Isolation and characterization of a molybdenum-reducing and azo-dye decolorizing Serratia marcescens strain Neni-1 from Indonesian soil

Heavy metals and organic xenobiotics including dyes are important industrial components with their usage amounting to the millions of tonnes yearly. Their presence in the environment is a serious pollution issue globally. Bioremediation of these pollutants using microbes with multiple detoxification capacity is constantly being sought. In this work we screen the ability of a molybdenum-reducing bacterium isolated from contaminated soil to decolorize various azo and triphenyl methane dyes. The bacterium reduces molybdate to molybdenum blue (Mo-blue) optimally at pH 6.0, and temperatures of between 25 and 40oC. Glucose was the best electron donor for supporting molybdate reduction followed by sucrose, trehalose, maltose, d-sorbitol, d-mannitol, d-mannose, myo-inositol, glycerol and salicin in descending order. Other requirements include a phosphate concentration of between 5.0 and 7.5 mM and a molybdate concentration between 10 and 20 mM. The absorption spectrum of the Mo-blue produced was similar to previous Mo-reducing bacterium, and closely resembles a reduced phosphomolybdate. Molybdenum reduction was inhibited bycopper, silver and mercury at 2 ppm by 43.8%, 42.3% and 41.7%, respectively. We screen for the ability of the bacterium to decolorize various dyes. The bacterium was able to decolorize the dye Congo Red. Biochemical analysis resulted in a tentative identification of the bacterium as Serratia marcescens strain Neni-1. The ability of this bacterium to detoxify molybdenum and decolorize azo dye makes this bacteriuman important tool for bioremediation

Effects of burrowing mud lobsters (Thalassina anomala Herbst 1804) on soil macro- and micronutrients in a Malaysian mangrove

The mud lobster, genus Thalassina is the least studied taxon compared to other mud crabs within Thalassinidae family. Burrowing thalassinid populations are considered to be an effective means of bioturbation, affecting the macro- and micronutrient properties in the substrates they occur in through nutrient redistribution. This study assessed the combined effects of fresh mud excavation and old mud deposition on soil turnover and vertical marconutrients including NH4–N, NO3–N, P, K, S, Na, Ca, and Mg and micronutrients including Fe, Cu, Zn and Mn distributions in a Malaysian mangrove, Sibuti Wildlife Sanctuary, Sarawak. The mud lobster Thalassina anomala (Decapoda: Thalassinidae) inhabits and builds mounds both seafront and inland mangroves. Their burrowing activities increased NH4–N, NO3–N, P, and Na concentrations in fresh mud and Fe, Cu and Zn concentrations in the old mud. The nutrient concentrations in excavated soils were greatly affected by habitat type, and depth. Burrowing processes can effectively turnover subsurface soil to the surface, which acidifies strongly upon oxidation. Higher S content in mud lobster soil together with low pH revealed mud lobsters play a strong role in the development of acidity in the study areas. These processes could stimulate formation of acid sulphate soil in the mangroves. Therefore, bioturbation not only affects soil physical and chemical properties but also ecological functions of mangroves, and needs proper attention during restoration and reclamation programs of mangrove forests

A Microsatellite Guided Insight into the Genetic Status of Adi, an Isolated Hunting-Gathering Tribe of Northeast India

Tibeto-Burman populations of India provide an insight into the peopling of India and aid in understanding their genetic relationship with populations of East, South and Southeast Asia. The study investigates the genetic status of one such Tibeto-Burman group, Adi of Arunachal Pradesh based on 15 autosomal microsatellite markers. Further the study examines, based on 9 common microsatellite loci, the genetic relationship of Adi with 16 other Tibeto-Burman speakers of India and 28 neighboring populations of East and Southeast Asia. Overall, the results support the recent formation of the Adi sub-tribes from a putative ancestral group and reveal that geographic contiguity is a major influencing factor of the genetic affinity among the Tibeto-Burman populations of India

An Experimental Study Of Combinational Logic Circuit Minimization Using Firefly Algorithm

Combinatorial logic circuit minimization is usualy done using Karnaugh’s Map or Bolean equation. This paper presents an aplication of Firefly Algorithm to design combinational logic circuit in which the objective function is to minimize the total number of gates used. Then, the algorithm is benchmarked with other literatures. Result indicates that it able to find optimal solution but further analysis is required for a more complex combinatorial ogic circuit minimizatio

Can ensemble techniques improve coral reef habitat classification accuracy using multispectral data?

Remote sensing has potential in studies of the benthic habitat and extracting the reflectance from the data of multispectral sensors, but traditional image classification techniques cannot provide coral habitat maps with adequate accuracy. This study tested five traditional and three ensemble classification techniques on QuickBird for mapping the benthic composition of coral reefs on the Lang Tengah Island (Malaysia). The common techniques, minimum distance, maximum likelihood, K-nearest neighbour, Fisher and parallelepiped techniques were compared with ensemble classifiers, such as majority voting (MV), simple averaging, and mode combination. The per-class accuracy of the habitat detection improved in the ensemble classifiers; in particular, the MV classifier achieved 95%, 65%, 75% and 95% accuracies for coral, sparse coral, coral rubble and sand, respectively. Ensembles increased the accuracy of the habitat mapping classification by 28%, relative to conventional techniques. Thus, the ensemble techniques can be preferred over the traditional for benthic habitat mapping

Experimental studies of engine single cylinder run on diesel-biodiesel-butanol blends

Biodiesel and butanol are excellent additive fuels, especially for diesel fuel. Many studies in the literature report that biodiesel-butanol with various ratios is applied to diesel engines. In this experiment, diesel engines operated using biodiesel-butanol blend in low proportions 5-5%, 5-10% 10-5%, 10-10%, 15-5% and 15-10% mixed with pure diesel, and the blend is characterized. This blend of fuels can be represented as B5Bu5, B5Bu10, B10B5, B10Bu10, B15Bu5 and B15B10 with a numeric number in the fuel blends. This fuel blend is used as test fuel which is operated on a single cylinder diesel engine, four steps, direct injection (DI) at a constant speed of 1200 rpm and engine load of 25% and 50%. The combustion characteristics, performance and engine emissions are analyzed and evaluated by comparing each load and the speed of the engine being operated. Furthermore, fuel additives with pure diesel are needed to check emissions from the engine when the engine is run with a blend of diesel-biodiesel-butanol fuel. Among the six fuel blends samples examined in this experiment, better performance was shown in the B5B10 blend and produced fewer emissions. The results of the whole experiment are presented in full in this paper

Coral habitat mapping: a comparison between maximum likelihood, Bayesian and Dempster–Shafer classifiers

This study deals with the mixed-pixel problem of detecting benthic habitat class membership and evaluates two soft classifiers for coral habitat mapping on Lang Tengah island (Malaysia). A comparison was made between the Bayesian and Dempster–Shafer (D–S) with a traditional maximum likelihood (ML). The heterogeneous pattern of reef environment, established by field observation, four classes of coral habitats containing various combinations of live coral, dead coral with algae, rubble coral and sand. Posterior probability and belief maps, generated by Bayesian and D–S, respectively, were evaluated by visual inspection and final coral habitat distribution maps were validated via accuracy assessment estimates. The accuracy validation tests agreed with the visual inspection of the probability, uncertainty and coral distribution maps. The Bayesian algorithm performed better, with a 34.7–68.5% improvement in accuracy compared to D–S and ML, respectively. Probability maps demonstrate the advantages of the soft classifier over the hard classifier for coral mapping

A holistic approach to manta ray conservation in the Papuan Bird’s Head Seascape: Resounding success, ongoing challenges

Despite a precipitous decline in global populations of sharks and rays over the past fifty years due to overfishing, and increasing concerns over the conservation status of manta and devil rays worldwide, manta ray populations in Raja Ampat in the Papuan Bird’s Head Seascape of Indonesia are seemingly thriving. Reef manta rays (Mobula alfredi) in particular are abundant and have higher rates of pregnancy than have been recorded elsewhere in the Indo-Pacific, and have demonstrated a significant population increase over the past decade of monitoring. Here we document two decades’ of conservation efforts in the Bird’s Head Seascape (BHS) which, when considered in their entirety, represent an organically-developed, holistic approach to manta ray conservation that has demonstrated compelling evidence of success despite ongoing challenges. We provide detailed insights on the adaptive, continuously evolving approach used for manta ray conservation in the BHS in order that this approach might inform similar efforts towards elasmobranch conservation in other areas of the developing tropics

Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: research protocol of a case-control study design

Background: Alzheimer’s disease (AD) is a major neurocognitive disorder identified by memory loss and a significant cognitive decline based on previous level of performance in one or more cognitive domains that interferes in the independence of everyday activities. The accuracy of imaging helps to identify the neuropathological features that differentiate AD from its common precursor, mild cognitive impairment (MCI). Identification of early signs will aid in risk stratification of disease and ensures proper management is instituted to reduce the morbidity and mortality associated with AD. Magnetic resonance imaging (MRI) using structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy ( 1 H-MRS) performed alone is inadequate. Thus, the combination of multiparametric MRI is proposed to increase the accuracy of diagnosing MCI and AD when compared to elderly healthy controls. Methods: This protocol describes a non-interventional case control study. The AD and MCI patients and the healthy elderly controls will undergo multi-parametric MRI. The protocol consists of sMRI, fMRI, DTI, and single-voxel proton MRS sequences. An eco-planar imaging (EPI) will be used to perform resting-state fMRI sequence. The structural images will be analysed using Computational Anatomy Toolbox-12, functional images will be analysed using Statistical Parametric Mapping-12, DPABI (Data Processing & Analysis for Brain Imaging), and Conn software, while DTI and 1 H-MRS will be analysed using the FSL (FMRIB’s Software Library) and Tarquin respectively. Correlation of the MRI results and the data acquired from the APOE genotyping, neuropsychological evaluations (i.e. Montreal Cognitive Assessment [MoCA], and Mini–Mental State Examination [MMSE] scores) will be performed. The imaging results will also be correlated with the sociodemographic factors. The diagnosis of AD and MCI will be standardized and based on the DSM-5 criteria and the neuropsychological scores. Discussion: The combination of sMRI, fMRI, DTI, and MRS sequences can provide information on the anatomical and functional changes in the brain such as regional grey matter volume atrophy, impaired functional connectivity among brain regions, and decreased metabolite levels specifically at the posterior cingulate cortex/precuneus. The combination of multiparametric MRI sequences can be used to stratify the management of MCI and AD patients. Accurate imaging can decide on the frequency of follow-up at memory clinics and select classifiers for machine learning that may aid in the disease identification and prognostication. Reliable and consistent quantification, using standardised protocols, are crucial to establish an optimal diagnostic capability in the early detection of Alzheimer’s disease

Design, Operation and Optimization of Constructed Wetland for Removal of Pollutant

Constructed wetlands (CWs) are affordable and reliable green technologies for the treatment of various types of wastewater. Compared to conventional treatment systems, CWs offer an environmentally friendly approach, are low cost, have fewer operational and maintenance requirements, and have a high potential for being applied in developing countries, particularly in small rural communities. However, the sustainable management and successful application of these systems remain a challenge. Therefore, after briefly providing basic information on wetlands and summarizing the classification and use of current CWs, this study aims to provide and inspire sustainable solutions for the performance and application of CWs by giving a comprehensive review of CWs’ application and the recent development of their sustainable design, operation, and optimization for wastewater treatment. To accomplish this objective, thee design and management parameters of CWs, including macrophyte species, media types, water level, hydraulic retention time (HRT), and hydraulic loading rate (HLR), are discussed. Besides these, future research on improving the stability and sustainability of CWs are highlighted. This article provides a tool for researchers and decision-makers for using CWs to treat wastewater in a particular area. This paper presents an aid for informed analysis, decision-making, and communication. The review indicates that major advances in the design, operation, and optimization of CWs have greatly increased contaminant removal efficiencies, and the sustainable application of this treatment system has also been improved