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The Programmable Hyperspectral Seawater Scanner (PHySS) represents a significant breakthrough in monitoring harmful algal blooms (HABs), specifically targeting the "Florida red tide" caused by Karenia brevis. By utilizing a Fourth-Derivative Spectral Similarity Index (SI), this study establishes a strong positive correlation between the SI and phytoplankton counts, underscoring the PHySS's potential for early detection and effective management of HABs. Our findings suggest that the PHySS could act as a predictive tool, offering crucial lead time to mitigate the ecological and economic repercussions of blooms. However, this study also identifies certain limitations of the PHySS technology, such as its inability to differentiate among various phytoplankton species without additional physical verification of cell counts. This limitation highlights the need for a multifaceted approach to HAB management. Our research suggests that adopting a multi-modal monitoring strategy could lead to more sophisticated and effective methods for combating HABs, fostering an optimistic outlook for future advancements in this area. [ABSTRACT FROM AUTHOR]

The Pearl River Estuary (PRE), an important place provides natural spawning ground and migration channel to multiple fish species located in the northern South China Sea. Keeping in mind limited data available on the taxonomic diversity of fishes from this region, we compiled time-series data on fish species from the PRE collected since the 1980s, and analyze diversity at different taxonomic levels using an inclusion index at the taxonomic level, and indexes of taxonomic diversity. Species inventory includes 18 orders, 79 families and 167 genera. Average numbers of (families, genera, species), (genera, species), and (species) per order, family, and genus, (4.39, 9.28, 14.94), (2.11, 3.41), and (1.61) were recorded. An average taxonomic distinctness of 75.0, and variation in taxonomic distinctness 99.8 were calculated. Whereas, an average taxonomic distinctness reveals genetic relationships between PRE fish species to be closer than in the East China Sea continental shelf (65.7) and Daya Bay (62.2), and more distant for the Dongsha Islands (55.2). Based on the overall results of the present study it is concluded that species abundance and taxonomic diversities in the PRE reflects healthy ecosystem of PRE. [ABSTRACT FROM AUTHOR]

Abstract Background The ethnobotanical analysis of two bordering areas allows for the in-depth understanding of the dynamics of Local Ecological Knowledge, which mirrors the naturalistic, historical, and sociopolitical features of each area. As part of the Interreg Italy-Switzerland B-ICE&Heritage and GEMME projects, this work is an ethnobotanical comparative study of two neighboring Alpine territories: Valmalenco (Italy) and Valposchiavo (Switzerland). Methods A total of 471 informants were interviewed on different fields of use (medicinal, food, veterinary, etc.). All data were organized in Excel™ spreadsheets. Informant Consensus Factor was calculated for the pathologies reported. Jaccard’s similarity indices were calculated to compare the Valmalenco and Valposchiavo areas. Subsequently, another comparison between Valmalenco/Valposchiavo and Italian/Swiss Alpine neighboring areas was carried out. Results The number of taxa for Valmalenco was 227 (77 families) and 226 in Valposchiavo (65). Out of the 10 most cited species, 7 were mentioned in both. Arnica montana L. was the most cited in Valmalenco, and Sambucus nigra L. in Valposchiavo. The 5 most cited families were the same. Regarding the medicinal and food fields, the similarity indices were fairly low (0.31 and 0.34 for the species; 0.22 and 0.31 for the uses). Concerning the comparison with Italian and Swiss Alps, similarity values were slightly higher with Italy (Valmalenco food species: 0.38 with Italy and 0.26 with Switzerland, medicinal: 0.26 IT and 0.14 SW; Valposchiavo food species: 0.36 with IT and 0.26 with SW, medicinal: 0.21 IT and 0.14 SW). Conclusion Although Valmalenco and Valposchiavo partly share natural environment, language, history, and culture, they had low similarity indices. They both seemed to have more similarities with Italy than Switzerland, maintaining low values with the surrounding territories too. They showed a common core of Local Ecological Knowledge with several divergent branches possibly due to pivotal historical happenings, as well as more modern external influences.

• We assessed the number of pulses required for prefrontal TMS-EEG testing. • The 80-pulse was found to be equivalent to 160/240-pulse in TEP waveform similarity. • The 40 pulses makes it difficult to obtain a stable TEP early component. • For reliable TMS-evoked EEG, around 80 pulses are considered reasonable. Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG), TMS-EEG, is a useful neuroscientific tool for the assessment of neurophysiology in the human cerebral cortex. Theoretically, TMS-EEG data is expected to have a better data quality as the number of stimulation pulses increases. However, since TMS-EEG testing is a modality that is examined on human subjects, the burden on the subject and tolerability of the test must also be carefully considered. In this study, we aimed to determine the number of stimulation pulses that satisfy the reliability and validity of data quality in single-pulse TMS (spTMS) for the dorsolateral prefrontal cortex (DLPFC). TMS-EEG data for (1) 40-pulse, (2) 80-pulse, (3) 160-pulse, and (4) 240-pulse conditions were extracted from spTMS experimental data for the left DLPFC of 20 healthy subjects, and the similarities between TMS-evoked potentials (TEP) and oscillations across the conditions were evaluated. As a result, (2) 80-pulse and (3) 160-pulse conditions showed highly equivalent to the benchmark condition of (4) 240-pulse condition. However, (1) 40-pulse condition showed only weak to moderate equivalence to the (4) 240-pulse condition. Thus, in the DLPFC TMS-EEG experiment, 80 pulses of stimulations was found to be a reasonable enough number of pulses to extract reliable TEPs, compared to 160 or 240 pulses. This is the first substantial study to examine the appropriate number of stimulus pulses that are reasonable and feasible for TMS-EEG testing of the DLPFC. [ABSTRACT FROM AUTHOR]

This study collects the results obtained using the Getis-Ord local spatial autocorrelation index (Gi) with the aim of improving the classification of burned area detection maps generated from spectral indices (i.e., dNBR index) derived from Sentinel-2 satellite data. Therefore, the work proposes an adaptive thresholding approach that also includes the application of a similarity index (Sorensen–Dice Similarity Index) with the aim of adaptively correcting classification errors (false-positive burned pixels) related to the spectral response of burned/unburned areas. In this way, two new indices derived from the application of the Getis-Ord local autocorrelation analysis were created to test their effectiveness. Three wildfire events were considered, two of which occurred in Southern Italy in the summer of 2017 and one in Sardinia in the summer of 2019. The accuracy assessment analysis was carried out using the CEMS (Copernicus Emergency Management Service) on-demand maps. The results show the remarkable performance of the two new indices in terms of their ability to reduce the false positives generated by dNBR. In the three sites considered, the false-positive reduction percentage was around 95–96%. The proposed approach seems to be adaptable to different vegetation contexts, and above all, it could be a useful tool for mapping burned areas to support post-fire management activities. [ABSTRACT FROM AUTHOR]

Background: The ethnobotanical analysis of two bordering areas allows for the in-depth understanding of the dynamics of Local Ecological Knowledge, which mirrors the naturalistic, historical, and sociopolitical features of each area. As part of the Interreg Italy-Switzerland B-ICE&Heritage and GEMME projects, this work is an ethnobotanical comparative study of two neighboring Alpine territories: Valmalenco (Italy) and Valposchiavo (Switzerland). Methods: A total of 471 informants were interviewed on different fields of use (medicinal, food, veterinary, etc.). All data were organized in Excel™ spreadsheets. Informant Consensus Factor was calculated for the pathologies reported. Jaccard's similarity indices were calculated to compare the Valmalenco and Valposchiavo areas. Subsequently, another comparison between Valmalenco/Valposchiavo and Italian/Swiss Alpine neighboring areas was carried out. Results: The number of taxa for Valmalenco was 227 (77 families) and 226 in Valposchiavo (65). Out of the 10 most cited species, 7 were mentioned in both. Arnica montana L. was the most cited in Valmalenco, and Sambucus nigra L. in Valposchiavo. The 5 most cited families were the same. Regarding the medicinal and food fields, the similarity indices were fairly low (0.31 and 0.34 for the species; 0.22 and 0.31 for the uses). Concerning the comparison with Italian and Swiss Alps, similarity values were slightly higher with Italy (Valmalenco food species: 0.38 with Italy and 0.26 with Switzerland, medicinal: 0.26 IT and 0.14 SW; Valposchiavo food species: 0.36 with IT and 0.26 with SW, medicinal: 0.21 IT and 0.14 SW). Conclusion: Although Valmalenco and Valposchiavo partly share natural environment, language, history, and culture, they had low similarity indices. They both seemed to have more similarities with Italy than Switzerland, maintaining low values with the surrounding territories too. They showed a common core of Local Ecological Knowledge with several divergent branches possibly due to pivotal historical happenings, as well as more modern external influences. [ABSTRACT FROM AUTHOR]

Movie Recommender systems are frequently used in academics and industry to give users with relevant, engaging material based on their rating history. However, most traditional methods suffer from the cold-start problem, which is the initial lack of item ratings and data sparsity. The Hybrid Machine Learning (ML) technique is proposed for a movie recommendation system. Demographic data is collected from the Movie Lens dataset, and attributes are evaluated using the Attribute Analysis module. The Aquila Optimization Algorithm is used to select the best attributes, while Random Forest classifier is used for classification. Data is clustered using Fuzzy Probabilistic Cmeans Clustering Algorithm (FPCCA), and the Correspondence Index Assessment Phase (CIAP) uses Bhattacharyya Coefficient in Collaborative Filtering (BCCF) for similarity index calculation. The Outcomes gives the proposed method obtained low error, such as MAE has 0.44, RMSE has 0.63 compared with the baseline methods. [ABSTRACT FROM AUTHOR]

Objective: Visual aids like length‐frequency histograms are widely used to examine fish population status and trends; however, comparing multiple histograms simultaneously becomes cumbersome and inefficient. Complicating matters further, overlaying covariates on histograms to highlight connections with length frequencies can be challenging. An alternative, and the subject of this Perspective, is to display length distributions as an ordination using similarity indexes; in many cases, this allows for improved visual organization and representation of relationships with covariates. Methods: I review the application of ordination methods for analysis of size structures using alternative visualizations that may facilitate the identification of connections that are concealed when analyzing a series of histograms. After a brief introduction to similarity indexes, types of ordinations, and sample sizes, I examine four case studies to illustrate size structure analysis via similarity indices: (1) unconstrained ordination to identify "bass‐crowded" populations in a set of 34 small fishing lakes, (2) unconstrained ordination to evaluate the effect of three consecutive length limits on a Largemouth Bass Micropterus nigricans population over a span of 28 years, (3) constrained ordination to assess the relationships between fish community size structure and in‐lake and off‐lake environmental descriptors in 30 oxbow lakes, and (4) constrained ordination to identify what aspects of Largemouth Bass size structure were related to six types of reservoir habitats. Result: Size structure analysis via similarity indexes enabled the exploration of extensive length‐frequency data. It is important to acknowledge that ordinations serve solely as a visual aid for assessing size structure—no statistical testing is involved. Conclusion: Ordination techniques and software are advancing at a quick pace, holding great promise for the future of size structure analysis via similarity indices. Impact statementLength ordinations provide a visual representation of complex size structure data, making it easier to understand patterns, relationships, and trends in size structure. The visual representation can facilitate the interpretation and communication of survey results to both experts and nonexperts. [ABSTRACT FROM AUTHOR]

(1) Background: The use of multiscale prediction or the optimal scaling of predictors can enhance soil maps by applying pixel size in digital soil mapping (DSM). (2) Methods: A total of 200, 50, and 129 surface soil samples (0–30 cm) were collected by the CLHS method in three different areas, namely, the Marvdasht, Bandamir, and Lapuee plains in southwest Iran. Then, four soil properties—soil organic matter (SOM), bulk density (BD), soil shear strength (SS), and mean weighted diameter (MWD)—were measured at each sampling point as representative attributes of soil physical and chemical quality. This study examined different-scale scenarios ranging from resampling the original 30 m digital elevation model and remote sensing indices to various pixel sizes, including 60 × 60, 90 × 90, 120 × 120, and up to 2100 × 2100 m. (3) Results: After evaluating 22 environmental covariates, 11 of them were identified as the most suitable candidates for predicting soil properties based on recursive feature elimination (RFE) and expert opinion methods. Furthermore, among different pixel size scenarios for SOM, BD, SS, and MWD, the highest accuracy was achieved at 1200 × 1200 m (R2 = 0.35), 180 × 180 m (R2 = 0.67), 1200 × 1200 m (R2 = 0.42), and 2100 × 2100 m (R2 = 0.34), respectively, in Marvdasht plain. (4) Conclusions: Adjusting the pixel size improves the capture of soil property variability, enhancing mapping precision and supporting effective decision making for crop management, irrigation, and land use planning. [ABSTRACT FROM AUTHOR]

Defining the seed dormancy profile (SDP) of plant communities may provide insight into species adaptive mechanisms, community structure, and dynamics. Golestan National Park (GNP) in Iran consists of different types of vegetation, namely deciduous temperate forest, matorral, and steppe in close proximity but with variability of environmental factors. Plant species, life forms, and kinds of seed dormancy were determined in the three vegetation types, and a SDP of types was generated and compared with corresponding ones in the world database. In all GNP vegetation types, 80%–82% and 2%–3% of the species had dormant (D), and nondormant (ND) seeds, respectively, but in 17% the class of dormancy was unknown. Physiological dormancy (PD) was the most abundant followed by physical dormancy (PY). The species percentage with ND seeds in GNP was significantly two or three times lower than that in the world database. The PD percentage in the matorral was significantly higher than that in the world database. The PY percentage was higher in the forests but lower in the matorral and steppe compared with the world database. The morphophysiological (MPD) dormancy percentage was significantly lower in the forests but higher in the matorral and steppe than in the global database. Seed dormancy profiles were not affected by the proximity of vegetation types in the GNP, but they differed from those of the world database for each vegetation type. The past climatic fluctuations associated with the present‐day seasonality of the region might be the selective pressure for the increased percentage of species with D seeds in the GNP. [ABSTRACT FROM AUTHOR]

The distribution and composition of the vegetation are greatly affected by the edaphology and topography of an area. The current study explores the vegetation structure of the herbaceous layer at various habitats of district Kohat for the first time. A survey was conducted during the spring seasons of 2021, 2022 and 2023 selecting 40 sites on the basis of edaphology, topography, altitude, aspect and status. Data was collected via quadrat approach to establish plant communities by species Importance Value (IV), point out dominant species by Total IV (TIV) and dominant families via Total Family IV (TFIV). The quantitative biological spectrum was also calculated. Communities' phytosociological characteristics were analyzed via various diversity indices (Shannon's Index (H), Simpson's Index (D), Species Richness (SR), Evenness (E) and Maturity index (Mi)) while similarity between the communities was calculated by using Sorensen's Index. The findings revealed a total of 253 species belonging to 57 families having the dominant species Cynodon dactylon (L.) Pers. (TIV, 484.3) followed by Saussuria heteromalla (D. Don) Hand. (TIV, 360.4), Anagallis arvensis L. (TIV, 353.2) and Aristida adscensionis L. (TIV, 349.65). Among 40 plant communities, Poaceae (TFIV, 2706.6), Asteraceae (TFIV, 2018.8), Fabaceae (TFIV, 1071.5) and Brassicaceae (TFIV, 825.9) were the dominant families. Therophytes (TIV, 7882) class was the dominant life form class followed by hemicryptophytes (TIV, 2517) while microphylls (TIV, 4669) class was the dominant leaf size class followed by nanophylls (TIV, 5469). Environmental factors i.e. topography and edaphic characteristics, showed significant effects on the diversity of the communities. The study concludes in a diverse pattern of distribution with a rich flora in the area warranting its documentation which will preserve the valuable species opening vistas for future research. [ABSTRACT FROM AUTHOR]

In the western United States, water supplies largely originate as snowmelt from forested land. Forests impact the water balance of these headwater streams, yet most predictive runoff models do not explicitly account for changing snow‐vegetation dynamics. Here, we present a case study showing how warmer temperatures and changing forests in the Henrys Fork of the Snake River, a seasonally snow‐covered headwater basin in the Greater Yellowstone Ecosystem, have altered the relationship between April 1st snow water equivalent (SWE) and summer streamflow. Since the onset and recovery of severe drought in the early 2000s, predictive models based on pre‐drought relationships over‐predict summer runoff in all three headwater tributaries of the Henrys Fork, despite minimal changes in precipitation or snow accumulation. Compared with the pre‐drought period, late springs and summers (May–September) are warmer and vegetation is greener with denser forests due to recovery from multiple historical disturbances. Shifts in the alignment of snowmelt and energy availability due to warmer temperatures may reduce runoff efficiency by changing the amount of precipitation that goes to evapotranspiration versus runoff and recharge. To quantify the alignment between snowmelt and energy on a timeframe needed for predictive models, we propose a new metric, the Vegetation‐Water Alignment Index (VWA), to characterize the synchrony of vegetation greenness and snowmelt and rain inputs. New predictive models show that in addition to April 1st SWE, the previous year's VWA and summer reference evapotranspiration are the most significant predictors of runoff in each watershed and provide more predictive power than traditionally used metrics. These results suggest that the timing of snowmelt relative to the start of the growing season affects not only annual partitioning of streamflow, but can also determine the groundwater storage state that dictates runoff efficiency the following spring. [ABSTRACT FROM AUTHOR]

The Vamanapuram River Basin (VRB) is home to a diverse range of plant species, including 152 distinct species from 50 botanical families. Poaceae, Leguminosae, Araceae, and Aseraceae are the most abundant, with 13 species. Euphorbiaceae, Acanthaceae, Apocynaceae, and Rubiaceae also contribute to the biodiversity hotspots. The VRB's vegetation profile is characterized by a dynamic interplay of plant forms and ecological niches, with 74 herbs, 30 shrubs, 12 grasses, 1 liana, and 35 towering trees. The Poaceae family thrives in this environment due to hydrological factors. The sampling sites P6 and P5 exhibit high relative frequency and density, with key species like Macaranga peltata, Ficus hispida, and Swietenia macrophylla. Diversity indices like the Shannon-Wiener diversity index reaffirm the VRB's tropical forest character. Beta-diversity patterns reveal unique plant species distribution dynamics among different panchayaths, emphasizing their ecological complexities. The study emphasizes the demand for specialized management and conservation techniques in this environmentally active region. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) are revolutionising diverse computer vision use case domains, from public safety surveillance to Search and Rescue (SAR), and other emergency management and disaster relief operations. The growing need for accurate face verification algorithms has prompted an exploration of synergies between UAVs and face verification. This promises cost-effective, wide-area, non-intrusive person verification. Real-world human-centric use cases such as a ”Drone Guard Angel” for vulnerable people can contribute to public safety management and offload significant police resources. These scenarios demand efficient face verification to distinguish correctly the end users for authentication, authorisation and customised services. This paper investigates the suitability of existing solutions, and analyses five state-of-the-art candidate face verification algorithms. Informed by the advantages and disadvantages of existing solutions, the paper proposes an extended dataset and a refined face verification pipeline. Subsequently, it conducts empirical evaluation of these algorithms using the proposed pipeline and dataset in terms of inference times and the distribution of the similarity indexes. Furthermore, this paper provides essential guidance for algorithm selection and deployment in UAV-based applications. Two candidate algorithms, ArcFace and FaceNet512, have emerged as the top performers. The choice between them will depend on the specific use case requirements.

In the design of furniture wood texture images, image restoration is a key issue. This study proposes a Bregmanized operator splitting optimization algorithm based on variable space. This study combines variable spatial morphology to process texture images and effectively extract image features using different operators, thereby achieving image restoration. The results of comparing the proposed algorithm with other image processing algorithms showed that the research algorithm achieved a peak signal-to-noise ratio of 29.86 and a structural similarity index of 0.87 in image denoising, respectively, and had a good denoising effect. In terms of image deblurring, the research algorithm had the lowest root mean square error values on the France and Boat datasets, with values of 8.98 and 8.82, respectively, indicating that the image processed by the algorithm had a high similarity with the real image. In terms of image resolution reconstruction, the peak signal-to-noise ratio and root mean square error values of the research algorithm reached 29.74 and 12.67, respectively, indicating that the reconstructed image had the best fit with the original image and the smallest error. In summary, the proposed algorithm has shown good performance in image processing and can be effectively applied in fields such as image denoising, deblurring, and resolution reconstruction. It provides effective methods and technical support for innovative design of wood texture images in indoor furniture.

Sweet potato [Ipomoea batatas (L.) Lam.] varieties can be distinguished by their flesh and skin colors (white, yellow, orange, and purple). The present study was undertaken to assess on-farm diversity and the status of genetic erosion of sweet potatoes in Haramaya district, Ethiopia. Data were collected for similarity/dissimilarity index, preference index, and genetic erosion. The result of the preference index indicated the highest preference index (25.60) with preference rank 1 recorded for the BeelaBochol genotype as the lowest preference index (12.10) was recorded for the BeelaBaleyso genotype. About 66% of the respondents use the intercropping system for sweet potato cultivation. The majority of respondents 97% observed loss of sweet potato varieties. Eighty-two percent of the respondent farmers suggested the use of their seed source for planting. About 73% of the respondents suggested the cultivation of sweet potato as a subsistence crop. The major constraints of sweet potato cultivation, as suggested by the respondents, were tiresome land preparation 37%, lack of improved variety 26%, land scarcity 23%, and market demand 15%. It can be concluded from the result of the present study that farmers can identify and prefer sweet potato genotypes frequently using storage root yield and boiled quality. [ABSTRACT FROM AUTHOR]

In a high proportion of wind–photovoltaic–hydro hybrid power systems, fluctuation and dispersion make it difficult to accurately quantify the output characteristics. Therefore, in this study, a cloud model and copula correlation coefficient matrix were constructed for a hybrid power generation system based on the output data. Multiple backward cloud transformation based on the sampling-with-replacement method was proposed to calculate the improved entropy and hyperentropy to analyze the fluctuation range and dispersion degree quantitatively. A similarity index was proposed to evaluate the similarity between wind power, PV power, and hydropower. A suitable copula function was selected, and the Kendall and Spearman coefficients show the correlation relationships of the hybrid systems. The temporal and spatial characteristics of the hybrid systems were analyzed based on the two models. A typical example in Qinghai proved the effectiveness and applicability of the method. The results show that the correlation between photovoltaic power and hydropower is better and that, in summer, hydropower can be used to adjust the output of renewable energy. [ABSTRACT FROM AUTHOR]

The American National Standards Institute/American Nuclear Society national standards 8.1 and 8.24 provide guidance on the requirements and recommendations for establishing confidence in the results of the computerized models used to support operation with fissionable materials. By design, the guidance is not prescriptive, leaving freedom to the analysts to determine how the various sources of uncertainties are to be statistically aggregated. Due to the involved use of statistics entangled with heuristic recipes, the resulting safety margins are often difficult to interpret. Also, these technical margins are augmented by additional administrative margins, which are required to ensure compliance with safety standards or regulations, eliminating the incentive to understand their differences. With the new resurgent wave of advanced nuclear systems, e.g., advanced reactors, fuel cycles, and fuel concepts, focused on economizing operation, there is a strong need to develop a clear understanding of the uncertainties and their consolidation methods to reduce them in manners that can be scientifically defended. In response, the current studies compare the analyses behind four notable methodologies for upper subcriticality limit estimation that have been documented in the nuclear criticality safety literature: the parametric, nonparametric, Whisper, and TSURFER methodologies. Specifically, the work offers a deep dive into the various assumptions of the noted methodologies, their adequacies, and their limitations to provide guidance on developing confidence for the emergent nuclear systems that are expected to be challenged by the scarcity of experimental data. To limit the scope, the current work focuses on the application of these methodologies to criticality safety experiments, where the goal is to calculate a bias, a bias uncertainty, and a tolerance limit for keff in support of determining an upper subcriticality limit for nuclear criticality safety. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) are revolutionising diverse computer vision use case domains, from public safety surveillance to Search and Rescue (SAR), and other emergency management and disaster relief operations. The growing need for accurate face verification algorithms has prompted an exploration of synergies between UAVs and face verification. This promises cost-effective, wide-area, non-intrusive person verification. Real-world human-centric use cases such as a ”Drone Guard Angel” for vulnerable people can contribute to public safety management and offload significant police resources. These scenarios demand efficient face verification to distinguish correctly the end users for authentication, authorisation and customised services. This paper investigates the suitability of existing solutions, and analyses five state-of-the-art candidate face verification algorithms. Informed by the advantages and disadvantages of existing solutions, the paper proposes an extended dataset and a refined face verification pipeline. Subsequently, it conducts empirical evaluation of these algorithms using the proposed pipeline and dataset in terms of inference times and the distribution of the similarity indexes. Furthermore, this paper provides essential guidance for algorithm selection and deployment in UAV-based applications. Two candidate algorithms, ArcFace and FaceNet512, have emerged as the top performers. The choice between them will depend on the specific use case requirements. [ABSTRACT FROM AUTHOR]

ARTICLE HIGLIGHTS - High demand for environmental services makes the park vulnerable to human activities. - Both ecosystems are well regenerated; seedling > sapling > pole > tree (inverted J) - Both ecosystems show normal diversity conditions and stable species distribution. - Growth of Maesopsis eminii needs monitoring to preserve forest purity. - Montane forests have greater biomass, carbon stocks, less anthropogenic disturbance ABSTRACT The Gunung Gede Pangrango National Park (GGPNP) area is one of the vital ecosystems that support the environment in West Java Province, Indonesia. It is a unique area that has multiple forest ecosystems, including lowland rainforest and montane rainforest ecosystems. Despite the GGPNP’s status as a conservation area, the high demand for the GGPNP’s environmental services makes the region vulnerable to disturbances from human activities. Several studies have been conducted in the GGPNP area (lowland and montane forest ecosystems), however, the results of this study are still necessary to explain the forest dynamics and forest carbon sequestration in this location. The objective of this research was to analyze the structure, composition, and carbon sequestration of stands in the lowland and montane rainforest ecosystems in the GGPNP area. Data processing and analyses were conducted using diversity indices, biomass-carbon stock estimation, and carbon dioxide sequestration estimation. The results showed that the GGPNP lowland and montane rainforest ecosystems were well regenerated. The number of seedlings > saplings > poles > trees and the graph showed a reverse “J” pattern. The GGPNP lowland rainforest ecosystem was dominated by Neonauclea lanceolata and had relatively higher species diversity. The GGPNP montane rainforest ecosystem was dominated by Castanopsis acuminatissima with a higher individual density, denser canopy, and more complex canopy strata. The lack of regeneration in several species of trees heightens the threat to these species’ existence in the future. Biomass, carbon stocks, and carbon sequestration in the GGPNP montane rainforest were greater than those in the GGPNP lowland rainforest. The GGPNP montane rainforest ecosystem had older forest stands, a larger average tree diameter, and lower potential for anthropogenic disturbances.

In its management, to prevent conflict of interests between the surrounding community and the government, the Burung Island Nature Tourism Park is divided into 5 blocks, and the object of research is the condition of the mangrove forests in 3 blocks, namely the Protection Block, Rehabilitation Block and Utilization Block. The condition of the forests in the three blocks is studied in this research. The aim of the research is to examine the condition and existence of the types of vegetation that make up the forest in the three blocks from the aspect of the minimum liveability value of each type of vegetation in each block, as well as the level of similarity in composition and structure of vegetation types between blocks. Data was collected using the Vegetation Analysis method using systematic plotted paths carried out by purposive sampling in the three blocks. The path is made with a width of 10 m and a length of 100 m, consisting of 9 paths that cut perpendicular to the coastline towards the mainland, with a distance of 100 m between paths. Nine types of vegetation were found, of which Rhizophora mucronata was the most dominant type in the three blocks at all growth levels. All types of vegetation at all growth levels in the three blocks have viability values above the minimum value, and the highest minimum viability value is Rhizophora mucronata. The composition and structure of the seedling and tree communities in the three blocks tend to be similar, while the sapling communities in the Protection Block and the Rehabilitation Block are not similar, but are similar in the Utilization Block. The seedling and tree communities in the Rehabilitation Block are similar to the Utilization Block, while the sapling communities are not similar.

The Programmable Hyperspectral Seawater Scanner (PHySS) represents a significant breakthrough in monitoring harmful algal blooms (HABs), specifically targeting the “Florida red tide” caused by Karenia brevis. By utilizing a Fourth-Derivative Spectral Similarity Index (SI), this study establishes a strong positive correlation between the SI and phytoplankton counts, underscoring the PHySS’s potential for early detection and effective management of HABs. Our findings suggest that the PHySS could act as a predictive tool, offering crucial lead time to mitigate the ecological and economic repercussions of blooms. However, this study also identifies certain limitations of the PHySS technology, such as its inability to differentiate among various phytoplankton species without additional physical verification of cell counts. This limitation highlights the need for a multifaceted approach to HAB management. Our research suggests that adopting a multi-modal monitoring strategy could lead to more sophisticated and effective methods for combating HABs, fostering an optimistic outlook for future advancements in this area.

In the current information technology era, plagiarism is a significant and critical issue in research. Plagiarism detection tools are essential in identifying instances of plagiarism. This study compared the similarity index generated by three leading plagiarism detection software platforms: iThenticate, Ouriginal, and Turnitin. Ten original documents (N = 10) were selected for analysis across the three software programs. The process involved first analyzing all documents with Ouriginal, then checking the same documents, followed by iThenticate, and Turnitin. These software programs generated originality reports detailing the number of matching sources, similar word counts, and an overall similarity index as a percentage. To detect notable differences within the dataset, a one-way ANOVA and a Tukey (HSD) post-hoc analysis were conducted. The threshold for statistical significance was established at p<0.05. Statistical analysis revealed that while there was a significant variance in the similarity index across the tools iThenticate, Ouriginal, and Turnitin (F (2, 27) = 5.436, p = .010), there were no notable differences in the sources they matched (F (2, 27) = 1.289, p = .292). This suggests that the plagiarism detection capabilities may vary significantly among these tools, but the sources they identify as matches are largely consistent. However, the average values indicated that Turnitin had the highest mean similarity detection followed by iThenticate, and then Ouriginal. In this study, evaluating the similarity index can help verify the effectiveness of anti-plagiarism tools and safeguard researchers against committing plagiarism. [ABSTRACT FROM AUTHOR]

Long-term occupation of coal gangue dumping sites (CGDS) may destroy ecological environment of nearby area. However, how the CGDS affects the distribution pattern of soil seed banks and vegetation in the nearby area is not clear. In this study, we investigated soil seed bank and vegetation at different distances from the second CGDS of Yangchangwan in Ningdong mining area, Lingwu, Ningxia. The results showed that soil seed bank was mainly distributed in 0-10 cm layer and decreased with increasing soil depth. Species richness of soil seed bank and vegetation first increased and then tended to be stable with increasing distance to the CGDS. The influence range of CGDS on soil seed banks was 300-500 m and was 100-300 m on aboveground vegetation. The CGDS did not affect the vertical distribution pattern of soil seed bank, but significantly affected the horizontal distribution pattern of soil seed banks and aboveground vegetation. The key area of vegetation restoration around the CGDS was between 100 m and 300 m. [ABSTRACT FROM AUTHOR]

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According to the scheme of age periodization of plant ontogenesis proposed by T.A. Rabotnov and A.A. Uranov, about a dozen of main age (ontogenetic) states are distinguished. Each population sample represents an ordered series of frequencies of occurrence of plants at these states: the so-called ontogenetic spectrum (OS). Different OS statistics are available according to the form of the OS, reflecting a greater or lesser representation of young, mature, or old plants in the population and making it possible to represent the temporal dynamics of the population. The Excel Ontogenetic Spectrum (ExOS) package allows their automatic computation and analysis. Input data are the numbers or frequencies of ontogenetic states in the sample. Output data are the classifications of OS and cenopopulation types according to various criteria; population–ontogenetic indices; and, for multiple population samples, similarity (or distance) between them and their ordination on delta–omega axes. The corresponding diagrams are captured automatically. [ABSTRACT FROM AUTHOR]

To reveal the typical features of text duplication in papers from four medical fields: basic medicine, health management, pharmacology and pharmacy, and public health and preventive medicine. To analyze the reasons for duplication and provide suggestions for the management of medical academic misconduct.

Power system stabilizer (PSS) is widely used to improve power system stability. The current parameter coordination optimization method is easy to fall into the local optimization, to solve the problem and find the optimal parameter combination of PSS, the sample screening method based on the similarity index of power system state (SIPSS) and BP neural network is proposed for global optimization parameters of PSS. The SIPSS screening method uses a similar metric index of the grid state variable as the criterion to screen out the required samples. The BP neural network fits the predicted and expected values of the minimum damping ratio of the system after random fluctuations of PSS parameters under various operating modes to minimize the mean square deviation by fitting the streamlined training samples. Firstly, the SIPSS-BP neural network model is obtained by analyzing the mapping relationship between generator power, node power, branch power, and minimum damping ratio. Then, the sensitivity of the PSS parameters damping ratio is calculated, and the PSS parameter optimization model is established. The optimal adjustment of the PSS parameter is obtained, and the minimum damping ratio is modified to improve the system’s stability. Finally, the minimum damping ratio after correction is obtained. The test results of the SIPSS-BP network with the IEEE 3-machines and 9-nodes show that the method can achieve good prediction accuracy, the parameter optimization effect of PSS can be remarkable, and the stability of the power system has been greatly improved.

(1) Background: The use of multiscale prediction or the optimal scaling of predictors can enhance soil maps by applying pixel size in digital soil mapping (DSM). (2) Methods: A total of 200, 50, and 129 surface soil samples (0–30 cm) were collected by the CLHS method in three different areas, namely, the Marvdasht, Bandamir, and Lapuee plains in southwest Iran. Then, four soil properties—soil organic matter (SOM), bulk density (BD), soil shear strength (SS), and mean weighted diameter (MWD)—were measured at each sampling point as representative attributes of soil physical and chemical quality. This study examined different-scale scenarios ranging from resampling the original 30 m digital elevation model and remote sensing indices to various pixel sizes, including 60 × 60, 90 × 90, 120 × 120, and up to 2100 × 2100 m. (3) Results: After evaluating 22 environmental covariates, 11 of them were identified as the most suitable candidates for predicting soil properties based on recursive feature elimination (RFE) and expert opinion methods. Furthermore, among different pixel size scenarios for SOM, BD, SS, and MWD, the highest accuracy was achieved at 1200 × 1200 m (R2 = 0.35), 180 × 180 m (R2 = 0.67), 1200 × 1200 m (R2 = 0.42), and 2100 × 2100 m (R2 = 0.34), respectively, in Marvdasht plain. (4) Conclusions: Adjusting the pixel size improves the capture of soil property variability, enhancing mapping precision and supporting effective decision making for crop management, irrigation, and land use planning.

This study collects the results obtained using the Getis-Ord local spatial autocorrelation index (Gi) with the aim of improving the classification of burned area detection maps generated from spectral indices (i.e., dNBR index) derived from Sentinel-2 satellite data. Therefore, the work proposes an adaptive thresholding approach that also includes the application of a similarity index (Sorensen–Dice Similarity Index) with the aim of adaptively correcting classification errors (false-positive burned pixels) related to the spectral response of burned/unburned areas. In this way, two new indices derived from the application of the Getis-Ord local autocorrelation analysis were created to test their effectiveness. Three wildfire events were considered, two of which occurred in Southern Italy in the summer of 2017 and one in Sardinia in the summer of 2019. The accuracy assessment analysis was carried out using the CEMS (Copernicus Emergency Management Service) on-demand maps. The results show the remarkable performance of the two new indices in terms of their ability to reduce the false positives generated by dNBR. In the three sites considered, the false-positive reduction percentage was around 95–96%. The proposed approach seems to be adaptable to different vegetation contexts, and above all, it could be a useful tool for mapping burned areas to support post-fire management activities.

Purpose: Spatial variability of soil properties is considered as one of the most important reasons for the variability of crop productions. The current research was conducted to determine the capability of machine learning models for the generalization of the modeling results from the reference area, i.e., Marvdasht plain, for estimating soil fertility attributes with the aims of extrapolating the modeling results to receptor area, i.e., Bandamir, in Iran with the aid of Homosoil concepts. Materials and methods: The field study consists of 200 and 50 soil sampling locations in the reference and the receptor areas, respectively. Then, four soil properties, namely, soil organic carbon, total nitrogen, available phosphorus, and exchangeable potassium were measured as soil fertility attributes. Eighty-two soil and environmental covariates were gathered from different sources, i.e., soil variables from field work and laboratory analysis, digital elevation model, and remote sensing data as potentially connected to "scorpan" factors in both areas. Here, seven soil variables (bulk density, clay, silt and sand contents, calcium carbonate equivalent, pH, and soil electrical conductivity), 36 covariates as proxy of surface and vegetation cover, and 39 attributes related to topography are representations of "s," "o," and "r" in scorpan model, respectively. Selection of the most relevant covariates, feature selection was made based on recursive feature elimination method and the performance of three ML models, i.e., cubist, random forest, and k-nearest neighbors, in the reference area for finding the best spatial model to apply in the receptor area. Results and discussion: The feature selection results showed that 15 soil and environmental covariates were most relevant and therefore were chosen as predictors of soil fertility attributes. The validation results showed that the soil fertility attribute maps in the receptor area were highly accurate than the prediction maps of the reference area based on the coefficient of determination for soil organic carbon in topsoil (R2 = 0.74) and subsoil (R2 = 0.52), exchangeable potassium in topsoil (R2 = 0.77) and subsoil (R2 = 0.27), and total nitrogen at the topsoil (R2 = 0.28) and subsoil (R2 = 0.25), also for available phosphorus, the prediction accuracy increased in the receptor area. The machine learning performances also showed that cubist outperformed the model in the prediction of soil fertility attributes in both areas. Also, the results revealed that soil variables identified as high-rank in the prediction of soil fertility attributes followed by topographic attributes. Conclusion: Generally, in areas where soil data is limited and detailed maps of soil properties are not available, extrapolation approach could be applied as an easy and quick methodology for preparing soil maps with low-cost and acceptable accuracy. Also, we are suggesting that the applied methodology employed in this study can be applied in another region with similar conditions. [ABSTRACT FROM AUTHOR]

International interest is growing in biodiversity conservation and sustainable use in drylands. Desert ecosystems across arid Central Asia are severely affected by global change. Understanding the changes in a plant community is an essential prerequisite to revealing the community assembly mechanism, vegetation conservation, and management. The knowledge of large-scale spatial variation in plant community structure in different Central Asian deserts is still limited. In this study, we selected the Taukum (TD, Kazakhstan) and the Gurbantunggut (GD, China) deserts as the research area, with similar latitudes despite being nearly 1000 km apart. Thirteen and 15 sampling plots were set up and thoroughly investigated. The differences in community structure depending on multiple plant attributes (individual level: plant height, canopy diameter, and plant volume, and community level: plant density, total cover, and total volume) were systematically studied. TD had a better overall environmental status than GD. A total of 113 species were found, with 68 and 74 in TD and GD, respectively. The number of species and plant attributes was unequally distributed across different families and functional groups between deserts. The values of several plant attributes, such as ephemerals, annuals, dicotyledons, and shrubs with assimilative branches in GD, were significantly lower than those in TD. The Motyka indices of six plant attributes (26.18–38.61%) were higher between the two deserts than the species similarity index (20.4%), indicating a more robust convergence for plant functional attributes. The community structures in the two deserts represented by different plant attribute matrices demonstrated irregular differentiation patterns in ordination diagrams. The most variance in community structure was attributed to soil and climatic factors, while geographic factors had the smallest proportion. Consequently, the community structures of the two distant deserts were both different and similar to an extent. This resulted from the long-term impacts of heterogeneous environments within the same region. Our knowledge is further deepened by understanding the variation in community structure in different deserts on a large spatial scale. This therefore provides valuable insights into conserving regional biodiversity in Central Asia. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of African Higher Education is the property of International Network for Higher Education in Africa (INHEA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Mustafa Kemal University Journal of Agricultural Sciences / Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi is the property of Mustafa Kemal University, Faculty of Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The presence of weeds in the sunflower crop is one of the main factors linked to the low increase in productivity of this crop, and to determine the most appropriate management of weeds, it is essential to carry out a diagnosis through the phytosociological survey. The objective of this study was to assess the influence of chemical control on the phytosociological community of weeds in three areas cultivated with sunflower in the Parecis region (Brazil). The areas were treated with 2,4-D + glyphosate for desiccation; S-metolachlor was used for pre-emergence control in the three areas; meanwhile, sulfentrazone and flumioxazin were applied only in one area; and, finally, clethodim was applied for post-emergence weed management. Sampling was carried out at two different times, in the initial and pre-harvest stages (at 35 and 100 days after the emergence of the crop, respectively), using a quadrate, in which weeds were identified and quantified to determine the frequency, relative frequency, density, relative density, abundance, relative abundance, importance index, and similarity index between areas and times. Seventeen weed species were found in the sunflower crop (70.6% dicot and 29.4% monocotyledonous) in the two seasons, grouped into nine botanical families, with Poaceae being the most diverse family. The dicots Tridax procumbens and Acanthospermum hispidium were present in low frequency only in the initial stages of development of the sunflower crop. The weeds with the highest importance index values in the initial and pre-harvest stages were Euphorbia hirta (104 and 91%) and Bidens pilosa (45 and 66%, respectively), both belonging to the dicots group. These two species were present in the two evaluated periods and in the three experimental areas, demonstrating that there was a similarity index between them with values above 93%. These results of the phytosociological study may contribute to determining more efficient management strategies for weed chemical control in the sunflower crop.

Bu çalışmanın amacı, 2002-2021 döneminde Türkiye’nin İslam İşbirliği Teşkilatı (İİT) üyelerinden 37’si ile olan dış ticaretinde Linder Hipotezi’nin geçerliliğini analiz etmektir. Uluslararası ticareti talep yönünden inceleyen Linder’e göre, talep yapıları benzer olan ülkelerin aralarında daha fazla ticaret gerçekleşmektedir. Talep yapılarının benzerlik durumları ise ortalama gelir seviyesiyle ele alınabilmektedir. Bu kapsamda, Türkiye’nin İİT üyeleriyle olan ikili ticareti genişletilmiş panel çekim modeliyle incelenmektedir. Analizde zamanla değişen değişkenlerin yanı sıra, zamanla değişmeyen değişkenleri de tahmin edebilme olanağı sunan Hausman-Taylor yöntemi kullanılmaktadır. Yapılan tahmin sonuçlarına göre, ilk olarak çekim modeli ile uyumlu şekilde, Türkiye’nin üye ülkelerle dış ticaretine Türkiye’nin ve ticaret partneri ülkenin kişi başına düşen GSYH büyüklüklerinin pozitif, ülkeler arasındaki mesafenin ise negatif yönde etki yaptığı anlaşılmıştır. İkinci olarak, Türkiye’nin söz konusu ülkelerle ikili ticaretinde Linder Hipotezi’nin geçerli olduğu dikkat çekmektedir. Son olarak, söz konusu ikili ticarette ortak sınır ve serbest ticaret anlaşmalarına ilişkin kukla değişkenlerin anlamsız olduğu görülmektedir.

Fault diagnosis and health monitoring of industrial rotating machines are of paramount importance for ensuring the reliability, safety, and efficiency of modern industrial operations. This paper proposes a Short-Time Fourier Transform (STFT)-based fault diagnosis approach for industrial rotating machinery. In this proposed model, the STFT of the reference vibration signals is evaluated and compared with the STFT of the other testing vibration signals to diagnose the fault types. Three different similarity operators: Euclidean distance, cosine similarity, and structural similarity are used to conclude the similarity index between the reference signal and test signal. By using variable speed vibration data with different fault types, the proposed model can better simulate real-world conditions and improve the accuracy and effectiveness of fault diagnosis. The results from the confusion matrices, heat maps, and t-SNE plots demonstrate the effectiveness of the proposed method for fault diagnosis and monitoring of variable-speed rotating machines using vibration signals. It is concluded that the structural similarity index proved to be a promising approach for accurate fault diagnosis in variable-speed rotating machines. The results are also compared with the existing approaches in the literature and it was concluded that the proposed model attains the highest accuracy for the variable speed rotating machines.

Rodents are important components of animal communities in forest ecosystems. This study investigated rodent species diversity in Jiangxi Wuyi Mountain National Nature Reserve of China in 2014-2015. Rodents were trapped at nine selected sampling sites varying in altitude for evaluating their diversity. Consequently, 16 rodent species belonging to eight families were recorded. Out of 376 individuals of rodent species trapped (capture rate = 4.7%), Apodemus agrarius, Eothenomys melanogaster, Niviventer fulvescens and N. confucicianus were identified as dominant species with relative abundances over 10%, in which N. fulvescens and N. confucicianus were trapped in eight and seven habitat types, respectively, indicating a larger altitude span of their distribution ranges. Bamboo planting areas were found to possess more rodent species than other habitats. Crocidura Dracula, Micromys minutus, Lepus sinensis, A. agrarius, Rattus nitidu, Tamiops swinhoei and R. norvegicus were each trapped in only one habitat. Among habitats, bamboo planting areas showed the highest diversity index and richness index of rodent community, while farmland harbored the highest dominance index and lowest diversity index. Rodent communities were classified into three categories, namely meadow type, forest type, and farmland type. The present study provides a comprehensive inventory of rodent species diversity of the reserve, and is of great significance in the protection and construction of biodiversity in the forest ecosystem of Wuyi Mountain area. [ABSTRACT FROM AUTHOR]

A Recommendation System (RS) is a method which filters the information and helped users' to choose the corresponding target from the huge amount of information obtainable in online. The system recommends useful and satisfactory products (items) such as books, music, jokes, and movies for targeting users based on their interest. The content-based filtering as well as collaborative are different systems used often while designing the RS that predicts the recommended item(s) based upon the user preferences. However, the collaborative filtering algorithm provides poor performance for data sparsity, and it is complex for tracking the change of user interest. Moreover, the hybrid system has combined both the techniques in multiple ways to overcome the shortcomings and optimize the outcomes. Thereby, this article plans to develop a new hybrid recommender system assisting with the optimization concept for optimal recommendation list based on user preference or interest. At first, the feature extraction process takes place, in which the content features and the collaborative features are extracted based on (a) profile construction, (b) content similarity index, (c) Neighbor finder, (d) Items generator, and (e) Items weight generator and variance generator. Consequently, the optimal recommendation is carried out on the basis of features extracted. Further, the developed work plans to carry out the optimal rating of recommendation using a FireFly with Weighted Crow Search Algorithm (FF-WCSA). At last, the outcomes of the developed model is computed to extant approaches in terms of various metrics like accuracy, FDR, MAE, MARE, MSE, MSRE, RMSE, and RMSRE, respectively. [ABSTRACT FROM AUTHOR]

Riparian vegetation, which plays important roles in conservation of regional biodiversity and provision of many environmental services, has been severely degraded in East Africa by human activities. To ameliorate this degradation, more knowledge of the vegetation and factors affecting it is required. Thus, effect of land use on the plant community composition, species richness and diversity patterns were investigated along 18 streams in the Gilgle Gibe River catchment, in south‐western Ethiopia, using 100 m2 plots established along transects on both sides of the streams at 35 sampling locations beside land designated as agricultural, forested, mixed vegetation or eucalyptus plantation. The communities in the plots were surveyed and classified by Two‐Way Indicator Species Analysis. In total, 107 vascular plant species belonging to 49 families were recorded. Species richness and diversity were lowest along streams beside agricultural land, which had narrow riparian buffers, and highest along forested streams, which had wider riparian buffers. The communities in the sampling plots were assigned to seven groups. Species richness was positively correlated buffer width (r = 0.74, p < 0.01). The results highlight the human influence on riparian vegetation and the importance of sustainable management that is compatible with its conservation and restoration. However, to address the severity and complexity of forest fragmentation, conservation strategies must embrace a multi‐site, contextual approach. [ABSTRACT FROM AUTHOR]

Recommendation systems are becoming more and more present in our daily lives, whether it is for suggesting items to buy, movies to watch or music to listen. They can be used in a large number of contexts. In this paper, we propose the use of a recommendation system in the context of a recruitment platform. The use of the recommendation system allows to obtain precise profile recommendations based on the competences of a candidate to meet the stated requirements and to avoid companies to have to perform a very time-consuming manual sorting of the candidates. Thus, this paper presents the context in which we propose this recommendation system, the data preprocessing, the general approach based on a hybrid content-based filtering (CBF) and similarity index (SI) system, as well as the means implemented to reduce the computational cost of such a system with the increasing evolution of the platform. [ABSTRACT FROM AUTHOR]

The presence of weeds in the sunflower crop is one of the main factors linked to the low increase in productivity of this crop, and to determine the most appropriate management of weeds, it is essential to carry out a diagnosis through the phytosociological survey. The objective of this study was to assess the influence of chemical control on the phytosociological community of weeds in three areas cultivated with sunflower in the Parecis region (Brazil). The areas were treated with 2,4-D + glyphosate for desiccation; S-metolachlor was used for pre-emergence control in the three areas; meanwhile, sulfentrazone and flumioxazin were applied only in one area; and, finally, clethodim was applied for post-emergence weed management. Sampling was carried out at two different times, in the initial and pre-harvest stages (at 35 and 100 days after the emergence of the crop, respectively), using a quadrate, in which weeds were identified and quantified to determine the frequency, relative frequency, density, relative density, abundance, relative abundance, importance index, and similarity index between areas and times. Seventeen weed species were found in the sunflower crop (70.6% dicot and 29.4% monocotyledonous) in the two seasons, grouped into nine botanical families, with Poaceae being the most diverse family. The dicots Tridax procumbens and Acanthospermum hispidium were present in low frequency only in the initial stages of development of the sunflower crop. The weeds with the highest importance index values in the initial and pre-harvest stages were Euphorbia hirta (104 and 91%) and Bidens pilosa (45 and 66%, respectively), both belonging to the dicots group. These two species were present in the two evaluated periods and in the three experimental areas, demonstrating that there was a similarity index between them with values above 93%. These results of the phytosociological study may contribute to determining more efficient management strategies for weed chemical control in the sunflower crop. [ABSTRACT FROM AUTHOR]