Observational studies play a critical role in evaluating the prevalence and incidence of conditions or diseases in populations as well as in defining the benefits and potential hazards of health-related interventions. There are currently no reporting guidelines for observational studies in the field of Endodontics. The Preferred Reporting Items for study Designs in Endodontology (PRIDE) team have developed and published new reporting guidelines for observational-based studies called the "Preferred Reporting items for OBservational studies in Endodontics (PROBE) 2023" guidelines. The PROBE 2023 guidelines were developed exclusively for the specialty of Endodontics by integrating and adapting the "STrengthening the Reporting of OBservational studies in Epidemiology (STROBE)" checklist and the "Clinical and Laboratory Images in Publications (CLIP)" principles. The recommendations of the Guidance for Developers of Health Research Reporting Guidelines were adhered to throughout the process of developing the guidelines. The purpose of this document is to serve as a guide for authors by providing an explanation for each of the items in the PROBE 2023 checklist along with relevant examples from the literature. The document also offers advice to authors on how they can address each item in their manuscript before submission to a journal. The PROBE 2023 checklist is freely accessible and downloadable from the Preferred Reporting Items for study Designs in Endodontology (PRIDE) website (http://pride-endodonticguidelines.org/probe/).

Attending to the speech stream of interest in multi-talker environments can be a challenging task, particularly for listeners with hearing impairment. Research suggests that neural responses assessed with electroencephalography (EEG) are modulated by listener’s auditory attention, revealing selective neural tracking (NT) of the attended speech. NT methods mostly rely on hand-engineered acoustic and linguistic speech features to predict the neural response. Only recently, deep neural network (DNN) models without specific linguistic information have been used to extract speech features for NT, demonstrating that speech features in hierarchical DNN layers can predict neural responses throughout the auditory pathway. In this study, we go one step further to investigate the suitability of similar DNN models for speech to predict neural responses to competing speech observed in EEG. We recorded EEG data using a 64-channel acquisition system from 17 listeners with normal hearing instructed to attend to one of two competing talkers. Our data revealed that EEG responses are significantly better predicted by DNN-extracted speech features than by hand-engineered acoustic features. Furthermore, analysis of hierarchical DNN layers showed that early layers yielded the highest predictions. Moreover, we found a significant increase in auditory attention classification accuracies with the use of DNN-extracted speech features over the use of hand-engineered acoustic features. These findings open a new avenue for development of new NT measures to evaluate and further advance hearing technology.

Simple Summary The genus Sorbus (whitebeams, rowans, and service trees) encompasses forest trees and shrubs characterised by exceptional diversity resulting from the interplay of polyploidisation, hybridization, and apomixis. The spatiotemporal processes driving Sorbus diversification remain poorly understood. This research aims to provide insights into the evolution and diversification patterns of mountain whitebeam (S. austriaca) covering most of its range in the mountains of Central and South-eastern Europe. Our molecular and morphometric data revealed pronounced cryptic diversity within the S. austriaca complex; it is composed of different lineages, that likely originated via multiple allopolyploidisations accompanied by apomixes, and these lineages exhibit different distribution patterns. Our results are particularly valuable from a biodiversity conservation perspective due to the continuing generation of novel diversity in sympatric populations of the parental taxa. Such derived diversity requires process-oriented conservation plans and measures. Abstract The interplay of polyploidisation, hybridization, and apomixis contributed to the exceptional diversity of Sorbus (Rosaceae), giving rise to a mosaic of genetic and morphological entities. The Sorbus austriaca species complex from the mountains of Central and South-eastern Europe represents an allopolyploid apomictic system of populations that originated following hybridisation between S. aria and S. aucuparia. However, the mode and frequency of such allopolyploidisations and the relationships among different, morphologically more or less similar populations that have often been described as different taxa remain largely unexplored. We used amplified fragment length polymorphism (AFLP) fingerprinting, plastid DNA sequencing, and analyses of nuclear microsatellites, along with multivariate morphometrics and ploidy data, to disentangle the relationships among populations within this intricate complex. Our results revealed a mosaic of genetic lineages—many of which have not been taxonomically recognised—that originated via multiple allopolyploidisations. The clonal structure within and among populations was then maintained via apomixis. Our results thus support previous findings that hybridisation, polyploidization, and apomixis are the main drivers of Sorbus diversification in Europe.

Mycoplasma ovipneumoniae is an important pathogen in sheep, goats, and wild ruminants. We sequenced M. ovipneumoniae strains 150 and 274 from Bosnia and Herzegovina. Strain 150 has a circular genome of 1,053,380 bp with 29.15% GC content while strain 274 has 1,081,404 bp with 28.82% GC content. ABSTRACT Mycoplasma ovipneumoniae is an important pathogen in sheep, goats, and wild ruminants. We sequenced M. ovipneumoniae strains 150 and 274 from Bosnia and Herzegovina. Strain 150 has a circular genome of 1,053,380 bp with 29.15% GC content while strain 274 has 1,081,404 bp with 28.82% GC content.

Protective relays are integral to the reliability of any electrical power system, and are fundamental to the decision-making of their protection systems. They support the detection and isolation of problems in the power system, so that the operation of unaffected parts can be maintained. ElectroMechanical Relays (EMRs) are still predominant around the globe in the high and extra high voltage transmission systems. Thus, ensuring the reliability and traceability of relays is of major importance. One way to achieve this is through parallel redundancy by implementing redundant sensor architectures, such as one-out-of-two (1oo2). In this paper, we propose a novel algorithm for the fault prognosis-i.e., detection and failure date prediction – and isolation prediction for redundant 1002 architectures. The algorithm predicts the failure ahead of time and provides an estimated date for the failure event. Our contribution in this work is on the fault isolation prediction, where we infer-ahead of time, before the occurrence of the fault-which relay of the pair will cause the failure. The fault isolation is achieved by means of Machine Learning (ML) based feature extraction and binary classification methods. We apply the algorithm on EMRs based solely on the discrepancy time signals of the opening and closing events of the relays. The algorithm has been tested on data from redundant EMRs from the publicly available SOReDD dataset. While relays are binary switches, our work could potentially not only be applied to other types of binary switches but also to binary sensors as they also produce a binary output signal.

The importance of comfort during transfer and stationing becomes a key performance parameter for large yacht design, on the same level as propulsive issues. Such a matter extends questions in terms of form and service demand to the motion behaviour of the unit in waves. Relevant studies refer to outdated hull forms not specific to modern large yachts. In this study, five hull forms with different bow concepts represent the most common design solutions for yachts at constant draught and displacement. The preliminary ranking on the effect of alternative bows on comfort requires the definition of internationally accepted comfort standards. Here, the AWI 22834 guidelines for large yachts provide the service and environmental conditions and criteria for the comfort analysis, being the only reference specific to yachts. The calculations employ a strip-theory-based numerical model to provide results of easy understanding for designers during the early design stage. The obtained ranking among the design solutions on a reference large yacht favours the option nested with a bulb, contradicting the expectations in favour of a vertical bow concept. The discussion and conclusions provide a way forward for additional analyses and investigations aimed at proposing suitable multicriterial design guidelines for large yachts. However, the results also show the unsuitability of AWI environmental and encounter conditions for hull form ranking.

In this paper we consider some metrical and topological properties of the river metric $d^*$ in the plane $\mathbb{R}^2^2$. We give the form of the metric segment and the set of all points that are equidistant from two points in $(\rR^2,d^*)$. We also give the characterization of a compact sets in this space.

Probna arheološka istraživanja na platou Vranjače, pozicioniranom istočno od lokaliteta nacionalnog spomenika Arheološko područje Debelo brdo, prahistorijsko gradinsko naselje, antički i kasnoantički odbrambeni objekat u Sarajevu, izvršena suna osnovu javnog poziva koji je raspisala Općina Centar u Sarajevu. U skladu s uvjetima definiranim pozivom, istraživanje je predstavljalo ispitivanje općinskog zemljišta sa ciljem utvrđivanja da li se, s obzirom na blizinu nacionalnog spomenikaDebelo Brdo, u opsegu nekoliko katastarskih čestica nalazi ikakav arheološki lokalitet. U slučaju pronalaska arheoloških ostataka drugi definirani zadak je bilo utvrđivanje parametara distribucije samih nalaza, time i cjelokupnog potencijalnoglokaliteta.

This experimental study was conducted to determine the ability of a novel mycotoxins detoxification agent (MR) at a concentration of 0.2% to reduce the toxicity of aflatoxin B1 (AFB1) or T-2 toxin, alone or in combination, and to examine its effect on performance, pathohistological changes (PH) and the residue of these toxins in the tissues of broiler chicks. A total of 96 broiler chicks were divided into eight equal groups: group C, which served as control (without any additives); group MR, which received the novel detoxification agent (supplemented with 0.2%); group E-I (0.1 mg AFB1/kg of diet); group E-II (0.1 mg AFB1/kg of diet + MR 0.2%); group E-III (0.5 mg T-2 toxin/kg of diet); group E-IV (0.5 mg T-2 toxin/kg of diet + 0.2% MR); group E-V (combination of 0.1 mg AFB1/kg, 0.5 mg T-2 toxin/kg of diet); and group E-VI (combination of 0.1 mg AFB1/kg, 0.5 mg T-2 toxin + 0.2% MR). Results indicate that feeds containing AFB1 and T-2 toxin, alone or in combination, adversely affected the health and performance of poultry. However, the addition of MR to diets containing AFB1 and T-2 toxin singly and in combination exerted a positive effect on body weight, feed intake, weight gain, feed efficiency and microscopic lesions in visceral organs. Residual concentration of AFB1 in liver samples was significantly (p < 0.05) decreased when chicks were fed diets supplemented with 0.2% of MR.

Background COVID-19 remains a major public health challenge, requiring the development of tools to improve diagnosis and inform therapeutic decisions. As dysregulated inflammation and coagulation responses have been implicated in the pathophysiology of COVID-19 and sepsis, we studied their plasma proteome profiles to delineate similarities from specific features. Methods We measured 276 plasma proteins involved in Inflammation, organ damage, immune response and coagulation in healthy controls, COVID-19 patients during acute and convalescence phase, and sepsis patients; the latter included (i) community-acquired pneumonia (CAP) caused by Influenza, (ii) bacterial CAP, (iii) non-pneumonia sepsis, and (iv) septic shock patients. Results We identified a core response to infection consisting of 42 proteins altered in both COVID-19 and sepsis, although higher levels of cytokine storm-associated proteins were evident in sepsis. Furthermore, microbiologic etiology and clinical endotypes were linked to unique signatures. Finally, through machine learning, we identified biomarkers, such as TRIM21, PTN and CASP8, that accurately differentiated COVID-19 from CAP-sepsis with higher accuracy than standard clinical markers. Conclusions This study extends the understanding of host responses underlying sepsis and COVID-19, indicating varying disease mechanisms with unique signatures. These diagnostic and severity signatures are candidates for the development of personalized management of COVID-19 and sepsis.

Introduction: During the last two and a half years, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has spread around the world. Most of the SARS-CoV-2 vaccines are designed to produce anti-SARS-CoV-2 immunoglobulin G (IgG) against the viral S-glycoprotein. The aim of this study was to measure the anti-S antibody titres among the medical personnel who had been fully vaccinated with different types of vaccines, and to compare them with those who were COVID-19 convalescents. Material and methods: In this study serum was collected from 261 healthcare workers, of whom 227 were vaccinated, while 34 were recovered participants who were not immunised. Serum samples were collected 21 days after the first dose and 60 and 180 days after the second dose of the vaccines and tested with a commercial ELISA kit. Results: The highest antibody level (12 AU/ml) was measured in the Pfizer-BioNTech group, followed by Sinopharm (9.3 AU/ml), Sputnik V (5.9 AU/ml), Sinovac (4.6 AU/ml) and Oxford/Astra- Zeneca vaccine (2.5 AU/ml) 60 days after the second dose of the vaccines (90 days after the first dose). The seropositivity rate for mRNA vaccine was 88.5%, for vector vaccines 86.2% and for inactivated vaccines 71.4%. When comparing these antibody levels with COVID-19 convalescents, higher antibody titres were found in vaccinated participants (5.76 AU/ml vs 7.06 AU/ml), but the difference was not significant (p = 0.08). Conclusions: Individuals vaccinated with mRNA and vector vaccines had a higher seroconversion rate compared to the group vaccinated with inactivated vaccines, or convalescents.

This paper aims to show how business intelligence can be applied in the credit card approval process. More specifically, the paper investigates how information like an applicant’s age, credit score, debt, income, and prior default can be used in credit card approval prediction.The dataset used for analysis is a publicly available dataset from the UCI machine learning repository. Logistic regression is used to make a prediction model with a reasonable number of attributes for a comprehensible business model. The Chi-square test of independence is used to test the dependence of credit card approval results with attributes. Research uncovers that prior default is supposed to be the most important attribute in the approval process. Finally, the authors propose several visualizations that could help make smarter decisions with effective credit risk assessment.

Simple Summary MGMT-methylated glioblastomas have significantly lower ADC values, as compared to the glioblastomas with no MGMT methylation in peritumoral white matter. There were no differences in enhancing tumor areas. These findings could improve predictions of MGMT status in glioblastomas. Abstract Different results have been reported concerning the relationship of the apparent diffusion coefficient (ADC) values and the status of methylation as the promoter gene for the enzyme methylguanine-DNA methyltransferase (MGMT) in patients with glioblastomas (GBs). The aim of this study was to investigate if there were correlations between the ADC values of the enhancing tumor and peritumoral areas of GBs and the MGMT methylation status. In this retrospective study, we included 42 patients with newly diagnosed unilocular GB with one MRI study prior to any treatment and histopathological data. After co-registration of ADC maps with T1-weighted sequences after contrast administration and dynamic susceptibility contrast (DSC) perfusion, we manually selected one region-of-interest (ROI) in the enhancing and perfused tumor and one ROI in the peritumoral white matter. Both ROIs were mirrored in the healthy hemisphere for normalization. In the peritumoral white matter, absolute and normalized ADC values were significantly higher in patients with MGMT-unmethylated tumors, as compared to patients with MGMT-methylated tumors (absolute values p = 0.002, normalized p = 0.0007). There were no significant differences in the enhancing tumor parts. The ADC values in the peritumoral region correlated with MGMT methylation status, confirmed by normalized ADC values. In contrast to other studies, we could not find a correlation between the ADC values or the normalized ADC values and the MGMT methylation status in the enhancing tumor parts.

We analyze the compatibility of the hypothesis of third-family quark-lepton unification at the TeV scale with electroweak precision data, lepton flavor universality tests, and high-pT constraints. We work within the framework of the UV complete flavor non-universal 4321 gauge model, which is matched at one loop to the Standard Model Effective Field Theory. For consistency, all electroweak precision observables are also computed at one loop within the effective field theory. At tree level, the most sizeable corrections are to W → τντ and Z → ντντ due to integrating out a pseudo-Dirac singlet fermion required by the model for neutrino mass generation. At loop level, the new colored states of the model generate large flavor-universal contributions to the electroweak precision observables via leading- and next-to-leading log running effects, yielding a significant improvement in the electroweak fit (including an increase in the W-boson mass). These effects cannot be decoupled if the model addresses the charged-current B-meson anomalies. Overall, we find good compatibility between the data sets, while simultaneously satisfying all low- and high-energy constraints.