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Global policies increasingly focus on the importance of maintaining or improving the integrity of ecosystems, but defining, assessing, and monitoring integrity in marine protected areas (MPAs) remains a challenge. In this paper, we conceptualized ecological integrity along dimensions of heterogeneity and stability containing seven components: physical structure, diversity, function, persistence, resistance, resilience, and natural variability. Through a structured literature search, we identified indicators and metrics used for quantifying ecosystem status components in the marine environment, then reviewed MPA management plans worldwide for inclusion of these components. We evaluated 202 papers applying 83 ecological indicators built from 72 metrics. Ecosystem components were most comprehensively addressed by metrics of taxa presence, organisms count, and area occupied by benthic organisms, and community structure, biomass, and percent cover indicators. Of the 557 MPA management plans we reviewed globally, 93% used at least one ecosystem status term or its synonym in an ecologically relevant context, but 39% did not address any components of stability. In particular, resistance was mentioned in only 1% of management plans, but in some cases it may be inferred from indicators and metrics used to track the best addressed component in management plans, diversity. Plans for MPAs with both an ecological/biological purpose and a research and education purpose contained ecosystem status terms more frequently than other plans, suggesting that engagement with the scientific community may have improved the application of these terms. An improved understanding of how to operationalize and measure ecological integrity can help MPA monitoring and management. [ABSTRACT FROM AUTHOR]

Objective: This purpose of this paper is to describe the characteristics of recovered Lake Trout Salvelinus namaycush populations in Lake Superior by describing its population dynamics, ecology, and recent research and management activities since 1993, when Lake Trout were declared rehabilitated. Methods: Data from commercial fisheries, recreational fisheries, agency stocking reports, and natural resource agency fishery‐independent survey data along with published research findings on lean Lake Trout in Lake Superior between 1993 and 2022 were synthesized and reported. Result: Currently, Lake Trout populations are self‐sustaining and lightly exploited with only a few areas with elevated total mortality rates. The total annual mortality has been far below the target maximum range of 42–45%. Furthermore, stocking of hatchery Lake Trout is no longer necessary. Conclusion: We have learned from research and management experience that the regulatory role of Lake Trout in the Great Lakes is critical to proper ecosystem function. Thus, continued commitment from natural resource agencies to cooperate and implement effective management actions is required to preserve the accomplishments of lakewide recovery of Lake Trout populations. Impact statementThe Lake Trout is the keystone predator in deepwater areas of the Great Lakes, and its successful recovery in Lake Superior has restored ecosystem stability and valued fisheries. This paper synthesizes information that describes the status of a highly managed species after restoration objectives have been achieved and maintained. [ABSTRACT FROM AUTHOR]

Climate change, land degradation, and limited land and water resources have challenged our ability to meet the food demand of a rapidly growing population. To tackle this challenge, modern agricultural systems are relying on new technologies like the Internet of Things (IoT) to improve agricultural productivity and resource use efficiency. Although IoT has gained considerable attention in the last few years, the key concepts of IoT and their applicability across different domains of agriculture are still new to many researchers, practitioners, managers, and policymakers. In this paper, we provide a comprehensive review of the use of different IoT platforms, wireless sensor networks, and other associated technologies like remote sensing, cloud computing, and big data analytics in digital agriculture. The review also explores the use of communication technologies, microcontrollers, and machine learning in smart irrigation and decision support systems. The necessity of interoperability (data transfer and communication without human interference) among devices is discussed in detail with regard to facilitating and exchanging agricultural data more effectively. The discussion also includes opportunities and challenges in standardizing IoT; developing energy‐efficient and affordable technologies; and improving data collection, transfer, storage, processing, security, anonymity, and privacy. This paper further calls for collaborative research in sensor and communication technologies in the agricultural sector. Core Ideas: Different platforms, sensors, and structures of IoT in digital agriculture were reviewed.The application of IoT in data management, interoperability, and precision farming was reviewed.Potential of IoT to improve agricultural quality and productivity was highlighted.Challenges and opportunities of IoT in digital agriculture were discussed. [ABSTRACT FROM AUTHOR]

The development of the Internet of Things (IoT) and machine learning (ML) technologies has triggered smart agricultural systems. In smart agriculture, irrigation management plays a major role to reduce water waste. The monitoring settings, hardware modules, communication technology, and storage systems used in smart irrigation systems were analyzed to determine the optimal nature of water flow. This assessment aims to give an overview of the current state of the irrigation system by taking into account weather and soil moisture. This paper provides a comprehensive review of the utilization of various hardware modules in smart irrigation systems. Moreover, various communication technologies that aid in data transfer for efficient smart irrigation are reviewed. The ML method used for prediction is also evaluated, as well as based storage technologies like the cloud and databases used to store data for predictive irrigation systems. As a result, the paper provides an overview of all the factors that contribute to irrigation systems' smart operation as well as potential future paths for improving agricultural systems through IoT. Core Ideas: Irrigation management is crucial in smart agriculture for minimizing water waste.This apper presents the ideal type of water flow that was determined by smart irrigation systems.Monitoring configurations, hardware modules, communication technology, and storage systems were analyzed in the smart irrigation system. [ABSTRACT FROM AUTHOR]

Leadership roles must incorporate representation from all involved individuals for the resulting decision‐making process to reflect the interests and expertise of a diverse organization. Many resources have rightly focused on developing historically underrepresented racial and ethnic (HURE) leaders. Though numbers of Black and Hispanic dental school deans have increased, more work is needed for these and other HURE groups such as American Indians. Asians are not classified as HURE. As an aggregated group they have robust presence in the dental workforce in North America, the United Kingdom and Australia. The assumption is they are fine, so the group is ignored. Previous research indicates Asians are almost invisible in leadership roles in dentistry, and while the "Glass Ceiling" phenomenon for women persists, Asian women face even greater obstacles to leadership. This paper explores cultural factors contributing to the "Bamboo Ceiling", such as Confucian values emphasizing collectivism and deference to authority. It examines challenges faced by Asian women at the intersection of gender and race. The impact of the "Model Minority Myth" compounds these challenges, leading to overlooking diverse needs. The importance of dispelling these harmful myths is underscored. This paper provides strategies to combat them, urging proactive efforts from minorities and management. By shedding light on the "Bamboo Ceiling" and the "Model Minority Myth", this paper aims to reassess existing norms, current policies and procedures pertaining to equitable representation and leadership opportunities for Asian women in academic dentistry, community oral health, research, and in dental corporations. [ABSTRACT FROM AUTHOR]

Creativity researchers are increasingly interested in understanding when, how, and for whom creativity can be beneficial. Previous reviews have demonstrated that creativity research largely ignores the study of its impact on factors that promote health, and well‐being among populations of adults. It is unclear, in fact, whether this gap in research also extends to creativity research among young children. This paper addresses this issue. Early childhood is a crucial stage for the cognitive development of young children who remain highly sensitive to stress, and adversity. It is therefore essential to identify and promote factors that are beneficial to early childhood resilience, thereby contributing to documenting more of the effects of creative activities on positive outcomes. This paper presents a review with a bibliometric analysis of 1000 randomly selected articles from the Web of Science, without bias towards any specific peer‐reviewed journal. The analysis of 454 included articles shows that approximately 80% of the included studies focus on creativity as an outcome (replicating previous findings with a larger sample), with only 3.78% investigating creative activities as predictors among young children. In this small percentage, most of the studies addressed creative activities in young children related to resilience outcomes. [ABSTRACT FROM AUTHOR]

The American Water Works Association (AWWA) awards individuals and organizations in various categories for their contributions to the water profession and industry. These awards recognize leadership, research, innovation, diversity and inclusion, public service, and volunteerism. The article also mentions awards for best articles, papers, source water protection, academic achievement, and scholarships. The recipients of these awards come from different regions and organizations, showcasing the diverse efforts and achievements in water management. [Extracted from the article]

Violence can be committed anywhere, even in crowded places. It is hence necessary to monitor human activities for public safety. Surveillance cameras can monitor surrounding activities but require human assistance to continuously monitor every incident. Automatic violence detection is needed for early warning and fast response. However, such automation is still challenging because of low video resolution and blind spots. This paper uses ResNet50v2 and the gated recurrent unit (GRU) algorithm to detect violence in the Movies, Hockey, and Crowd video datasets. Spatial features were extracted from each frame sequence of the video using a pretrained model from ResNet50V2, which was then classified using the optimal trained model on the GRU architecture. The experimental results were then compared with wavelet feature extraction methods and classification models, such as the convolutional neural network and long short‐term memory. The results show that the proposed combination of ResNet50V2 and GRU is robust and delivers the best performance in terms of accuracy, recall, precision, and F1‐score. The use of ResNet50V2 for feature extraction can improve model performance. [ABSTRACT FROM AUTHOR]

The performance of face recognition (FR) has reached a plateau for public benchmark datasets, such as labeled faces in the wild (LFW), celebrities in frontal‐profile in the wild (CFP‐FP), and the first manually collected, in‐the‐wild age database (AgeDB), owing to the rapid advances in convolutional neural networks (CNNs). However, the effects of faces under various fine‐grained conditions on FR models have not been investigated, owing to the absence of relevant datasets. This paper analyzes their effects under different conditions and loss functions using K‐FACE, a recently introduced FR dataset with fine‐grained conditions. We propose a novel loss function called MixFace, which combines classification and metric losses. The superiority of MixFace in terms of effectiveness and robustness was experimentally demonstrated using various benchmark datasets. [ABSTRACT FROM AUTHOR]

This paper presents methods for reducing the peak‐to‐average power ratio (PAPR) of the orthogonal time frequency space (OTFS) signal. These methods mainly consist of two operations: symbol interferometry (SI) and either μ‐law or A‐law companding. SI spreads the data of one OTFS symbol onto all symbols and is implemented using a simple inverse fast Fourier transform operation on each OTFS symbol. During the second operation, the PAPR of the OTFS signal is significantly reduced. For our performance analysis, the complementary cumulative distribution function, probability density function, and bit error rate are illustrated through simulations performed in MATLAB. The performance is also analyzed using a solid‐state power amplifier at the transmitter and compared with OTFS, μ‐law‐based OTFS, and SI OTFS systems. The results indicate that the proposed OTFS system achieves a low PAPR. [ABSTRACT FROM AUTHOR]

THIS MONTH: Cleaning surgical instruments after use in a procedure involving chemotherapeutic medications Key words: deactivation, decontamination, cleaning, disinfection, chemotherapeutic medication. Paper count sheets sterilized inside instrument sets Key words: count sheets, instrument sets, printer ink, toner, toxicity. Off‐label use of dental devices during direct laryngoscopy Key words: mouth guard, dental injury, direct laryngoscopy, anesthesia, intubation. Using intermittent pneumatic compression devices on patients in lithotomy position Key words: mechanical compression devices, compartment syndrome, lithotomy, venous thromboembolism, thromboprophylaxis. [ABSTRACT FROM AUTHOR]

The dilemma surrounding faculty shortages within dental education continues to present significant challenges for the dental profession. There remains a tremendous need to create an effective and sustainable pathway for the recruitment of faculty into dental academia, with an emphasis on the establishment of a more diverse and representative faculty composition. This perspective paper proposes a blueprint to nurture and inspire dental students into academia. [ABSTRACT FROM AUTHOR]

With an explosive increase of data produced annually, researchers have been attempting to develop solutions for systems that can effectively handle large amounts of data. Single‐operating‐system (OS) non‐uniform memory access (NUMA) abstraction technology is an important technology that ensures the compatibility of single‐node programming interfaces across multiple nodes owing to its higher cost efficiency compared with scale‐up systems. However, existing technologies have not been successful in optimizing user performance. In this paper, we introduce a single‐OS NUMA abstraction technology that ensures full compatibility with the existing OS while improving the performance at both hypervisor and guest levels. Benchmark results show that the proposed technique can improve performance by up to 4.74 × on average in terms of execution time compared with the existing state‐of‐the‐art open‐source technology. [ABSTRACT FROM AUTHOR]

In this paper, we mathematically investigate a downlink non‐orthogonal multiple access (NOMA) system for short‐packet communications (SPC) in which the near users are used as full‐duplex (FD) relays to forward intended signals from the source to a far user. In addition, partial relay selection is employed to enhance the performance of the FD relays under the impact of imperfect interference cancellation. At the far user, selection combining (SC) or maximal ratio combining (MRC) is employed to combine the signals received from the source and the selected FD relay. The analytical expressions for the average block error rate (BLER) of two users over flat Rayleigh fading channels are derived. Furthermore, closed‐form asymptotic expressions of the average BLERs at the near and far users in high signal‐to‐noise ratio (SNR) regimes are obtained. The numerical results show that the analytical BLERs of the near user and far user closely match the simulation results. [ABSTRACT FROM AUTHOR]

This paper demonstrates improved throughput and energy efficiency of wireless communications by exploiting nonorthogonal multiple access (NOMA), multiple input–multiple output (MIMO), and radio frequency energy harvesting (EH) technologies. To assess the performance of NOMA MIMO communications with EH (MMe), we consider the nonlinear characteristics of EH devices and propose explicit expressions for throughput and outage probability. Based on our results, the system performance is significantly mitigated by EH nonlinearity and is considerably improved by increasing the number of antennas. Additionally, by appropriately adjusting the system parameters, our NOMA MMe innovation can avert complete outages while optimizing system performance. Moreover, the results demonstrate the superiority of the NOMA MMe over its orthogonal multiple access MMe counterparts. [ABSTRACT FROM AUTHOR]

A novel inductance simulation circuit employing only two dual‐output voltage‐differencing buffered amplifiers (DO‐VDBAs) and a single capacitance (grounded) is proposed in this paper. The reported configuration is a purely resistor‐less realization that provides electronically controllable realized inductance through biasing quantities of DO‐VDBAs and does not rely on any constraints related to matched values of parameters. This structure exhibits excellent behavior under the influence of tracking errors in DO‐VDBAs and does not exhibit instability at high frequencies. The simple and compact metal‐oxide semiconductor (MOS) implementation of the DO‐VDBAs (eight MOS per DO‐VDBA) and adoption of grounded capacitance make the proposed circuit suitable for on‐chip realization from the perspective of chip area consumption. The function of the pure grounded inductance is validated through high pass/bandpass filtering applications. To test the proposed design, simulations were performed in the PSPICE environment. Experimental validation was also conducted using the integrated circuit CA3080 and operational amplifier LF‐356. [ABSTRACT FROM AUTHOR]

The proposal by Wan & al. intended to maintain maximal nomenclatural stability by proposing to conserve Selaginella (Selaginellaceae) with a conserved type, regardless of how and when Selaginella is to be split into several or more genera, as has already been done in some recent studies. Valdespino & al. do not seem to have understood the nomenclatural benefit of the Wan & al. proposal and mix up this proposal with the classification by Zhou & Zhang. In addition, their rebuttal paper appears to contain a number of issues. We respectably urge the Nomenclature Committee and the botanical community to reject their rebuttal and make a decision that will benefit long‐term nomenclatural stability in Selaginellaceae. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of previously overlooked names published in the third volume of the Encyclopédie by Diderot and d'Alembert in 1753. These names primarily originate from Tournefort's pre‐Linnaean work, including textual copies of Tournefort's descriptions. We identified 21 names as having been validly published. Notably, among these are five generic names (Castanea, Chamaemelum, Chrysanthemoides, Citreum, Cydonia) wherein the taxonomic authorship shifts from Miller to Daubenton according to priority. Consequently, by our typifications, Miller's names from 1754 are later isonyms. Additionally, the generic name Chamaebuxus takes priority over Polygaloides. As a result, we propose a new combination, Chamaebuxus paucifolia and designate types for 31 generic names and isonyms: Caprifolium, Castanea, Chamaebuxus, Chamaecerasus, Chamaemelum, Chamaerhododendros, Chrysanthemoides, Cichorium, Cicuta, Cicutaria, Clandestina, Clymenum, Colocynthis, Citreum, Clematitis, Coa, Comaroides, Cydonia, Gramen, Scorpioides, and Sisarum, and lectotypes for two species names: Chamaebuxus paucifolia and Polygala uniflora. [ABSTRACT FROM AUTHOR]

Where does creativity come from and what is its purpose? The paper revisits these ever‐turning questions to correct the prevalent but, arguably, inaccurate historical interpretation of creativity as a concept that emerged in modernity. First, I substantiate that a close study of the ancient Greek texts suggests that although creativity seems to occupy a peripheral position in the ancient philosophical thinking, it is a central, yet, hidden, subject of speculation. Second, I overturn the worn‐out view that the ancient Greek philosophy conceives creativity as a God‐given talent breathed into a fortunate few. Last, I demonstrate that a more encompassing understanding of creativity is implied by several Greek philosophers. To achieve this, (a) I discuss the contemporary interpretations of the ancient notion; (b) I examine the historical origin and etymology of the Greek term demiourgein ("to create") to discuss its relevant uses; and (c) I develop a nuanced framework for conceptualizing ancient creativity and its interrelation to human agency, politics, and social life. [ABSTRACT FROM AUTHOR]

Ongoing assessment of patients with Alzheimer's disease (AD) in postapproval studies is important for mapping disease progression and evaluating real‐world treatment effectiveness and safety. However, interpreting outcomes in the real world is challenging owing to variation in data collected across centers and specialties and greater heterogeneity of patients compared with trial participants. Here, we share considerations for observational postapproval studies designed to collect harmonized longitudinal data from individuals with mild cognitive impairment or mild dementia stage of disease who receive therapies targeting the underlying pathological processes of AD in routine practice. This paper considers key study design parameters, including proposed aims and objectives, study populations, approaches to data collection, and measures of cognition, functional abilities, neuropsychiatric status, quality of life, health economics, safety, and drug utilization. Postapproval studies that capture these considerations will be important to provide standardized data on AD treatment effectiveness and safety in real‐world settings. [ABSTRACT FROM AUTHOR]

Increasing grain yields in maize (Zea mays L.) have been widely witnessed over the lifespan of many aging farmers. This paper aims to capture and summarize the overlapping explanations for the significant increases in maize yields. Changes in management practices have resulted in higher planting densities; however, genetic alterations allowed for maize varieties to tolerate increased stress levels. Increased stress levels, such as light availability, prompted genetic changes to leaf area index, radiation use efficiency, and leaf angles. The narrowing of the anthesis–silking interval is more significant in maize planted in higher densities. Stress factors affecting maize grain yields can be managed by both management changes such as water or pesticide application, and breeding modifications, such as genetic resistance to abiotic, temperature, or moisture, and biotic, pest, disease, and insect stressors. The increase in maize grain yields over the past century can be attributed to a combination of achievements in crop breeding and alternations of management practices. [ABSTRACT FROM AUTHOR]

Purpose: The Medical Education Research Study Quality Instrument (MERSQI) has been used frequently to assess the methodological quality of medical education but not for dental education. The present study aimed to assess the methodological quality using MERSQI scores of articles published in the Journal of Dental Education (JDE) and the European Journal of Dental Education (EJDE). Methods: A cross‐sectional assessment of the quality of manuscripts published in 2012, 2017, and 2022 JDE and EJDE was conducted. MERSQI data, numbers of authors, first and corresponding author degrees, geographic origins, and funding information were also extracted for each included study. Descriptive and analytical statistics were conducted, and significance level was set at α < 0.05. Results: Four hundred ninety‐five articles met the inclusion criteria. The most common study design was a single‐group cross‐sectional or single‐group posttest and conducted in one institution for all studied years. In all journals and years, studies were assessed mainly by participants. The study outcome was mostly satisfaction, attitudes, perceptions, opinions, and general facts. The total mean MERSQI score for each journal and year varied. Year and geographic origin significantly affected the total MERSQI score. Papers originating from Asia had the highest score, followed by South America, Europe, North America, Oceania, and Africa. Conclusion: MERSQI score is applicable to the assessment of the methodological quality of dental educational research. The MERSQI score for most of the domains was similar for both journals. The MERSQI score was affected by publication years and geographic origins. [ABSTRACT FROM AUTHOR]

Background and Objectives: In the accompanying paper (Part 1), it was reported that forced convection roasting of wheat before milling can be directed to tailor the viscosifying properties of flour. The objective of the present work was to examine the effect of prior wheat roasting on flour proteins. Findings: Effective control of wheat roasting conditions proved to be essential to avoid the irreversible loss of flour functionality as deduced from the flour ethanol and lactic acid solvent retention capacity and mixography data. Response surface models predicted roasting at 108°C and 80 Hz (135 s) to maintain protein integrity. The microstructure of flour and isolated starch as well as X‐ray diffraction patterns revealed starch to be relatively unaffected by this heat treatment. Conclusions: Flour produced from roasted wheat can still be used for products that require the formation of a gluten network. Significance and Novelty: Protein is more sensitive to roasting conditions than starch. [ABSTRACT FROM AUTHOR]

In agriculture, important unanswered questions about machine learning and artificial intelligence (ML/AI) include will ML/AI change how food is produced and will ML algorithms replace or partially replace farmers in the decision process. As ML/AI technologies become more accurate, they have the potential to improve profitability while reducing the impact of agriculture on the environment. However, despite these benefits, there are many adoption barriers including cost, and that farmers may be reluctant to adopt a decision tool they do not understand. The goal of this special issue is to discuss cutting‐edge research on the use of ML/AI technologies in agriculture, barriers to the adoption of these technologies, and how technologies can affect our current workforce. The papers are separated into three sections: Machine Learning within Crops, Pasture, and Irrigation; Machine Learning in Predicting Crop Disease; and Society and Policy of Machine Learning. Core Ideas: There are concerns that decision‐making tools using machine learning and artificial intelligence (ML/AI) in farming could replace human knowledge and labor.ML/AI technologies have the potential to improve precision farming using site‐specific algorithms.This special issue aims to open a dialogue about the role of ML/AI in agriculture and identify inequalities that may result from its use. [ABSTRACT FROM AUTHOR]

Precision agriculture (PA) has been defined as a "management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production." This definition suggests that because PA should simultaneously increase food production and reduce the environmental footprint, the barriers to adoption of PA should be explored. These barriers include (1) the financial constraints associated with adopting decision support system (DSS); (2) the hesitancy of farmers to change from their trusted advisor to a computer program that often behaves as a black box; (3) questions about data ownership and privacy; and (4) the lack of a trained workforce to provide the necessary training to implement DSSs on individual farms. This paper also discusses the lessons learned from successful and unsuccessful efforts to implement DSSs, the importance of communication with end users during DSS development, and potential career opportunities that DSSs are creating in PA. Core Ideas: Decision support systems (DSSs) are one component of precision agriculture (PA).The accuracy of DSSs may be improved by using algorithms based on machine learning.Barriers to DSSs include financial constraints, hesitancy to change, data privacy, and workforce limitations.Professional opportunities exist to overcome DSS adoption barriers. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) represents technologies with human‐like cognitive abilities to learn, perform, and make decisions. AI in precision agriculture (PA) enables farmers and farm managers to deploy highly targeted and precise farming practices based on site‐specific agroclimatic field measurements. The foundational and applied development of AI has matured considerably over the last 30 years. The time is now right to engage seriously with the ethics and responsible practice of AI for the well‐being of farmers and farm managers. In this paper, we identify and discuss both challenges and opportunities for improving farmers' trust in those providing AI solutions for PA. We highlight that farmers' trust can be moderated by how the benefits and risks of AI are perceived, shared, and distributed. We propose four recommendations for improving farmers' trust. First, AI developers should improve model transparency and explainability. Second, clear responsibility and accountability should be assigned to AI decisions. Third, concerns about the fairness of AI need to be overcome to improve human‐machine partnerships in agriculture. Finally, regulation and voluntary compliance of data ownership, privacy, and security are needed, if AI systems are to become accepted and used by farmers. Core Ideas: Model transparency and explainability can help foster trust between farmers and those providing artificial intelligence (AI) solutions.Assigning clear responsibility and accountability to AI decisions can improve farmers' acceptance and use of these technologies.Development of fair and equitable AI can improve human‐machine partnerships in agriculture.Regulation or voluntary compliance with data ownership, privacy, and security is needed if AI systems are to be used by farmers. [ABSTRACT FROM AUTHOR]

The early identification of plant diseases is crucial for preventing the loss of crop production. Recently, the advancement of deep learning has significantly improved the identification of plant leaf diseases. However, most approaches depend on a single convolutional neural network (CNN) to extract the leaf features, ignoring the opportunity to take full advantage of the feature richness available in the images. This paper explores a novel CNN model with multiple automated feature extractors, namely, dense fusion CNN (DFNet), for classifying plant leaf diseases. DFNet aims to increase the diversity of extracted features in order to improve discrimination. Instead of using a single‐CNN model, DFNet relies on a double‐pretrained CNN model, MobileNetV2 and NASNetMobile, as the feature extractor. The features extracted from each CNN are fused in the fusion layer using a fully connected network. The proposed method was evaluated using corn (Zea mays L.) and coffee (Coffea canephora) leaf disease datasets and compared to the existing models. The experiment showed that DFNet is superior and consistent to other CNN methods by achieving an accuracy of 97.53% for corn leaf diseases and 94.65% for coffee leaf diseases. Core Ideas: Propose a novel CNN model with multiple automated feature extractors.Apply feature fusion scheme to DFNet.Evaluate the proposed models for corn and coffee leaf disease detection.DFNet improves the performance in plant leaf disease detection. [ABSTRACT FROM AUTHOR]

Objective: Dentistry produces waste contributing to climate change and adverse health outcomes, thus reducing waste is essential; however, there has been minimal emphasis on sustainability or climate action in dentistry. Waste audits quantify the type and amount of waste produced and may inform waste reduction strategies. We conducted a waste audit to identify areas of potential waste reduction and recommend interventions to reduce waste. Methods: In this cross‐sectional study, we conducted a waste audit of garbage produced during a typical 4‐hour pre‐clinical restorative dentistry simulation exercise. The sample was composed of 72 second‐year dental students. This exercise is part of a standard curriculum with a uniform format regarding supplies used and participants. Potentially infectious materials were not used during this exercise. Results: In total, 26.6 kg of waste was discarded. Plastic was the largest contributor by mass (57.5%), followed by paper barriers (19.6%), then impression materials (6.5%). We found 894 gloves and 70 masks discarded. Conclusions: Based on these findings, we categorized waste reduction opportunities into policy changes, purchasing sustainable materials, and increasing awareness through education. Specific suggested actions include: relaxing glove and gown requirements during laboratory simulations; replacing single use items with more sustainable options; increasing use of intraoral scanners; and posting informational signage with examples of what can be recycled. [ABSTRACT FROM AUTHOR]

The increase in scientific knowledge, oral healthcare, new dental hygiene workforce models, and the latest clinical skills, have elevated the need for doctoral prepared dental hygienists and dental therapists. These oral care providers need to be empowered with advanced preparation in education, research, and leadership. Therefore, the purpose of this paper is to present two curricular models for a doctorate of philosophy and a doctorate of oral health practice recognizing that students may have different goals and interests in educational pursuits. The doctoral program models support the conduct of research and scholarship, which supports the research infrastructure of the profession and emphasizes the dissemination of scholarly works. Creation of doctoral programs for dental hygienists and dental therapists provides opportunities to broaden choices and strive for autonomy throughout their careers. These programs may support the development of additional scholars and advanced practitioners who can contribute to the scientific body of knowledge and create policies and pathways to improve population oral health. [ABSTRACT FROM AUTHOR]

In this paper, we describe a neural network‐based application that recommends multiple items using dialog context input and simultaneously outputs a response sentence. Further, we describe a multi‐item recommendation by specifying it as a set of clothing recommendations. For this, a multimodal fusion approach that can process both cloth‐related text and images is required. We also examine achieving the requirements of downstream models using a pretrained language model. Moreover, we propose a gate‐based multimodal fusion and multiprompt learning based on a pretrained language model. Specifically, we propose an automatic evaluation technique to solve the one‐to‐many mapping problem of multi‐item recommendations. A fashion‐domain multimodal dataset based on Koreans is constructed and tested. Various experimental environment settings are verified using an automatic evaluation method. The results show that our proposed method can be used to obtain confidence scores for multi‐item recommendation results, which is different from traditional accuracy evaluation. [ABSTRACT FROM AUTHOR]

This paper presents the performance evaluation of an amplify‐and‐forward (AF) relay‐assisted multiuser multiple input–multiple output (MU–MIMO) downlink transmission system for correlated fading channels. The overall system performance was improved by incorporating a double‐quadrature spatial modulation (DQSM) scheme. The bit error rate (BER) performance and detection complexity of the AF–MU–MIMO–DQSM system were analyzed and compared with those of a conventional AF–MU–MIMO system under the same conditions and parameters. The results showed that the correlated fading channel severely affected the performance of systems with higher spectral efficiency (SE). Considering an SE of 12 bpcu/user, the AF–MU–MIMO–DQSM system yielded a gain of up to 3 dB in BER performance compared with that of its conventional counterpart for the analyzed cases. In terms of detection complexity, the AF–MU–MIMO–DQSM system showed a reduction of up to 56 % compared with that of the conventional system for the optimal maximum likelihood detection criterion. [ABSTRACT FROM AUTHOR]

To treat the novel COronaVIrus Disease (COVID), comparatively fewer medicines have been approved. Due to the global pandemic status of COVID, several medicines are being developed to treat patients. The modern COVID medicines development process has various challenges, including predicting and detecting hazardous COVID medicine responses. Moreover, correctly predicting harmful COVID medicine reactions is essential for health safety. Significant developments in computational models in medicine development can make it possible to identify adverse COVID medicine reactions. Since the beginning of the COVID pandemic, there has been significant demand for developing COVID medicines. Therefore, this paper presents the transfer‐learning methodology and a multilabel convolutional neural network for COVID (MLCNN‐COV) medicines development model to identify negative responses of COVID medicines. For analysis, a framework is proposed with five multilabel transfer‐learning models, namely, MobileNetv2, ResNet50, VGG19, DenseNet201, and Inceptionv3, and an MLCNN‐COV model is designed with an image augmentation (IA) technique and validated through experiments on the image of three‐dimensional chemical conformer of 17 number of COVID medicines. The RGB color channel is utilized to represent the feature of the image, and image features are extracted by employing the Convolution2D and MaxPooling2D layer. The findings of the current MLCNN‐COV are promising, and it can identify individual adverse reactions of medicines, with the accuracy ranging from 88.24% to 100%, which outperformed the transfer‐learning model's performance. It shows that three‐dimensional conformers adequately identify negative COVID medicine responses. [ABSTRACT FROM AUTHOR]

This paper presents a novel circular fractal ring monopole antenna for ultra‐wideband (UWB) hardware with dual band‐notched properties. The proposed antenna consists of four crescent‐shaped nested rings, a tapered feeding line at the front of the dielectric material, and a semicircular ground plane on the backside. In this design, the nested rings are used both as a radiation element and a band rejection element. The proposed antenna has a bandwidth of 9.03 GHz, which works efficiently in the range of 2.63 GHz–11.66 GHz with the dual notched bands of Worldwide Interoperability for Microwave Access (WiMAX) at 3.15 GHz–3.66 GHz and wireless local area network (WLAN) at 4.9 GHz–5.9 GHz, respectively. The antenna has a compact size of 20 mm × 30 mm × 1 mm (0.177 × 0.265 × 0.0084 λ0) and is implemented using a flame‐retardant type 4 (FR4) material. It has a maximum gain of approximately 4 dB in its operating range, and experimental results support the simulation predictions with high accuracy. The findings of this study imply that the designed antenna can be utilized in UWB applications. [ABSTRACT FROM AUTHOR]

This paper proposes a surveillance model for plant pests that can optimally allocate resources among survey tools with varying properties. While some survey tools are highly specific for the detection of a single pest species, others are more generalized. There is considerable variation in the cost and sensitivity of these tools, but there are no guidelines or frameworks for identifying which tools are most cost‐effective when used in surveillance programs that target the detection of newly invaded populations. To address this gap, we applied our model to design a trapping surveillance program in New Zealand for bark‐ and wood‐boring insects, some of the most serious forest pests worldwide. Our findings show that exclusively utilizing generalized traps (GTs) proves to be highly cost‐effective across a wide range of scenarios, particularly when they are capable of capturing all pest species. Implementing surveillance programs that only employ specialized traps (ST) is cost‐effective only when these traps can detect highly damaging pests. However, even in such cases, they significantly lag in cost‐effectiveness compared to GT‐only programs due to their restricted coverage. When both GTs and STs are used in an integrated surveillance program, the total expected cost (TEC) generally diminishes when compared to programs relying on a single type of trap. However, this relative reduction in TEC is only marginally larger than that achieved with GT‐only programs, as long as highly damaging species can be detected by GTs. The proportion of STs among the optimal required traps fluctuates based on several factors, including the relative pricing of GTs and STs, pest arrival rates, potential damage, and, more prominently, the coverage capacity of GTs. Our analysis suggests that deploying GTs extensively across landscapes appears to be more cost‐effective in areas with either very high or very low levels of relative risk density, potential damage, and arrival rate. Finally, STs are less likely to be required when the pests that are detected by those tools have a higher likelihood of successful eradication because delaying detection becomes less costly for these species. [ABSTRACT FROM AUTHOR]

Gastrointestinal helminth parasites undergo part of their life cycle outside their host, such that developmental stages interact with the soil and dung fauna. These interactions are capable of affecting parasite transmission on pastures yet are generally ignored in current models, empirical studies and practical management. Dominant methods of parasite control, which rely on anthelmintic medications for livestock, are becoming increasingly ineffective due to the emergence of drug‐resistant parasite populations. Furthermore, consumer and regulatory pressure on decreased chemical use in agriculture and the consequential disruption of biological processes in the dung through nontarget effects exacerbates issues with anthelmintic reliance. This presents a need for the application and enhancement of nature‐based solutions and biocontrol methods. However, successfully harnessing these options relies on advanced understanding of the ecological system and interacting effects among biotic factors and with immature parasite stages. Here, we develop a framework linking three key groups of dung and soil fauna—fungi, earthworms, and dung beetles—with each other and developmental stages of helminths parasitic in farmed cattle, sheep, and goats in temperate grazing systems. We populate this framework from existing published studies and highlight the interplay between faunal groups and documented ecological outcomes. Of 1756 papers addressing abiotic drivers of populations of these organisms and helminth parasites, only 112 considered interactions between taxa and 36 presented data on interactions between more than two taxonomic groups. Results suggest that fungi reduce parasite abundance and earthworms may enhance fungal communities, while competition between dung taxa may reduce their individual effect on parasite transmission. Dung beetles were found to impact fungal populations and parasite transmission variably, possibly tied to the prevailing climate within a specific ecological context. By exploring combinations of biotic factors, we consider how interactions between species may be fundamental to the ecological consequences of biocontrol strategies and nontarget impacts of anthelmintics on dung and soil fauna and how pasture management alterations to promote invertebrates might help limit parasite transmission. With further development and parameterization the framework could be applied quantitatively to guide, prioritize, and interpret hypothesis‐driven experiments and integrate biotic factors into established models of parasite transmission dynamics. [ABSTRACT FROM AUTHOR]

Wetlands in arid or semiarid zones are vital for maintaining biodiversity but face growing threats. Flooding regime variability is a key driver of ecological dynamism in these systems, dictating primary productivity on a large spatial scale. The functional composition or diversity of wetland-dependent bird species has been found to be sensitive to fluctuations in hydrological regimes and can thus be indicative of cascading ecosystem responses associated with climate change. In this paper, we investigate whether large-scale changes in inundation and fire--a significant additional biodiversity determinant in (semi-)arid landscapes--are reliable predictors of functional group responses of wetland-dependent birds along a perennial channel of the Okavango Delta, Botswana. We fit generalized additive models (GAMs) to 6 years of bird survey data collected along ~190-km-long annual transects and use remotely sensed landscape-level inundation estimates, as well as spatiotemporal distance to fire, to predict the responsiveness of seven trait-based functional group abundances. During the surveys, a total of 89 different wetland-dependent bird species were recorded, including 76 residents, across all years, with below-surface feeding waders consistently the most abundant functional group. Including estimated spatiotemporal variability in flooding and fire, as well as their interactions, improved model fit for all seven functional groups, explaining between 46.8% and 68.3% of variability in functional group abundances. Covariates representing longer-term variability in inundation generally performed better than shorter-term ones. For example, variability in inundation over the 5 months preceding a survey best predicted the responses of all functional groups, which also all exhibited responsiveness to the interaction between flooding and fire. We were able to interpret the responses of individual functional groups, based on the resource exploitation assumption. Overall, our results suggest that perennial waters in dryland wetlands offer functional refugia to wetland-dependent birds and highlight the indicative power of large-scale traitbased bird monitoring. Our findings demonstrate the potential utility of such a monitoring regime for dryland wetland ecosystems vulnerable to industrial-scale anthropogenic pressure and associated climate change. [ABSTRACT FROM AUTHOR]

Background and Objectives: Proso millet is a traditional grain that can be divided into waxy and nonwaxy varieties based on amylose content. However, research on different varieties of cooked proso millet is limited, especially as a whole grain. This paper investigated the quality properties and aroma characterization of cooked nonwaxy proso millet (NPM) and waxy proso millet (WPM). Findings: Scanning electron microscopy images showed that cooked NPM exhibited a more compact structure, whereas cooked WPM displayed a porous structure. Cooked NPM presented higher water absorption ratio, expansion ratio, hardness, and better chewiness than cooked WPM. Correlation analysis indicated that the texture properties were positively correlated with the cooking characteristics as well as the amylose and protein contents. The resistant starch content of cooked NPM (35.97%) was higher than that of cooked WPM (28.85%). Aroma analysis revealed that cooked NPM and WPM contained 56 and 67 volatile substances, respectively. Conclusion: Cooked NPM and WPM exhibited different properties mainly attributed to the various amylose and protein contents. Significance and Novelty: These findings may provide a theoretical basis for the processing and commercial development of the proso millet resource. [ABSTRACT FROM AUTHOR]

Despite its high prevalence among dementias, Lewy body dementia (LBD) remains poorly understood with a limited, albeit growing, evidence base. The public‐health burden that LBD imposes is worsened by overlapping pathologies, which contribute to misdiagnosis, and lack of treatments. For this report, we gathered and analyzed public‐domain information on advocacy, funding, research outputs, and the therapeutic pipeline to identify gaps in each of these key elements. To further understand the current gaps, we also conducted interviews with leading experts in regulatory/governmental agencies, LBD advocacy, academic research, and biopharmaceutical research, as well as with funding sources. We identified wide gaps across the entire landscape, the most critical being in research. Many of the experts participated in a workshop to discuss the prioritization of research areas with a view to accelerating therapeutic development and improving patient care. This white paper outlines the opportunities for bridging the major LBD gaps and creates the framework for collaboration in that endeavor. Highlights: A group representing academia, government, industry, and consulting expertise was convened to discuss current progress in Dementia with Lewy Body care and research.Consideration of expert opinion,natural language processing of the literature as well as publicly available data bases, and Delphi inspired discussion led to a proposed consensus document of priorities for the field. [ABSTRACT FROM AUTHOR]

The article discusses recent advancements in artificial intelligence (AI) and their impact on speech and language comprehension. It highlights the emergence of speech and language technologies as major topics in AI research, enabling computers to interpret human language in both written and spoken forms. The article also provides summaries of 12 papers included in a special issue on speech and language technologies, covering topics such as question answering, coreference resolution, essay grading, named entity recognition, morphological analysis, code generation, Alzheimer's disease recognition, backchannel prediction, spoken-to-written text conversion, multimodal speech recognition, and language tutoring systems. The authors express their gratitude to the contributors and emphasize the importance of these studies for the future design and implementation of AI systems. [Extracted from the article]

This paper presents the development of language tutoring systems for non‐native speakers by leveraging advanced end‐to‐end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non‐native speech, high‐performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying on precise transcriptions. End‐to‐end ASR is implemented and enhanced by using diverse non‐native speaker speech data for model training. For performance enhancement, we combine semisupervised and transfer learning techniques using labeled and unlabeled speech data. Automatic proficiency evaluation is performed by a model trained to maximize the statistical correlation between the fluency score manually determined by a human expert and a calculated fluency score. We developed an English tutoring system for Korean elementary students called EBS AI PengTalk and a Korean tutoring system for foreigners called KSI Korean AI Tutor. Both systems were deployed by South Korean government agencies. [ABSTRACT FROM AUTHOR]

Objective: The geoduck show‐factor is the probability an individual geoduck is detectable to a diver during a stock assessment survey. It is one of the values used to estimate the abundance of geoducks. This paper presents estimates of show‐factor according to data collected during 21 approximately monthly surveys over a 32‐month period. The new estimates are compared against other long‐term studies of show‐factor and against estimates made from shorter term (approximately daily surveys over a period of approximately 1 week) studies. Methods: Data were collected from three plots near Marina Island, British Columbia, and three novel methods were used for the analysis. Two of the methods estimate show‐factors at the time of data collection, while the third method treats show‐factor as a function of the time of year. All three methods generate probabilistic results. Result: Each method of show‐factor analysis indicated a strong seasonal effect. Show‐factors were highest from March to June and lowest from October to December. The difference between the high and low show‐factors was at least a factor of two. The three methods generated estimates of show‐factor that are generally lower than the values previously used as part of stock assessment on the coast of British Columbia. Conclusion: If this difference between long‐ and short‐term show‐factor can be generalized to the many commercial beds on the coast of British Columbia, the abundance of geoducks has been underestimated and the fishery is even more cautious than currently believed. As of yet, long‐term data have not been collected on a coastwide basis and conclusions cannot be more definitive. Impact statementBased upon data collected from a single location, over 32 months, under a new protocol, there are likely more undetected geoducks than previously expected. The geoduck fishery is likely even more sustainable than previously believed. [ABSTRACT FROM AUTHOR]

This article discusses the management of invasive alien species (IAS) in China. It highlights the negative impacts of biological invasions on ecosystems, the environment, and the economy. The article presents 24 papers that cover a wide range of topics related to IAS management, including risk analysis, mechanisms of invasion success, performance of successful IAS, and impact and control of invasive species. The studies use various methods such as field surveys, experiments, ecological modeling, and molecular techniques to assess invasion risks, investigate mechanisms, and develop control strategies. The article emphasizes the importance of interdisciplinary research and effective management strategies to address the increasing threat of IAS in China. [Extracted from the article]

Recurrent selection is an effective breeding method for improving complex traits in wheat (Triticum aestivum L.) breeding. In this study, we propose a genitor selection strategy, employing a multi‐trait selection approach and genetic diversity analysis. To evaluate our proposed method, we conducted a lattice design trial during the winter seasons of 2020 and 2021 in Viçosa, MG, Brazil, comprising 87 lines and 13 commercial cultivars. It assessed various traits such as plant height, days to heading, wheat leaf rust, tan spot of wheat, a hundred grain mass, hectoliter weight, and grain yield, and the best linear unbiased predictor (BLUP) was obtained for each trait via restricted maximum likelihood. Next, a genotypic distance matrix, derived from principal component analysis using the BLUP values, was computed to perform hierarchical clustering via the unweighted pair group method with arithmetic mean. The selection of superior genotypes was made utilizing the multi‐trait genotype‐ideotype distance index, resulting in the identification of eight lines and two commercial cultivars as candidates. Furthermore, the genetic diversity analysis revealed distinct clusters among the selected genotypes. To assess the divergence of the chosen genitors, this study proposes a complementarity matrix using factor analysis. Our results indicate that this selection strategy effectively directed the identification of the best and divergent genitors. The complementarity matrix developed in this paper to evaluate the crossings proposal can also be used to evaluate combinations in any panel selected via a multi‐trait approach and can be easily applied and interpreted by breeders of various programs. Core Ideas: Novel strategy to select divergent genitors for cycle zero of recurrent selection program is presented.Multi‐trait selection and genetic diversity analysis of tropical wheat on phenotypic data is presented.A complementarity index based on a factor analysis is presented to evaluate the proposed crossings. [ABSTRACT FROM AUTHOR]

The article discusses the role and limitations of peer review in scientific publishing. It acknowledges that peer review is seen as a necessary process to ensure rigor and credibility in scientific research. However, the author questions the effectiveness of peer review in filtering out poor-quality science and highlights the growing issue of predatory journals that publish papers without proper peer review. The article suggests that while peer review is not perfect, it still serves as a filter and can lead to better papers. It emphasizes the importance of maintaining a healthy skepticism and critical approach when consuming scientific information. [Extracted from the article]

The article discusses the taxonomic naming of Cordiada trichotoma, a deciduous tree native to southern regions of South America. The name Cordiada trichotoma was originally published in 1829 but faced challenges to its stability due to delayed publication. The article proposes to retain the widely recognized name Cordiada trichotoma over the comparatively obscure name Cordia frondosa to maintain nomenclatural stability and prevent disruptions in scientific discourse. Cordiada trichotoma has been extensively used and cited in scientific papers, regional floristic works, and studies on its properties and utilization. The proposal aims to uphold the integrity of botanical nomenclature while preserving the prevailing understanding and recognition of the species. [Extracted from the article]

This document is a corrigendum for an article titled "Ebselen induces reactive oxygen species (ROS)-mediated cytotoxicity in Saccharomyces cerevisiae with inhibition of glutamate dehydrogenase being a target." The corrigendum states that there were duplicated panels in Figures 4 and 7 of the original article. The authors removed the duplicated panels and made amendments to the figures to indicate the changes. The corrigendum assures that these changes do not impact the conclusions of the paper. [Extracted from the article]

RETRACTION: L. Wang, Y. Gao, D. Tong, X. Wang, C. Guo, B. Guo, Y. Yang, L. Zhao, J. Zhang, J. Yang, Y. Qin, L. Liu, and C. Huang, "MeCP2 Drives Hepatocellular Carcinoma Progression Via Enforcing HOXD3 Promoter Methylation and Expression Through the HB‐EGF/EGFR Pathway," Molecular Oncology 15, no. 11 (2021): 3147‐3163, https://doi.org/10.1002/1878-0261.13019. The above article, published online on 24 May 2021 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor‐in‐Chief, Kevin Ryan; FEBS Press; and John Wiley and Sons Ltd. The retraction has been agreed upon following an investigation into concerns raised by a third party regarding an image duplication between Figures 2C (MeCP2 panel) and 4G (left panel). The investigation also revealed inconsistencies in the gel blots of Figures 2J and 3N. The partial raw data shared by the authors was deemed insufficient to address these concerns. Therefore, the editors have lost confidence in the presented data, consider the conclusions substantially compromised and are retracting the paper. The authors were informed of the decision to retract but did not agree to the retraction or the retraction wording. [ABSTRACT FROM AUTHOR]

RETRACTION: M. Lagadari, N. R. Zgajnar, L. I. Gallo and M. D. Galigniana, 'Hsp90‐binding immunophilin FKBP51 forms complexes with hTERT enhancing telomerase activity', Molecular Oncology 10, no. 7 (2016): 1086–1098, https://doi.org/10.1016/j.molonc.2016.05.002. The above article, published online on 17 May 2016 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor in Chief, Kevin Ryan and John Wiley and Sons Ltd. The retraction has been agreed due to several instances of image manipulation in figures 1C, 5B, 4A and 5A. The available raw data were not compelling. Based on the number of inappropriate duplications, the editors consider the conclusions substantially compromised and are therefore retracting the paper. The author, Mario D. Galigniana, disagrees with the retraction; acknowledgement of the retraction could not be obtained from the remaining co‐authors. [ABSTRACT FROM AUTHOR]

The article titled "Corrigendum to: A Hill type equation can predict target gene expression driven by p53 pulsing" contains an error in Equation 18. The corrected equation is provided in the document. It is important to note that this change does not impact the results of the paper. [Extracted from the article]