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Objective.Automatic segmentation of prostatic zones from MRI can improve clinical diagnosis of prostate cancer as lesions in the peripheral zone (PZ) and central gland (CG) exhibit different characteristics. Existing approaches are limited in their accuracy in localizing the edges of PZ and CG. The proposed boundary-aware semantic clustering network (BASC-Net) improves segmentation performance by learning features in the vicinity of the prostate zonal boundaries, instead of only focusing on manually segmented boundaries.Approach.BASC-Net consists of two major components: the semantic clustering attention (SCA) module and the boundary-aware contrastive (BAC) loss. The SCA module implements a self-attention mechanism that extracts feature bases representing essential features of the inner body and boundary subregions and constructs attention maps highlighting each subregion. SCA is the first self-attention algorithm that utilizes ground truth masks to supervise the feature basis construction process. The features extracted from the inner body and boundary subregions of the same zone were integrated by BAC loss, which promotes the similarity of features extracted in the two subregions of the same zone. The BAC loss further promotes the difference between features extracted from different zones.Main results.BASC-Net was evaluated on the NCI-ISBI 2013 Challenge and Prostate158 datasets. An inter-dataset evaluation was conducted to evaluate the generalizability of the proposed method. BASC-Net outperformed nine state-of-the-art methods in all three experimental settings, attaining Dice similarity coefficients of 79.9% and 88.6% for PZ and CG, respectively, in the NCI-ISBI dataset, 80.5% and 89.2% for PZ and CG, respectively, in Prostate158 dataset, and 73.2% and 87.4% for PZ and CG, respectively, in the inter-dataset evaluation.Significance.As prostate lesions in PZ and CG have different characteristics, the zonal boundaries segmented by BASC-Net will facilitate prostate lesion detection.

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INTRODUCTION: Learning is a long-term memory process heavily influenced by the control processes implemented by working memory, including recognition of semantic properties of items by which subjects generate a semantic structure of engrams. AIM: The aim of this study is to investigate the verbal learning strategies of patients affected by a tumor in the left frontal lobe to highlight the role of area 9. METHOD: Ten patients with frontal low-grade gliomas and ten healthy control subjects, matched for age, sex and education, were recruited and then evaluated with a two-part verbal learning test: multi-trial word list learning in free recall, and multi-trial word list learning preceded by an explicit semantic strategy cue. Frontal patients were divided into two groups: those either with frontal lesions involving or sparing area 9. RESULTS: In comparison to healthy control subjects, frontal patients with lesions involving area 9 memorized fewer words and displayed difficulty in using semantic strategies. When the strategy was suggested by the examiner, their performance improved, but to a lesser extent than the healthy control. Conversely, frontal patients with lesions sparing area 9 showed similar results to healthy control subjects. CONCLUSION: The results suggested that, while the identification of the categorical criterion requires the integrity of the entire dorsolateral prefrontal area, only area 9, and not the surrounding areas, could be responsible for the effective use of semantic strategies in learning tasks.

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Writing about negative experiences can produce multiple benefits, including improvements in mental and emotional health. However, writing about negative experiences potentially be detrimental, as reliving and reexperiencing a negative memory can be painful. Although the emotional effects of writing about negative experiences are well established, the cognitive effects are less heavily explored, and no work to date has examined how writing about a stressful experience might influence episodic memory. We addressed this issue in the present study (N = 520) by having participants encode a list of 16 words that were organised around four semantic clusters, randomly assigning participants to write about an unresolved stressful experience (n = 263) or the events of the previous day (n = 257), and assessing their memory in a free recall task. Writing about a stressful experience did not influence overall memory performance; however, the stressful writing manipulation increased semantic clustering of information within memory for men, whereas the stressful writing manipulation did not influence semantic clustering of information within memory in women. Additionally, writing with more positive sentiment improved semantic clustering and reduced serial recall. These results provide evidence for unique sex differences in writing about stressful experiences and the role of sentiment in the effects of expressive writing.

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The Context Dependency Effect is the well-established finding in which memory performance is enhanced under conditions in which the encoding and retrieval contexts overlap (i.e., Same-Context) and diminished when the overlap between encoding and retrieval contexts is low (i.e., Different-Context). Despite much research on context-dependent memory, most prior work examined only mean performance levels. The current experiment examined the influence of context change, manipulated by using three different pieces of background music, on semantic organization during free recall. Recall driven by semantic organization captures an important, ecologically valid aspect of memory retrieval: because narratives of real-life events are typically comprised of semantically related concepts (e.g., "sea," "bathing suit," and "sand" when recalling a trip to the beach), their recall is likely driven by semantic organization. Participants in the current study were tested in the same or different context as the material was learned. The results showed that although the mean number of correctly recalled items was numerically greater in the Same-Context condition compared to the Different-Context condition, the Context Dependency Effect was not significant. In contrast, however, semantic clustering-an established measure of semantic organization-was greater in the Different-Context condition compared to the Same-Context condition. Together, these results suggest that when contextual cues at recall are relatively meager, participants instead use semantic information as cues to guide memory retrieval. In line with previous findings, temporal organization, patterns of errors, and serial position analyses showed no differences between the two context conditions. The present experiment provides novel evidence on how external context change affects recall organization.

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INTRODUCTION: On some list-learning tasks, such as the California Verbal Learning Test (CVLT) or Hopkins Verbal Learning Test (HVLT), examinees have the opportunity to group words based on semantically related categories (i.e., semantic clustering). Semantic clustering (SC) is often considered the most efficient organizational strategy and adopting SC is presumed to improve learning and memory. In addition, SC is conceptualized as reflecting higher-order executive functioning skills. Although SC measures have intuitive appeal, to date, there are no comprehensive reviews of the SC literature base that summarize its psychometric utility. In this systematic review, we synthesize the literature to judge the validity of SC scores. METHOD: We conducted a systematic literature search for empirical articles reporting SC from the CVLT and HVLT. We qualitatively described the relationship of SC with other list-learning and cognitive test scores and clinical diagnoses, contrasting SC with serial clustering and total learning scores when possible. RESULTS: SC was inversely correlated with serial clustering. Higher SC was strongly associated with better learning and memory performances. When compared with cognitive tests, SC tended to have the strongest relationships with other memory measures and modest relationships with tests of executive functioning. SC had negligible to small relationships with most other cognitive domains. Traditional memory scores yielded stronger relationships to cognitive test performances than did SC. SC across clinical groups varied widely, but clinical groups tended to use SC less often than healthy comparison groups. CONCLUSION: Our comprehensive review of the literature revealed that SC is strongly related to measures of learning and memory on the CVLT and HVLT and is correlated with a wide range of cognitive functions. SC has been understudied in relevant populations and additional research is needed to test the degree to which it adds incremental validity beyond traditional measures of learning and memory.

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The argument for a female advantage in word list learning is often based on partial observations that focus on a single component of the task. Using a large sample (N = 4403) of individuals 13-97 years of age from the general population, we investigated whether this advantage is consistently reflected in learning, recall, and recognition and how other cognitive abilities differentially support word list learning. A robust female advantage was found in all subcomponents of the task. Semantic clustering mediated the effects of short-term and working memory on long-delayed recall and recognition, and serial clustering on short-delayed recall. These indirect effects were moderated by sex, with men benefiting more from reliance on each clustering strategy than women. Auditory attention span mediated the effect of pattern separation on true positives in word recognition, and this effect was stronger in men than in women. Men had better short-term and working memory scores, but lower auditory attention span and were more vulnerable to interference both in delayed recall and recognition. Thus, our data suggest that auditory attention span and interference control (inhibition), rather than short-term or working memory scores, semantic and/or serial clustering on their own, underlie better performance on word list learning in women.

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Introduction: Age-related decline in episodic memory performance in otherwise healthy older adults is indisputably evident. Yet, it has been shown that under certain conditions episodic memory performance in healthy older adults' barely deviates from those seen in young adults. Here we report on the quality of object encoding in an ecologically valid, virtual-reality based memory assessment in a sample of healthy older and younger adults with comparable memory performance. Methods: We analyzed encoding by establishing both a serial and semantic clustering index and an object memory association network. Results: As expected, semantic clustering was superior in older adults without need for additional allocation of executive resources whereas young adults tended more to rely on serial strategies. The association networks suggested a plethora of obvious but also less obvious memory organization principles, some of which indicated converging approaches between the groups as suggested by a subgraph analysis and some of which indicated diverging approaches as suggested by the respective network interconnectivity. A higher interconnectivity was observed in the older adults' association networks. Discussion: We interpreted this as a consequence of superior semantic memory organization (extent to which effective semantic strategies diverged within the group). In conclusion, these results might indicate a diminished need for compensatory cognitive effort in healthy older adults when encoding and recalling everyday objects under ecologically valid conditions. Due to an enhanced and multimodal encoding model, superior crystallized abilities might be sufficient to counteract an age-related decline in various other and specific cognitive domains. This approach might potentially elucidate age-related changes in memory performance in both healthy and pathological aging.

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Several studies suggest poorer episodic memory among adults with overweight (OW) relative to those with healthy weight (HW); however, few have used food stimuli. To understand the salience of food-related items when assessing memory, we adapted an episodic memory task, by replacing some non-food words with snack foods. Participants were 96 weight-loss seeking adults with OW compared to 48 adults with HW from the community matched on age, gender, ethnicity, and education. Overall memory ability was similar, although a trend showed the adults with HW performed better than adults with OW on immediate recall (d = 0.32, p = 0.07). However, there were clear differences in the use of learning strategies. Adults with HW utilized sematic clustering more effectively than adults with OW during all test phases (ds = 0.44-0.62; ps ≤ 0.01). Adults with HW also utilized serial clustering more effectively (d = 0.51; p < 0.01). Adults with HW showed better semantic clustering for both food and non-food words during immediate and short delay recall (ds = 0.42-0.78; ps ≤ 0.01) but semantic clustering was only better for the non-food category at long delay (d = 0.55; p < 0.01). These results show that adults with OW utilized less efficient learning strategies throughout the task and food-related content may impact learning. Clinically, these findings may suggest that weight-loss treatments should consider incorporating the teaching of learning and memory strategies to help increase utilization of new skills.

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The present study intended to investigate, first, the impact of semantic clustering on the recall and recognition of incidentally learned words in a new language, and second, how the interaction between semantic clustering and frequency of occurrence may modulate learning. To that end, Spanish university students watched an intentionally created video which contained Spanish target words that were either semantically related to others of the set, or not semantically linked at all. Furthermore, frequency of appearance changed among target words (1|4|8). All these words were paired with pseudowords that appeared as on-screen text during the videos. Participants were completely naive to the phases and the procedure of the experiment. After viewing the video, participants completed a recall test and a recognition test. Results showed that words presented in semantically unrelated categories were better recalled and better recognized than those presented in semantic clusters, especially when the words were presented more often.

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Recently, substantial research has explored the development of deep-learning-based methods to diagnose faults in rotating machinery. For these diagnosis methods, it is difficult to obtain high target diagnosis accuracy when the amount of labeled data obtained pertaining to the rotating machinery under study is insufficient or in cases involving a discrepancy in the distribution types found in the training and test data sets. To deal with this research need, the paper outlines a new method, a domain adaptation with semantic clustering (DASC), capable of diagnosing faults in rotating machinery. The method outlined in this research learns both domain-invariant and discriminative features. The method reduces the domain discrepancy by minimizing the domain-related loss. In addition, by defining an additional loss, which is called semantic clustering loss, and reducing it at multiple feature levels, the DASC method learns features that make samples better semantically clustered, according to their health conditions. Consequently, fault diagnosis performance for target rotating machinery can be enhanced through the use of the DASC approach. The effectiveness of the DASC approach is confirmed by examining various fault diagnosis situations with domain discrepancies across the source and target domains, using experimental data from three bearing systems. Also, various analyses are explored to better understand the advantages of the DASC method.

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Temporal and semantic associative processes during the acquisition of new verbal information undergo various changes across the life span. Temporal order clusters and subjective clusters were monitored during verbal learning trials using the Rey (Auditory Verbal Learning Task) for 1471 participants aged 8-91. Pairs, three-word, and four-word clusters were measured. Subjective clusters were generated at similar frequency across the whole life span. By contrast, a clear inverted-U curve across life span was indicated for temporal clusters. More words were subjectively clustered than clustered by temporal presentation order. The number of words clustered increased across trials, and cluster types showed a different increase profile across trials. The subjective cluster increment was faster and steeper than the temporal cluster increment in most of the age segments. Life span trajectory tendencies in the formation of temporal and semantic associations in recall were interpreted in relation to different frameworks of cognitive life span changes.

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We studied mental representations of literal, metonymically different, and metaphorical senses in Russian adjectives. Previous studies suggested that in polysemous words, metonymic senses, being more sense-related, were stored together with literal senses, whereas more distant metaphorical senses had separate representations. We hypothesized that metonymy may be heterogeneous with respect to its mental storage. "Whole-part" metonymy ("sad person" - "sad eyes"), which is cognitively closer to the literal sense and more regular, should be stored differently from temporal, causal or resultative metonymy ("sad person" - "sad time;" "sad person" - "sad news;" "lead.ADJ ball" - "lead.ADJ poisoning"), which is irregular and semantically distant from the literal sense. We conducted an online experiment with semantic clustering task in which the participants were asked to classify sentences with a literal, proximal metonymic, distal metonymic, or metaphorical sense of an adjective into virtual baskets so that sentences with the same perceived sense were put in the same basket. Our results showed that proximal metonymies were grouped together with the literal sense and with each other more often than with distal metonymies and metaphors. Distal metonymies, in turn, were grouped with literal senses more often than with metaphors. Overall, we concluded that literal senses and proximal metonymies were stored in single representations, distal metonymies formed hybrid representations with literal senses, and metaphors were stored separately from literal senses. Additionally, we discovered that perception of semantic differences is affected by the surrounding senses: distal metonymies were more discernible from literal senses when presented with proximal metonymies, and less so when presented with metaphors.

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A massive amount of textual data now exists in digital repositories in the form of research articles, news articles, reviews, Wikipedia articles, and books, etc. Text clustering is a fundamental data mining technique to perform categorization, topic extraction, and information retrieval. Textual datasets, especially which contain a large number of documents are sparse and have high dimensionality. Hence, traditional clustering techniques such as K-means, Agglomerative clustering, and DBSCAN cannot perform well. In this paper, a clustering technique especially suitable to large text datasets is proposed that overcome these limitations. The proposed technique is based on word embeddings derived from a recent deep learning model named "Bidirectional Encoders Representations using Transformers". The proposed technique is named as WEClustering. The proposed technique deals with the problem of high dimensionality in an effective manner, hence, more accurate clusters are formed. The technique is validated on several datasets of varying sizes and its performance is compared with other widely used and state of the art clustering techniques. The experimental comparison shows that the proposed clustering technique gives a significant improvement over other techniques as measured by metrics such Purity and Adjusted Rand Index.

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When it comes to inferring relations between entities in biomedical texts, Relation Extraction (RE) has become key to biomedical information extraction. Although previous studies focused on using rule-based and machine learning-based approaches, these methods lacked efficiency in terms of the demanding amount of feature processing while resulting in relatively low accuracy. Some existing biomedical relation extraction tools are based on neural networks. Nonetheless, they rarely analyze possible causes of the difference in accuracy among predicates. Also, there have not been enough biomedical datasets that were structured for predicate classification. With these regards, we set our research goals as follows: constructing a large-scale training dataset, namely Biomedical Predicate Relation-extraction with Entity-filtering by PKDE4J (BioPREP), based on SemMedDB then using PKDE4J as an entity-filtering tool, evaluating the performances of each neural network-based algorithms on the structured dataset. We then analyzed our model's performance in-depth by grouping predicates into semantic clusters. Based on comprehensive experimental outcomes, the experiments showed that the BioBERT-based model outperformed other models for predicate classification. The suggested model achieved an f1-score of 0.846 when BioBERT was loaded as the pre-trained model and 0.840 when SciBERT weights were loaded. Moreover, the semantic cluster analysis showed that sentences containing key phrases were classified better, such as comparison verb + 'than'.

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The ability to learn and remember verbal information is highly relevant to many work roles and environments, but we know little about the underlying cognitive mechanisms of those associations. This study examined the hypothesis that unemployment is associated with decreased spontaneous use of higher-order encoding strategies deployed during list learning and recall. Participants were 120 employed and 59 unemployed community-dwelling adults who completed the California Verbal Learning Test-Second Edition (CVLT-II) as part of a broader neuropsychological assessment. Standardized measures of semantic, serial, and subjective clustering were generated from the CVLT-II. After adjusting for data-driven covariates, a significant interaction emerged between employment status and clustering strategy, whereby participants in the employed group exhibited significantly higher scores on semantic clustering, but not serial or subjective clustering, than the unemployed group. The semantic clustering slope score was higher among the employed group and was positively associated with executive functions and declarative memory. These findings suggest that higher-order semantic organizational strategies during supraspan list learning may be relevant to maintaining gainful employment (e.g., mentally organizing work-related instructions and task lists). Future studies might examine semantic clustering in relation to employment changes and work performance, as well as the potential benefit of metacognitive interventions for learning and employment success.

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Alzheimer's disease (AD) is the most common form of dementia, impacting global cognitive performance, including episodic memory. Semantic clustering is a learning strategy involving grouping words of similar meaning and can improve episodic memory performance, e.g., list learning. As the APOE ε4 allele is the most validated genetic risk factor for AD, we predicted that its presence would be associated with poorer list learning performance, and we hypothesized that semantic clustering moderates or mediates this association. The sample comprised 699 healthy older adults participating in the CHARIOT PRO Main Study, 169 of whom were APOE ε4 carriers. Participants' ability to form groups of related stimuli (assessed via a categorization task, CAT), and their use of semantic clustering during list learning, were investigated using the Neuropsychological Assessment Battery (NAB). CAT scores predicted the use of semantic clustering in, and performance on, the list learning task. CAT scores were not significantly lower in APOE ε4 carriers, suggesting that the ability to categorize was preserved. However, APOE ε4 carriers made less use of semantic clustering in list learning. Semantic clustering use partially mediated the relationship between CAT scores and list learning performance, and, in women only, moderated the impact of APOE ε4 on list learning performance. The results suggest that better categorization ability is associated with greater use of mnemonic strategies and better performance on memory tasks regardless of genetic risk, but that APOE ε4 carriers make less use of such strategies. Furthermore, female APOE ε4 carriers may benefit more than their non-carriers from using semantic clustering to aid list learning. Thus, semantic clustering may be a contributing factor of their "cognitive reserve", compensating for potential deficits in episodic memory.

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The Arctic Region experienced a series of significant changes due to shifting climate conditions, resulting in multiple opportunities and challenges for international actors, and encouraging both Arctic and non-Arctic states to promote their own national interests. Hence, the region has become a global priority, and a focus of scientific studies across the Natural Sciences, and Social Sciences and Humanities (SSH) disciplines. This study systematically analyses the literature on the Arctic Region, conducting a multidimensional bibliometric analysis and content analysis on the basis of semantic clustering. The purpose of the analysis is to determine future Arctic-related research themes. The study follows a three-level research framework. The first level of the analysis highlights a disciplinary shift in the Arctic literature from Natural Sciences towards Social Sciences and Humanities, particularly, focusing on the environment, technology, political and energy-related issues. The second level identifies 9 research themes which are validated in the third level. The third level reveals the most prominent terms and prioritized research areas in the Arctic literature, namely, Governance, Security Issues, Economic Factors, Legal Issues, Energy and Natural Resources, Logistics, Climate Change and Environment, Technology, and Socio-cultural and Ethnic Issues.

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Constructed emergency response scenarios provide a basis for decision makers to make management decisions, and the development of such scenarios considers earlier historical cases. Over the decades, the development of emergency response scenarios has mainly implemented the elements of historic cases to describe the grade and influence of an accident. This paper focuses on scenario construction and proposes a corresponding framework based on natural language processing (NLP) using text reports of marine oil spill accidents. For each accident, the original textual reports are first divided into sentence sets corresponding to the temporal evolution. Each sentence set is regarded as a textual description of a marine oil spill scenario. A method is proposed in this paper, based on parsing, named entity recognition (NER) and open information extraction (OpenIE) to process the relation triples that are extracted from the sentence sets. Finally, the relation triples are semantically clustered into different marine oil spill domains to construct scenarios. The research results are validated and indicate that the proposed scenario construction framework can be effectively used in practical applications.

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Objective: The relative importance of various mechanisms supporting declarative verbal memory among older adults remains uncertain. The present study examined the impact of strategy use (specifically semantic clustering) versus other variables known to impact memory performance (age, sex, education, FSIQ, processing speed, and executive functioning) on verbal memory functioning among healthy older adults.Methods: Healthy older adults from the California Verbal Learning Test, Second Edition standardization sample were selected (N = 242). Relationships between verbal memory, demographics variables, and neuropsychological factors were established, and a hierarchical regression analysis was conducted to examine the individual contributions of these variables in predicting memory performance.Results: Bivariate correlations suggested that memory was significantly related to demographic factors, IQ, executive functioning, and semantic clustering. Importantly, hierarchical regression analysis revealed that semantic clustering significantly and independently contributed to recall performance beyond the demonstrated impacts of FSIQ, speed, executive functioning, and demographic variables. Furthermore, FSIQ did not moderate the relationship between semantic clustering and memory indicating that this strategy is an important factor in bolstering recall, independent of FSIQ.Conclusions: Our results highlight the critical importance of semantic clustering utilization in enhancing memory performance among healthy older adults.

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Delayed memory deficits are common for patients with mild traumatic brain injury (mTBI), according to a recent systematic review of meta-analyses (Karr et al., 2014). However, there has been little work to identify different cognitive processes that may be underpinning these delayed memory deficits for mTBI. Frontal cortex is important for delayed memory, and is implicated in the pathophysiology of mTBI; moreover, frontal lobes are typically considered the locus of executive abilities. To further explore these relationships, we sought to partly explain delayed memory deficits after mTBI by examining behavioral indicators of executive function. Results showed that sub-acute as well as chronic mTBI patients performed worse than controls on the delayed memory trial of the Hopkins Verbal Learning Test-Revised (Brandt & Benedict, 2001), recalling approximately 18% and 15% fewer words, respectively. Furthermore, worse delayed memory performance was associated with less use of the cognitive strategy of semantic clustering, and with lower scores for the executive function composite from a standardized neuropsychological battery (NIH EXAMINER; Kramer et al., 2014). In contrast, serial clustering, a memory organizational strategy thought to be less dependent on executive function, did not show strong relationships to clinical status or delayed memory performance. This exploratory work suggests novel hypotheses to be tested in future, confirmatory studies, including that general executive functions and/or semantic clustering will mediate delayed memory deficits following mTBI.

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