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Identifying near‐fault pulse‐like ground motions from extensive ground motion databases holds paramount importance, as it provides a pivotal foundation for further inquiries into this specific type of ground motions, including the modeling of such stochastic processes as well as thorough analysis of their potential impact on structures and infrastructure systems. Currently, a diverse array of quantitative methods for identifying pulse‐like ground motions have emerged, all of which demonstrate good accuracy within their respective research scopes. However, due to the limitations of each individual method in identifying specific cases, these diverse approaches often yield inconsistent results for certain ground motion records, posing a significant challenge in establishing a reliable classification criterion that relies solely on a single identification method. To address this issue, the present study adopts a multifaceted approach. Instead of improving a single time‐frequency analysis‐based identification method, it carefully conducts a selection of seven baseline methods through a systematic overview of the field. By leveraging the analytic hierarchy process (AHP), a comprehensive categorization method is developed that integrates the strengths of each approach, resulting in a more robust and credible classification criterion. According to the devised category indicator, ground motions can be classified into four categories: Category A comprises definitively pulse‐like ground motions; Category B comprises apparently pulse‐like ground motions; Category C consists of probably pulse‐like ground motions; and Category D encompasses ground motions unlikely to exhibit pulse‐like characteristics. It provides a more elaborate classification beyond the binary distinction of pulse‐like and non‐pulse‐like ground motions associated with traditional onefold classification methods. For validation purposes, a basic dataset comprising near‐fault ground motion records from the NGA‐West 2 database has been utilized. To verify the comprehensive categorization method, two datasets of pulse‐like ground motion records suggested by FEMA and PEER and one dataset of ground motion records collected during the 1999 Chi‐Chi earthquake are addressed. Numerical examples illustrate the remarkable effectiveness of the proposed method in identifying near‐fault pulse‐like ground motions based on their varying degrees of pulse‐like characteristics. [ABSTRACT FROM AUTHOR]

Honey, as a natural sweet substance, has always been favored by consumers due to its various functional activities, such as regulating the gastrointestinal tract, antibacterial, anti-inflammatory, and antioxidant properties. However, the production of honey is far less than the market demand for it, so driven by interests, honey is often adulterated, leading to quality deterioration. The adulteration of honey seriously undermines its natural attributes, having a negative impact on the honey industry. To safeguard the interests of consumers and producers, uphold the industry’s reputation, and promote its sustainable development, it is crucial to establish and improve methods for assessing honey authenticity. This article reviews the major methods for identifying the authenticity of honey, including traditional analytical techniques, targeted and non-targeted analytical techniques. In particular, the characteristic components in honey have been used for the identification of honey authenticity in recent years, which is achieved directly by analyzing the overall properties and chemical characteristics of honey are consistent with each other or not, but not relying on any prior knowledge of the adulterants. This paper aims to provide theoretical references for the authenticity identification of honey.

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department 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.)

Clay minerals are widely distributed and are important components in sedimentary rocks. The identification and quantification of detrital and authigenic clay minerals have been hot topics recently due to the needs of petroleum geology, paleoclimate, and sedimentary history research. Detrital clay minerals exhibit the phenomenon of discrete grain boundaries, while authigenic clay minerals have various specific particle shapes. The differences in crystal structure of different clay mineral origins are reflected in the polytype character of clay minerals, especially for illite and chlorite. Different origins of clay minerals inherently have different chemical characteristics. Instead of focusing only on conventional techniques (scanning electron microscopy, X-ray diffraction, and geochemical analysis), here we review established approaches and introduce emerging analytical techniques (automated mineralogy techniques and artificial intelligence techniques) that can complement current methods. In addition, the applications of these techniques in illite age analysis, paleoclimate reconstruction, and reservoir properties are discussed. Further, different state-of-the-art techniques for clay mineral identification and quantification (e.g., scanning electron microscopy for specific petrographic characterization, X-ray diffraction for bulk crystal structure identification, etc.) are discussed. We propose that combining individual and bulk techniques obtained at multiple scales can provide novel insights for deciphering various clay mineral origins. Understanding the characteristics of clay minerals from different origins is of great importance to scientific issues such as shale oil and gas exploration.

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department 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 exploration of threshold concepts, which represent a transformed way of understanding, interpreting, or viewing something necessary for a learner’s progress, has significantly influenced teaching and learning in higher education, gaining broad acceptance in academic circles. Despite widespread enthusiasm, the scientific development of the field faces obstacles, especially epistemological and ontological uncertainties, directly implying the reliability of identification techniques and, by extension, raising questions about the validity of previous findings. This comprehensive review delves into 60 articles sourced from the Web of Science database to scrutinize the literature on threshold concept identification. The findings confirm the adaptability of threshold concepts across diverse disciplines. However, the fluid definition inherent in these concepts introduces ontological challenges, influencing biases in the identification process. The review highlights the diverse identification methods influenced by knowledge area specificities, community affinities, and research practice traditions. A diagram depicting the methods employed to identify threshold concepts is offered to highlight five central decisions to be considered. Acknowledging professors as pivotal mediators adept at navigating the epistemological and ontological dimensions of threshold concepts while integrating theoretical and applied knowledge, this study enhances our nuanced understanding of threshold concept identification. Emphasizing methodological validity and reliability, it acknowledges the crucial role of experienced educators in this issue and presents future perspectives for advancing current research, fostering the maturation of the field.

The exploration of threshold concepts, which represent a transformed way of understanding, interpreting, or viewing something necessary for a learner's progress, has significantly influenced teaching and learning in higher education, gaining broad acceptance in academic circles. Despite widespread enthusiasm, the scientific development of the field faces obstacles, especially epistemological and ontological uncertainties, directly implying the reliability of identification techniques and, by extension, raising questions about the validity of previous findings. This comprehensive review delves into 60 articles sourced from the Web of Science database to scrutinize the literature on threshold concept identification. The findings confirm the adaptability of threshold concepts across diverse disciplines. However, the fluid definition inherent in these concepts introduces ontological challenges, influencing biases in the identification process. The review highlights the diverse identification methods influenced by knowledge area specificities, community affinities, and research practice traditions. A diagram depicting the methods employed to identify threshold concepts is offered to highlight five central decisions to be considered. Acknowledging professors as pivotal mediators adept at navigating the epistemological and ontological dimensions of threshold concepts while integrating theoretical and applied knowledge, this study enhances our nuanced understanding of threshold concept identification. Emphasizing methodological validity and reliability, it acknowledges the crucial role of experienced educators in this issue and presents future perspectives for advancing current research, fostering the maturation of the field. [ABSTRACT FROM AUTHOR]

With the rapid development of unmanned aerial vehicle (UAV) technology, UAV has been widely used in agricultural plant protection, electric power inspection, security patrols, and other fields. However, the control system of the UAV is a complex human–computer interaction system, which requires higher requirements in practical applications. Due to differences in hardware design, software development, and other aspects among different manufacturers, these UAV control systems require high hardware requirements, resulting in a long development cycle. At the same time, in practical applications, due to various reasons, there are equipment failures that are difficult to detect and eliminate in a timely manner. This paper used the UAV graphical control strategy identification method based on cloud server technology, and used the support vector machine (SVM) algorithm to analyze its identification accuracy. The research results showed that when other conditions were the same, the number of researchers and experts who were satisfied with the drone trial effect of the cloud server was 42 and 10, respectively, accounting for 84% and 100%. It indicates that they believe that the cloud server can effectively improve the effectiveness of the drone graphical control strategy recognition method, indicating a positive relationship between the two. [ABSTRACT FROM AUTHOR]

The number of buildings experiencing humidity problems and fungal growth appears to be increasing as energy-saving measures and changes in construction practices and climate become more common. Determining the cause of the problem and documenting the type and extent of fungal growth are complex processes involving both building physics and indoor mycology. New detection and identification methods have been introduced, and new fungal species have been added to the list of building-related fungi. However, the lack of standardised procedures and general knowledge hampers the effort to resolve the problems and advocate for an effective renovation plan. This review provides a framework for building inspections on current sampling methods and detection techniques for building-related fungi. The review also contains tables with fungal species that have been identified on commonly used building materials in Europe and North America (e.g., gypsum wallboard, oriented strand board (OSB), concrete and mineral wool). The most reported building-associated fungi across all materials are Penicillium chrysogenum and Aspergillus versicolor. Chaetomium globosum is common on all organic materials, whereas Aspergillus niger is common on all inorganic materials. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) with a large chemical diversity are emitted by plant flowers. These compounds play an important role in the ecology of plants. This review presents the different ecological roles of VOCs present in the odor plumes of plant flowers, such as pollination, defense, adaptation to their environment, and communication with other organisms. The production and accumulation sites of VOCs in plants with their spatial and temporal variations, including environmental issues, are also summarized. To evaluate the qualitative and quantitative chemical composition of VOCs, several methods of extraction and analysis were used. Headspace (HS) sampling coupled with solid phase microextraction (SPME) is now well-developed for the extraction process. Parameters are known, and several fibers are now available to optimize this extraction. Most of the time, SPME is coupled with gas chromatography-mass spectrometry (GC-MS) to determine the structural identification of the VOCs, paying attention to the use of several complementary methods for identification like the use of databases, retention indices, and, when available, comparison with authentic standards analyses. The development of the knowledge on VOCs emitted by flowers is of great importance for plant ecology in the context of environmental and climate changes. [ABSTRACT FROM AUTHOR]

Identifying gifted and talented students is one of the biggest challenges that face those working with them. As a result, the purpose of this research was to investigate the most effective methods of identifying gifted and talented students. Furthermore, the study employed both quantitative and qualitative methods. The study's sample size was 465 teachers and administrators, and the results revealed that the level of effective identification methods for gifted and talented students from the teachers' and administrators' point of view who work with them was moderate. As well, the findings showed statistically significant differences due to the gender variable in favor of males and due to the experience variable in favor of those with more than 10 years of experience. Furthermore, the study recommended using new technologies to identify gifted and talented students, as well as rehabilitating and training teachers and administrators on methods of identifying gifted and talented students, whether before or during their service, and providing them with all the necessary knowledge and practical experiences. [ABSTRACT FROM AUTHOR]

Introduction. Vascular pathologies associated with thromboembolism are common complications and the leading cause of morbidity and mortality among patients of various nosological groups. Previously, we obtained water-soluble 2-hydroxy-4-oxo-4-R-2-butenoates of hetarylammonium, which exhibit a significant pharmacological effect on the blood coagulation system». A compound with a pronounced anticoagulant effect was found in various routes of administration. It was of interest to study various methods of confirming the authenticity of a potential anticoagulant.Aim. Development of methods for identification of a potential anticoagulant 2-hydroxy-4-oxo-(4-chlorophenyl)-2-butenoate of thiazolinammonium.Materials and methods. The studies were carried out on three series of the substance 2-hydroxy-4-oxo-(4-chlorophenyl)-2-butenoate of thiazolinammonium obtained in laboratory conditions. The melting point of BAS was measured by the capillary method according to GF XV OFS.1.2.1.0011 "Melting point". The solubility of the substance was determined in accordance with GF XV of the OFS.1.2.1.0005 "Solubility". The absorption spectra in the IR region were taken in accordance with GF XV of the OFS.1.2.1.1.0002 "Spectrophotometry in the middle infrared region". Absorption spectra in the UV region were taken in accordance with GF XV of the OFS.1.2.1.1.0003 "Spectrophotometry in the ultraviolet and visible regions". In carrying out qualitative reactions, reagents prepared in accordance with GF XV of the OFS were used.1.3.0001 "Reagents. Indicators".Results and discussion. A description of the substance has been carried out. The melting point and solubility of the compound were determined. Spectra in the IR and UV regions of the spectrum were taken. Methods were selected, and qualitative reactions of authenticity of a potential anticoagulant were carried out.Conclusion. The studied characteristics of the new BAS can be used in the standardization of the substance according to the indicators "Description", "Solubility", "Identification", "Melting point". These indicators characterize the physico-chemical properties of 2-hydroxy-4-oxo-(4-chlorophenyl)-2-butenoate of thiazolinammonium, and will be included in the draft regulatory documentation for the substance in the future.

At the current stage of economic relations development, taking into account external challenges, certain prerequisites have been formed for the application of project management in the activities of individual business entities, as well as at the level of executive power. The analysis of the results of the implementation of national, federal, regional and departmental projects has shown that the application of the methodology and tools of project management has yielded positive results in solving both economic and social problems. At the same time, state, regional and sectoral problems were identified, which can be avoided with a properly organized risk management system in projects. The existing risk management standards contain the principles on which the risk management system in projects should be based, but they need to be linked to the conditions of national and other projects, which are characterized by scale, long implementation period and a large number of participants. The organization participating in the project has its own risks, which the risk management system is focused on, but getting into the new system of interaction of organizations, additional risks arise. According to the researchers of this problem, new mechanisms are needed not only in each organization, but also an integrated system covering all project participants. The authors believe that one of the possible risk management tools in large-scale projects can be considered a scenario approach to project planning, which will allow the most reasonable formation of financial reserves in the risk management system. It will ensure more effective risk management by building their hierarchical structure in the form of a decision tree with consideration of alternatives to risk exposure. In the risk management system, it is necessary to provide for the process of improvement as an actualization of risks, taking into account the dynamics of factors of the external and internal environment of the project.

Copyright of Acta Sedimentologica Sinica is the property of Acta Sedimentologica Sinica Editorial Office 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.)

Energy poverty is one of the three major crises of the global energy system. It tends to deepen as a result of the imbalance between supply and demand, energy transition and financial factors, especially in rural areas of developing countries. This paper took rural household energy poverty as the subject and collected 27 Chinese papers and 44 English papers from Google Scholar, Sci-hub, CNKI and other academic websites in the academic field on the definition, identification methods, influencing factors and governance countermeasures of energy poverty. It focused on analyzing the influence of income level, geographic location, urban–rural differences, demographic characteristics and other factors on energy poverty, as well as the profound impact of energy poverty on the population's health, the population's economic status, social equity, welfare of the population, the national economic development, etc. It finally landed on the government's countermeasures to govern energy poverty so as to provide references for solving the problem of energy poverty by systematically sorting out the literature. [ABSTRACT FROM AUTHOR]

A study on scientific data citation is crucial to promote data sharing and is the basis for the examination of scientific data measurement and analysis. To this end, it is necessary to identify and label data reference information. Currently, there are many supervised methods for entity recognition and relationship extraction of diseases, drugs, proteins, symptoms, etc., but they have not discussed the effectiveness of scientific data recognition. To fill this gap, the effectiveness of the classical machine learning model and the deep learning model on recognizing scientific data citation are discussed in this study. In experiments, this study took the full text of scientific and technical papers as the research object, conducted annotated citation classification based on rules and manual recognition of their references to form a dataset. The results of the empirical study showed that: (1) the methods used in this paper can achieve automatic identification and extraction of data citations and can address the problem of automating the construction of citation relationships between scientific and technical literature and scientific data; (2) the BERT-based models have the optimal effectiveness in the recognition task of scientific data citation, especially the BioBERT and SciBERT; (3) the full-text information has a crucial impact on the recognition results. [ABSTRACT FROM AUTHOR]

The development of underground artificial cavities plays an important role in the exploitation of urban spatial resources. As the rapidly growing number of underground artificial cavities with different depths and scales increases, the detection and identification of underground artificial cavities has become a key issue in underground engineering studies. Geophysical techniques have been widely used for the construction, management, and maintenance of underground artificial cavities. In this study, we present two identification methods for underground artificial cavities. Apparent resistivity imaging is the most popular technique for quickly identifying underground artificial cavities, using the forward simulation results of a three-dimensional earth model and comparing these with the preset positions of artificial cavities, as demonstrated in the experiment. To further improve the efficiency of underground artificial cavity identification, we developed a fast recognition approach for underground artificial cavities based on the Bayesian convolutional neural network (BCNN). Compared to a traditional convolutional neural network, the performance of the BCNN method was greatly improved in terms of the classification accuracy and efficiency of identifying underground artificial cavities with apparent resistivity image datasets. [ABSTRACT FROM AUTHOR]

The relevance of the analysis of scientific publications devoted to the study of the composition, properties, methods of preparation, areas of application, as well as the qualitative and quantitative identification of glycolipids is determined by the prospects for their use as alternative natural surfactants. Glycolipids possessing comparable surfactant properties with widely used surfactants of a petrochemical nature, and distinguished by the absence of toxicity and environmental friendliness, exhibit pronounced physiological and functional properties.Currently, there are no systematic data covering various aspects of the composition, physicochemical properties of glycolipids.The purpose of this research is to clarify the classification of glycolipids, to summarize data on the advantages and disadvantages of various industrial methods for obtaining glycolipids; systematization of data on the properties of glycolipids by application; identification of the most effective methods for the qualitative and quantitative identification of glycolipids.Particular attention is paid to the analysis of data on the possibility of isolating glycolipids from plant materials, including secondary resources of the oil and fat industry.The data presented in the review indicate that glycolipids, including those isolated from plant materials, are characterized by a high biotechnological potential for their use in the creation of pharmaceuticals, cosmetics, and functional foods.Of the known methods for the industrial production of glycolipids, currently the most common and cost-effective methods are those based on microbiological and enzymatic synthesis.Promising raw materials for the production of glycolipids are secondary products of processing of oilseeds – phosphatide emulsions and phosphatide concentrates containing up to 5% glycolipids in their composition. There are currently no methods for obtaining glycolipids from this type of raw material.Of the known methods for the qualitative and quantitative identification of glycolipids (TLC, HPTLC, HPLC, NMR), the most promising method is high-resolution NMR spectroscopy, as it is the most informative, rapid and accurate.

Papilio saharae Oberthür, 1879 (Papilionidae) was reported from Sicily on a handful of occasions in the last decade or so. On at least two instances, the taxon was claimed to have been discovered in museum collections, respectively by Moonen (2012) at the Zoological Museum, Amsterdam (ZMA) and Leraut (2016) at the Muséum National d'Histoire Naturelle in Paris. These records and a proposed nomenclatural change for P. machaon melitensis, were subsequently rejected by Coutsis et al. (2018). The present contribution provides a critique of the methodologies employed by the various authors and acknowledges that there remains much scope to investigate the P. machaon-complex further while maintaining that a more holistic approach is required to better understand the multidimensional dynamics that have shaped the biogeography of the central Mediterranean area. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University 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.)

Volatile organic compounds (VOCs) with a large chemical diversity are emitted by plant flowers. These compounds play an important role in the ecology of plants. This review presents the different ecological roles of VOCs present in the odor plumes of plant flowers, such as pollination, defense, adaptation to their environment, and communication with other organisms. The production and accumulation sites of VOCs in plants with their spatial and temporal variations, including environmental issues, are also summarized. To evaluate the qualitative and quantitative chemical composition of VOCs, several methods of extraction and analysis were used. Headspace (HS) sampling coupled with solid phase microextraction (SPME) is now well-developed for the extraction process. Parameters are known, and several fibers are now available to optimize this extraction. Most of the time, SPME is coupled with gas chromatography-mass spectrometry (GC-MS) to determine the structural identification of the VOCs, paying attention to the use of several complementary methods for identification like the use of databases, retention indices, and, when available, comparison with authentic standards analyses. The development of the knowledge on VOCs emitted by flowers is of great importance for plant ecology in the context of environmental and climate changes.

Biometrics plays a pivotal role in enhancing security, ensuring accurate identification, and offering convenient solutions across diverse industries. Its uniqueness, reliability, and potential for future advancements establish it as a crucial and valuable field in today's digital landscape. Fingerprint authentication in ATMs presents primary advantages such as heightened security through distinctive identification and user convenience by eliminating the reliance on PINs or passwords. This research paper focuses on conducting a comprehensive review and comparative analysis of various approaches for fingerprint identification, aiming to contribute to the understanding of effective and efficient methods in the context of ATM authentication. [ABSTRACT FROM AUTHOR]

This paper is concerned with identifying the instantaneous modal parameters of forced oscillatory systems with response-dependent generalized inertia (mass, inductance, or equivalent) based on their measured dynamics. An identification method is proposed, which is a variation of the "FORCEVIB" method. The method utilizes analytic signal representation and the properties of the Hilbert transform to obtain an analytic relationship between a system's natural frequency and damping coefficient to its response and excitation signals. The proposed method is validated by comparing the identification results to the asymptotic solution of a simple system with response-dependent inertia and is then demonstrated, numerically and experimentally, for other more complicated nonlinear systems. [ABSTRACT FROM AUTHOR]

Energy poverty is one of the three major crises of the global energy system. It tends to deepen as a result of the imbalance between supply and demand, energy transition and financial factors, especially in rural areas of developing countries. This paper took rural household energy poverty as the subject and collected 27 Chinese papers and 44 English papers from Google Scholar, Sci-hub, CNKI and other academic websites in the academic field on the definition, identification methods, influencing factors and governance countermeasures of energy poverty. It focused on analyzing the influence of income level, geographic location, urban–rural differences, demographic characteristics and other factors on energy poverty, as well as the profound impact of energy poverty on the population’s health, the population’s economic status, social equity, welfare of the population, the national economic development, etc. It finally landed on the government’s countermeasures to govern energy poverty so as to provide references for solving the problem of energy poverty by systematically sorting out the literature.

In this paper, some multivariate and double multivariate modelling approaches are presented. Moreover, this article provides an overview of the modelling of the structure of the covariance matrix. Furthermore, some methods of covariance structure identification are given. [ABSTRACT FROM AUTHOR]

Specific learning disorder (SLD) identification is arguably one of the most significant controversies in school psychology. One component of this issue is that guidelines and practices vary substantially across professionals and states, which leads to inconsistent identification rates and outcomes for students. To assess the extent of this problem at the district level, we surveyed special education administrators from 725 US school districts regarding their districts' current specific learning disability (SLD) identification practices in the USA. Significant differences in SLD identification methods were reported across districts. Significant differences in SLD identification methods were also found across regions and between districts that used different educators to collect academic achievement test data. Curriculum-based measures were also used more frequently in districts that identify SLD using response to intervention. Implications of these findings for policy and for practice are considered. [ABSTRACT FROM AUTHOR]

Water-retaining structures built with or on dispersive soil may easily be destroyed then after dangerous accidents associated with dispersive soil conditions, such as piping, caves and gullies, can occur. This study aims to propose a complete procedure to be followed when there is dispersive soil in water conservancy engineering or geotechnical engineering. The field investigations, empirical formulas and laboratory tests were conducted to define the dispersivity of Huaaopao soil samples. Among them, laboratory tests include pinhole tests, crumb tests, double hydrometer tests, pore water soluble cation tests and exchangeable sodium ion percentage tests. The dispersive mechanisms of the soil samples with dispersivity were analyzed from physical and chemical views. And the modified dose of lime on the dispersive soil samples was tested by pinhole tests and crumb tests. The results show that the soil samples TK4, TK8 to TK13 were dispersive, the soil sample TK15 was transitional, and the soil sample TK21 was not dispersive. The clay content of TK9 was less than 10% (physical level); the pH, the ESP and the PS were greater than 9.5, 7% and 60% (chemical level), respectively, resulting in its dispersivity. The TK4, TK8, TK10 to TK13 were dispersive only because of chemical factors with higher pH, ESP and PS. It is suggested to use 1 ~ 2% lime (mass fraction) to alter the dispersivity of dispersive soil samples in Huaaopao water conservancy project. [ABSTRACT FROM AUTHOR]

Microplastic is an emerging pollutant causing trouble worldwide due to its extensive distribution and potential hazards to the ecological system. Some fundamental questions about microplastics, such as their presence, source, and possible hazards, remain unanswered. These issues develop because of a lack of systematic and comprehensive microplastic analysis. As a result, we thoroughly evaluated current knowledge on microplastics, including detection, characterization, occurrence, source, and potential harm. Microplastics are found in seawater, soil, wetlands, and air matrices worldwide based on findings. Visual classification, which can be enhanced by combining it with additional tools, is one of the most used methods for identifying microplastics. As soon as is practicable, microplastics analytical methods ought to be standardized. New techniques for analyzing nano-plastics are urgently needed in the meantime. Numerous studies have shown that microplastics’ impacts on people and soil are significantly influenced by their size, shape, and surface physicochemical characteristics. Finally, this study suggests areas for future research based on the knowledge gaps in the area of microplastics. [ABSTRACT FROM AUTHOR]

Clay minerals are widely distributed and are important components in sedimentary rocks. The identification and quantification of detrital and authigenic clay minerals have been hot topics recently due to the needs of petroleum geology, paleoclimate, and sedimentary history research. Detrital clay minerals exhibit the phenomenon of discrete grain boundaries, while authigenic clay minerals have various specific particle shapes. The differences in crystal structure of different clay mineral origins are reflected in the polytype character of clay minerals, especially for illite and chlorite. Different origins of clay minerals inherently have different chemical characteristics. Instead of focusing only on conventional techniques (scanning electron microscopy, X-ray diffraction, and geochemical analysis), here we review established approaches and introduce emerging analytical techniques (automated mineralogy techniques and artificial intelligence techniques) that can complement current methods. In addition, the applications of these techniques in illite age analysis, paleoclimate reconstruction, and reservoir properties are discussed. Further, different state-of-the-art techniques for clay mineral identification and quantification (e.g., scanning electron microscopy for specific petrographic characterization, X-ray diffraction for bulk crystal structure identification, etc.) are discussed. We propose that combining individual and bulk techniques obtained at multiple scales can provide novel insights for deciphering various clay mineral origins. Understanding the characteristics of clay minerals from different origins is of great importance to scientific issues such as shale oil and gas exploration., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The development of underground artificial cavities plays an important role in the exploitation of urban spatial resources. As the rapidly growing number of underground artificial cavities with different depths and scales increases, the detection and identification of underground artificial cavities has become a key issue in underground engineering studies. Geophysical techniques have been widely used for the construction, management, and maintenance of underground artificial cavities. In this study, we present two identification methods for underground artificial cavities. Apparent resistivity imaging is the most popular technique for quickly identifying underground artificial cavities, using the forward simulation results of a three-dimensional earth model and comparing these with the preset positions of artificial cavities, as demonstrated in the experiment. To further improve the efficiency of underground artificial cavity identification, we developed a fast recognition approach for underground artificial cavities based on the Bayesian convolutional neural network (BCNN). Compared to a traditional convolutional neural network, the performance of the BCNN method was greatly improved in terms of the classification accuracy and efficiency of identifying underground artificial cavities with apparent resistivity image datasets.

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of "-omics" approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis. [ABSTRACT FROM AUTHOR]

DNA barcoding allows the identification of an organism by comparing the sequence of selected DNA regions (barcodes) with a previously compiled database, and it can be useful for taxonomic identification of species in complex genera, such as Tamarix. Many species of this genus show convergent morphology, which leads to frequent errors in their identification. Highly variable genetic markers, such as microsatellites or short sequence repeats (SSR), could be used to differentiate species where DNA barcodes fail. Here, we tested the ability of both, 5 different marker regions (rbcL, matK, ITS, trnH‐psbA, and ycf1), and 14 microsatellites, to properly identify Tamarix species, especially those from the Mediterranean Basin, and compared the pros and cons of the different analytical methods for species identification. DNA barcoding allows the genetic identification of certain species in Tamarix. The two‐locus barcodes matK + ITS and ITS + ycf1 were the best‐performing combinations, allowing up to 69% and 70%, respectively, correct identification. However, DNA barcoding failed in phylogenetically close groups, such as many Mediterranean species. The use of SSR can aid the identification of species, and the combination of both types of data (DNA barcoding and SSR) improved the success. The combination of data was especially relevant in detecting the presence of hybridization processes, which are common in the genus. However, caution must be exercised when choosing the clustering methods for the SSR data since different methods can lead to very different results. [ABSTRACT FROM AUTHOR]

We consider the problem of estimating a vector of unknown constant parameters for a class of hybrid dynamical systems – that is, systems whose state variables exhibit both continuous (flow) and discrete (jump) evolution – with dynamics that depend linearly on the unknown parameters. Using a hybrid systems framework, we propose a hybrid estimation algorithm that can operate during both flows and jumps that, under a notion of hybrid persistence of excitation, guarantees convergence of the parameter estimate to the true value. Furthermore, we show that the parameter estimate is input-to-state stable with respect to a class of hybrid disturbances. Simulation results including a spacecraft application show the merits of our proposed approach. [ABSTRACT FROM AUTHOR]

Models of dynamical systems are often built from observed data using system identification techniques, and the uncertainty in the model parameters is commonly described using confidence regions to which the true model parameters belong with a certain probability. In this paper we propose methods which use the scenario approach to solve robust optimisation problems for model based design where there is uncertainty in the model parameters. The methods draw samples (scenarios) of the uncertain model parameters and solve an optimisation problem only involving the drawn scenarios. Both a Bayesian system identification setting where the model parameters are stochastic, and a non-Bayesian system identification setting where the model parameters are treated as being deterministic are considered. The Bayesian and non-Bayesian settings require different treatment, and whereas standard scenario optimisation theory can be directly utilised in the Bayesian setting, this is not the case in the non-Bayesian setting. For that reason the model class is restricted to linear regression models with deterministic regressors in the non-Bayesian case. Algorithms are proposed for drawing samples of the parameters such that the uncertainties in the system identification models are reflected in the samples. Theoretical results are given bounding the probability that the found solution to the scenario optimisation problem will give a worse performance when applied to the true system than seen on the drawn scenarios. The methods are illustrated in simulation examples showing good performance. [ABSTRACT FROM AUTHOR]

As an alternative resource, reclaimed water is rich in the various nutrients and organic matter that may irreparably endanger groundwater quality through the recharging process. During groundwater recharge with reclaimed water, hot spots and hot moments (HSHMs) in the hyporheic zones, located at the groundwater–reclaimed water interface, play vital roles in cycling and processing energy, carbon, and nutrients, drawing increasing concern in the fields of biogeochemistry, environmental chemistry, and pollution treatment and prevention engineering. This paper aims to review these recent advances and the current state of knowledge of HSHMs in the hyporheic zone with regard to groundwater recharge using reclaimed water, including the generation mechanisms, temporal and spatial characteristics, influencing factors, and identification indicators and methods of HSHMs in the materials cycle. Finally, the development prospects of HSHMs are discussed. It is hoped that this review will lead to a clearer understanding of the processes controlling water flow and pollutant flux, and that further management and control of HSHMs can be achieved, resulting in the development of a more accurate and safer approach to groundwater recharge with reclaimed water. [ABSTRACT FROM AUTHOR]

In this research, the risk identification methods on chemical industry safety were reviewed at home and abroad, involving the chemicals, chemical reactions, production facilities and transmission pipelines,. Both qualitative and quantitative analysis are conducted to compare these methods of risk identification. As the most frequently used qualitative method, HAZOP (Hazard and Operability Analysis) was usually used for the identification of technology deviation and FMEA (Failure Model and Effects Analysis) was aimed to identify the cause of accident. Besides, FTA (Fault Tree Analysis) and ETA (Event Tree Analysis) were used to identify the severity of accident consequences from a quantitative perspective. The identification on possibility and severity of accidents in the whole chemical industry can be achieved by combining the qualitative and quantitative methods, but the fuzzy risk factors in chemical industry should be analyzed by using the fuzzy mathematics method. In the future, risk identification methods need to be combined with the statistical model and big data algorithms so as to improve the intrinsic safety level of chemical technology. [ABSTRACT FROM AUTHOR]

• Identification of microorganisms is necessary for cultural heritage prevention. • Microorganisms can colonise and deteriorate any cultural heritage object. • A wide range of microbial identification studies have emerged since first NGS. • Culture-dependant techniques still dominate in the field of cultural heritage. Cultural heritage includes everything that mankind has created in the past and has impacted the development of culture. These objects can be subject to biodeterioration, including the activity of microorganisms, which can lead to the incalculable loss of records of our history. Therefore, it is essential to identify the microorganisms present on the surface of historical objects, monitor their metabolic activity, and based on this knowledge, find a possible way to protect the cultural heritage. This paper focuses on the most endangered cultural heritage objects (wooden objects, written documents, audio-visual materials, textiles, stone objects, paintings, and stained-glass windows), describes the materials that these objects are made of and the reasons for their biodeterioration. Furthermore, we provide an overview of all microbial identification methods used in the field of cultural heritage since 2005, when the first next-generation sequencing technique originated. [ABSTRACT FROM AUTHOR]

The reliability of evidence in a criminal trial is a multidimensional issue and relates to the assessment of the evidential value of a specific circumstance established in the case through activities performed by expert witness or authorities. The reliability (trustworthy) of the source of evidence and identification methods, performance of research, deduction and the context of other evidence seem to be one of the important implications for the evidential value. Results of the survey of participants of the criminal trial (police officers, prosecutors and experts) and comparative group on the perception of various features of identification methods and selected aspects related to the status of a forensic expert is presented in the article. In the first part of the study, the identification methods were ranked in terms of their scientificity, reliability and willingness to convict on the basis of the method’s results. The research shows that the assessment of the method’s reliability is significantly correlated with the assessment of its scientificity. However, some exceptions to this relationship have been identified, indicating that the reliability of the method may also be the result of an assessment of its suitability and effectiveness. The second part of the research was focused on assessing the reliability of various expert opinions. The place of examinations carried out by an expert is important for the participants of the criminal trial. Opinions of forensic experts performed at specialist institutions were assessed as the most reliable. [ABSTRACT FROM AUTHOR]

The high-resolution nuclear magnetic resonance method presents great opportunities for the identification and screening evaluation of vegetable oils and their mixtures. In recent years, a large number of studies have appeared that have shown that the use of high-resolution nuclear magnetic resonance is a modern effective alternative to traditional methods of instrumental analysis in identifying and evaluating the quality of vegetable oils. At the same time, to optimize the method and improve the accuracy and reliability of the results obtained, it is necessary to continue research and form a data bank for various types of oils and their mixtures. The purpose of this work is to study the prospects and possibilities of using the nuclear magnetic resonance method to identify the most common vegetable oils and their mixtures. 8 samples of vegetable oils of various types and methods of processing, including a mixture of sunflower oil with olive oil, were studied. Nuclear magnetic resonance spectra were obtained and processed for all the samples studied and the correlation of the obtained data with the composition of fatty acids was carried out. The paper proposes a method for analyzing experimental high-resolution nuclear magnetic resonance spectra of vegetable oils. The data obtained has confirmed that the high-resolution nuclear magnetic resonance method can be successfully used for screening analysis of various vegetable oils and their mixtures to identify and determine the presence of foreign substances. [ABSTRACT FROM AUTHOR]

Electrical injury is a relatively uncommon but potentially devastating form of multi-system injury with high morbidity and mortality. In common electric injury cases, it is usually difficult to find characteristic changes of electric injury in major organs by using routine histopathological test methods unless there are landmark traces of electric injury, known as electric marks. How to determine electric shock death, especially in the absence of typical electrical marks on the body surface in some cases (which account for about two-thirds of electric injury cases), remains a challenging problem in forensic practice. Our summary shows that many current related studies have focused their efforts to find characteristic histopathological changes in major organs of the body caused by electric injury. Based on the results obtained through comparison of the literature, we find that it may be more urgent and important to find the optimal autopsy or sampling sites in cases with no typical electric marks, knowing that these sites may often reflect the most significant histopathological changes of electric injury, for instance anatomy and sampling of the anterior wrist and the medial malleolus in cases involving the hand-to-foot electric circuit pathway. In this article, we make a summary of advances in identification methods of electric injury, hoping that it could provide some new insights for further research in this field. [ABSTRACT FROM AUTHOR]

Resistome is a cluster of microbial genes encoding proteins with necessary functions to resist the action of antibiotics. Resistome governs essential and separate biological functions to develop resistance against antibiotics. The widespread clinical and nonclinical uses of antibiotics over the years have combined to select antibiotic-resistant determinants and develop resistome in bacteria. At present, the emergence of drug resistance because of resistome is a significant problem faced by clinicians for the treatment of Salmonella infection. Antibiotic resistome is a dynamic and ever-expanding component in Salmonella. The foundation of resistome in Salmonella is laid long before; therefore, the antibiotic resistome of Salmonella is reviewed, discussed, and summarized. We have searched the literature using PubMed, MEDLINE, and Google Scholar with related key terms (resistome, Salmonella, antibiotics, drug resistance) and prepared this review. In this review, we summarize the status of resistance against antibiotics in S. typhi, highlight the seminal work in the resistome of S. typhi and the genes involved in the antibiotic resistance, and discuss the various methods to identify S. typhi resistome for the proactive identification of this infection and quick diagnosis of the disease. [ABSTRACT FROM AUTHOR]

We sought to operationalize and validate data-driven approaches for identifying transgender individuals in the Veterans Health Administration (VHA) of the US Department of Veterans Affairs (VA) through a retrospective analysis using VA administrative data from 2006–2018. Besides diagnoses of gender identity disorder (GID), a combination of non-GID data elements was used to identify potentially transgender veterans, including 1) an International Classification of Diseases (Ninth or Tenth Revision) code of endocrine disorder, unspecified or not otherwise specified; 2) receipt of sex hormones not associated with the sex documented in the veteran's records (gender-affirming hormone therapy); and 3) a change in the veteran's administratively recorded sex. Both GID and non-GID data elements were applied to a sample of 13,233,529 veterans utilizing the VHA of the VA between January 2006 and December 2018. We identified 10,769 potentially transgender veterans. Based on a high positive predictive value for GID-coded veterans (83%, 95% confidence interval: 77, 89) versus non–GID-coded veterans (2%, 95% confidence interval: 1, 11) from chart review validation, the final analytical sample comprised only veterans with a GID diagnosis code (n  = 9,608). In the absence of self-identified gender identity, findings suggest that relying entirely on GID diagnosis codes is the most reliable approach for identifying transgender individuals in the VHA of the VA. [ABSTRACT FROM AUTHOR]

This paper considers system identification (ID) of linear and nonlinear non-autonomous systems from noisy and sparse data. We analyze an optimization objective derived from Bayesian inference for the dynamics of hidden Markov models. We then relate this objective to that used in several state-of-the-art approaches for both linear and nonlinear system ID. In the former, we analyze least squares approaches for Markov parameter estimation, and in the latter, we analyze the multiple shooting approach. We demonstrate the limitations of the optimization problems posed by these existing methods by showing that they can be seen as special cases of the proposed optimization objective under certain simplifying assumptions: conditional independence of data and zero model error. Furthermore, we observe that the proposed approach has improved smoothness and inherent regularization that make it well-suited for system ID and provide mathematical explanations for these characteristics' origins. Finally, numerical simulations demonstrate a mean squared error over 8.7 times lower compared to multiple shooting when data are noisy and/or sparse. Moreover, the proposed approach identifies accurate and generalizable models even when there are more parameters than data or when the system exhibits chaotic behavior. • Modeling of model uncertainty with process noise leads to inherent regularization. • Process noise induces objective function smoothness similarly to multiple shooting. • Certain Markov parameter estimation methods treat data as conditionally independent. • Bayesian system ID outperforms state-of-the-art methods on small, noisy datasets. [ABSTRACT FROM AUTHOR]

Fungal infections of the skin, hair, and nails are the most prevalent among all fungal infections, currently affecting over 20–25% of the world’s human and animal populations. Dermatophytes are the etiological factors of the most superficial fungal infections. Among other pathogenic filamentous fungi, what distinguishes them is their unique attribute to degrade keratin. The remarkable ability of this group of fungi to survive in different ecosystems results from their morphological and ecological diversity as well as high adaptability to changing environmental conditions. Dermatophytes, although they are one of the oldest groups of microorganisms recognised as pathogens, have not been classified in a stable taxonomic system for a long time. In terms of diagnostics, dermatophytes still pose a serious problem in the identification procedure, which is often related to therapeutic errors. The increasing number of infections (including zoonoses), the lack of taxonomic stability, and the ambiguous clinical picture of dermatomycosis cases necessitate the search for new methods for the rapid, cheap, and reproducible species identification of these fungi. In turn, the species identification is determined by the clarity of classification criteria combined with the taxonomic division generally accepted by microbiologists and referring to the views expressed by clinicians, epidemiologists, and scientists. In this paper, the authors present the evolution of taxonomic systems for dermatophytes over the history of microbiology development. The discovery of new facts about the biology and ecology of dermatophytes and the development of techniques applied in a mycological diagnosis laboratory facilitated the development of new identification strategies at various points in the history. The modern molecular classification system of these pathogens seems to be stable and widely accepted. However, will it end the long-standing classification confusion and the period of hundreds of nomenclatural changes, which are a diagnostician’s nightmare? It can be argued that the taxonomy of dermatophytes, in particular that of anthropophilic species, is sufficiently established and stable for the benefit of both clinicians and scientists.

Background: There is evidence that tap water is the vehicle through which nontuberculous mycobacteria (NTM) infect or colonize the human body. The objective of this study was to determine the presence and diversity of NTM in the water distribution system of Bahía Blanca city, Argentina (sites S2/S3) and in the dike that supplies water to it (S1). Methods: Culture-dependent method, biochemical tests, and molecular method (16S rRNA sequencing gene) were combined to detect and identify NTM. Results: NTM were isolated in 51.6% (64/124) of all the samples analyzed. Mycobacterium gordonae was the most frequently isolated organism (15/64) in all samples analyzed, followed by Mycobacterium peregrinum and Mycobacterium frederiksbergense. Significant differences were found in the residual chlorine values between sampling S2 and S3. In both sites, maximum counts were recorded but they did not correlate with low chlorine values. A concentration higher than 500 colony-forming unit/L of NTM was never found, which can be attributed to the negative effect caused by decontamination methods being a point to consider for the recovery of NTM. In 46.9% (30/64) of samples, both methods coincided in the identification, and the obtained sequences presented ≥99% identity. Identification at the species level was achieved in 50% (32/64) of the isolates. Nearly 17.2% (11/64) of the isolates showed a similarity

piRNAs are a class of small non-coding RNA molecules, which interact with the PIWI family and have many important and diverse biological functions. The present review is aimed to provide guidelines and contribute to piRNA research. We focused on the four types of identification models on piRNA-related molecules, including piRNA, piRNA cluster, piRNA target, and disease-related piRNA. We evaluated the types of tools for the identification of piRNAs based on five aspects: datasets, features, classifiers, performance, and usability. We found the precision of 2lpiRNApred was the highest in datasets of model organisms, piRNN had a better performance of datasets of non-model organisms, and 2L-piRNA had the fastest recognition speed of all tools. In addition, we presented an overview of piRNA databases. The databases were divided into six categories: basic annotation, comprehensive annotation, isoform, cluster, target, and disease. We found that piRNA data of non-model organisms, piRNA target data, and piRNA–disease-associated data should be strengthened. Our review might assist researchers in selecting appropriate tools or datasets for their studies, reveal potential problems and shed light on future bioinformatics studies. [ABSTRACT FROM AUTHOR]

The obtaining of gas turbine engine mathematical models from experimental data with identification or refinement of their unit characteristics and the use of such models in parametric diagnostics methods is considered. The solution of improperly posed problems, where the number of equations is not equal to the number of unknowns, is proposed to be solved by a mathematical method specially developed using the stability of estimates. [ABSTRACT FROM AUTHOR]