Concentrations of natural and fall-out radionuclides in the offshore seawater and sediment from some parts of the Bay of Bengal, Bangladesh, were determined using a coaxial germanium detector. The average activities of (238)U, (232)Th, (40)K and (137)Cs were recorded as 31.2±5.8, 51.9±9.4, 686.4±170.5 and 0.5±0.6 Bq kg(-1) dry weight, respectively, for sediment, and 4.8±1.2, 5.4±1.2 and 39.1±8.6 Bq L(-1) for (238)U, (232)Th and (40)K, respectively, in seawater. The concentration of (137)Cs in seawater was below the detection limit. The concentration of sediment (238)U was found to be positively correlated with (232)Th ([Formula: see text], p<0.05) and (40)K (r=0.96, p<0.01), while (232)Th was positively correlated with (40)K (r=0.91, p<0.05). In sediment, the concentration of (238)U was negatively correlated (r=-0.86, p<0.05) with sea depth. In the seawater sample, the only significant relationship found was between concentration of (232)Th and water depth (r=-0.86, p<0.05). One-factor analysis of variance (ANOVA) showed that the level of radioisotope concentrations of seawater and sediment was highly significant for (238)U (F=122, df=11, p=0.01), (232)Th (F=143, df=11, p=0.01) and (40)K (F=86, df=11, p=0.01). The results showed that the level of radioactivity decreased from coast to open sea. Imminent threat due to radioactivity was not observed in these parts of the Bay of Bengal.
Potentially toxic metals pollution in the Straits of Malacca warrants the development of rapid, simple and sensitive assays. Enzyme-based assays are excellent preliminary screening tools with near real-time potential. The heavy-metal assay based on the protease ficin was optimized for mercury detection using response surface methodology. The inhibitive assay is based on ficin action on the substrate casein and residual casein is determined using the Coomassie dye-binding assay. Toxic metals strongly inhibit this hydrolysis. A central composite design (CCD) was utilized to optimize the detection of toxic metals. The results show a marked improvement for the concentration causing 50% inhibition (IC50) for mercury, silver and copper. Compared to one-factor-at-a-time (OFAT) optimization, RSM gave an improvement of IC50 (mg/L) from 0.060 (95% CI, 0.030-0.080) to 0.017 (95% CI, 0.016-0.019), from 0.098 (95% CI, 0.077-0.127) to 0.028 (95% CI, 0.022-0.037) and from 0.040 (95% CI, 0.035-0.045) to 0.023 (95% CI, 0.020-0.027), for mercury, silver and copper, respectively. A near-real time monitoring of mercury concentration in the Straits of Malacca at one location in Port Klang was carried out over a 4 h interval for a total of 24 h and validated by instrumental analysis, with the result revealing an absence of mercury pollution in the sampling site.
Matched MeSH terms: Water Pollutants, Chemical/analysis
Honey is a well-known natural sweetener and is rich in natural antioxidants that prevent the occurrence of oxidative stress, which is responsible for many human diseases. Some of the biochemical compounds in honey that contribute to this property are vitamins and phenolic compounds such as phenolic acids and flavonoids. However, the extent to which these molecules contribute towards the antioxidant capacity in vitro is inconsistently reported, especially with the different analytical methods used, as well as other extrinsic factors that influence these molecules' availability. Therefore, by reviewing recently published works correlating the vitamin, total phenolic, and flavonoid content in honey with its antioxidant activities in vitro, this paper will establish a relationship between these parameters. Based on the literature, vitamins do not contribute to honey's antioxidant capacity; however, the content of phenolic acids and flavonoids has an impact on honey's antioxidant activity.
Mass valuation of properties is important for purposes like property tax, price indices construction, and understanding market dynamics. There are several ways that the mass valuation can be carried out. This paper reviews the conventional MRA and several other advanced methods such as SAR, Kriging, GWR, and MWR. SAR and Kriging are good for modeling spatial dependence while GWR and MWR are good for modeling spatial heterogeneity. The difference between SAR and Kriging is the calculation of weights. Kriging weights are based on the spatial dependence or so called the semi-variogram analysis of the price data whereas the weights in SAR are based on the spatial contiguity between the sample data. MWR and GWR are special types of regression where study region is subdivided into local sections to increase the accuracy of prediction through neutralizing the heterogeneity of autocorrelations. MWR assigns equal weights for observations within a window while GWR uses distance decay functions. The merits and drawbacks of each method are discussed.
Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimized. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.
Postural movements potentially affect aiming stability in archery, thus contributing to chances of inconsistent hits. According to the expertisenovice paradigm, the factor that sets winners apart from ordinary athletes is the former’s ability to control minute changes in their performance. The
present study seeks to determine the relationship between postural sway and shooting performance amongst Malaysian skilled recurve archers. Twenty one skilled Malaysian archers participated in this study, where performance level was measured by rank tournaments International Archery Federation (FITA) score. Postural sway was assessed in terms of anterior deviation (positive value) and posterior deviation (negative value) using ZEPHYR Bio-Harness. Postural sway was analysed at the following three phases; (i) setup, (ii) aiming, and (iii) release. Participants shot 12 arrows to a 30-meter target. Data yielded a significant relationship between postural sway and shooting performance. The correlation coefficients between shooting performance and postural sway value for skilled archers ranged between (r = -0.021 to 0.248) with the highest correlation recorded at the release phase, with the lowest at the aiming phase. The setup phase showed the only anterior deviation throughout the test. During the setup and release phases, correlation between postural sway with shooting performance was significantly noted (p < 0.001). Multiple regression analysis showed that postural sway during the setup and release phases were the significant indicators for shooting performance, accounting approximately 17% and 24% of the variances respectively. In sum, the results indicate that reducing postural sway
during the release phase can increase shooting performance of skilled archery athletes, thus establishing a significant relationship between the postural sway value with shooting performance of skilled archers.
Black jelly mushroom (Auricularia polytricha) is a well-known Chinese traditional food that has therapeutic effects. This study evaluated the effects of different cooking methods (boiling, steaming, microwaving, and stir-frying) on the physicochemical characteristics (i.e., total phenolic content, antioxidants, α,α-diphenyl-β-picryl-hydrazyl [DPPH] free radical scavenging, and ferric reducing antioxidant power [FRAP]) along with color, texture, moisture, and sensory properties of black jelly mushrooms. Lightness (L*) was significantly lower for the stir-frying method (29.93) compared to the control (34.62). Stir-fried mushrooms had significantly lower firmness force (texture) and moisture content (80.13 N and 61.98%, respectively) compared to the control (2000.37 N and 86.52%). The steaming method contributed significantly higher total phenolic content (11.23 mg gallic acid equivalents/g) and antioxidant activity measured using the FRAP (33.54 mg Trolox equivalents/g) and DPPH (90.41% inhibition) assays compared to the respective controls.
Palm oil production has increased significantly, specifically in Indonesia and Malaysia. However, this growth has raised environmental concerns due to the high discharge of empty fruit bunches, palm oil mill effluents, and other solid wastes. Therefore, this study aims to examine the treatment of palm oil waste by composting and systematically review insights into its application through a systematic literature review approach. Among the 1155 articles, a total of 135 were selected for a systematic review of palm oil waste management developments and their applications, while 14 were used for determining compost quality according to the criteria and requirements established in the systematic literature review. Moreover, using Egger's test, JAMOVI 1.6.23 software was used to analyze random effects models with 95% confidence intervals and publication bias. The results showed that palm oil waste was optimally treated by composting, which is considered as a sustainable technology for protecting the environment, human safety, and economic value. The in-vessel method with a controlled composting chamber is the best system with a minimum time of 14 days. However, it requires tight control and provides a final product with a high microbial colony form outdoors and indoors compared to the windrow system. This study is useful to see the bias of research results and helps to find new studies that need to be developed, especially in this case related to the management of palm oil waste into organic compost fertilizer and its application methods in the field. It is suggested that applying palm oil waste or compost is mainly performed by mulching. In contrast, new challenges for better processing to produce organic fertilizers and applicable technologies for sustainable waste management are recommended. The method must be affordable, efficient, and practical, combining compost quality with maximum nutrient recovery.
This study describes two novel species of marine dinophytes in the genus Alexandrium. Morphological characteristics and phylogenetic analyses support the placement of the new taxa, herein designated as Alexandrium limii sp. nov. and A. ogatae sp. nov. Alexandrium limii, a species closely related to A. taylorii, is distinguished by having a shorter 2'/4' suture length, narrower plates 1' and 6'', with larger length: width ratios, and by the position of the ventral pore (Vp). Alexandrium ogatae is distinguishable with its metasert plate 1' having almost parallel lateral margins, and by lacking a Vp. Production of paralytic shellfish toxins (PSTs), cycloimines, and goniodomins (GDs) in clonal cultures of A. ogatae, A. limii, and A. taylorii were examined analytically and the results showed that all strains contained GDs, with GDA as major variants (6-14 pg cell-1) for all strains except the Japanese strain of A. limii, which exclusively had a desmethyl variant of GDA (1.4-7.3 pg cell-1). None of the strains contained detectable levels of PSTs and cycloimines.
Food adulteration and illegal supplementations have always been one of the major problems in the world. The threat of food adulteration to the health of consumers cannot be ignored. Food of questionable origin causes economic losses to consumers, but the potential health risks cannot be ignored. However, the traditional detection methods are time-consuming and complex. This review mainly discusses the types of adulteration and technologies used to detect adulteration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is also emphasized in the detection of adulteration and authenticity of origin analysis of various types of food (milk, meat, edible oil, etc.), and the future application direction and feasibility of this technology are analyzed. On this basis, MALDI-TOF MS was compared with other detection methods, highlighting the advantages of this technology in the detection of food adulteration. The future development prospect and direction of this technology are also emphasized.
The halal status of meat products is an important factor being considered by many parties, especially Muslims. Analytical methods that have good specificity for the authentication of halal meat products are important as quality assurance to consumers. Metabolomic and lipidomic are two useful strategies in distinguishing halal and non-halal meat. Metabolomic and lipidomic analysis produce a large amount of data, thus chemometrics are needed to interpret and simplify the analytical data to ease understanding. This review explored the published literature indexed in PubMed, Scopus, and Google Scholar on the application of chemometrics as a tool in handling the large amount of data generated from metabolomic and lipidomic studies specifically in the halal authentication of meat products. The type of chemometric methods used is described and the efficiency of time in distinguishing the halal and non-halal meat products using chemometrics methods such as PCA, HCA, PLS-DA, and OPLS-DA is discussed.
Partial least squares discriminant analysis (PLS-DA) is a well-known technique for feature extraction and discriminant analysis in chemometrics. Despite its popularity, it has been observed that PLS-DA does not automatically lead to extraction of relevant features. Feature learning and extraction depends on how well the discriminant subspace is captured. In this paper, discriminant subspace learning of chemical data is discussed from the perspective of PLS-DA and a recent extension of PLS-DA, which is known as the locality preserving partial least squares discriminant analysis (LPPLS-DA). The objective is twofold: (a) to introduce the LPPLS-DA algorithm to the chemometrics community and (b) to demonstrate the superior discrimination capabilities of LPPLS-DA and how it can be a powerful alternative to PLS-DA. Four chemical data sets are used: three spectroscopic data sets and one that contains compositional data. Comparative performances are measured based on discrimination and classification of these data sets. To compare the classification performances, the data samples are projected onto the PLS-DA and LPPLS-DA subspaces, and classification of the projected samples into one of the different groups (classes) is done using the nearest-neighbor classifier. We also compare the two techniques in data visualization (discrimination) task. The ability of LPPLS-DA to group samples from the same class while at the same time maximizing the between-class separation is clearly shown in our results. In comparison with PLS-DA, separation of data in the projected LPPLS-DA subspace is more well defined.
The aim of semivariogram modeling is to infer the structure of spatial continuity of the measurements. Practical experiences show that semivariogram modeling is an important step in spatial interpolation. The usual empirical semivariogram is sensitive to extreme data and shows a noised pattern. Some robust empirical semivariogram was proposed. This paper reports the application of pairwise relative empirical semivariogram to Kamojang geothermal decline rate. Using the same data, the usual empirical semivariogram and pairwise semivariogram are compared. Comparative study shows that the empirical pairwise relative semivariogram is able to infer the structure of spatial continuity of the process.
Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). One problem associated with IT2FCM is that it tends to be sensitive to initialization conditions and therefore, fails to return global optima. This problem has been addressed by optimizing IT2FCM using Ant Colony Optimization approach. However, IT2FCM-ACO obtain clusters for the whole dataset which is not suitable for clustering large streaming datasets that may be coming continuously and evolves with time. Thus, the clusters generated will also evolve with time. Additionally, the incoming data may not be available in memory all at once because of its size. Therefore, to encounter the challenges of a large data stream environment we propose improvising IT2FCM-ACO to generate clusters incrementally. The proposed algorithm produces clusters by determining appropriate cluster centers on a certain percentage of available datasets and then the obtained cluster centroids are combined with new incoming data points to generate another set of cluster centers. The process continues until all the data are scanned. The previous data points are released from memory which reduces time and space complexity. Thus, the proposed incremental method produces data partitions comparable to IT2FCM-ACO. The performance of the proposed method is evaluated on large real-life datasets. The results obtained from several fuzzy cluster validity index measures show the enhanced performance of the proposed method over other clustering algorithms. The proposed algorithm also improves upon the run time and produces excellent speed-ups for all datasets.
In dairy product sector, butter is one of the potential sources of fat soluble vitamins, namely vitamin A, D, E, K; consequently, butter is taken into account as high valuable price from other dairy products. This fact has attracted unscrupulous market players to blind butter with other animal fats to gain economic profit. Animal fats like mutton fat (MF) are potential to be mixed with butter due to the similarity in terms of fatty acid composition. This study focused on the application of FTIR-ATR spectroscopy in conjunction with chemometrics for classification and quantification of MF as adulterant in butter. The FTIR spectral region of 3910-710 cm⁻¹ was used for classification between butter and butter blended with MF at various concentrations with the aid of discriminant analysis (DA). DA is able to classify butter and adulterated butter without any mistakenly grouped. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the frequency regions of 3910-710 cm⁻¹. The equation obtained for the relationship between actual value of MF and FTIR predicted values of MF in PLS calibration model was y = 0.998x + 1.033, with the values of coefficient of determination (R²) and root mean square error of calibration are 0.998 and 0.046% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with MF. Using 9 principal components, root mean square error of prediction (RMSEP) is 1.68% (v/v). The results showed that FTIR spectroscopy can be used for the classification and quantification of MF in butter formulation for verification purposes.