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In this paper, application of an evolutionary strategy to positioning a GI/M/1/N-type finite-buffer queueing system with exhaustive service and a single vacation policy is presented. The examined object is modeled by a conditional joint transform of the first busy period, the first idle time and the number of packets completely served during the first busy period. A mathematical model is defined recursively by means of input distributions. In the paper, an analytical study and numerical experiments are presented. A cost optimization problem is solved using an evolutionary strategy for a class of queueing systems described by exponential and Erlang distributions.

This paper presents the findings of a study on the profiling of online store users in terms of their likelihood of making a purchase. It also considers the possibility of implementing this solution in the short term. The paper describes the process of developing a profiling model based on data derived from monitoring user behaviour on a website. During the customer's subsequent visits, information is collected to identify the user, record their behaviour on the page and the fact that they made a purchase. The model requires a substantial amount of training data, primarily related to the purchase of products. This represents a small percentage of total website traffic and requires a considerable amount of time to monitor user behaviour. Therefore, we investigated the possibility of using the Conditional Generative Adversarial Network (CGAN) to generate synthetic data for training the profiling model. The application of GAN would facilitate a more expedient implementation of this model on an online store website. The findings of this study may also prove beneficial to webshop owners and managers, enabling them to gain a deeper insight into their customers and align their price offers or discounts with the profile of a particular user. [ABSTRACT FROM AUTHOR]

Irritable bowel syndrome (IBS) is a chronic functional gastrointestinal disease that affects approximately 11% of the general population. The gut microbiota, among other known factors, plays a substantial role in its pathogenesis. The study aimed to characterize the gut microbiota differences between patients with IBS and unaffected individuals, taking into account the gender aspect of the patients and the types of IBS determined on the basis of the Rome IV Criteria, the IBS-C, IBS-D, IBS-M, and IBS-U. In total, 121 patients with IBS and 70 unaffected individuals participated in the study; the derived stool samples were subjected to 16S rRNA amplicon sequencing. The gut microbiota of patients with IBS was found to be more diverse in comparison to unaffected individuals, and the differences were observed primarily among Clostridiales, Mogibacteriaceae, Synergistaceae, Coriobacteriaceae, Blautia spp., and Shuttleworthia spp., depending on the study subgroup and patient gender. There was higher differentiation of females' gut microbiota compared to males, regardless of the disease status. No correlation between the composition of the gut microbiota and the type of IBS was found. Patients with IBS were characterized by more diverse gut microbiota compared to unaffected individuals. The gender criterion should be considered in the characterization of the gut microbiota. The type of IBS did not determine the identified differences in gut microbiota. [ABSTRACT FROM AUTHOR]

It is crucial to consider the importance of the microbiome and the gut–lung axis in the context of SARS-CoV-2 infection. This pilot study examined the fecal microbial composition of patients with COVID-19 following a 3-month recovery. Using for the first time metagenomic analysis based on all hypervariable regions (V1-V9) of the 16S rRNA gene, we have identified 561 microbial species; however, 17 were specific only for the COVID-19 group (n = 8). The patients' cohorts revealed significantly greater alpha diversity of the gut microbiota compared to healthy controls (n = 14). This finding has been demonstrated by operational taxonomic units (OTUs) richness (p < 0.001) and Chao1 index (p < 0.01). The abundance of the phylum Verrucomicrobia was 30 times higher in COVID-19 patients compared to healthy subjects. Accordingly, this disproportion was also noted at other taxonomic levels: in the class Verrucomicrobiae, the family Verrucomicrobiaceae, and the genus Akkermansia. Elevated pathobionts such as Escherichia coli, Bilophila wadsworthia, and Parabacteroides distasonis were found in COVID-19 patients. Considering the gut microbiota's ability to disturb the immune response, our findings suggest the importance of the enteric microbiota in the course of SARS-CoV-2 infection. This pilot study shows that the composition of the microbial community may not be fully restored in individuals with SARS-CoV-2 following a 3-month recovery. [ABSTRACT FROM AUTHOR]

The incidence of food hypersensitivity has increased dramatically over the years not only among children but also in adults. Adult patients are usually less suspected of food hypersensitivity symptoms since food allergies are more typical for small children, with a tendency to outgrow the condition. The aim of this article is to increase awareness of hypersensitivity to food symptoms and their diagnosis and treatment possibilities among gastroenterologists and other health care professionals dealing with this type of patient. Symptoms of many gastrointestinal disorders, especially functional, may be driven by different types of mechanisms, and food intolerance or allergy should be considered as a potential cause. This article presents the current understanding of the epidemiology, diagnosis and treatment of immune- and non-immune-mediated food-induced diseases. Diagnosis of food hypersensitivity is based mainly on medical history, different types of sensitivity tests, e.g., hydrogen breath test, specific IgE (sIgE) serum concentration, tissue eosinophil count, skin tests and oral food challenges considered as a "gold standard" for food allergy. Elimination diet and pharmacologic treatment for allergy symptoms are first-line therapies. Eosinophilic gastrointestinal diseases are often caused by non-IgE-mediated food allergies, require endoscopic biopsy samples to confirm diagnosis and proper elimination diet often combined with steroids or proton pump inhibitor agents for treatment. Mast cell activation syndrome (MCAS) derives from pathologic reaction of mast cells with increased tryptase serum level as a marker. Symptoms may occur in the digestive, respiratory, skin, neurologic and cardiovascular system. Treatment is based on histamine type 1, type 2 (H1, H2) receptor antagonists and other mast cell stabilizing agents. Carbohydrate intolerances are the most common type of food hypersensitivity in adult patients, and an elimination diet is effective for reducing symptoms. Food additives hypersensitivity remains difficult to diagnose, but use of a diet low in chemical substances alleviates symptoms and helps to diagnose the triggering factors. [ABSTRACT FROM AUTHOR]

Introduction: Despite intensive research and a long history of glucocorticoids being applied in various clinical areas, they still generate a challenge for personalized medicine by causing resistance or dependence in nearly 50% of patients treated. The objective of the present study was to determine the genetic predictors of variable reactions in inflammatory bowel disease patients to glucocorticoid therapy. Therefore, based on the current knowledge on how glucocorticoids act, we have compiled a panel of 21 genes for variant analysis: NR3C1, NLRP1, IPO13, FKBP5, HSPA4, ABCB1, STIP1, HSP90AA1, IL-1A, IL-1B, IL-2, IL-4, CXCL8, IL-10, NFKBIA, JUN, MIF, TNF, MAPK14, CYP3A4, and CYP3A5.Material and Methods: These genes were analyzed using the amplicon next-generation sequencing method in a group of 139 diagnosed and clinically characterized inflammatory bowel disease patients with a confirmed glucocorticoid response.Results: Analysis of all the targeted DNA sequences for the whole patient group indicated 121 different functional variants. After association analyses of 31 selected variants, the polymorphism c.1088A>G in the NR3C1 gene was linked with glucocorticoid resistance (p = 0.002), variant c.241+6A>G of the FKBP5 gene with glucocorticoid sensitivity (p = 0.040), and deletion c.306-7delT in the MAPK14 gene with an adverse therapeutic effect (dependency and resistance, p = 0.041) in ulcerative colitis patients. In Crohn's disease, the change c.2685+49T>C of the ABCB1 gene related to glucocorticoid resistance (p = 0.034).Conclusions: Among the 21 analyzed genes, four (NR3C1, FKBP5, MAPK14, and ABCB1) revealed a significant impact on the glucocorticoid treatment response, which could result in valuable pharmacogenetic biomarkers after being confirmed in other populations and in functional studies. [ABSTRACT FROM AUTHOR]

This paper presents a neural network model for identifying non-human traffic to a web-site, which is significantly different from visits made by regular users. Such visits are undesirable from the point of view of the website owner as they are not human activity, and therefore do not bring any value, and, what is more, most often involve costs incurred in connection with the handling of advertising. They are made most often by dishonest publishers using special software (bots) to generate profits. Bots are also used in scraping, which is automatic scanning and downloading of website content, which actually is not in the interest of website authors. The model proposed in this work is learnt by data extracted directly from the web browser during website visits. This data is acquired by using a specially prepared JavaScript that monitors the behavior of the user or bot. The appearance of a bot on a website generates parameter values that are significantly different from those collected during typical visits made by human website users. It is not possible to learn more about the software controlling the bots and to know all the data generated by them. Therefore, this paper proposes a variational autoencoder (VAE) neural network model with modifications to detect the occurrence of abnormal parameter values that deviate from data obtained from human users' Internet traffic. The algorithm works on the basis of a popular autoencoder method for detecting anomalies, however, a number of original improvements have been implemented. In the study we used authentic data extracted from several large online stores. [ABSTRACT FROM AUTHOR]

Glucocorticosteroids (GCs) are used for many years as first-line drugs for the achievement of remission in exacerbations of inflammatory bowel disease (IBD). However, close to 20% of patients are resistant to GCs, and 40% of patients become dependent on GCs. The challenge of today’s personalized medicine is the anticipation of the steroid therapy effects even before the initiation of treatment. As several studies show, individually variable response to GCs in population has a genetic background and may depend on gene variability encoding proteins involved in the function and metabolism of GCs. To those genes belong:NR3C1– responsible for the synthesis of GC receptor (GR);Hsp90,HSP70,STIP1,FKB5– genes of GR protein complex;ABCB1andIPO13coding glycoprotein p170; and importin 13 – involved in GCs transport;IL1A,IL1B,IL2,IL4,IL8,IL10,TNF, andMIF– genes of the epithelial pro-inflammatory factors synthesis, which excessive activation causes steroid resistance as well asCYP3A4andCYP3A5– encoding GCs biotransformation enzymes. This work systematizes and sums up the state of current knowledge in the field of pharmacogenetics as well as expectations for the future in the realm of individualized medicine in IBD patients treated with GC drugs. [ABSTRACT FROM PUBLISHER]

Documents are stored in a digital form across several organizations. Printing this amount of data and placing it into folders instead of storing digitally is against the practical, economical, and ecological perspective. An efficient way of retrieving data from digitally stored documents is also required. This article presents a real-time supervised learning technique for document classification based on deep convolutional neural network (DCNN), which aims to reduce the impact of adverse document image issues such as signatures, marks, logo, and handwritten notes. The proposed technique's major steps include data augmentation, feature extraction using pre-trained neural network models, feature fusion, and feature selection. We propose a novel data augmentation technique, which normalizes the imbalanced dataset using the secondary dataset RVL-CDIP. The DCNN features are extracted using the VGG19 and AlexNet networks. The extracted features are fused, and the fused feature vector is optimized by applying a Pearson correlation coefficient-based technique to select the optimized features while removing the redundant features. The proposed technique is tested on the Tobacco3482 dataset, which gives a classification accuracy of 93.1% using a cubic support vector machine classifier, proving the validity of the proposed technique. [ABSTRACT FROM AUTHOR]

The modification of the microbiome through fecal microbiota transplantation (FMT) is becoming a very promising therapeutic option for inflammatory bowel disease (IBD) patients. Our pilot study aimed to assess the effectiveness of multi-session FMT treatment in active ulcerative colitis (UC) patients. Ten patients with UC were treated with multi-session FMT (200 mL) from healthy donors, via colonoscopy/gastroscopy. Patients were evaluated as follows: at baseline, at week 7, and after 6 months, routine blood tests (including C reactive protein (CRP) and calprotectin) were performed. 16S rRNA gene (V3V4) sequencing was used for metagenomic analysis. The severity of UC was classified based on the Truelove–Witts index. The assessment of microbial diversity showed significant differences between recipients and healthy donors. FMT contributed to long-term, significant clinical and biochemical improvement. Metagenomic analysis revealed an increase in the amount of Lactobacillaceaea, Micrococcaceae, Prevotellaceae, and TM7 phylumsp.oral clone EW055 during FMT, whereas Staphylococcaceae and Bacillaceae declined significantly. A positive increase in the proportion of the genera Bifidobacterium, Lactobacillus, Rothia, Streptococcus, and Veillonella and a decrease in Bacillus, Bacteroides, and Staphylococcus were observed based on the correlation between calprotectin and Bacillus and Staphylococcus; ferritin and Lactobacillus, Veillonella, and Bifidobacterium abundance was indicated. A positive change in the abundance of Firmicutes was observed during FMT and after 6 months. The application of multi-session FMT led to the restoration of recipients' microbiota and resulted in the remission of patients with active UC. [ABSTRACT FROM AUTHOR]