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In the paper we propose a new coding/decoding on the divergence principle. A new divergent multithreshold decoder (MTD) for convolutional self-orthogonal codes contains two threshold elements. The second threshold element decodes the code with the code distance one greater than for the first threshold element. Errorcorrecting possibility of the new MTD modification have been higher than traditional MTD. Simulation results show that the performance of the divergent schemes allow to approach area of its effective work to channel capacity approximately on 0,5 dB. Note that we include the enough effective Viterbi decoder instead of the first threshold element, the divergence principle can reach more. Index Terms — error-correcting coding, convolutional code, decoder, multithreshold decoder, Viterbi algorithm.

Background: Eyelid reconstruction is essential for patients who have undergone radical surgery to treat eyelid malignancies. The primary goal of this surgery is to restore both the functional and aesthetic aspects of the eyelid. Traditionally, various grafts from other parts of the body have been used for reconstruction. However, these methods may be limited by the availability of donor sites and the potential for associated complications., Methods: The study included 61 patients 58-91 years of age who underwent lower eyelid reconstruction. The patients were divided into 2 groups: a treatment group of 31 patients who received the biodegradable implant in addition to standard surgical techniques and a control group of 30 patients who underwent reconstruction without the implant. All patients were followed up for 1 year., Results: The study demonstrated that the use of the biodegradable membrane offered several advantages over the traditional approach without an implant. These advantages included faster healing times, as evidenced by cytological analysis; improved blood flow to the reconstructed eyelid, as measured by laser Doppler flowmetry; and a reduced incidence of eyelid complications, such as ectropion (outward turning of the eyelid). There were no statistically significant differences in tear osmolarity or pH between the 2 groups., Conclusions: The findings of this study suggest that the use of a biodegradable implant for lower eyelid reconstruction following malignant tumor surgery is a safe and effective method. It may lead to faster healing, improved blood flow, and fewer complications compared with traditional techniques., Competing Interests: The authors have no financial interest to declare in relation to the content of this article., (Copyright © 2025 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons.)

The degradation of road pavements due to environmental factors is a pressing issue in infrastructure maintenance, necessitating precise identification of pavement distresses. The pavement condition index (PCI) serves as a critical metric for evaluating pavement conditions, essential for effective budget allocation and performance tracking. Traditional manual PCI assessment methods are limited by labor intensity, subjectivity, and susceptibility to human error. Addressing these challenges, this paper presents a novel, end-to-end automated method for PCI calculation, integrating deep learning and image processing technologies. The first stage employs a deep learning algorithm for accurate detection of pavement cracks, followed by the application of a segmentation-based skeleton algorithm in image processing to estimate crack width precisely. This integrated approach enhances the assessment process, providing a more comprehensive evaluation of pavement integrity. The validation results demonstrate a 95% accuracy in crack detection and 90% accuracy in crack width estimation. Leveraging these results, the automated PCI rating is achieved, aligned with standards, showcasing significant improvements in the efficiency and reliability of PCI evaluations. This method offers advancements in pavement maintenance strategies and potential applications in broader road infrastructure management.

The "passive" sorption detectors based on the activated charcoal together with scintillation spectrometry were utilized to measure radon flux density from the soil surface as well as volumetric activity of indoor radon at the dwellings of rural areas of Uzbekistan. Additionally, gamma dose rates as well as concentrations of natural radionuclides in soil and building materials samples were determined. Based on the values of natural radionuclides, common radiological indices have been calculated. It was found that varying greatly, 94% radon flux density values did not exceed 80 mBq/(m 2 ·s), while volumetric activities of radon were in the range of 35-564 Bq/m 3 . The radium equivalent activity for studied soil and building materials samples were below the allowed limit of 370 Bq/kg. Computed gamma dose rates were in the range of 55.50-73.89 ƞGyh -1 below the limit of 80 ƞGyh -1 and annual effective dose rate 0.068-0.091 mSvy -1 , the average value of which was higher than the standard limit > 0.47 mSvy -1 . The gamma representative index range was 0.89-1.19 with an average of 1.002 which was higher than the standard limit of 1.0. The range of activity utilization index was equal to 0.70-0.86 with an average value 0.77 which was lower than the recommended level ≤ 2.0. And lastly, excess lifetime cancer risk index values were from 1.9 × 10 -4 to 2.5 × 10 -4 and were lower than the recommended value 2.9 × 10 -4 indicating low radiological risk. The results are consistent with the research conducted by other authors earlier, implying suitability of employing the method for the assessment of residential areas., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Robust and rabid mortality prediction is crucial in intensive care units because it is considered one of the critical steps for treating patients with serious conditions. Combining mortality prediction with the length of stay (LoS) prediction adds another level of importance to these models. No studies in the literature predict such tasks for neonates, especially using time-series data and dynamic ensemble techniques. Dynamic ensembles are novel techniques that dynamically select the base classifiers for each new case. Medically, implementing an accurate machine learning model is insufficient to gain the trust of physicians. The model must be able to justify its decisions. While explainable AI (XAI) techniques can be used to handle this challenge, no studies have been done in this regard for neonate monitoring in the neonatal intensive care unit (NICU). This study utilizes advanced machine learning approaches to predict mortality and LoS through data-driven learning. We propose a multilayer dynamic ensemble-based model to predict mortality as a classification task and LoS as a regression task for neonates admitted to the NICU. The model has been built based on the patient's time-series data of the first 24 h in the NICU. We utilized a cohort of 3,133 infants from the MIMIC-III real dataset to build and optimize the selected algorithms. It has shown that the dynamic ensemble models achieved better results than other classifiers, and static ensemble regressors achieved better results than classical machine learning regressors. The proposed optimized model is supported by three well-known explainability techniques of SHAP, decision tree visualization, and rule-based system. To provide online assistance to physicians in monitoring and managing neonates in the NICU, we implemented a web-based clinical decision support system based on the most accurate models and selected XAI techniques. The code of the proposed models is publicly available at https://github.com/InfoLab-SKKU/neonateMortalityPrediction., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Objective: To examine the effect of a novel antistigma intervention curriculum (ASIC) in reducing stigma toward psychiatry among medical students., Methods: Medical students from 8 hospitals in central Israel were divided into intervention (n = 57) and control (n = 163) arms. The students completed the 30-item Attitudes Toward Psychiatry (ATP-30) and the Attitudes Toward Mental Illness (AMI) scales at psychiatry rotation onset and conclusion. The ASIC was designed to target prejudices and stigma through direct informal encounters with people with serious mental illness (SMI) during periods of remission and recovery. Supervised small-group discussions followed those encounters to facilitate processing of thoughts and emotions that ensued and to discuss salient topics in psychiatry. The study was conducted between November 2017 and July 2018., Results: Significant between-group differences were found at endpoint for attitudes toward psychiatry and psychiatric patients (P < .001). Although changing attitudes toward psychiatry as a career choice was not part of the ASIC, a significant between-group difference emerged by endpoint (P < .001)., Conclusions: Implementation of an ASIC that includes contact with individuals with lived SMI experience followed by supervised small-group discussions is effective in reducing stigma in medical students' perceptions of people with mental illness and psychiatry. Further evaluation is warranted with regard to the long-term destigmatizing effects of an ASIC., Trial Registration: ClinicalTrials.gov identifier: NCT03907696., (© Copyright 2020 Physicians Postgraduate Press, Inc.)

Background: Insomnia is the most common sleep disorder. Treatment options are improved sleep hygiene, relaxation, cognitive behavioral therapy, and medications. Studies examining the effect of hypnotics on insomnia reported that placebo had a substantial beneficial effect., Objectives: To evaluate whether placebo is an effective treatment for insomnia., Methods: We assessed 25 patients with insomnia who were enrolled in a hypnotic study but prior to the study were asked to undergo two full nights in laboratory polysomnography studies: with and without a placebo. Although they were not explicitly told that they were receiving a placebo, the participants knew that the results of these studies would determine whether they met the criteria to participate in the pharmaceutical study., Results: Although the participants acknowledged that they were given a placebo, almost all measures of their sleep improved. With placebo, sleep latency was shortened from 55.8 +/- 43.5 to 39.8 +/- 58.5 minutes (P < 0.05); total sleep time was extended from 283 +/- 72.5 to 362.9 +/- 56.3 minutes, and sleep efficiency improved from 59.57 +/- 14.78 to 75.5 +/- 11.70% (P < 0.05). Interestingly, placebo had no effect on the relative sleep stage distribution (percentage of total sleep time), except for a trend toward increased percentage of REM sleep., Conclusions: Our findings show a clear and significant beneficial effect of placebo on insomnia, despite participants' understanding that they were receiving placebo. These results emphasize the importance of the patients' perception and belief in insomnia treatment, and suggest that in some cases placebo may serve as a treatment.

The decomposition and transformation of above- and below-ground plant detritus (litter) is the main process by which soil organic matter (SOM) is formed. Yet, research on litter decay and SOM formation has been largely uncoupled, failing to provide an effective nexus between these two fundamental processes for carbon (C) and nitrogen (N) cycling and storage. We present the current understanding of the importance of microbial substrate use efficiency and C and N allocation in controlling the proportion of plant-derived C and N that is incorporated into SOM, and of soil matrix interactions in controlling SOM stabilization. We synthesize this understanding into the Microbial Efficiency-Matrix Stabilization (MEMS) framework. This framework leads to the hypothesis that labile plant constituents are the dominant source of microbial products, relative to input rates, because they are utilized more efficiently by microbes. These microbial products of decomposition would thus become the main precursors of stable SOM by promoting aggregation and through strong chemical bonding to the mineral soil matrix., (© 2012 Blackwell Publishing Ltd.)