16 weeks of exposures on Polygonum minus after two weeks. It was found that P. minus under T2 obtained the highest photosynthesis rate (14.892 µmol CO2 m−2 s−1), followed by T3 = T1. The increase in photosynthesis rate was contributed by the enhancement of the leaf pigments content (chlorophyll a and chlorophyll b). This was shown by the positive significant correlations observed between photosynthesis rate with chlorophyll a (r2 = 0.536; p ≤ 0.05) and chlorophyll b (r2 = 0.540; p ≤ 0.05). As the shading levels and time interval increased, the production of total anthocyanin content (TAC) and antioxidant properties of Ferric Reducing Antioxidant Power (FRAP) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) also increased. The total phenolic content (TPC) and total flavonoid content (TFC) were also significantly enhanced under T2 and T3. The current study suggested that P.minus induce the production of more leaf pigments and secondary metabolites as their special adaptation mechanism under low light condition. Although the biomass was affected under low light, the purpose of conducting the study to boost the bioactive properties in Polygonum minus has been fulfilled by 50% shading under 16 weeks’ exposure

Development of Nuclear DNA Markers for Applications in Genetic Diversity Study of Oil Palm-Pollinating Weevil Populations

The oil palm-pollinating weevil (Elaeidobius kamerunicus Faust) was introduced from Cameroon, West Africa, to Malaysia in 1981, and subsequently, to other oil palm-growing countries as well. This study aims to develop a set of robust E. kamerunicus-specific nuclear DNA markers to directly assess the genetic diversity of the weevil populations. A total of 19,148 SNP and 223,200 SSR were discovered from 48 weevils representing three origins (Peninsular Malaysia, Sabah, and Riau) using RAD tag sequencing. Subsequent filtering steps further reduced these to 1000 SNP and 120 SSR. The selected 220 SNP exhibited a polymorphism information content (PIC) of 0.2387 (±0.1280), and 8 SSR had the PIC of 0.5084 (±0.1928). These markers were found to show sufficient polymorphism, making it possible to assign 180 weevils into three major clusters from Ghana, Cameroon, and Southeast Asia (mainly in Malaysia and Indonesia). These DNA markers successfully confirmed the Cameroon origin of the Southeast Asian cluster. However, the presence of null alleles in the SSR markers, due to limited flexibility of the probe design on the short RAD tags, led to an underestimation of heterozygosity within the populations. Hence, the developed SNP markers turned out to be more efficient than the SSR markers in the genetic diversity assessment of the E. kamerunicus populations. The genetic information provides useful insight into developing guidelines for the genetic monitoring and conservation planning of E. kamerunicus

Development of Nuclear DNA Markers for Applications in Genetic Diversity Study of Oil Palm-Pollinating Weevil Populations

The oil palm-pollinating weevil (Elaeidobius kamerunicus Faust) was introduced from Cameroon, West Africa, to Malaysia in 1981, and subsequently, to other oil palm-growing countries as well. This study aims to develop a set of robust E. kamerunicus-specific nuclear DNA markers to directly assess the genetic diversity of the weevil populations. A total of 19,148 SNP and 223,200 SSR were discovered from 48 weevils representing three origins (Peninsular Malaysia, Sabah, and Riau) using RAD tag sequencing. Subsequent filtering steps further reduced these to 1000 SNP and 120 SSR. The selected 220 SNP exhibited a polymorphism information content (PIC) of 0.2387 (±0.1280), and 8 SSR had the PIC of 0.5084 (±0.1928). These markers were found to show sufficient polymorphism, making it possible to assign 180 weevils into three major clusters from Ghana, Cameroon, and Southeast Asia (mainly in Malaysia and Indonesia). These DNA markers successfully confirmed the Cameroon origin of the Southeast Asian cluster. However, the presence of null alleles in the SSR markers, due to limited flexibility of the probe design on the short RAD tags, led to an underestimation of heterozygosity within the populations. Hence, the developed SNP markers turned out to be more efficient than the SSR markers in the genetic diversity assessment of the E. kamerunicus populations. The genetic information provides useful insight into developing guidelines for the genetic monitoring and conservation planning of E. kamerunicus