Internal Criteria Research Articles

FACTORS OF SOCIO-PSYCHOLOGICAL ADAPTATION AND ANXIETY OF REFUGEES DURING THE WAR

The article provides a theoretical analysis of the problem of anxiety, the tendency of a person to experience anxiety, which is connected with the premonition of real or imagined danger. The purpose of the article is to review and analyse the factors of socio-psychological adaptation and anxiety of refugees in terms of war, as well as psychological techniques to develop in them a new attitude to stress reactions as a resource that can strengthen immunity to traumatization. The study used the methods of terminological, substantive and statistical analysis in determining the content and essence of anxiety as a state and process of experiencing, as well as modelling and projecting methods to find factors of social and psychological adaptation and reducing the level of anxiety of refugees during the war. It has been emphasized that anxiety is an individual psychological feature reflecting an increased tendency to feel alarm in various life situations, in particular those that do not objectively foresee this. Common and distinctive features between anxiety and alarm have been identified. In the structure of anxiety, cognitive, emotional and operational components have been found and described, among which the dominant position is occupied by an emotional response to an unfavourable life situation. It has been shown that anxiety is divided into two main categories: covert and overt. It has been pointed out that there is a connection between the state of alarm and the strength of the individual’s nervous system. Assumptions are expressed regarding the inverse correlation of the strength and sensitivity of the subject’s nervous system. The analysis of scientific research has shown that anxiety enables an individual to respond to a threatening situation adaptively. Anxiety also changes the nature of the behaviour, leads to increased behavioural activity, encourages more intense and purposeful efforts, and thereby performs an adaptive function. It has been emphasized that if the anxiety is intense and long-lasting, it prevents the formation of adaptive behaviour and leads to violations of behavioural integration, and sometimes to clinically expressed disorders of the psyche and behaviour. Peculiarities of the person’s psychological states in terms of war events have been analysed. It is argued that the most important self-preservation strategy is to change the subject’s attitude to war traumatization. A person should know that it is not at all necessary to become a victim of life’s trials, that not every stress causes post-traumatic disorders, and that stress energy can be transformed and used effectively. It has been established that a new attitude to stress reactions as a resource strengthens immunity to trauma and promotes post-traumatic growth. It has been noted that adaptation and the ability to adapt is a prerequisite for the future active and productive activity of an individual in any sphere of life. When a person feels free and comfortable (adapted), they perform both their social and professional roles well, which is very important in the process of social interaction both during education and in later life. Adaptation is divided into external and internal, and such types of adaptation are distinguished as pedagogical, professional, social, biological, and psychological ones. Factors have been clarified, and external and internal criteria of psychological and pedagogical adaptation have been distinguished. At the same time, it has been concluded that socio-psychological adaptation to the conditions of a military conflict occurs as an adaptation to a socially tense, constantly changing environment. Therefore, it is important to shift the emphasis from the state of adaptation to the properties of adaptability of the individual and the community, which are associated with such constructs as resilience, psychological resilience, and group efficiency.

Application of QSAR models for acute toxicity of tetrazole compounds administrated orally and intraperitoneally in rat and mouse

Tetrazoles and their derivatives possess various biological activities, such as antibacterial, anti-fungal, and other activities. However, these compounds may induce specific cumulative and toxic effects in living organisms. Therefore, quantitative structure-activity relationship (QSAR) models were constructed to study the acute oral toxicity of tetrazoles in rats and mice. The toxicity data of 111 tetrazole compounds were collected using the ChemIDplus, ChEMBL and ECHA databases as response variables, while the PaDEL-descriptor generated the 2D descriptors as independent variables. The models were developed and validated following the OECD guidelines by the DTC-QSAR tool. Three QSAR models were successfully established for the oral routes of rat and mouse and the intraperitoneal route of mouse, respectively. The scatter plots showed high consistency between the training and test data sets. All the models successfully met the external and internal validation criteria. Most of the descriptors kept in the final models exhibited positive correlations with toxicity, whereas only 6 descriptors exhibited negative associations. Several chemicals were identified as response or structural outliers, based on the standardized residuals and leverage values. In conclusion, the findings of this investigation demonstrate that the proposed QSAR models hold promise in forecasting the acute toxicity of recently developed or synthesized tetrazole compounds, thereby mitigating potential risks to human health and the environment.

Multiplexed RT-qPCR Coupled with Whole-Genome Sequencing to Monitor a SARS-CoV-2 Omicron Variant of Concern in a Hospital Laboratory Setting in Latvia.

At the end of 2021, the SARS-CoV-2 Omicron variant of concern (VOC) displaced the previously dominant Delta VOC and enhanced diagnostic and therapeutic challenges worldwide. Respiratory specimens submitted to the Riga East University Hospital Laboratory Service by the central and regional hospitals of Latvia from January to March 2022 that were positive for SARS-CoV-2 RNA were tested by commercial multiplexed RT-qPCR targeting three of the Omicron VOC signature mutations: ΔH69/V70, E484A, and N501Y. Of the specimens tested and analyzed in parallel by whole-genome sequencing (WGS), 964 passed the internal quality criteria (genome coverage ≥90%, read depth ≥400×) and the Nextstrain's quality threshold for "good". We validated the detection accuracy of RT-qPCR for each target individually by using WGS as a control. The results were concordant with both approaches for 938 specimens, with the correct classification rate exceeding 96% for each target (CI 95%); however, the presumptive WHO label was misassigned for 21 specimens. The RT-qPCR genotyping provided an acceptable means to pre-monitor the prevalence of the two presumptive Omicron VOC sublineages, BA.1 and BA.2.

Investigating the relationship between ownership structure, board composition, and company performance: An extensive overview of companies in the textile industry in Iran

The present study examines the relationship between the composition of the board of directors, ownership structure, and company performance in companies that are members of the Iranian capital market. This research has been investigated in a statistical sample of 113 companies from the member companies of Iran's capital market between 2011 and 2021. The results of this research have been analysed by the panel analysis method which we use two internal and external criteria to examine the company's performance. Thus the results show that there is a correlation between the proportion of foreign directors on the board of directors and the concentration of ownership with the company's internal performance criteria. Also, another result of this research is that there is a relationship between the proportion of foreign directors on the board of directors and the concentration of ownership with the external measure of the company's performance. Moreover, this research paper analyses companies in the textile industry in Iran during the sample period.

Why are these publications missing? Uncovering the reasons behind the exclusion of documents in free‐access scholarly databases

AbstractThis study analyses the coverage of seven free‐access bibliographic databases (Crossref, Dimensions—non‐subscription version, Google Scholar, Lens, Microsoft Academic, Scilit, and Semantic Scholar) to identify the potential reasons that might cause the exclusion of scholarly documents and how they could influence coverage. To do this, 116 k randomly selected bibliographic records from Crossref were used as a baseline. API endpoints and web scraping were used to query each database. The results show that coverage differences are mainly caused by the way each service builds their databases. While classic bibliographic databases ingest almost the exact same content from Crossref (Lens and Scilit miss 0.1% and 0.2% of the records, respectively), academic search engines present lower coverage (Google Scholar does not find: 9.8%, Semantic Scholar: 10%, and Microsoft Academic: 12%). Coverage differences are mainly attributed to external factors, such as web accessibility and robot exclusion policies (39.2%–46%), and internal requirements that exclude secondary content (6.5%–11.6%). In the case of Dimensions, the only classic bibliographic database with the lowest coverage (7.6%), internal selection criteria such as the indexation of full books instead of book chapters (65%) and the exclusion of secondary content (15%) are the main motives of missing publications.

PENGEMBANGAN MODUL FISIKA STATISTIK BERBASIS LEARNING CYCLE TERINTGRASI PROFETIK

Development is research with the output of a product, either simply or structurally. Development research is used to design and produce a product systematically and meet internal practicality criteria. universal and use the framework of science. To realize physics education students, of course, the statistical physics module is in accordance with student needs. This study aims to develop a learning cycle-based statistical physics module/book. The method used is Research and Development (R&D) with the 4-D model (Four D) which is a learning device development model. The 4D development model consists of 4 main stages, namely: 1. Define (Delimitation), 2. Design (Design), 3. Develop (Development) and 4. Disseminate (Dissemination), adapted to the 4-P Model, namely Defining, Designing, Development , and Dissemination. The products developed are in the form of modules or textbooks. The data source is physics education students at FKIP UHAMKA. Data sources were obtained from informants, documents, activity processes and validators. Data collection techniques using questionnaires and documentation, while the data analysis techniques used the gain score test, quantitative and qualitative descriptive analysis. Model validation was carried out using expert judgment using the Delphi technique.The results of this study are the modules / textbooks of physics statistics. Validation from material experts / academic experts, display media and revisions were 77.03 and 86.38 with very good categories. The results of the reaction evaluation to measure the respondents' responses to the quality of the implementation of the modules / textbooks were considered good. In the effectiveness of the use of modules/textbooks there are significant changes to students before and after, as evidenced by the high effectiveness or feasibility of the statistical physics module/textbook in the criteria of "Very High" and the N-Gain percentage score shows the number 92 meaning the module/coursebook statistical physics. For prophetic value, in this case it is integrated through effectiveness in using the modules / textbooks used, prophetic assessors are taken from several criteria, namely shidiq means honest with an average of 8.64, amanah means responsibility with an average of 9.08 and tabliq / truth / communicative with an average of 9.33, fathonah which means intelligent / curious, with an average of 8.67. The conclusions from the results of this study are in the form of modules / textbooks that can be used as a guide by students and lecturers in conducting lectures at FKIP UHAMKA

The influence of natural image statistics on upright orientation judgements

Humans have well-documented priors for many features present in nature that guide visual perception. Despite being putatively grounded in the statistical regularities of the environment, scene priors are frequently violated due to the inherent variability of visual features from one scene to the next. However, these repeated violations do not appreciably challenge visuo-cognitive function, necessitating the broad use of priors in conjunction with context-specific information. We investigated the trade-off between participants' internal expectations formed from both longer-term priors and those formed from immediate contextual information using a perceptual inference task and naturalistic stimuli. Notably, our task required participants to make perceptual inferences about naturalistic images using their own internal criteria, rather than making comparative judgements. Nonetheless, we show that observers' performance is well approximated by a model that makes inferences using a prior for low-level image statistics, aggregated over many images. We further show that the dependence on this prior is rapidly re-weighted against contextual information, even when misleading. Our results therefore provide insight into how apparent high-level interpretations of scene appearances follow from the most basic of perceptual processes, which are grounded in the statistics of natural images.

Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm

ABSTRACT The horse herd optimization algorithm (HOA), one of the more contemporary metaheuristic algorithms, has demonstrated superior performance in a number of challenging optimization tasks. In the present work, the descriptor selection issue is resolved by classifying different essential oil retention indices using the binary form, BHOA. Based on internal and external prediction criteria, Z-shape transfer functions (ZTF) were tested to verify their efficiency in improving BHOA performance in QSPR modelling for predicting retention indices of essential oils. The evaluation criteria involved the mean-squared error of the training and testing datasets (MSE), and leave-one-out internal and external validation (Q 2). The degree of convergence of the proposed Z-shaped transfer functions was compared. In addition, K-fold cross validation with k = 5 was applied. The results show that ZTF, especially ZTF1, greatly improves the performance of the original BHOA. Comparatively speaking, ZTF, especially ZTF1, exhibits the fastest convergence behaviour of the binary algorithms. It chooses the fewest descriptors and requires the fewest iterations to achieve excellent prediction performance.

Certification by the German Society for Neurorehabiliation, DGNR : Performance and quality of the "Centers for weaning from aventilator in early neurological and neurosurgical rehabilitation"

Certification of centers for weaning from aventilator in neurological neurosurgical early rehabilitation (NNER) by the German Society for Neurorehabilitation (DGNR) is possible since 1 October 2021. The results of certification of facilities in the first year after starting the procedure are presented. As part of the certification process 28criteria are assessed including aset of mandatory characteristics of the facility. The criteria are divided into structural criteria (i = 7), diagnostic criteria (i = 6), personnel criteria (i = 3), internal organization criteria (i = 7), and quality management criteria (i = 5). A total of 13 centers were certified in the first year, with acombined total of 283 beds for weaning from aventilator in the NNER and served 2278 persons to be weaned from aventilator in the year before certification, with amedian of 134 per facility (range 44-414). Only rarely was weaning unsuccessful, requiring conversion to home mechanical ventilation before discharge (invasive home mechanical ventilation median per facility 10persons, range 2-25; non-invasive home mechanical ventilation median 0persons, range 0-57). Ahigh level of process and structural quality was documented for the certified centers: across all areas of assessment, the individual certification criteria were met in the vast majority of cases (median degree of complete fulfilment 86%) or met with improvement potentials documented by the auditors (median 11%). Successful weaning in NNER and ahigh level of process and structural quality can be demonstrated by the certification results of centers that follow this integrative approach to weaning from aventilator in aNNER setting.

Safety Performance and Failure Criteria of Lithium-Ion Batteries under Mechanical Abuse

With the increasing global focus on environmental issues, controlling carbon dioxide emissions has become an important global agenda. In this context, the development of new energy vehicles, such as electric vehicles, is flourishing. However, as a crucial power source for electric vehicles, the safety performance of lithium-ion batteries under mechanical abuse has drawn widespread attention. Evaluating the safety performance of lithium-ion batteries requires in-depth research. This paper provides a review of recent experimental and numerical simulation studies on the mechanical abuse of lithium-ion batteries. It showcases the main methods and conclusions of experimental research, compares different response forms under quasi-static and dynamic loading, discusses the causes of strain-rate dependence in lithium-ion batteries, and briefly describes the impact of the state of charge (SOC) on safety performance under mechanical abuse, as well as the influence of mechanical abuse on battery capacity and impedance characteristics. Furthermore, this paper summarizes the methods of numerical simulation research, analyzes the advantages and disadvantages of detailed modeling and homogenized modeling methods, summarizes the strain-based internal short circuit failure criteria, and reviews numerical predictive models based on multiphysics coupling. Finally, it presents the latest progress in studying the safety performance of battery packs through numerical simulations.

Motivasi Petani dalam Pemanfaatan Limbah Ternak sebagai Pupuk Organik di Kabupaten Karanganyar

Indonesia is primarily an agricultural country with a wealth of natural resources, making agriculture one of the most significant foundations of the nation's economy. One initiative in agricultural growth is organic farming. Organic farming requires that chemical compounds not pollute the land used and have good accessibility. One of the efforts to prevent agricultural and environmental pollution is to use organic fertilizers. Organic fertilizers are obtained from the utilization of livestock waste. Farmers still do not fully use organic fertilizers in their farming. So, motivation is needed to encourage farmers to utilize livestock waste as organic fertilizer. This study aimed to investigate the elements that affect farmer motivation, the extent to which farmers are motivated to use animal waste, and the variables that affect farmers' motivation to use livestock waste as organic fertilizer. The sample data collection technique was purposive. As many as 77 farmer respondents used livestock waste. Multiple linear regression analysis is employed in this study's quantitative descriptive methodology to examine the elements that influence farmers' decisions to use animal manure. The study's findings indicate that while non-formal education falls into the high category, internal criteria like age, experience, and formal education fall into the moderate category. External elements are categorized in the high category and consist of capital accessibility, infrastructure accessibility, and counseling intensity. Farmers' motivation to use animal manure is another indicator of their high level of motivation. Age, formal education, and non-formal education are internal factors that have no impact on farmers' inclination to use animal waste; nevertheless, farming experience has an impact. Farmers' willingness to use livestock waste is influenced by external factors such as the accessibility of capital, the quality of infrastructure, and the level of counseling.

ClusterBMA: Bayesian model averaging for clustering.

Various methods have been developed to combine inference across multiple sets of results for unsupervised clustering, within the ensemble clustering literature. The approach of reporting results from one 'best' model out of several candidate clustering models generally ignores the uncertainty that arises from model selection, and results in inferences that are sensitive to the particular model and parameters chosen. Bayesian model averaging (BMA) is a popular approach for combining results across multiple models that offers some attractive benefits in this setting, including probabilistic interpretation of the combined cluster structure and quantification of model-based uncertainty. In this work we introduce clusterBMA, a method that enables weighted model averaging across results from multiple unsupervised clustering algorithms. We use clustering internal validation criteria to develop an approximation of the posterior model probability, used for weighting the results from each model. From a combined posterior similarity matrix representing a weighted average of the clustering solutions across models, we apply symmetric simplex matrix factorisation to calculate final probabilistic cluster allocations. In addition to outperforming other ensemble clustering methods on simulated data, clusterBMA offers unique features including probabilistic allocation to averaged clusters, combining allocation probabilities from 'hard' and 'soft' clustering algorithms, and measuring model-based uncertainty in averaged cluster allocation. This method is implemented in an accompanying R package of the same name. We use simulated datasets to explore the ability of the proposed technique to identify robust integrated clusters with varying levels of separation between subgroups, and with varying numbers of clusters between models. Benchmarking accuracy against four other ensemble methods previously demonstrated to be highly effective in the literature, clusterBMA matches or exceeds the performance of competing approaches under various conditions of dimensionality and cluster separation. clusterBMA substantially outperformed other ensemble methods for high dimensional simulated data with low cluster separation, with 1.16 to 7.12 times better performance as measured by the Adjusted Rand Index. We also explore the performance of this approach through a case study that aims to identify probabilistic clusters of individuals based on electroencephalography (EEG) data. In applied settings for clustering individuals based on health data, the features of probabilistic allocation and measurement of model-based uncertainty in averaged clusters are useful for clinical relevance and statistical communication.

Evaluación de los programas de investigación de un plan de estudios de licenciatura en psicología

Higher educational institutions must accredit and certify their study plans to improve their academic quality, through continuous evaluation. The Iztacala Faculty of Higher Studies implemented a new curriculum, from which three generations have already graduated, formally allowing its evaluation. The objective of this research was to evaluate the programs of courses in the Research field from the Behavioral, Cognitive-behavioral, and Interbehavioral traditions; precisely, their internal coherence, consistency between them, and their connection with the graduation profile. Using an adaptation of Bloom's taxonomy, rubrics and an instrument were designed so that 18 teachers, participating in the study, who evaluated the courses. Analysis was performed using internal coherence criteria: the complexity of the general and specific objectives, a hierarchy of the specific objectives, the relationship between objectives and content, feasibility and updating of the bibliography; and for consistency, were overlaps or repetitions of objectives and contents between the subjects, thematic gaps and the connection between the graduation profile and the objectives of the set of academic courses. In the results it can be noted that the five courses evaluated require modifications in some aspect of internal coherence. Regarding consistency, some overlapping objectives and thematic contents were identified, as well as thematic gaps. A proposal to modify the academic programs is discussed according to the results found for an eventual discussion and approval by the professors in the field of research.

A Pedagogical Appraisal of the Higher Secondary Textbook of Bangladesh for Teaching Listening and Speaking Skills

Textbook evaluation is essential to determine whether the text is standard enough to achieve the teaching objectives. The researcher used the qualitative research method to collect data for this study to investigate the suitability of the textbook of Higher Secondary Level in Bangladesh for teaching listening and speaking skills. Based on the internal evaluation criteria (MacDonough & Shaw, 2013) of the text and semi-structured interviews with eight teachers, the findings reveal that the book includes inadequate lessons and inappropriate activities for improving learners’ listening skills. However, the study finds the book satisfactory for teaching speaking skills with suitable lessons and activities, although there is still room for improvement in the text by including more diverse speaking activities.

Mathematical modelling of the manganese level in the muscle tissue of cattle

The results of determining the most effective model for predicting the level of manganese in the muscle tissue of Hereford cattle for in vivo assessment of the elemental status of animals by low invasive methods are presented. The experiment was carried out using hematological and biochemical blood tests and atomic absorption analysis of the muscle tissue of cattle. The data obtained are used to fit the regression model using the least square method. Skeletal muscle samples weighing 100 g from the diaphragm muscle of the Hereford cattle bred in the southern part of Western Siberia in the conditions of industrial complex were taken for analysis. Manganese concentration in tissues was assessed by atomic absorption analysis on an MGA-1000 spectrometer. The content of erythrocytes, leukocytes, and hemoglobin was determined on an automatic hematology analyzer PCE-90VET. Protein, albumin, globulin, urea, uric acid, and cholesterol levels were determined by photometric methods on a Photometer-5010 semi-automatic biochemical analyzer. The effects of regression models were calculated using the least square method. Selection of the best model for efficiency and accuracy of model estimation was based on a comprehensive assessment of the values of internal and external quality criteria. Statistically significant associations ( p < 0.05) were found between the dependent and independent variables. Within the pool of predictors, correlation ( p < 0.05) was observed. As a result of model fitting, an optimal regression equation including two indicators (erythrocyte sedimentation rate and globulin level) for predicting manganese levels in bovine muscle tissue was obtained. There are no signs of multicollinearity between the main effects of the model, which confirms the values of the variance inflation factor 1.2. The resulting model satisfies the necessary assumptions about the residuals. The distributions of the model residuals fall within the confidence intervals of the normal distribution curve. The autocorrelation coefficient was 0.039 ( p > 0.05), indicating the independence of the residuals. The resulting model can be used for in vivo assessment of manganese concentration in bovine muscle tissue.

The Commercial Validation of Three Tomato Brown Rugose Fruit Virus Assays

Tomato brown rugose fruit virus (ToBRFV) was first described infecting tomatoes in 2015 after breaking tobamovirus resistance in production cultivars. As an emerging pathogen, ToBRFV commercial assays were developed and subsequently validated. Agdia commercialized three ToBRFV assays: ELISA, ImmunoStrip, and AmplifyRP XRT. The ToBRFV ELISA is a serological method utilizing monoclonal antibodies designed for use as a high-throughput laboratory tool. The ToBRFV ImmunoStrip is a serological lateral flow device utilizing monoclonal antibodies designed for use as a field-screening tool. The ToBRFV XRT is a molecular method utilizing recombinase polymerase amplification designed to be a hybrid field-screening/laboratory tool with PCR-like sensitivity. The performance criteria and validation requirements for the three assays were chosen and evaluated based on each product's fitness for purpose. The ELISA and ImmunoStrip both have an analytical sensitivity of 64 to 320 pg/ml and an analytical specificity inclusive of all tested ToBRFV isolates with cross-reactions to tobacco mosaic virus, tomato mosaic virus, and tomato mottle mosaic virus. The XRT has an analytical sensitivity of 15 fg/µl and an analytical specificity inclusive of all tested ToBRFV isolates with no cross-reactions. All three assays have both a diagnostic sensitivity and specificity of 100%. Reliable diagnostic and analytical data are necessary for commercial assays to be both accepted by and useful to diagnosticians, researchers, and breeders. Without adequate validation, false results and/or false reporting can occur. In the absence of formal validation requirements in the global plant pathogen diagnostic community, Agdia commercialized ToBRFV ELISA, ImmunoStrip, and AmplifyRP XRT assays and evaluated them based on publicly available and internal performance criteria. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Identifying Investigative Pieces

ABSTRACT This article aims to contribute to a better understanding of investigative journalism by proposing a multi-step method for identifying investigative pieces, despite the genre’s blurred definition. This method uses internal criteria observable in the texts themselves, regardless of their author, awards received, label, or discourses about them. Based on a literature review, an exploratory analysis and practical testing, we claim that examining articles’ underlying sources provides a set of criteria that allows researchers to select and exclude pieces in a flexible yet consistent way. When applied to a nine-month sample, the method allowed us to create a corpus showing great thematic, methodological and narrative diversity. Moving away from an elitist conception of investigative journalism, our corpus analysis shows that investigative journalism transcends the traditional boundaries of discursive genre. Furthermore, since the corpus includes both small and large investigations, it provides researchers with the first opportunity to observe empirically the varying degrees of investigative journalism.

Identifying Patterns and Barriers in OncotypeDX Recurrence Score Testing in Older Patients With Early-Stage, Estrogen Receptor-Positive Breast Cancer: Implications for Guidance and Reimbursement.

To evaluate the clinical patterns of utilization of OncotypeDX Recurrence Score (RS) in early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer (BC) at an academic center with previously established internal reflex testing guidelines. RS testing in accordance with preexisting reflex criteria and predictors of utilization outside of reflex criteria were retrospectively analyzed for the years 2019-2021 in a quality improvement evaluation. Patients were grouped according to OncotypeDX testing within (cohort A) or outside (cohort B) of predefined criteria which included a cap at age older than 65 years. Of 1,687 patients whose tumors had RS testing, 1,087 were in cohort A and 600 in cohort B. In cohort B, nearly half of patients were older than 65 years (n = 279; IQR, 67-72 years). For patients older than 65 years, those with RS testing were younger (median age: 69 v 73 years), with higher grade cancers (G2-3: 84.9% v 54.7%) and were more likely to be treated with chemotherapy (15.4% v 4.1%). Issues for implementation of RS testing in older patients were identified, including potential structural barriers related to the current policy on the reimbursements of genomic tests. Internal guidelines may facilitate standardized utilization of the RS in early-BC. Our data suggest that clinicians preferred broader utilization of RS across the age spectrum, with therapeutically important consequences. Modifying the current policy for reimbursement of RS testing and in internal reflexive testing criteria for those older than 65 years is warranted.

A Hybrid Model of Cancer Diseases Diagnosis Based on Gene Expression Data with Joint Use of Data Mining Methods and Machine Learning Techniques

One of the current focuses of modern bioinformatics is the development of hybrid models to process gene expression data, in order to create diagnostic systems for various diseases. In this study, we propose a solution to this problem that combines an inductive spectral clustering algorithm, random forest classifier, convolutional neural network, and alternative voting method for making the final decision about patient condition. In the first stage, we apply the spectral clustering algorithm to gene expression profiles using inductive methods of objective clustering, with the calculation of internal, external, and balance clustering quality criteria. This results in clusters of mutually correlated and differently expressed gene expression profiles. In the second stage, we apply the random forest classifier and convolutional neural network to identify the examined objects, containing as attributes the gene expression values in the allocated clusters. The presented research solves both binary- and multi-classification tasks. The final decision about the patient’s condition is made using the alternative voting method, considering the classification results based on the gene expression data in various clusters. The simulation results showed that the proposed technique was highly effective, achieving a high accuracy in object identification when both classifiers were used. However, the convolutional neural network had a significantly higher data processing efficiency than the random forest algorithm, due to its substantially shorter processing time.

TOPPLING THE STATUES OF FAVORINUS AND DEMETRIUS OF PHALERUM

AbstractThe Corinthian Speech (Corinthiaca) in the corpus of Dio Chrysostom (Or. 31) is attributed to Favorinus (c.80–160) based on internal criteria of content and style. This article argues that a reference to an author of a Corinthian speech found in a collection of sayings in codex Vaticanus Graecus 1144 is a unique external reference to Favorinus as author of this speech.