Miracle-dz/UniFAR-FTUs huggingface dataset:
A modern approach with follower-leading clustering algorithm for visualizing author collaborations and article themes in skin cancer research: A bibliometric analysis

Background: Skin cancers (SCs) arise due to the proliferation of atypical cells that have the potential to infiltrate or metastasize to different areas of the body. There is a lack of understanding regarding the country-based collaborations among authors (CBCA) and article themes on SCs. A clustering algorithm capable of categorizing CBCA and article themes on skin cancer is required. This study aimed to apply a follower-leading clustering algorithm to classify CBCA and article themes and present articles that deserve reading in recent ten years. Methods: Between 2013 and 2022, a total of 6526 articles focusing on SC were extracted from the Web of Science core collection. The descriptive, diagnostic, predictive, and prescriptive analytics model was employed to visualize the study results. Various visualizations, including 4-quadrant radar plots, line charts, scatter plots, network charts, chord diagrams, and impact beam plots, were utilized. The category, journal, authorship, and L-index score were employed to assess individual research achievements. Diagnostic analytics were used to cluster the CBCA and identify common article themes. Keyword weights were utilized to predict article citations, and noteworthy articles were highlighted in prescriptive analytics based on the 100 most highly cited articles on SC (T100SC). Results: The primary entities contributing to SC research include the United States, the University of California, San Francisco in US, dermatology department, and the author Andreas Stang from Germany, who possess higher category, journal, authorship, and L-index scores. The Journal of the American Academy of Dermatology has published the highest number of articles (n = 336, accounting for 5.16% of the total). From the T100SC, 7 distinct themes were identified, with melanoma being the predominant theme (92% representation). A strong correlation was observed between the number of article citations and the keyword weights (F = 81.63; P < .0001). Two articles with the highest citation counts were recommended for reading. Conclusion: By applying the descriptive, diagnostic, predictive, and prescriptive analytics model, 2 noteworthy articles were identified and highlighted on an impact beam plot. These articles are considered deserving of attention and could potentially inspire further research in the field of bibliometrics, focusing on relevant topics related to melanoma.
Life quality improvement of patients with non-small cell lung cancer undergoing targeted therapy: A case study of continuous care

To investigate the improvement effect of targeted therapy on non-small cell carcinoma patients life quality after the continuous nursing intervention. 104 non-small cell lung cancer patients in our hospital from July 2017 to November 2019 were allocated evenly and randomly into the control group (C) and the study group (S). By using clinical baseline data, quality of life questionnaire core 30 for cancer patients, evaluation of patient compliance behavior, the MOS item short-form health survey (SF-36), self rating depression scale (SDS), self rating anxiety scale (SAS), Overall Survival (OS) progression-free survival and adverse reaction symptoms were evaluated for the life quality of patients. There was comparability between the 2 sets of basic data. There was no significant difference in quality of life questionnaire core 30, SF-36, SAS, or SDS scores before treatment. After 3 months, there was a significant difference in the scores of various scales before treatment. At the same time, there was significant statistical significance before and after treatment in Group S. Their compliance rates were 84.62% and 98.08%. Adverse reactions incidence in Group S was lower. Taking a 2-year follow-up period as an example, significant statistical differences existed in OS and progression-free survival rates between adenocarcinoma and squamous carcinoma. SDS and SAS had high consistency in scoring with QLQ-30 and SF-36 scales. Targeted treatment for non-small cell carcinoma patients significantly improves their life quality and reduces the incidence of adverse reactions after continuous nursing intervention.
Women’s lived experience of endometriosis-related fertility issues

Objective The aim of the present study is to conduct a qualitative investigation to provide a deeper understanding of women’s views about endometriosis, fertility and their perception of reproductive options. Methods Semi-structured interviews were conducted by two female psychiatrists, specialized in gynecology and obstetrical consultation-liaison psychiatry, trained in qualitative procedures, with experience in qualitative studies and in psychological support of women attending infertility consultations. No prior relationship with respondents was established before data collection. Interviews were tape-recorded and transcribed. Interviews lasted 45–75 minutes. The transcripts were then analysed using thematic content analysis. Results Twenty-nine women were contacted. Twelve agreed to an interview at the hospital’s infertility clinic. Eleven women with diverse sociodemographic characteristics were included. The key findings of thematic content analysis can be grouped into four topics: (1) Diagnostic announcement and initial delay; (2) Negative perceptions of initial care: pre-diagnosis phase; (3) Struggle with endometriosis and its treatment; (4) Issues related to health problems, fertility and reproductive options. Conclusion Our analysis of the interviews corroborates the distressing impact of the trivialization of pain and the uncertainty of or the long quest for diagnosis. The findings also stress various associated issues, from the diagnostic delay to the low success rates of fertility treatments. This qualitative analysis contributes to better understand the accumulation of negative emotions within the illness trajectory and the poor dyadic adjustment within the couple.
Natural products for the treatment of depression: Insights into signal pathways influencing the hypothalamic–pituitary–adrenal axis

Depression, a prevalent psychiatric malady, afflicts a substantial global demographic, engendering considerable disease burden due to its elevated morbidity and mortality rates. Contemporary therapeutic approaches for depression encompass the administration of serotonin reuptake inhibitors, monoamine oxidase inhibitors, and tricyclic antidepressants, albeit these pharmaceuticals potentially induce adverse neurological and gastrointestinal effects. Traditional Chinese Medicine (TCM) natural products proffer the benefits of multi-target, multi-level, and multi-channel depression treatment modalities. In this investigation, we conducted a comprehensive literature review of the past 5 years in PubMed and other databases utilizing the search terms “Depression,” “Natural medicines,” “Traditional Chinese Medicine,” and “hypothalamic–pituitary–adrenal axis. ” We delineated the 5 most recent and pertinent signaling pathways associated with depression and hypothalamic–pituitary–adrenal (HPA) axis dysregulation: nuclear factor kappa light-chain-enhancer of activated B cell, brain-derived neurotrophic factor, mitogen-activated protein kinase, cyclic AMP/protein kinase A, and phosphoinositide 3-kinase/protein kinase B. Additionally, we deliberated the antidepressant mechanisms of natural medicines comprising alkaloids, flavonoids, polyphenols, saponins, and quinones via diverse pathways. This research endeavor endeavored to encapsulate and synthesize the progression of TCMs in modulating HPA axis-associated signaling pathways to mitigate depression, thereby furnishing robust evidence for ensuing research in this domain.
Comprehensive assessment of the efficacy and safety of a clay mask in oily and acne skin

Oily skin, characterized by excessive sebum production, can lead to acne and have psychosocial impacts due to changes in appearance. Recent research has shown interest in treatments for oil control, with kaolin and bentonite emerging as promising options. Despite their potential, comprehensive studies on these ingredients are still in the nascent stages.
AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation

Few-shot image generation (FSIG) aims to learn to generate new and diverse images given few (e.g., 10) training samples. Recent work has addressed FSIG by leveraging a GAN pre-trained on a large-scale source domain and adapting it to the target domain with few target samples. Central to recent FSIG methods are knowledge preservation criteria, which select and preserve a subset of source knowledge to the adapted model. However, a major limitation of existing methods is that their knowledge preserving criteria consider only source domain/task and fail to consider target domain/adaptation in selecting source knowledge, casting doubt on their suitability for setups of different proximity between source and target domain. Our work makes two contributions. Firstly, we revisit recent FSIG works and their experiments. We reveal that under setups which assumption of close proximity between source and target domains is relaxed, many existing state-of-the-art (SOTA) methods which consider only source domain in knowledge preserving perform no better than a baseline method. As our second contribution, we propose Adaptation-Aware kernel Modulation (AdAM) for general FSIG of different source-target domain proximity. Extensive experiments show that AdAM consistently achieves SOTA performance in FSIG, including challenging setups where source and target domains are more apart.
An experimental study of secondary oil migration in a three-dimensional tilted porous medium

A three-dimensional physical experiment was conducted to study secondary oil migration under an impermeable inclined cap. Light-colored oil was released continuously at a slow rate of about 0.1 mL/min from a point at the base of an initially water-saturated porous model. With buoyancy as a primary driving force, a vertical cylindrical shape of an oil migration pathway was observed first, and then a layer-shaped lateral migration pathway was observed beneath the top inclined sealing plate once the oil cluster had reached the top cap. Magnetic resonance imaging was used to observe the migration processes—for example, morphology of the migration pathway, intermittency of oil bubbles, and variation of oil saturation within the migration paths. Results show that the snap-off phenomenon (related to fast local imbibition processes) occurred more commonly during vertical migration than it did during lateral migration. The lateral migration pathway that parallels to the top inclined cap has a typical vertical thickness of 2 to 4 cm (0.8–1.6 in.) (i.e., roughly 40–80 pores). This thickness is consistent with the prediction derived from scaling laws related to pore size and Bond number. Along the lateral migration direction, the sectional area and the horizontal width of the migration pathway fluctuate significantly, although the average oil saturation along the pathway remains almost the same. After stopping the initial oil injection, the sectional area of the migration pathway shrinks significantly. Therefore, we believe that this significant shrinking of the migration pathway is the main reason why only a relatively small volume of oil and gas has been lost during secondary migration.
Geochemistry of Sandstones from the Upper Miocene Kudankulam Formation, Southern India: Implications for Provenance, Weathering, and Tectonic Setting

ABSTRACT Petrographic, major, trace, and rare earth element compositions of sandstones from the upper Miocene Kudankulam Formation, Southern India, have been investigated to determine their provenance, tectonic setting, and weathering conditions. All sandstone samples are highly enriched in quartz (Q) but poor in feldspar (F) and lithic fragments (L). The major-element concentrations of these sandstones reveal the relative homogeneity of their source. Geochemically, the Kudankulam sandstones are classified as arkose, subarkose, litharenite, and sublitharenite. The CIA values (chemical index of alteration; mean value 44.5) for these sandstones and the A-CN-K diagram suggest their low-weathering nature. Similarly, their Fe2O3* + MgO (mean 2.7), Al2O3/SiO2 ( 0.09), K2O/Na2O ( 2.2) ratios and TiO2 contents ( 0.3) are consistent with a passive-margin setting. The Eu/Eu* ( 0.5), (La/Lu)cn ( 21), La/Sc ( 5.9), Th/Sc ( 1.9), La/Co ( 5.7), Th/Co ( 1.8), and Cr/Th ( 5.3) ratios support a felsic source for these sandstones. Chondrite-normalized REE patterns with LREE enrichment, flat HREE, and negative Eu anomaly also are attributed to felsic source-rock characteristics for Kudankulam sandstones. Total REE concentrations of these sandstones reflect the variations in their grain-size fractions. The source rocks are probably identified to be Proterozoic gneisses, charnockites, and granites of the Kerala Khondalite Belt, which must have been exposed at least since the late Miocene. Finally, the unusual Ni enrichment in the Kudankulam sandstones, unaccompanied by a similar enrichment in Cr, Co, and V, may be related to either the presence of pyrite in the sandstones or, more likely, the fractionation of garnet from the source rocks during transportation.
Sensitivity of habitat network models to changes in maximum dispersal distance

Predicting the presence or absence (occurrence-state) of species in a certain area is highly important for conservation. Occurrence-state can be assessed by network models that take suitable habitat patches as nodes, connected by potential dispersal of species. To determine connections, a connectivity threshold is set at the species’ maximum dispersal distance. However, this requires field observations prone to underestimation, so for most animal species there are no trustable maximum dispersal distance estimations. This limits the development of accurate network models to predict species occurrence-state. In this study, we performed a sensitivity analysis of the performance of network models to different settings of maximum dispersal distance. Our approach, applied on six amphibian species in Switzerland, used habitat suitability modelling to define habitat patches, which were linked within a dispersal distance threshold to form habitat networks. We used network topological measures, patch suitability, and patch size to explain species occurrence-state in habitat patches through boosted regression trees. These modelling steps were repeated on each species for different maximum dispersal distances, including a species-specific value from literature. We evaluated mainly the predictive performance and predictor importance among the network models. We found that predictive performance had a positive relation with the distance threshold, and that almost none of the species-specific values from literature yielded the best performance across tested thresholds. With increasing dispersal distance, the importance of the habitat-quality-related variable decreased, whereas that of the topology-related predictors increased. We conclude that the sensitivity of these models to the dispersal distance parameter stems from the very different topologies formed with different movement assumptions. Most reported maximum dispersal distances are underestimated, presumably due to leptokurtic dispersal distribution. Our results imply that caution should be taken when selecting a dispersal distance threshold, considering higher values than those derived from field reports, to account for long-distance dispersers.
The net effect of wealth on health—Investigating noncommunicable diseases mortality in the context of regional affluence

The wealth-health relationship is not unambiguous and constant. Greater wealth affects individual and population health in opposite ways. Increased risk factors especially raise the probability of noncommunicable diseases (NCDs) impacting a population. Conversely, better healthcare and awareness reduce the chances of developing these diseases or increase the likelihood of treatment and cure. Therefore, this paper aims to assess and quantify the hard-to-grasp overall impact of prosperity on mortality from selected NCDs, allowing us to capture the relevant differences between European regions. In particular, we attempt to estimate the net effect of affluence and the health economic threshold of the GDP-mortality relationship, by developing a dedicated analytical tool based on joinpoint regression and forecasting methods. Our results show that in the case of most investigated diseases in more impoverished regions, a clear pattern reflects mortality rising with prosperity. After crossing the health economic threshold of around 20 thousand euros per capita, the trend changes by stabilising or reversing. The research we present shows that health policy should be more diversified locally to enable health convergence at the national and European regional levels. Moreover, health policy should evolve to prioritise mental and neurological disorders, by improving the resource allocation and increasing public awareness.
Prediction of sentinel lymph node metastasis in breast cancer by using deep learning radiomics based on ultrasound images

Sentinel lymph node metastasis (SLNM) is a crucial predictor for breast cancer treatment and survival. This study was designed to propose deep learning (DL) models based on grayscale ultrasound, color Doppler flow imaging (CDFI), and elastography images, and to evaluate how DL radiomics can be used to classify SLNM in breast cancer. Clinical and ultrasound data of 317 patients diagnosed with breast cancer at the Second Affiliated Hospital of Nanchang University were collected from January 2018 to December 2021 and randomly divided into training and internal validation cohorts at a ratio of 7:3. An external validation cohort comprising data from Nanchang Third Hospital with 42 patients collected. Three DL models, namely DL-grayscale, DL-CDFI, and DL-elastography, were proposed to predict SLNM by analyzing grayscale ultrasound, CDFI, and elastography images. Three DL models were compared and evaluated to assess diagnostic performance based on the area under the curve (AUC). The AUCs of the DL-grayscale were 0.855 and 0.788 in the internal and external validation cohorts, respectively. For the DL-CDFI model, the AUCs were 0.761 and 0.728, respectively. The diagnostic performance of DL-elastography was superior to that of the DL-grayscale and DL-CDFI. The AUC of the DL-elastography model was 0.879 in the internal validation cohort, with a classification accuracy of 86.13%, sensitivity of 91.60%, and specificity of 82.79%. The generalization capability of DL-elastography remained high in the external cohort, with an AUC of 0.876, and an accuracy of 85.00%. DL radiomics can be used to classify SLNM in breast cancer using ultrasound images. The proposed DL-elastography model based on elastography images achieved the best diagnostic performance and holds good potential for the management of patients with SLNM.
An investigation of the population connectivity of sardines (Sardinops sagax) of the KZN sardine run using meristic, morphological and genetic data.

ii Preface iii Declaration iv Plagiarism iv Publications v Other research outputs vi Acknowledgements 1 Chapter one: 2 General introduction 2 1.1. The sardine run: an overview 2 1.2. Ecological phenomenon: The sardine run and it’s fishery 4 1.3. Proximate and ultimate factors: current hypotheses about the sardine run 6 1.3. 1. Ultimate factors 6 1.3. 2. Proximate factors 11 1.4. Motivation and rationale for this study 12 1.4. 1. Population genetic and morphological techniques in population delineation 12 1.4. 2. Conclusions 15 1.4. 3. Arrangement of dissertation 17 Chapter two: 18 Materials and methods 18 2.1 Study sites and sample collection 18 2.2 Meristic data collection and analysis 21 2.3. Morphological data collection and analysis 22 2.3. 1. Material collection and preparation 22 2.3. 2. Multivariate and Geometric analysis 23 2.4 Genetic material, primer and data collection, and analysis 26 2.4. 1. Primer selection 26 2.4. 2. Material collection and preparation 29 2.4. 3. EPIC encoded data collection and analysis 30 2.4. 4. mtCOI data collection and analysis 31 Chapter three: 35
Bibliometric review on sleep and Alzheimer disease between 1986 and 2023

Objective: Alzheimer disease (AD) is a major disease that affects the elderly worldwide. Therefore, this study aimed to examine the relationship between AD and sleep disorders, identify journal publications and collaborators, and analyze keywords and research trends using a bibliometric method. Methods: Data retrieval is based on the Web of Science Core Collection database. CiteSpace V.6. 1.R6 was used to analyze bibliometric analysis, calculate centrality, and draw co-occurrence maps of countries/regions, institutions, authors, published journals, cited literature, keyword co-occurrence maps, cluster maps, time graphs, and emergent maps from January 1986 to April 2023. Results: There were 4677 publications relevant to AD and sleep disorders. From 1986 to 2023, the number of publications per year showed an increasing trend. The United States not only has the largest output of publications, the first in the centrality ranking, but also owns the 3 highest frequencies of publication institutions. The journal NEUROLOGY has the highest citation frequency, reaching 2671, with a median centrality value of 0.64. A comprehensive analysis of centrality showed that AD, circadian rhythm, dementia, Parkinson disease, sleep, and older adults are both high-frequency words and high centrality words, becoming core keywords in this field. Conclusions: This was the first study to provide an overview, about the current main status of development, hot spots of the study, and the future trends in sleep disorders and AD, which provides a comprehensive review of the trends and gaps in field of sleep and AD, and thus lays the groundwork for future research.
Exploring determinants of formation of cognitive anchors from altruistic messages: A fuzzy DEMATEL approach

Altruistic communication by non-profit organizations plays a crucial role in shaping individuals’ perceptions and beliefs about altruism. One of the indicators of effective communication is the anchoring of the messages. Therefore, understanding the underlying determinants of anchoring in altruistic communication is essential. Despite the importance of anchoring in the communication of altruism, extant research has not done much to examine the determinants of anchoring in altruistic communication. This paper investigates the determinants of anchoring in non-profit organizations’ altruistic communication through the lens of the dual process theory. It applies the Fuzzy Decision Making Trial and Evaluation Laboratory (F-DEMATEL) method to analyze the causal and effect factors. Data were gathered from 12 social communication experts based in Taiwan. Out of the 12 proposed determinants, three factors, namely consistency, cultural consideration, and emotional anchoring, were established as significant causal factors. Consistency had causal effects on five other factors, namely, the use of metaphors, the use of antinomies, thematic anchoring, understanding the cognitive ability of the audience, and crafting engaging information. Cultural consideration had causal effects on feedback, naming, use of antinomies, thematic anchoring, emotional anchoring, and repetition. Emotional anchoring had causal effects on thematic anchoring, use of antinomies, use of metaphors, consistency, naming, feedback, understanding the cognitive ability of the audience, and repetition. On the other hand, feedback, naming, and use of antinomies were established as significant effect factors. The study’s findings offer crucial contributions to the social communication literature and provide important insights for social communication practitioners.