Full-text Scientific Articles Research Articles

Growth performance, antioxidant status, intestinal morphology, and body composition of Nile tilapia (Oreochromis niloticus) supplemented with essential oils: A meta-analysis

This study aimed to evaluate the effects of dietary supplementation with essential oils (EOS) on growth performance, antioxidant status in blood serum, intestinal morphology, and whole-body composition of Nile tilapia (Oreochromis niloticus) through a meta-analytic approach. The search and collection of scientific articles were conducted using the PRISMA methodology, and 45 full-text scientific articles were obtained. The data used in the meta-analysis were extracted from these 45 documents. The effect size was assessed through weighted mean differences (WMD) using Der-Simonian and Laird random effects models. Dietary supplementation with EOS increased (P < 0.001) final weight, body weight gain, specific growth rate, feed intake, protein efficiency ratio, and survival but decreased (P < 0.001) feed conversion ratio. In blood serum, EOS supplementation decreased (P < 0.001) the concentration of malondialdehyde and increased (P < 0.001) the concentration of catalase, superoxide dismutase, and glutathione peroxidase. In the foregut, midgut, and hindgut, greater (P < 0.01) villus height, villus width, and number of goblet cells were observed in response to EOS supplementation. EOS supplementation increased (P < 0.01) crude protein content and decreased (P < 0.05) crude lipid content in the whole-body. In conclusion, essential oils can be used as a dietary additive to improve growth performance, antioxidant status in blood serum, and intestinal morphology in Nile tilapia. Likewise, supplementation with essential oils increases the protein content and decreases the fat content in the whole-body of Nile tilapia.

Advancing language models through domain knowledge integration: a comprehensive approach to training, evaluation, and optimization of social scientific neural word embeddings

This article proposes a comprehensive strategy for training, evaluating, and optimizing domain-specific word2vec-based word embeddings, using social science literature as an example. Our primary objectives are: (1) to train the embeddings utilizing a corpus of social science text, (2) to test their performance against domain-unspecific embeddings using our developed intrinsic and extrinsic evaluation strategy, and (3) to enhance their performance even further by using domain knowledge. As an integral part of this approach, we present SociRel-461, a domain-knowledge dictionary designed for the intrinsic evaluation and subsequent refinement of social science word embeddings. Using a dataset of 100,000 full-text scientific articles in sociology, we train multiple vector space models, which we then benchmark against a larger, pre-trained general language embedding model as part of our extrinsic evaluation. Furthermore, we developed a transfer learning multi-label classification task for extrinsic evaluation. Our findings reveal that domain-specific embeddings outperform their domain-unspecific counterparts in both intrinsic and extrinsic evaluations. We also investigated the retrofitting post-processing method to enhance domain-unspecific embeddings with the domain knowledge embedded in SociRel-461. While retrofitting does not enhance our domain-specific vector space models, it significantly improves the performance of the domain-unspecific embeddings. This highlights the potential of retrofitting for the transfer of domain knowledge to domain-unspecific embeddings. Our results emphasize the importance of utilizing domain-specific word embeddings for better performance in domain specific transfer learning tasks, as they outperform conventional embeddings trained on everyday language.

Tracing Class and Capital in Critical AI Research

This article explores the rapidly developing field of Critical AI Studies and its relation to issues of class and capitalism through a hybrid approach based on distant reading of a newly collected corpus of 300 full-text scientific articles, the creation of which is itself a first attempt at properly delineating the field. We find that words related to issues of class are predominantly but not exclusively confined to a set of studies that make up their own distinct subfield of Critical AI Studies, in contrast to, e.g., issues of race and gender, which are more broadly present in the corpus.

Current trends in telemedicine and teledentistry, their application in providing dental care to patients of different ages

Relevance. The significant spread of dental diseases across the population and the failure to provide timely medical care in a medical facility, including emergency services, for various reasons, calls for other ways of doctor-patient interactions, e.g., virtual communication. Telemedicine is an innovative way of dental care provision using electronic information and telecommunication technologies.Material and methods. The review includes the results of original publications on teledentistry implementation into dental practice and the results of its use in patients of different age groups. The studies focused on the application and limitations of teledentistry for the prevention, detection, diagnosis and treatment of oral diseases. Data sources: a search was performed of full-text scientific articles published between 2012 and November 30, 2022, in English, in the electronic databases elibrary, cyberleninka, PubMed and Google Academy.Results. An initial electronic data search identified 2740 publications. Of these, upon exclusion of duplicates and checking for the title and abstract availability, 1100 studies were selected, while 1640 remaining publications were excluded for nonconformance to the inclusion criteria. Then, after the study of the titles and abstracts, 389 studies were subject to a full-text evaluation. Of these, 295 were excluded due to the lack of the doctor-patient interaction analysis. The systematic review included 91 publications, subject to the study evaluation and could be involved in numerical comparisons.Conclusion. Teledentistry has a vast application scope, e.g., online consultations, oral disease diagnosis and prevention. Teledentistry offers opportunities for providing higher-quality oral hygiene care to older patients. Teleconsultation allows for decreasing stress associated with a dental visit. It is especially crucial for patients with dementia who refuse face-to-face communication with the doctor.

Subject-Spatial and Physical Urban Environment as a Condition for the Psychological Security of Urban Residents

Urban residents make up more than half of the world’s population. They are the main resource of any modern city or town, and focus on them and their involvement are decisive factors in any successful urbanistic transformation. The purpose of the study is to summarize research in the field of environmental psychology aimed at identifying the conditions for creating psychological security for urban residents. The author made an analysis of more than 385 articles in Russian and English available in the national bibliographic database of scientific publications (Russian Science Citation Index), scientific publishing houses (Elsevier, SprigerLink, SAGE Publishing), publishing houses of open-access scientific journals (MDPI, Frontiers Media), and free digital repository of open-access full-text scientific articles (PubMed Central). Most of them dated back to the last twenty years. Of these, 80 were selected for an analysis. The facts under consideration were systematized in two aspects: objective security conditions associated with the physical environment (visual complexity, soundscape, climate, etc.) and subjective security conditions associated with the peculiarities of their perception by urban residents. To visualize the obtained conditions of the psychological security of urban residents and create an image of a safe city, the Midjourney neural network was used, which makes it possible to generate text-based images. As a result of the analysis of studies of the psychological safety of urban life, it became possible to describe the conditions that form the feeling of psychological security among urban residents; using the Midjourney neural network, to visualize the image of a safe city; to show the role of the soundscape, ordered environment, social control, segmentation of habitable space and its connection with nature; and to justify to some extent the interchangeability of security components.

Magnetic resonance diagnostic criteria of non-compaction cardiomyopathy: new diagnostic criteria still needed?

Summary Non-compaction cardiomyopathy (NCC) is a rare pathology, but the exact rates of its prevalence are not known due to the lack of a diagnostic gold standard. The purpose of this article is to analyse the available cardiovascular magnetic resonance (CMR) diagnostic criteria of non-compaction described in the literature and to compare their sensitivity and specificity in the diagnosis of NCC. A search of available literature related to the CMR diagnostic criteria of myocardial non-compaction was conducted in the medical database PubMed in February of 2022. The period of publication of scientific articles covered the years from 1996 to 2022. A total of 7 full-text scientific articles were included in the final literature review. The main diagnostic criteria were used: the maximum non-compact (NCM) to compact myocardial layers (CM) ratio (NCM:CM), the percentage of trabeculated left ventricular (LV) myocardial mass, the percentage of trabeculated LV myocardial volume, the non-compact myocardial mass index of the total LV, and the determination of the total LV and the maximal fractal dimension (FD) of the apex with the use of fractal analysis. The lack of accurate diagnostic criteria results in an overdiagnosis of NCC. The highest sensitivity and specificity are associated with the maximum FD &gt; 1.30 of the apex established by applying the fractal analysis method. Fractal analysis requires dedicated software, and this method is difficult to apply in routine clinical practice. Thus, the diagnostic criteria for the NCC using magnetic resonance imaging with higher diagnostic value remain to be sought.

Preferences for Online Learning among Nursing Students: A Systematic Review

Background and objectives: The traditional teaching methods have transitioned to distance learning in all fields of education, including medical and nursing education during the Covid 19 pandemic. We aimed to perform a systematic review on preferences for online modes of learning among nursing students.. Materials and Methods: The investigator conducted a thorough literature search on PubMed and Google scholar using comprehensive search strategies to find published English free full-text scientific articles related to preferences of nursing students to online and face-to-face learning modes. Based on the inclusion criteria, articles were searched. Results: The studies that were selected based on databases give the evidence to convince the different perceptions of nursing students to online learning modes. Out of six, 4 studies show less than 50% of preferences for online learning. Interpretation and conclusions: Current evidence suggests that the online mode of learning has increasing preference along with face-to-face learning in nursing. However, further studies with a larger sample size and longer duration are required. Keywords : Online learning, preferences, nursing students

Social competence and self-esteem: a systematic review

This systematic review aimed to analyze the relationship between social competence and self-esteem in any type of population. The inclusion criteria selected were: (i) studies with results of the relationship between social competence and self-esteem; (ii) experimental and observational empirical studies; (iii) original full-text scientific journal articles written in English. Exclusion criteria referred to studies that could not be included in the inclusion criteria. The search platforms were ProQuest and the meta-search engines SCOPUS and Web of Science. The risk of bias was assessed with the Q-SSP quality checklist and the method of summary of the results was performed with a Microsoft Excel table. The results of the selected studies revealed a correlation between social competence and self-esteem indirectly, so it is concluded that social competence is positively related to self-esteem. Limitations are recognized in terms of the low number of studies found and the restricted variety of experimental designs.

Background of suicide amidst COVID-19 pandemic in India: A review of published literature

Background and Objectives: Globally, suicide is a pertinent public health crisis that affects almost all nations cross-culturally. Suicide is one of the leading causes of death in many countries, even before the COVID-19 pandemic hit worldwide. India, a nation developing rapidly, is also not free from the leashes of suicide deaths. COVID-19 augmented the rate of suicide due to multifaceted determinants. Adequate empirical evidence about data on suicide is also scarce. Materials and Methods: This review synthesizes determinants, available demographic correlates, and reported rates of suicide published in the Indian context. The authors conducted a thorough literature search to find published English free full-text scientific articles related to suicide during the COVID-19 pandemic in the Indian context. Databases relied on for literature were PubMed, Google scholar, and PLOS one databases using comprehensive search strategies to avail the maximum number of studies. Results: Ten out of 76 studies available in the initial search were analyzed thoroughly for ruling out determinants, rates, and sociodemographic correlates of suicide. Fear of COVID-19 infection, financial crisis, mental breakdown, and job loss are cardinal reasons attributed for suicide, and male suicides are more prevalent in this arena. Interpretation and Conclusions: Findings portray factors such as fear of COVID-19 diagnosis, apprehension to become infected, financial crisis, loss of job, and isolation are some of the significant determinants quoted out. The study points out the need for multifaceted policies in preventing this public health crisis.

Scite: A smart citation index that displays the context of citations and classifies their intent using deep learning

Abstract Citation indices are tools used by the academic community for research and research evaluation that aggregate scientific literature output and measure impact by collating citation counts. Citation indices help measure the interconnections between scientific papers but fall short because they fail to communicate contextual information about a citation. The use of citations in research evaluation without consideration of context can be problematic because a citation that presents contrasting evidence to a paper is treated the same as a citation that presents supporting evidence. To solve this problem, we have used machine learning, traditional document ingestion methods, and a network of researchers to develop a “smart citation index” called scite, which categorizes citations based on context. Scite shows how a citation was used by displaying the surrounding textual context from the citing paper and a classification from our deep learning model that indicates whether the statement provides supporting or contrasting evidence for a referenced work, or simply mentions it. Scite has been developed by analyzing over 25 million full-text scientific articles and currently has a database of more than 880 million classified citation statements. Here we describe how scite works and how it can be used to further research and research evaluation.

Smart(er) Citations

Smart(er) Citations

Factores que afectan la recuperación funcional del adulto mayor independiente con fractura de cadera

Introducción: El incremento acelerado e inevitable de la población adulta mayor hace esperar un aumento en los casos de fracturas de cadera, lo cual supone un reto para el sistema de salud de Costa Rica. Objetivo: El objetivo de esta revisión fue establecer los factores que afectan la recuperación funcional de las personas adultas mayores independientes con fractura de cadera. Metodología: estudio de revisión bibliográfica de literatura de las siguientes bases de datos: Pubmed, Tripdatabase y EBSCO. Se eligieron 28 artículos científicos en texto completo publicados entre el año 2011 y 2019, en idioma español o inglés. Según la clasificación de Sackett el 3,5% con nivel de evidencia 1, 35,7% nivel 2, 10,7% nivel 3, 46,4% nivel 4 y 3,5% nivel 5. Resultados: la independencia funcional previa en adultos mayores con fractura de cadera es un factor de buen pronóstico funcional. La afectación de las actividades de vida diaria se da tanto en las actividades básicas como instrumentales, con mayor afectación de las actividades que requieren mayor descarga de peso y fuerza de la extremidad afectada, requiriendo así mismo mayor tiempo para su recuperación. Además, la afectación de la calidad de vida relacionada con la salud se da en todas las dimensiones, con una mayor afectación de la movilidad y las actividades de vida diaria. Conclusión: La recuperación de la capacidad funcional previa y la calidad de vida en adultos mayores independientes con fractura de cadera están influenciadas por múltiples factores, de ahí la importancia de un abordaje interdisciplinario y temprano que permita planificar las mejores estrategias de atención.

Worldwide inequality in access to full text scientific articles: the example of ophthalmology.

BackgroundThe problem of access to medical information, particularly in low-income countries, has been under discussion for many years. Although a number of developments have occurred in the last decade (e.g., the open access (OA) movement and the website Sci-Hub), everyone agrees that these difficulties still persist very widely, mainly due to the fact that paywalls still limit access to approximately 75% of scholarly documents. In this study, we compare the accessibility of recent full text articles in the field of ophthalmology in 27 established institutions located worldwide.MethodsA total of 200 references from articles were retrieved using the PubMed database. Each article was individually checked for OA. Full texts of non-OA (i.e., “paywalled articles”) were examined to determine whether they were available using institutional and Hinari access in each institution studied, using “alternative ways” (i.e., PubMed Central, ResearchGate, Google Scholar, and Online Reprint Request), and using the website Sci-Hub.ResultsThe number of full texts of “paywalled articles” available using institutional and Hinari access showed strong heterogeneity, scattered between 0% full texts to 94.8% (mean = 46.8%; SD = 31.5; median = 51.3%). We found that complementary use of “alternative ways” and Sci-Hub leads to 95.5% of full text “paywalled articles,” and also divides by 14 the average extra costs needed to obtain all full texts on publishers’ websites using pay-per-view.ConclusionsThe scant number of available full text “paywalled articles” in most institutions studied encourages researchers in the field of ophthalmology to use Sci-Hub to search for scientific information. The scientific community and decision-makers must unite and strengthen their efforts to find solutions to improve access to scientific literature worldwide and avoid an implosion of the scientific publishing model. This study is not an endorsement for using Sci-Hub. The authors, their institutions, and publishers accept no responsibility on behalf of readers.

Word embeddings for application in geosciences: development, evaluation, and examples of soil-related concepts

Abstract. A large amount of descriptive information is available in geosciences. This information is usually considered subjective and ill-favoured compared with its numerical counterpart. Considering the advances in natural language processing and machine learning, it is possible to utilise descriptive information and encode it as dense vectors. These word embeddings, which encode information about a word and its linguistic relationships with other words, lay on a multidimensional space where angles and distances have a linguistic interpretation. We used 280 764 full-text scientific articles related to geosciences to train a domain-specific language model capable of generating such embeddings. To evaluate the quality of the numerical representations, we performed three intrinsic evaluations: the capacity to generate analogies, term relatedness compared with the opinion of a human subject, and categorisation of different groups of words. As this is the first attempt to evaluate word embedding for tasks in the geosciences domain, we created a test suite specific for geosciences. We compared our results with general domain embeddings commonly used in other disciplines. As expected, our domain-specific embeddings (GeoVec) outperformed general domain embeddings in all tasks, with an overall performance improvement of 107.9 %. We also presented an example were we successfully emulated part of a taxonomic analysis of soil profiles that was originally applied to soil numerical data, which would not be possible without the use of embeddings. The resulting embedding and test suite will be made available for other researchers to use and expand upon.

Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases

Full-text scientific articles are increasingly available, but capturing the meaning conveyed within an article automatically remains a bottleneck for semantic search and reasoning systems. In this paper we consider elliptical coordinated compound noun phrases that authors use to save space in an article. Systems that do not attend to coordination would incorrectly interpret “breast or lung cancer” as a body part (breast) and a disease (lung cancer) rather than two diseases. The algorithmic approach introduced in this paper uses a generate-and-test strategy where candidate expansions for forward, backward and complex ellipses are generated from syntactic dependencies. Dependencies are also used to create a dictionary of non-coordinated noun phrases that is used during the test phrase. Experiments on 21,280 full-text articles show that more than a million noun phrases were impacted by coordinated ellipses. The system achieves 73.07% precision, 75.38% recall, 74.23% F-score and 94.72% accuracy for new noun phrases in the development set. The precision was higher for backward (82.62 vs. 78.63) and forward expansions (64.82 vs. 60.17) and lower for complex expansions (63.41 vs. 72.59) in a test set. On average 10.79% of all noun phrases would be missed if coordination were not resolved, which corresponds to 48 new noun phrases per article in the journal Carcinogenesis, 52 new phrases per article in Diabetes, and 56 new phrases per article in Endocrinology. Results also show coordinated ellipses are more prevalent in abstracts (12.31% of all noun phrases) than in the body of an article (10.70%). To further test the generalizability of this approach the system (without modification) was used on two new collections.

INFLUENŢA TRATAMENTULUI DE SUPRAFAŢĂ ASUPRA STABILITĂŢII MINI-IMPLANTURILOR ORTODONTICE

Mini-screws have brought new perspectives on the prognosis of the orthodontic treatment due to their ability to provide maximum anchorage and minimum compliance from the patient. Biomaterials used for mini-implant manufacturing are stainless steel, chrome-cobalt alloy, commercially pure titanium and grade 5 titanium alloy. These materials influence the type of cellular response in the host tissue, the stability of the device and, finally, the clinical success. Recent research has met the need for clinicians to enhance the stability of these devices through a series of changes to the surface which is in direct contact with bone. This paper aims to analyze the methods used as a surface treatment for orthodontic mini-implants and to evaluate their influence on the stability of these devices. This paper is a synthesis of existing data in the literature, based on inclusion in the analysis of full-text scientific articles relevant for the chosen topic.

METODE DE EVALUARE A OSTEOINTEGRĂRII IMPLANTURILOR DENTARE

The stability of dental implants is a prerequisite for osseointegration. Osseointegration is the process that involves the formation of bone around the dental implant, resulting in increased stability and its integration in the organism. Therefore, successful osseointegration contributes to a functionally optimal treatment. There is a need for a clinical method capable of measurement of bone quality at the time and following implant placement, to measure the degree of osseointegration and the ability of the implants to distribute loads to the surrounding bone. Research to date focuses on finding an ideal method to assess the osseointegration of dental implants in order to improve and broaden the clinical indications of dental implant systems. This paper aims to supply information about current methods used to assess the osseointegration of dental implants. In this regard, a literature review was conducted. Full-text scientific articles relevant to the chosen topic, written in English or whose text could be accessed in English were included.

Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles

Databases of curated biomedical knowledge, such as the protein–locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts.

RETROSPECTIVĂ DIN LITERATURĂ PRIVIND GREFELE OSOASE AUTOGENE MAXILO-MANDIBULARE

This study is a review of the specialised literature regarding the intraoral autogenous bone grafts used in oral implantology. 382 abstracts of scientific papers, 71 full-text scientific articles and 9 specialized books, out of which 113 included in the references, were studied. The area behind the mandibular third molar, the posterior buccal area of the mandible body and the mandibular symphysis are the most frequently used sites for intraoral block bone harvesting. The mandible should be the first choice in the intraoral donor site selection for peri-implant augmentation, if the quantity of bone that is going to be harvested is considered to be enough.

Layout-aware text extraction from full-text PDF of scientific articles

BackgroundThe Portable Document Format (PDF) is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the ‘Layout-Aware PDF Text Extraction’ (LA-PDFText) system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications.ResultsOur paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1) Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2) Classifying text blocks into rhetorical categories using a rule-based method and (3) Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF. Finally, we discuss preliminary error analysis for our system and identify further areas of improvement.ConclusionsLA-PDFText is an open-source tool for accurately extracting text from full-text scientific articles. The release of the system is available at http://code.google.com/p/lapdftext/.