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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

The above article, published online on 29 April 2016 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 due to several image duplications in Figures 4B,E,G, and 5C,D, and inconsistencies between tumour luminescence images and the quantification in Figure 4K. Compelling raw data images were not available from the authors. The editors consider the conclusions substantially compromised and are therefore retracting the paper. Corresponding author Pritha Ray agrees to this retraction, since the raw data are no longer available for analysis and validation. Reference 1 Thakur B, Ray P. p53 loses grip on PIK3CA expression leading to enhanced cell survival during platinum resistance. Mol Oncol. 2016;10(8):1283–1295. https://doi.org/10.1016/j.molonc.2016.06.006 [ABSTRACT FROM AUTHOR]