bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wave runup and overtopping on smooth-slope NEXC block
Authors: Benson’ YA , Wahab A K Abd , Othman I K , Jamal M H , Desa S Mat , Lee H L , Noh M N Md 
Published: November 2021

Abstract
Constant wave runup and overtopping during monsoon coupled with storm-surge events have poses threat to the coastal’s community in flooding and land loss. The study was to further the research on the wave interaction issue using the modified NAHRIM Coastal Protection and Expansion (NEXC) block. The aim was to determine the significant relationship prediction model from the experiment variables due to water level changes. The study was conducted in 30 m long, 2 m height, and 1.5 m width of wave flume using gamma 3.30 of wave height JONSWAP spectrum under 1:15 and 1:8 mobile bed scenarios. Parameters were downscaled to 1:10 and based on Peninsular Malaysia’s east coast hydrodynamics conditions. 36 different test scenarios were simulated every 20 minutes with three repetitions, enables 108 samples to be retrieved. Using statistical tools, correlation tests between the variables in the experiment results indicates wave runup, significant wave height and overtopping discharges are strongly correlated to the bed gradient and smooth-slope NEXC block. Changes in water level from shallow to deep, mild to steep mobile bed gradient with 30° to 60° block affect the relationship Hs-q decrease while Ru2%-q positively increase. Overtopping was not directly affected by water level but positively affected on wave runup and negatively to significant wave height. The fitted relationship design model using a General Full Factorial method was verified with 0.338069 of standard error and 98.12 % of R-square. Finally, the significant relationship predictive model was obtained to have 26 interaction terms in the model successful.
The influence of temperature and nutrient concentrations on growth rate, biomass, Chlorophyll-a, and biochemical compositions of Tetraselmis suecica (Chlorophyta)
Authors: Sas A A , Turki A J , Affan A , Al-Taisan W A , Das S K , Su S N , Cob Z C 
Published: November 2021

Abstract
Microalgae have been got high attention due to its potentiality in aquaculture as live feed, and in industries as ingredients for pharmaceutical, cosmetics, and biofuel industries. The objective of this study was to know the optimum culture condition for profuse growth and biochemical composition of Tetraselmis suecica under two parameters: temperature (20°C, 25°C, and 30°C) and modified F/2 medium nutrients concentrations. Culture of group “A” 20°C was categorized as A1 (F/2 stock solution-A; 0.50 ml. L-1 and F/2 stock solution-B; 0.20 ml. L-1), A2 (F/2 stock solution-A; 1. 00 ml L-1 and F/2 stock solution-B; 0.40 ml. L-1) and A3 (F/2 stock solution-A;1.50 ml. L-1 and F/2 stock solution-B; 0.60 ml. L-1). Cultures in 25°C and 30°C were also categorized as groups “B” 25° C (B1, B2, and B3) and “C” 30°C (C1, C2, and C3), respectively. The culture was done for 2 weeks with L:D cycle of 12:12 by using fluorescent light. The highest biomass production was 0.80, 0.64, and 0.45 gL-1 in C2, B3, and A3, respectively. Biochemical analysis showed that protein; 21.92, 20.83, and 18.68 %, lipid; 10.76, 9.42, and 11.71 %, carbohydrate; 38.51, 37.78, and 41.49 %, ash; 15.89, 15.61, and 13.7 %, and moisture; 14.26, 15.02, and 14.42 % in biomass grown of “A”, “B” and “C” culture group, respectively. From the study, it could be said that T. suecic is a eurythermal and mesotrophic habitant microalga which produce high protein and high carbohydrate in low and high temperature, respectively.
A case study on water price calculation of key projects at Fenglinwan irrigation areas in JiangXi Province, China
Authors: Tan Linlu , Zhu Xiaoming , Liu Xiaoping , Wan Yiguo , Fitri Arniza , Melinda Siska 
Published: November 2021

Abstract
Reasonable water price plays an important role in the healthy operation of an irrigation area. This study evaluates the current operation and management of Fenglinwan irrigation area in JiangXi Province, including implementation of agricultural water price, employee salary, current comprehensive agricultural water price and investment of engineering facilities. The cost of agricultural water supply of key project in irrigation area and the total cost of irrigation area were calculated to measure the agricultural water price. The result shows that the cost which has been spent for operation and maintenance of irrigation area was about 3.76 million yuan per year and the total cost for irrigation area was about 5.33 million yuan per year. The excessive number of employees and low wage level have greatly affected the work enthusiasm of employees. The cost of engineering maintenance was too small to guarantee the good operation of irrigation and water conservancy projects. The current implementation of agricultural water price which is about 20 yuan per mu is lower than the evaluated operation and maintenance cost for agricultural water supply which is 71.13 yuan per mu. A part of that, the current comprehensive agricultural water price which is 49.20 yuan per mu is also lower than the whole cost for agricultural water supply which is about 100.87 yuan per mu. Neither the current implementation of agricultural water price nor the current comprehensive agricultural water price can meet the basic requirements of operation and management.
Study of the effect of climate variation on irrigated and rainfed rice productivity based on aquacrop crop modelling simulation (Case Study of Java Island)
Authors: Aprilina K , Susandi A , Sopaheluwakan A , Harsa H 
Published: November 2021

Abstract
Aquacrop is free-licensed Food and Agricultural Organization’s crop modelling that requires minimum inputs of climate variables namely rainfall, maximum temperature, minimum temperature variables and geographic information of the area to be simulated (longitude, latitude, altitude). This study aims to measure the difference in irrigated and rainfed rice productivity from the Aquacrop crop modelling simulation to the influence of climate pattern variations in Java Island, Indonesia. The k-means clustering method applied to the rainfall, maximum, and minimum temperature variables from the bias-corrected MERRA2 data resulted in two climate regions. The principal component analysis result showed that the maximum and minimum temperature variables are the variables that most contribute to the determination of the clustering area using the k-means method compared to the rainfall variable. This study has calculated the probability of the irrigated and rainfed rice productivity resulting from the Aquacrop simulation in those climate regions during La Nina [El Nino] years that will be higher [smaller] than the mean value of rice productivity during neutral years. However, the validation between the actual irrigated and rainfed rice productivity with the Aquacrop simulation results from 2001-2014 showed low correlation values that vary between negative and positive values in all climate regions. Meanwhile, the validation on the El Nino composite years generally showed positive correlation values. In addition, the neutral and La Nina composite years resulted in varying correlation values between negative and positive correlation.
Analyzing canopy height variations in secondary tropical forests of Malaysia using NASA GEDI
Authors: Adrah E , Mohd Jaafar W S Wan , Bajaj S , Omar H , Leite R V , Silva C A , Cardil A , Mohan M 
Published: November 2021

AbstractTropical forests play a significant role in regulating the average global atmospheric temperature encompassing 25 % of the carbon present in the terrestrial biosphere. However, the rapid change in climate, arising from unsustainable human practices, can significantly affect their carbon uptake capability in the future. For understanding these deviations, it is important to identify and quantify the large-scale canopy height variations arising from previous anthropogenic disturbances. With the advent of NASA GEDI spaceborne LiDAR (light detection and ranging), it is now possible to acquire three-dimensional vertical structural data of forests globally. In this study, we evaluate the applicability of GEDI for analyzing relative canopy height variations of secondary tropical forests of different age groups located across multiple geographical regions of peninsular Malaysia. The results for RH98 GEDI metric trends for the lowland and hill forests category across 4 different disturbance groups show a positive correlation between mean relative height and secondary forest ages. The consistency of these findings with previous studies in the region indicate the usefulness of GEDI to provide valuable insights into the patterns and drivers of forest height variation. Thus, this study contributes toward the operationalization of spaceborne LiDAR technology for monitoring forest disturbances and measuring biomass recovery rates and should help support large-scale sustainable forest management initiatives with respect to the tropical forests of Malaysia.
Effect of different heating rate on properties of fired brick produced from industrial waste and natural clay
Authors: Hamid N J A , Kadir A A , Hashar N N H , Hashim A A , Sarani N A , Hassan M I H 
Published: November 2021

Abstract
Gypsum waste is generated from the wastewater treatment plant activities from chemical industry. The environmental issues and secured landfill costs caused by this waste increasing every year. Therefore, this study is an attempted to reuse gypsum waste as a substitution material for natural clay in fired brick production. This study consisted of two stages where in the first stage, fired brick were produced from natural clay and gypsum waste with substitution of clay with 5%, 10%, 15% and 20% gypsum waste. The second stage was the investigation of the experimental when the brick samples were fired at different heating rates (1 °C/min, 2 °C/min and 3 °C/min). Next, the shrinkage, dry density, water absorption and compressive strength for each sample were examined and were compared to the control brick. Based on the results, the shrinkage and water absorption increased with the addition of gypsum waste in brick samples. In contrast, the density and compressive strength values were decreased in the brick samples containing gypsum waste. The mechanical properties met the conditions prescribed in the specified standards for all the samples and the optimization result showed that up to 10% of gypsum waste incorporation into fired brick (fired at 1°C/min heating rate) had a sufficient compressive strength over 20 MPa. The reclamation of gypsum waste was proved for the fired brick production insights reducing the environmental pollution. Gypsum waste can be used as a natural clay substitution whilst fulfilling the demand for fired brick requisition.
Water Quality of Rooftop Rainwater Harvesting System (MyRAWAS)
Authors: Nizam N U M , Hanafiah M M , Mokhtar M B , Jalal N A 
Published: November 2021

Abstract
Prolonged drought, population growth and water demand for various purposes have increased the water scarcity issue. To overcome this issue, a rainwater harvesting system can be utilized as an alternative for clean water supply. A rainwater harvesting system is a method of collecting rainwater from man-made surfaces such as rooftops and constructed surfaces and can be used for various sectors including household, agricultural and commercial. This study was conducted to determine the quality of rainwater harvested collected directly from rooftop. The quality of the rooftop rainwater was taken in three consecutive months and the water quality for before and after treatment was measured and compared. Commercial activated carbon was used to treat the rainwater obtained from the rooftop. The water quality was compared with the Water Quality Index (WQI) and the National Water Quality Standards (NWQS). The parameters involved are pH, temperature, conductivity, dissolved oxygen (DO), total suspended solids (TSS), ammoniacal nitrogen (NH3-N), biochemical oxygen demand (BOD), chemical oxygen demand (COD),E.coli and total coliform bacteria. The results showed that the total value of WQI before and after treatment was 86.3 ± 8.963 and 87.6±2.081, respectively. Positive correlations were found for parameter NH3-N, COD and pH, while paired T-test showed a significant in the COD and the presence of bacteria. Total Coliform is still at a safe level by NWQS with the average value and the standard deviation for before and after treatment were 38.11 ± 13.960 cfu/ml and 10.33 ± 6.671 cfu/ml, respectively.
Comparative response of Malaysian weedy rice (Oryza sativa) initial growth towards the allelopathic potential of Leucaena leucocephala (Lam.) de Wit and Dicranopteris linearis (Burm. f.) Underw
Authors: Ishak M S , Iberahim Z , Mardiana-Jansar K 
Published: November 2021

Abstract
The infestation of weedy rice has becoming a threat which leads to competition between weedy rice and commercial rice for nutrient uptake. Weedy rice management is more dependent on the herbicides application that can contribute to various environmental problems. Thus, this study was conducted to assess the allelopathic potential of two invasive plants namely L. leucocephala and D. linearis in controlling the growth of weedy rice. The allelopathic potential was evaluated through laboratory bioassay namely the dish pack method, sandwich method and plant box method to determine the allelopathic potential on the seedling growth of two weedy rice variants collected in Peninsular Malaysia (designated as WRE and WRN) and MR220 CL2 rice variety. Highest concentration of L. leucocephala leaf litter (50 mg) inhibited the radicle elongation of MR220 CL2, WRN and WRE by 49 %, 51 % and 83 % compared to control, respectively. Through the dish pack method, the volatile compound from D. linearis leaf were found to disrupt the radicle growth of MR220 CL2, WRN and WRE by 21 %, 29 % and 25 % of the control at the nearest distance (41 mm) of the bioassay plants with the D. linearis leaf. Compared with D. linearis, the root exudate from L. leucocephala exhibited higher inhibitory effect towards the bioassay species. Overall, the findings from this study showed that the allelopathic potential of L. leucocephala was more preferable to be investigated further for sustainable weedy rice management in the future by infusing the biological approach.
Parameter estimation and hypothesis testing of geographically and temporally weighted bivariate Gamma regression model
Authors: Wasani Desy , Purhadi  , Sutikno  
Published: November 2021

Abstract
Geographically Weighted Regression (GWR) study potential relationships in regression models that distinguish geographic spaces using non-stationary parameters to overcome spatial effects. The use of gamma regression, namely regression with the dependent variable with a gamma distribution, can be an alternative if the data do not follow a normal distribution. Gamma distribution is a continuous set of non-negative values, generally skewed to the right or positive skewness. Gamma regression is developed to be Bivariate Gamma Regression (BGR) when there are two dependent variables with gamma distribution. If the observation units are location points, spatial effects may occur. The Geographically Weighted Bivariate Gamma Regression (GWBGR) model can be a solution for spatial heterogeneity. However, during its development, many cases require information from panel data. Using panel data can provide complete information because it covers several periods, but it allows for temporal effects. This study developed a Geographically and Temporally Weighted Bivariate Gamma Regression (GTWBGR) model to handle spatial and temporal heterogeneity simultaneously. The estimation of the GTWBGR model parameters uses the Maximum Likelihood Estimation (MLE) method that followed by the numerical iteration of Berndt Hall Hall Hausman (BHHH). The simultaneous testing uses the Maximum Likelihood Ratio Test (MLRT) method to get a test statistic. With a large sample size, the distribution of the test statistic approaches chi-square. Meanwhile, partial testing uses the Z test statistic.
Mixed estimator of spline truncated, Fourier series, and kernel in biresponse semiparametric regression model
Authors: Husain Hartina , Budiantara I N , Zain Ismaini 
Published: November 2021

Abstract
Regression analysis is a method of analysis to determine the relationship between the response and the predictor variables. There are three approaches in regression analysis, namely the parametric, nonparametric, and semiparametric approaches. Biresponse Semiparametric regression model is a regression model that uses a combination approach between parametric and nonparametric components, where two response variables are correlated with each other. For data cases with several predictor variables, different estimation technique approaches can be used for each variable. In this study, the parametric component is assumed to be linear. At the same time, the nonparametric part is approached using a mixture of three estimation techniques, namely, spline truncated, Fourier series, and the kernel. The unknown data pattern is assumed to follow the criteria of each of these estimation techniques. The spline is used when the data pattern tends to change at certain time intervals, the Fourier series is used when the data pattern tends to repeat itself, and the kernel is used when the data does not have a specific way. This study aims to obtain parameter estimates for the mixed semiparametric regression model of spline truncated, Fourier series, and the kernel on the biresponse data using the Weighted Least Square (WLS) method. The formed model depends on the selection of knot points, oscillation parameters, and optimal bandwidth. The best model is based on the smallest Generalized Cross Validation (GCV).
Antibacterial activity of aquatic extract of Myrtus communis leaves against Periodontitis isolated bacteria
Authors: Nayf Eman Mubdir , Salman Hamzah Abdulrhaman 
Published: November 2021

Abstract

Myrtus communis is an evergreen plant that can survive stressful environments and high-temperature seasons. Treatment using green plants was the most trended in recent years. The present study aimed to evaluate the antibacterial effects of Myrtus communis leaves against bacteria isolated from periodontitis. Fifty samples were collected from periodontitis subjects in both genders (female 32 % and male 68 %). The isolates were diagnosed by morphological characterization and biochemical tests. M. communis leaves were identified, collected, and prepared for extraction. The plant leaves were extracted using distilled water. The antibacterial susceptibility testing was performed by the well diffusion method. Antibiotics susceptibility patterns were executed using the disc diffusion method. All the isolates belonged to gram-positive bacteria. Among the isolated bacteria, 20, 18, and 12 were Lactobacillus spp., Streptococcus spp., and Staphylococcus aureus, respectively. The antibacterial susceptibility testing of M. communis extract showed a potential zone of inhibition against all the tested bacteria. Of the different concentrations, 30 mg/ml showed the highest zone of inhibition, 18.2 mm, 19.50 mm, and 30.66 mm against Streptococcus spp., Staphylococcus spp., and Lactobacillus spp. Among the tested antibiotics, ciprofloxacin and chloramphenicol exhibited the highest zone of inhibition against the tested bacteria. The aquatic extract of M. communis leaves was found to be effective against gram-positive bacteria. Further studies are warranted to investigate the active bio-compounds.
The use of entropy based fuzzy membership on weighted logistic regression for the unbalanced data
Authors: Harumeka Ajiwasesa , Purnami Santi Wulan , Rahayu Santi Puteri 
Published: November 2021

Abstract
Logistic regression is a popular and powerful classification method. The addition of ridge regularization and optimization using a combination of linear conjugate gradients and IRLS, called Truncated Regularized Iteratively Re-weighted Least Square (TR-IRLS), can outperform Support Vector Machine (SVM) in terms of processing speed, especially when applied to large data and have competitive accuracy. However, neither SVM nor TR-IRLS is good enough when applied to unbalanced data. Fuzzy Support Vector Machine (FSVM) is an SVM development for unbalanced data that adds fuzzy membership to each observation. The fuzzy membership makes the interest of each observation in the minority class higher than the majority class. Meanwhile, TR-IRLS developed into a Rare Event Weighted Logistic Regression (RE-WLR) by adding weight to logistic regression and bias correction. The weighting of the RE-WLR depends on the undersampling scheme. It allows an “information loss”. Between FSVM and RE-WLR has a similarity, the weight based only on class differences (minority or majority). Entropy Based Fuzzy Support Vector Machine (EFSVM) is a method used to accommodate the weaknesses of FSVM by considering the class certainty of class observations. As a result, EFSVM is able to improve SVM performance for unbalanced data, even beating FSVM. For this reason, we use EF on the TR-IRLS algorithm to classify large and unbalanced data, as a proposed method. This method is called Entropy-Based Fuzzy Weighted Logistic Regression (EF-WLR). This Research shows the review of EF-WLR for unbalanced data classification.
Spatiotemporal assessment of effects of leachate from landfills on groundwater in Kano Metropolis, Nigeria
Authors: Suleiman H A , Hanafiah M M 
Published: November 2021

Abstract
Improper solid waste management in Kano Metropolis, Nigeria has become a serious threat to human health and ground water quality. Groundwater monitoring should be conducted to assess the groundwater contamination, especially originated from leachate generated from the dumpsites. Most of the dumpsites are located nearby water body that subsequently affecting the quality of the water for human purposes. This study aims to investigate the relationships between different physical-chemical and biological parameters during the two seasons (dry and wet seasons) in Kano Metropolis area as well as to identify the sources of variation during the two seasons. The level of some physical-chemical and biological parameters of the groundwater (wells) and dump sites were assessed (i.e. temperature, pH, conductivity, suspended solids, turbidity, hardness colour, e-coli and coliform). Mean concentration of some physical-chemical and biological parameters except that of temperature, colour, pH and total dissolved solids were found to be above the acceptable limit of the National and International standard of drinking water quality, NESREA and WHO. The sources and variations of the samples results were tested using statistical analysis. The water samples show a considerable level of pollution. The analysis of the groundwater and that of dump sites reveals no significant difference in the parameters measured. It is therefore recommended that the water from this source should be monitored and treated properly before consumption.