Highest Similarity Index Research Articles

Boosting Magnetic Resonance Image Denoising With Generative Adversarial Networks

Denoising plays an important role in the Magnetic Resonance Imaging (MRI) applications for medical diagnosis. MRI images usually contain undesired noises which would negatively affect the exactitude of pathological diagnosis. Recently, many models for MRI denoising have been developed from deep learning networks. In this paper, we propose a novel MRI image denoising method using the conditional Generative Adversarial Networks (GANs). Specifically, a Convolutional Neural Network (CNN) is utilized as the discriminator in the process to distinguish whether the image pair obtained from the conditional GAN is a real pair which consists of a noisy image and a noise-free image or a fake pair which, on the other hand, contains a noisy image and a denoised image. In our design, the convolutional encoder-decoder networks-based generator is used to remove the noise in the noisy MRI images as much as possible. The whole architecture is trained by adversarial learning. Experiments using both synthetic and real clinical MRI datasets are conducted. When tested on the synthetic T1w images with 10% noise level, our method performed better in terms of reaching a high structural similarity index (SSIM) at 0.9489 while that of the next best method was only 0.7485. Moreover, when the image noise level was increased from 1% to 10%, our method was more stable that the SSIM only dropped about 3.2% while that of the next best method dropped about 23.7%. Simulation results demonstrate that the proposed method is more robust and outperforms the conventional methods in both the denoising level and preservation of the anatomical structures and defined contrast.

U-ASD Net: Supervised Crowd Counting Based on Semantic Segmentation and Adaptive Scenario Discovery

Crowd counting considers one of the most significant and challenging issues in computer vision and deep learning communities, whose applications are being utilized for various tasks. While this issue is well studied, it remains an open challenge to manage perspective distortions and scale variations. How well these problems are resolved has a huge impact on predicting a high-quality crowd density map. In this study, a hybrid and modified deep neural network (U-ASD Net), based on U-Net and adaptive scenario discovery (ASD), is proposed to get precise and effective crowd counting. The U part is produced by replacing the nearest upsampling in the encoder of U-Net with max-unpooling. This modification provides a better crowd counting performance by capturing more spatial information. The max-unpooling layers upsample the feature maps based on the max locations held from the downsampling process. The ASD part is constructed with three light pathways, two of which have been learned to reflect various densities of the crowd and define the appropriate geometric configuration employing various sizes of the receptive field. The third pathway is an adaptation path, which implicitly discovers and models complex scenarios to recalibrate pathway-wise responses adaptively. ASD has no additional branches to avoid increasing the complexity. The designed model is end-to-end trainable. This integration provides an effective model to count crowds in both dense and sparse datasets. It also predicts an elevated quality density map with a high structural similarity index and a high peak signal-to-noise ratio. Several comprehensive experiments on four popular datasets for crowd counting have been carried out to demonstrate the proposed method’s promising performance compared to other state-of-the-art approaches. The proposed model achieves the lowest count error in terms of the MAE in ShanghaiTech Part A, Part B, and Mall datasets with 64.6, 7.5, and 1.8, respectively. Moreover, it achieves the lowest count error in terms of the MSE in ShanghaiTech Part B, UCF CC 50, UCSD, and Mall datasets with 12.4, 217.8, 2.1, 2.2, respectively. In addition, the proposed model accomplishes the best quality density maps on all the utilized datasets. Furthermore, a new dataset with its manual annotations, called Haramain with three different scenes and different densities, is introduced and used for evaluating the U-ASD Net.

Do medicine and cell biology talk to each other? A study of vocabulary similarities between fields.

A close interaction between basic science and applied medicine is to be expected. Therefore, it is important to measure how far apart the field of cell biology and medicine are. Our approach to estimating the distance between these fields was to compare their vocabularies and to quantify the difference in word repertoire. We compared the vocabulary of the title and abstract of articles available in PubMed in two selected high-impact journals in each field: cell biology, medicine, and translational science. Although each journal has its own editorial policy, we showed that within each field there is a small vocabulary difference between the two journals. We developed a word similarity index that can measure how much journals share a common vocabulary. We found a high similarity index between each cell biology (91%), medical (71-74%), and translational journal (65%). In contrast, the comparison between medicine and biology journals produced low correlation values (22-36%), suggesting that their vocabularies are quite dissimilar. Translational medicine journals had medium similarity values when compared to cell biology journals (52-70%) and medicine journals (27-59%). This approach was also performed in 10-year periods to evaluate the evolution of each field. Using the “onomics” strategy presented here, we observed that differences in vocabulary of basic science and medicine have been increasing over time. Since translational medicine has an intermediate vocabulary, we confirmed that translational medicine is an efficient approach to bridge this gap.

Morphological and molecular genetic diversity analysis of pearl millet (Pennisetum glaucum) maintainers and restorers

The success of any pearl millet hybrid programme depends upon the assessment of the structure of parental diversity. In this investigation, polymorphism data generated using 42 simple sequence repeat (SSR) markers and 12 agromorphological traits were used for genetic diversity assessment among 32 genotypes (29 restorers and 3 maintainers) of pearl millet [Pennisetum glaucum (L.) R. Br.].In contrast to morphological data, SSR based clustering pattern and Principal Coordinate Analysis revealed that the genotypes were found to be consistent with their pedigree and origin. Polymorphism information content (PIC) values based on microsatellites ranged from 0.117 to 0.841 per locus with an average PIC of 0.348. Allelic richness varied from two to five per locus. The highest similarity index (0.74) was observed between restorers WGI 58 and WGI 148, whereas the lowest similarity index (0.27) was observed between seed parent 841 B and PPMI 269. AMOVA analysis observed more genetic variance among the individuals than within individuals.The study led to the identification of maintainer 841 B as a genetically diverse parent from other maintainers as well as among most of the restorers and hence may be used in future hybrid development programmes. Further, the correlation between phenotypic and genetic distance matrices was observed to be very low. Appropriate heterotic combinations were identified based on morphological and molecular diversity.

An Ensemble of Feature Extraction with Whale Optimization Algorithm for Content Based Image Retrieval System

In recent days, content based image retrieval (CBIR) becomes a hot research area, which aims to determine the relevant images to the query image (QI) from the available large sized database. This paper presents an optimal hybrid feature extraction with similarity measure (OHFE-SM) for CBIR. Initially, histogram equalization of images takes place as a preprocessing step. Then, texture, shape and color features are extracted. The texture features include Gray Level Co-Occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM) is extracted, where the optimal number of features will be chosen by whale optimization algorithm (WOA). Afterwards, the shape feature extraction takes place by Crest lines and color feature extraction process will be carried out using Quaternion moments. Finally, Euclidean distance will be applied as a similarity measure to determine the distance among the feature vectors exist in the database and QI. The images with higher similarity index will be considered as relevant images and is retrieved from the database. A detailed experimental validation takes place against Corel10K dataset. The simulation results showed that the proposed OHFE-SM model has outperformed the existing methods with the higher average precision of 0.915 and recall of 0.780.

MORPHOMETRY OF BLUE LAND CRAB (CARDISOMA GUANHUMI) BURROWS: ICHNOLOGICAL CONTEXT AND PALEOENVIRONMENTAL IMPLICATIONS

ABSTRACT A large brachyuran, the blue land crab (Cardisoma guanhumiLatreille, 1825) is a keystone species and a prolific burrower in a variety of low-latitude supratidal habitats; however, few studies have addressed its ichnological aspects. Here we present a detailed morphological assessment of C. guanhumi burrows and make comparisons to Macanopsis plataniformis, a trace fossil thought to be constructed by a similar brachyuran. Using nine burrow casts from a mangrove wetland on San Salvador Island, Bahamas, 29 dimensionless morphometric parameters were compared. Results of Bray-Curtis tests show high overall similarity index (0.85) between casts, with complexity, tortuosity, and opening inclination angle having moderate to high similarity (> 0.8). End chamber angle of the blue land crab has highest similarity both within the modern morphometric parameter dataset (> 0.9) and to that of M. plataniformis (0.88). The large terminal chamber is particularly important because of its high preservation potential, as a repository for organic remains, and as a reliable water table (∼ sea-level) indicator. Cluster analysis suggests size-independent Macanopsis-resembling burrow morphology among different extant taxa can be discriminated via quantitative neoichnological methods. Our findings demonstrate how a quantitative assessment of modern burrows and their likely counterparts from the sedimentary record can help constrain tracemaker identity and aid paleoenvironmental reconstruction of low-energy microtidal settings.

Microwave Imaging of Voids in Oil Palm Trunk Applying UWB Antenna and Robust Time-Reversal Algorithm

The oil palm trees in Southeast Asia face a great challenge due to voids within tree trunks. Besides, both plantations and the palm oil industry suffered considerable losses due to ineffective inspection of defective trees. Several techniques such as ultrasound, X-ray, capacitive volume, gamma computed tomography, and microwave tomography were applied to detect and control the decay of a trunk. However, all the techniques showed substantial drawbacks (such as limited resolution, tedious processing time, and use of bulky equipment with limited mobility) except for microwave tomography which overtook the other techniques by using a method that distinguishes the dielectric properties of healthy and diseased trunks. This work proposes ultra-wide-band (UWB) signal transmission and reception using antenna sensor arrays that record reflections from affected regions in the trunk. Various factors have been considered, such as different cylindrical arrays of 4, 8, 12, and 16 antennas; different positions of hollows; a heterogeneous trunk; multiple targets; and larger trunk samples (16–30 cm). To validate the system’s capabilities, two cylindrical wood samples with different diameters of 100 mm and 140 mm and with one hollow and three hollows within are 3D-printed, investigated, and then measured. The authors recommended a robust time-reversal algorithm (RTR) to reconstruct 2D images that successfully identified and localized cavities with the smallest diameter of 3.5 mm. Furthermore, reconstructed images of measured data verified a practical and reliable oil palm trunk imaging and sensing system with a high structural similarity index and resolution.

COMPOSITION AND DIVERSITY OF NON-TIMBER FOREST PRODUCTS (NTFPs) IN BATURIYA WETLAND GAME RESERVE, JIGAWA STATE, NIGERIA

Inadequate documentation and information of Non-Timber Forest Products (NTFPs) in the study sites call for the assessment of composition and diversity of the concern products. Therefore, the aim of the study is to assess the Composition and Diversity of Non- Timber Forest Products (NTFPs) in Baturiya Wetland Game Reserve, Jigawa State, Nigeria. A four (4) transects of 1km length was laid at an interval of 400 m. Likewise, in each transect, 4 plots of 100 x 100 m was laid alternately along each transect at 200 m interval. Also four (4) quadrants of 1m x1m in size for small non-timber forest products was randomly laid in each 100 x100m plot for each of the habitats in each plot, plant stocks identified were recorded. Data collected were analysed using Simpson index, Sorenson index and descriptive statistic. Results showed that Upland area had the highest species, number of individual and diversity of Non–Timber Forest Product followed by Swampy area and Fadama area with the values of (94, 1464, D-0.981), (63, 842, D-0.970) and (60, 805, D-0.969) respectively. Upland area and Swampy area had the highest similarity index of 78.5%. The results suggest that the documentation, inventory and management of NTFPs should be addressed in operational plan to enhance its diversity

FDM: Fuzzy-Optimized Data Management Technique for Improving Big Data Analytics

Big data analytics and processing require complex architectures and sophisticated techniques for extracting useful information from the accumulated information. Visualizing the extracted data for real-time solutions is demanding in accordance with the semantics and the classification employed by the processing models. This article introduces fuzzy-optimized data management (FDM) technique for classifying and improving coalition of accumulated information based semantics and constraints. The dependency of the information is classified on the basis of the relationships modeled between the data based on the attributes. This technique segregates the considered attributes based on similarity index boundaries to process complex data in a controlled time. The performance of the proposed FDM is analyzed using a real-time weather forecast dataset consisting of sensor data (observed) and image data (captured). With this dataset, the functions of FDM such as input semantics analytics and classification based on similarity are performed. The metrics classification and processing time and similarity index are analyzed for the varying data sizes, classification instances, and dataset records. The proposed FDM is found to achieve 36.28% less processing time for varying classification instances, and 12.57% high similarity index.

An Omics Study of Iron and Zinc Homeostasis in Finger Millet: Biofortified Foods for Micronutrient Deficiency in an Era of Climate Change?

The future of food and sustainability of the staple food crops are of utmost importance in the 21st century. Micronutrient deficiency, for example, in iron and zinc, is a common cause of human diseases. Mineral content of the staple food crops has therefore crosscutting importance for food engineering and planetary health. Finger millet, a staple food of agricultural importance worldwide, is rich in iron and zinc, and an ideal model to study the prospects of biofortified foods in times of climate change. We report here a multiomics study of the iron and zinc homeostasis in the finger millet. We identified and characterized 15 candidate genes potentially involved in iron and zinc homeostasis pathways in the finger millet. Structural and functional annotation of the candidate genes revealed a high similarity index with their respective homologs (Oryza sativa, Triticum aestivum, Zea mays, Hordeum vulgare, and Setaria italica). Transcriptome-wide expression analysis showed that genes involved in uptake and translocation of iron and zinc are highly expressed in the GP-1 genotype, while those involved in bioavailability of iron and zinc are expressed more in the GP-45 genotype of the finger millet. In conclusion, finger millet, being a stress-resilient crop, utilizes a combination of strategies in iron and zinc homeostasis pathway, which appear to play an important role in food crop acquisition of iron and zinc, despite environmentally limiting conditions. These data offer molecular insights on iron and zinc accumulation and paves the way for new strategies toward staple food crop with mineral biofortification.

Diversity of Ground-Dwelling Ants (Hymenoptera: Formicidae) in Phulchowki Hill, Lalitpur, Nepal

The study assesses the diversity of ground-dwelling ants (Hymenoptera: Formicidae) in Phulchowki Hill, Lalitpur, Nepal focusing their species richness altitudinally and seasonally. Ants were sampled from June 2018 to February 2019using pitfall traps, bait traps and hand collection methods covering an altitudinal range from 1500 m to 2700 m in five selected sites (1500 m, 1800 m, 2100 m,2400 m, and 2700 m). A total of 1443 specimens representing four subfamilies, 12genera and 18 morph species were collected. Formicinae (57.58%) was recorded as the most abundant subfamily followed by Myrmicinae (38.53%), Ponerinae (2.21%) and Pseudomyrmicinae (1.66%). Camponotus was the most speciose (4morphospecies) genus and was most abundant in all seasons. The highest Similarity index (0.667) was recorded between the first and second sites among five sites. Species richness (16), Shannon diversity index (1.504) and abundance (631) were the highest in autumn. Similarly, species richness (12), Shannon diversity index (1.399) and species evenness (0.563) were recorded highest at 2100 m altitude, while species abundance (519) was maximum at 1500 m.

Detecting changes in multitemporal multispectral Landsat images using spatial frequency-based undecimated wavelet transform fusion

Changes in surface water are normally detected by extracting the water features from individual multispectral (MS) images. We present an approach based on pixel fusion of MS and panchromatic (PAN) bands of multitemporal Landsat images to detect the changes in surface water. Spatial frequency and the maximum amplitude selection-based fusion rule on multiresolution undecimated wavelet transform (UDWT) coefficients for extracting and injecting the spatial and spectral content from MS and PAN images is introduced. Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper (ETM+) of 2010 and 2000 images acquired from the US Geological Survey were fused to investigate the potential of the proposed spatial frequency-based UDWT in highlighting the changes. Various component substitution and multiresolution analysis-based fusion algorithms were also applied. It was observed that UDWT with spatial frequency effectively extracts the spectral information from MS images and the spatial information from PAN images. The performance was evaluated based on visual interpretation and spatial and spectral quality assessment metrics. A high correlation coefficient (0.9992), high contrast similarity (0.99937), high structural similarity index measure (0.9884), less relative average spectral error (23.6426), less root mean squared error (2.2256), relatively less blind referenceless image spatial quality evaluator, natural image quality evaluator, and perception-based image quality evaluator significantly support the proposed fusion technique in yielding the pansharpened image, making it more suitable for detecting the multitemporal changes in remote sensing applications.

Mangrove vegetation and bird communities around Tegal Port, Central Java, Indonesia

Abstract. Isworo S, Oetari PS. 2020. Mangrove vegetation and bird communities around Tegal Port, Central Java, Indonesia. Biodiversitas 21: 1551-1560. The ecological balance in Tegal harbor area needs to get serious attention due to the impacts of Tegal Port activities. For this purpose, the diversity of mangrove and avifauna (bird) can be used as bio-indicators of the ecological stability of the area. This study aimed to assess and analyze the diversity of plants and avifauna (birds) that live in mangrove and coastal zones around Tegal Port development area. Data collection was conducted using purposive random sampling method on two sites for vegetation and three sites for avifauna. The importance value index, Shannon-Wiener diversity index and Sorensen’s similarity index was calculated for the vegetation. For birds, we calculated the diversity and similarity index as well as identified their conservation status based on the IUCN Red List, CITES and government regulations. In terms of vegetation, Rhizophora mucronata and Avicennia marina dominate Site 2 (Tegalsari) while Casuarina equisetifolia and R. mucronata dominate Site 3 (Alam Indah Beach). Overall, the vegetation has low biodiversity index and similarity between sites is also low. For bird, there are 37 species from 18 families. Site 1 (Muara Reja) has the highest number of species with 29 species, followed by Site 2 (Tegalsari) with 25 species, and Site 3 (Alam Indah Beach) with 22 species. The three sites have moderate diversity index and there is high similarity index between sites. All bird species found in the study sites are listed as Least Concern under IUCN Red List, while there are two species protected under national protection law, i.e. Ardea alba and Glareola maldivarum. In general, the condition of mangrove vegetation around Tegal Port has low diversity. This suggests that the pressure on the environment is quite high, causing only few plant species to be able to live and dominate the ecosystem. The limited vegetation also causes birds community, especially the protected A. alba and G. maldivarum in Site 2, becomes increasingly difficult to find, because places to find food, breeding places and places to rest are disturbed.

System Analysis Approach to Visual Object Tracking

In the modern-day study of system behaviour and analysis, understanding the response of how the system will behave in a certain condition is considered vital. Thus, keeping object behaviour as the primary objective and object detection as a core instrument this project intends to identify the object and track the motion of the desired object. This paper provides an overview of how a closed-loop control-based system was designed using a camera as visual input. The video signal is analyzed to detect distinct color and shape similarities to a desired object. Based on a high similarity index the Raspberry Pi controller generates a pulse width modulation signal to regulate the angular position of the rotary actuator to align the camera frame of view according to a desired object’s position. Post system design experimentation results and potential realized system faults are expressed within the conclusion.

Sediment Geochemistry and Benthic Foraminiferal Response to Fish Farming after Conversion from a Red Laver (Seaweed) Farm

Jeong, D.U.; Lee, Y.G.; Kang, J.; Woo, H.J., and Choi, Y.H., 2020. Sediment geochemistry and benthic foraminiferal response to fish farming after conversion from a red laver (seaweed) farm. Journal of Coastal Research, 36(3), 559–574. Coconut Creek (Florida), ISSN 0749-0208.To understand the effects of biodeposits discharged from a fish farm (which was previously a red laver farm) on geochemistry of the sediment and benthic ecology, trace metals and element analyses, 210Pb dating, and benthic foraminiferal analyses were conducted on sediment cores collected below the fish farm cages. Sediment core sampling was also carried out at a control plot (160 m away) to understand the spreading of biodeposits. The geochemical effect of fish farming is pronounced. There was an increase in silt content and sedimentation fluxes of Znex (Zn in excess fractions), Cuex, Asex, and TPex (total phosphorus in excess fractions) after red laver farming. The silt content increased from 45.01% to 50.07%, with a sediment accumulation rate of ∼0.61 cm/y, on average. TPex, with 0.15% ± 0.06% on average, showed that the fish farming effects increased by 0.22% ± 0.07%. Znex, Cuex, Cdex, and Asex showed a positive relationship with TPex increase: 19.92 ± 1.79, 10.23 ± 3.99, 0.57 ± 0.19, and 0.92 ± 0.04 µg/cm2/y, respectively. The high sedimentation fluxes of Znex and Asex in the control plot may signify an expansion of influence of the fish farm by tidal currents. Seven benthic foraminifera appeared during the fish and red laver farming periods, with the dominant species being Cribroelphidium excavatum; however, they were characterized by a high similarity index of 88.1% and very low frequency of abundance, indicating bad habitat conditions. Among them, the C. excavatum–Ammonia beccarii–Ammonia ketienziensis–Cribroelphidium subarcticum assemblage ranged from 21 cm depth to the uppermost layer, characterized by increases in A. beccarii. This increase may have been caused by the accumulation of organic matter discharged from the fish farm after red laver farming, rather than from an increase in the trace metals. A. beccarii may be a species tolerant to fish farming.

Long-Term Monitoring of Parrotfish Species Composition in the Catch of Fishermen from the Spermonde Islands, South Sulawesi, Indonesia

Parrotfishes, aside from playing an important ecological role in coral reef ecosystems, are an economically important fish group exploited for human consumption. Excessive exploitation of parrotfishes could cause ecological disturbances in the coral reef ecosystem. This study aimed to examine the species composition and population dynamics of parrotfishes caught by fishermen in the Spermonde Islands, South Sulawesi, Indonesia. Parrotfishes were collected from the catches landed in Makassar Fisheries Port. Monthly samples comprised all parrotfishes landed on the sampling day. Sampling was carried out throughout 2014 and from January 2018 to May 2019. The parameters observed were the name and the number of each species. The composition and dynamics of the Parrotfishes species were analysed using the Diversity Index, Evenness Index, Dominancy Index, and Similarity Index. During the study, 6,684 parrotfishes were collected belonging to 34 species, of which 10 species had a mean sampling presence over 90%, i.e. Chlorurus bleekeri, C. capistratoides, C. sordidus, Scarus chameleon, S. flavipectoralis, S. ghobban, S. niger, S. quoyi, S. rivulatus, and S. schlegeli. Long-term monitoring of parrotfish species composition indicate that parrotfish diversity was consistently at the moderate level, indicating moderate productivity, fairly balanced ecosystem conditions, and moderate ecological pressure. Over the study period, parrotfish species were evenly distributed, no one species was really dominant, and the high Similarity Index indicated little change in species composition. These results indicate that the fishing pressure from traditional capture of parrotfishes using nets and spears has not had a serious impact on the condition of parrotfish resources.

Fish biodiversity in false gharial habitat (Tomistoma schlegelii Müller, 1838) in Labuhan Batu district

The purpose of this research was to determine the fish biodiversity in the False Gharial (Tomistoma schlegelii) habitat at Aek Kundur, Labuhanbatu District. This research was conducted from February to April 2019. The sampling locations was determined based on information from local people. Fish samples were caught using gillnets, fishing rods, and durung (trap). The sampling was done one time every month for three months at three sampling stations. The diversity index (H'), Evenness index (J') and similarity index (SI) were analyzed in this study. The results showed that the highest number of fish caught was Anumalura oxygaster (188 individuals) and the lowest number of fish was Monopterus albus (1 individual). The highest diversity index (H') value was at station 1 (2.224) and the lowest at station 2 (2.202) categorized as medium level. The evenness index value at station 1 was 0.867, station 2 was 0.856 and station 3 was 0.826, indicate the high evenness. While the highest Similarity Index (SI) was found at stations 3 and 1 (90%) and the lowest SI was recorded at stations 2 and 3 (80%). It is concluded that the diversity index value in Aek Kundur is categorized as medium level. The Evennes index value is categorized as high uniformity of population, and the fish community was in stable condition.

Molecular Identification and Evaluation of Genetic variability among Some Aflatoxigenic Aspergillus flavus Strains Isolated from Fish Feed in Egypt

AFLATOXINS are among the most potent carcinogenic, mutagenic and teratogenic natural compounds occurring in food and feed. In this study, molecular typing based on sequence variations in the ITS1-5.8S-ITS2 region was used to identify and genetically discriminate five selected strains of A. flavus, four strains (AUMC13909, AUMC13910, AUMC13911 and AUMC13917) were aflatoxigenic isolates recovered from fish feed. A. flavus AUMC10311 is a non-aflatoxigenic reference strain which was used as a negative control to investigate the molecular variability of the studied strains concerning their aflatoxigenic potential. The ITS data of the studied strains were submitted to NCBI GenBank with the accession numbers: MK491621, MK491622, MK491623, MK491624 and MK491625. Cluster analysis of these strains was performed depending on their ITS sequences, which discriminate them into three different sub-clusters. The highest genetic similarity (100%) was observed between AUMC13911 and AUMC10311. Proteins banding patterns of the examined strains were analyzed using SDS-PAGE, which resolved six polymorphic protein bands out of a total of 22 bands, ranged from 14 to 125kDa. Interestingly, a protein band (~ 40kDa) was relatively overexpressed in case of the aflatoxigenic strains while was hardly detected in the non-aflatoxigenic strain, suggesting that this protein might be involved in aflatoxin biosynthesis. Cluster analyses based on this banding pattern grouped the tested strains into two major clusters. The highest similarity index (97%) was between AUMC13911 and AUMC10311. These results confirmed the genetic variation among the examined A. flavus strains and the necessity for greater insight into cluster assembly using different Omics approaches.

Blended divergences: local food and medicinal plant uses among Arbëreshë, Occitans, and autochthonous Calabrians living in Calabria, Southern Italy

A study focusing on traditional uses of wild plants for gastronomic and medicinal purposes was carried out among three linguistic communities in Calabria, southern Italy. Ninety interviews with local elderly informants were conducted among Occitans and Arbëreshë, two linguistic minorities, and the dominant culture of autochthonous Calabrians. We recorded 85 taxa belonging to 39 botanical families and 66 different detailed use-reports including 35 culinary and 31 medicinal uses. Our overall data show the permanence of traditional ecological knowledge related to wild and semi-domesticated food and medicinal plants; however, high similarity indices among the three communities demonstrate that traditional ecological knowledge is following the pathway of homogenization and standardization toward the dominant culture, facilitated by a context of linguistic erosion, limited intergenerational transmission, and a centuries-old diffusion with Calabrian culture. Moreover, our study calls for further field surveys in isolated areas of Calabria to analyze how traditional ecological practices can be key tools in the development of local small-scale economies through the promotion of artisanal food entrepreneurship of wild food plant transformation.

How does oil palm plantation impact bird species diversity? a case study from PKWE Estate, West Kalimantan

The prospect of Indonesian palm oil industry nowadays tends positive and shows an increasing trend. This matter also caused many negative responses to the presence of environmental damage and biodiversity loss, including bird species diversity. Since there are only a few researches related to oil palm plantation impact on bird species diversity, this research is necessary to enrich the data related. Data retrieval was carried out on March 2018, in PKWE Estate, West Kalimantan, using strip transect method in six different types of habitat/land cover. Two types of land cover which are secondary forest and shrubs considered as land cover before the establishment of oil palm plantation (baseline), while the others are habitat types that exist in oil palm plantation. The result shows that both baselines have the highest number of species among all habitat types, with a total of 26 species were found in each baseline. However, as a unity, turn out that the level of bird species diversity in oil palm plantation area is higher than the baseline area, where 33 species of bird were found (Dmg = 6.98). The existence of oil palm plantation also has changed the composition of bird species, the highest similarity index with both baselines is showed by old growth of oil palm. The change of species composition caused ten birds species lost and 17 species were gained on the secondary forest cover, meanwhile, 11 species lost and 18 species were gained in shrubs.