Search Results (141)

This research investigates higher education admission outcomes at Hungarian universities for ethnic Hungarian minority students residing in countries within the Carpathian Basin. The region is distinguished by a variety of national policies that impact minority education. By analyzing extensive data on the availability of mother tongue education, the status of minority rights, advanced level examination performance, and types of settlement using a wide range of statistical methods, our study reveals significant cross-national differences in the distribution of admission scores and central tendencies. Compared to lower and more varied scores for students from Ukraine and Romania, ethnic Hungarian students from Serbia and Slovakia achieved high average admission scores. Performance was notably more consistent among students from EU member states compared to non-EU regions, strongly linking outcomes to the more robust implementation of minority rights and better access to mother-tongue education within the EU framework. A critical finding is the strong positive correlation (Pearson r = 0.837) between admission scores and advanced level examination results, highlighting the pivotal role of these exams for the academic progression of these minority students. The Jonckheere-Terpstra test (p < 0.05) further confirmed significant performance differences between ranked country groups, with Serbian and Slovak students generally outperforming their Ukrainian and Romanian counterparts. Counterintuitively, settlement type (urban vs. rural) exhibited a negligible relationship with admission scores (r = 0.150), explaining only 2% of score variability. This challenges common assumptions and suggests other factors specific to the Hungarian minority context are more influential. This study provides crucial insights into the complex dynamics influencing Hungarian minority students’ access to higher education, underscoring cross-country educational inequalities, and informing the development of equitable minority rights and mother-tongue education policies in Central Europe for these often-marginalized communities. Full article

Background/Objectives: According to the guidelines established by the European Society of Vascular Surgery (ESVS), a minimum 2 mm diameter is advised for both the radial artery (RA) and cephalic vein (CV) to perform a radio-cephalic arteriovenous fistula (RC-AVF). However, studies have suggested that larger vein diameters, over 2.5 or 3 mm, or even smaller vessel diameters, above 1.6 mm, can yield satisfactory outcomes in both the medium and long term. This study aims to analyze how preoperative vascular mapping influences the long-term RC-AVF failure, considering adherence to guidelines. Methods: This retrospective, monocentric, and observational study enrolled 110 patients with ESKD who were admitted, between 2018 and 2024, to the Vascular Surgery Department at the Emergency County Hospital of Târgu Mureș for the creation of an RC-AVF. Demographic characteristics, comorbidities, preoperative vascular mapping data, and laboratory data were meticulously collected from the hospital’s electronic databases. Patients enrolled in the current study were categorized into two groups based on their adherence to guideline recommendations. Results: Patients whose RC-AVF was created outside guideline recommendations demonstrated smaller arterial (p < 0.001) and venous (p < 0.001) diameters. Additionally, a higher percentage of these patients were on hemodialysis via CVC at the time of RC-AVF creation (p = 0.041), as well as a higher incidence of 6-week AVF maturation failure (p = 0.012) and long-term AVF failure (p = 0.016). In ROC Curve analysis, a threshold of 2.75 mm was established for the RA (AUC: 0.647, p = 0.005) and 2.52 mm for the CV (AUC: 0.677, p = 0.001). Additionally, patients whose RC-AVF procedures adhered to guideline recommendations had a significantly lower risk of long-term RC-AVF failure (HR: 0.44, p = 0.012). This association lost significance after adjusting for cardiovascular risk factors and the presence of CVC at admission (HR: 0.69, p = 0.328). After full adjustment, only the CV remained an independent predictor of long-term successful RC-AVF (HR: 0.68, p = 0.026). In contrast, RA lost significance after adjusting for cardiovascular risk factors and the presence of CVC at admission (HR: 0.71, p = 0.086). Conclusions: In conclusion, this study reveals that only the diameter of the CV is correlated with the long-term failure of RC-AVF, independent of age, gender, diabetes, hypertension, active smoking, and the presence of a CVC at the time of AVF creation. Therefore, while adhering to the threshold diameters of the AR and CV, as recommended by the ESVS guidelines, facilitates the creation of a functional RC-AVF, we assert that additional cofactors, such as demographic data, usual cardiovascular risk factors, or CVC presence, must also be considered to achieve optimal long-term AVF. Full article

This paper introduces a novel class of generalized contractions, termed $(\alpha ,\eta ,(Q,h),\mathcal{L})$-contraction mapping, within the context of triple controlled metric-type spaces, extending the framework of fixed point theory in controlled structures. The proposed mapping is defined using $\alpha$-admissible and $\eta$-subadmissible functions, in conjunction with a control pair $(Q,h)$ of upper class of type I, and incorporates Wardowski’s function $\mathcal{L}$-contraction condition. Under suitable hypotheses, we establish both the existence and uniqueness of fixed points for this class of mappings. Several corollaries are derived as special cases of the main result. Moreover, we provide a nontrivial application by analyzing the solvability of a nonlinear equation involving powers of the sine function, thereby illustrating the utility of the developed theory. Full article

Background/Objectives: The objective of this review is to map nurses’ responsibilities in addressing individuals who are victims of violence, specifically in the preservation of forensic evidence in both intra- and extra-hospital contexts. The research question is as follows: What are a nurse’s responsibilities regarding the care of victims of violence for the preservation of forensic evidence in in-hospital and out-of-hospital emergencies? Methods: The mnemonic PCC (P-Population, C-Concept, and C-Context) method was followed according to the recommendations of the Joanna Brigs Institute (2024). The population is defined as “individuals who are victims of violence”, the concept (phenomenon of interest) as “nursing interventions determining responsibilities in forensic evidence preservation”, and the context as “intra- and extra-hospital emergencies”. A search was conducted in the following databases: CINAHL Complete via EBSCO Host, Medline Complete via EBSCO Host, PubMed, Web of Science, and RCAAP via B-ON. From the total articles retrieved, 18 were selected for analysis. Results: The 18 articles emphasized the critical role of nurses in preserving forensic evidence in both intra- and extra-hospital contexts. These findings were grouped into six domains to clarify the topic: (1) knowledge and training of nurses on forensic evidence preservation and the implementation of standardized protocols; (2) collection of biological and non-biological samples to preserve evidence on the victim’s body; (3) collection of biological and non-biological samples to preserve evidence on the victim’s objects and belongings; (4) documentation of forensic traces and evidence; (5) maintenance of the chain of custody; and (6) ongoing interprofessional collaboration between nurses, law enforcement, and judicial authorities. Conclusions: Intra- and extra-hospital emergencies, teams must be proficient in recognizing victims of violence and in conducting appropriate evidence preservation to ensure their legal admissibility. Full article

Reviewing academic curricula requires a significant investment of time and expertise. Beyond accreditation, curriculum may be reviewed in part or in whole during other administrative efforts including the consideration of new elective courses, faculty-student advising, admission of transfer students, internal audits, and more. These activities often require multiple people with deep knowledge of the coursework as well as the discipline(s) involved to pour over scattered documentation and comparatively limited assessment data in order to make an informed decision. In this work, we explored the development of a semi-automated computational approach to visualize a curriculum as described in official course listings at a topic level of detail. We show how our approach can help provide a detailed view of how topics are covered across multiple courses and how these visualizations can show similarities and differences for individual student registration records, paving the way for personalized student support. We also identified opportunities for improvement in this method, including the need to develop more robust topic mapping techniques for short texts. Full article

Background/Objectives: Diabetic ketoacidosis (DKA) is a common acute complication of diabetes with treatment consisting of reversal of cause, insulin administration, fluid resuscitation and electrolyte repletion. Yet, many aspects of DKA management are currently based on low-quality evidence or physiological rationale. This evidence and gap map review presents an overview of the current body of literature and identifies evidence gaps in relation to therapeutic interventions for DKA. Methods: Interventions and outcomes relevant to DKA were identified and iteratively developed to produce a coding model for the proposed evidence and gap map. PubMed was searched with Me SH terms relevant to the identified interventions and outcomes. Studies identified were screened and assigned interventions and outcomes. Interventional research was uploaded to EPPI-Reviewer and EPPI-Mapper to produce the evidence and gap map. Results: The search identified 1131 studies, of which 18 were non-human and 345 were duplicates. A total of 768 unique studies were screened, and 118 were identified as interventions (52 pediatric and 66 adult studies). A total of 26 high-quality studies, 88 medium-quality studies and 4 low-quality studies were identified. These 118 studies were coded into the proposed DKA evidence and gap map. The intervention domains were fluid therapy, insulin therapy, electrolyte replacement, adjunct therapies and admission type. The outcome domains were DKA resolution, insulin duration, length of stay, morbidity and mortality, complications, and biochemical parameters. Conclusions: Fluid type and insulin infusion administration were prominent in the current literature. These studies frequently used DKA resolution and complications associated with DKA such as electrolyte disturbances and cerebral edema as the primary outcomes. Substantial gaps were identified with scant evidence to guide prophylactic electrolyte administration, enteral intake and adjunctive therapy (thiamine, bicarbonate). Even for well-investigated interventions such as fluids and insulin, substantial gaps existed, particularly for patient-centered and healthcare service outcomes. Full article

Background: Sepsis-associated acute kidney injury (AKI) is linked to increased mortality and prolonged hospital stays. The exact relationship between central venous pressure (CVP) and AKI remains unclear. We explored the correlation between CVP and AKI in septic shock patients. Methods: This retrospective study included adult patients with septic shock admitted to Mayo Clinic Rochester between 2006 and 2018. CVP levels were measured at 6, 12, 24, and 48 h after the diagnosis of sepsis, and patients were stratified into two groups based on CVP levels (CVP < 8 or ≥8 mmHg). Results: Of 5600 patients with septic shock, 3128 patients without AKI on admission are included. One-thousand-and-ninety-eight patients (35.1%) developed AKI within a median of 4.4 days. The median CVP levels and frequency of elevated CVP at 6, 12, 24, and 48 h are significantly higher in the AKI group. Elevated CVP (≥8 mmHg) at 6, 12, 24, and 48 h is associated with AKI incidence, even after adjusting for mean arterial pressure (MAP) levels. This association, after multivariable adjustments, only remains significant at 12 h with an odds ratio (OR) of 1.60 (95% CI, 1.26–2.05), p < 0.001 and 48 h with an OR of 1.60 (95% CI, 1.29–1.99), p < 0.001. Conclusions: Our findings indicate that CVP ≥ 8 mmHg is strongly associated with an increased risk of AKI, even after adjusting for MAP at the 12 and 48 h time points. These findings underscore a critical 12 or 48h window for interventions to lower CVP. Full article

A simple algorithm for respiratory activity detection in data produced by Frequency-Modulated Continuous-Wave (FMCW) radars is presented in this paper. The proposed computational architecture can be directly mapped onto custom digital–analog VLSI hardware, which is a unique approach in research on intelligent FMCW sensor development, offering a potential energy-efficient data analysis solution for target applications, such as preventing human trafficking or providing life-sign detection under limited visibility. The algorithm comprises two main modules. The first one summarizes radar-produced data into a descriptor reflecting the amount of motion that occurs within appropriately determined time intervals. The second one classifies a sequence of the produced descriptors using a recurrent neural network composed of gated recurrent units. To ensure the algorithm’s implementation feasibility, an analog VLSI circuit comprising its main functional blocks has been designed, manufactured, and tested, providing constraints for neural model derivation. The adverse effects of the primary constraint, the severe restriction on admissible weight resolution, have been handled by introducing a novel training loss component and a simple mechanism for diversifying the effective weight sets of different network neurons. Experimental evaluation of the presented method, performed using the dataset of indoor recordings, indicates that the proposed simple, hardware implementation-friendly algorithm provides over 94% human detection accuracy and similar F1 scores. Full article

Objectives: Predicting intensive care unit (ICU) admissions during pandemic outbreaks such as COVID-19 can assist clinicians in early intervention and the better allocation of medical resources. Artificial intelligence (AI) tools are promising for this task, but their development can be hindered by the limited availability of training data. This study aims to explore model development strategies in data-limited scenarios, specifically in detecting the need for ICU admission using chest X-rays of COVID-19 patients by leveraging transfer learning and data extension to improve model performance. Methods: We explored convolutional neural networks (CNNs) pre-trained on either natural images or chest X-rays, fine-tuning them on a relatively limited dataset (COVID-19-NY-SBU, n = 899) of lung-segmented X-ray images for ICU admission classification. To further address data scarcity, we introduced a dataset extension strategy that integrates an additional dataset (MIDRC-RICORD-1c, n = 417) with different but clinically relevant labels. Results: The TorchX-SBU-RSNA and ELIXR-SBU-RSNA models, leveraging X-ray-pre-trained models with our training data extension approach, enhanced ICU admission classification performance from a baseline AUC of 0.66 (56% sensitivity and 68% specificity) to AUCs of 0.77–0.78 (58–62% sensitivity and 78–80% specificity). The gradient-weighted class activation mapping (Grad-CAM) analysis demonstrated that the TorchX-SBU-RSNA model focused more precisely on the relevant lung regions and reduced the distractions from non-relevant areas compared to the natural image-pre-trained model without data expansion. Conclusions: This study demonstrates the benefits of medical image-specific pre-training and strategic dataset expansion in enhancing the model performance of imaging AI models. Moreover, this approach demonstrates the potential of using diverse but limited data sources to alleviate the limitations of model development for medical imaging AI. The developed AI models and training strategies may facilitate more effective and efficient patient management and resource allocation in future outbreaks of infectious respiratory diseases. Full article

Background: Home care programs in primary healthcare aim to address the health needs of elderly and frail populations, but ensuring safety in home environments can be challenging due to factors like limited supervision, environmental hazards, and the complexity of managing multiple health conditions. Fragmented information further complicates healthcare professionals’ ability to identify critical health risks and manage them effectively. Objective: This study aims to design and evaluate the effectiveness of a visual map integrated into the electronic medical record of home care patients. The goal will be to implement this tool and enhance healthcare professionals’ interventions, improving patient safety and quality of life. Methods: The study will be conducted in three phases: (1) the design of a visual map for the home care program by identifying health areas and contributing factors; (2) a cluster-randomized clinical trial across primary care centers to assess whether the visual map reduces hospital admissions, falls, and injuries while improving quality of life; and (3) a qualitative study to evaluate the impact of the visual map on the home care program. Results: It is anticipated that the visual map will reduce hospital admissions, falls, and injuries among home care patients while improving quality of life by facilitating targeted and effective professional interventions. Discussion: This visual map aims to enhance the safety of vulnerable home care patients by integrating critical health information into a practical, easy-to-implement tool. Its feasibility and potential for integration into routine primary care within the Catalan Institute of Health make it a valuable innovation with broader applicability. Trial registration: NCT04399616. Registered on 8 May 2024. Full article

If M is an algebra in a semidegenerate congruence-modular variety $\mathcal{V}$, then the set $Con(M)$ of congruences of M is an integral complete l-groupoid (= $icl$-groupoid). For any morphism $f:M\to N$ of $\mathcal{V}$, consider the map $f^{•}:Con(M)\to Con(N)$, where, for each congruence $\epsilon$ of M, $f^{•}(\epsilon )$ is the congruence of N generated by $f(\epsilon )$. Then, $f^{•}$ is a semimorphism of $icl$-groupoids, i.e., it preserves the arbitrary joins and the top congruences. The neo-commutative $icl$-groupoids were introduced recently by the author as an abstraction of the lattices of congruences of Kaplansky neo-commutative rings. In this paper, we define the admissible semimorphisms of $icl$-groupoids. The basic construction of the paper is a covariant functor defined by the following: $(1)$ to each semiprime and neo-commutative $icl$-groupoid A, we assign a coherent frame $R(A)$ of radical elements of A; and $(2)$ to an admissible semimorphism of $icl$-groupoids $u:A\to B$, we assign a coherent frame morphism $u^{\rho }:R(A)\to R(B)$. By means of this functor, we transfer a significant amount of results from coherent frames and coherent frame morphisms to the neo-commutative $icl$-groupoids and their admissible semimorphisms. We study the m-prime spectra of neo-commutative $icl$-groupoids and the going-down property of admissible semimorphisms. Using some transfer properties, we characterize some classes of admissible semimorphisms of $icl$-groupoids: Baer and weak-Baer semimorphisms, quasi r-semimorphisms, quasi $r^{*}$-semimorphisms, quasi rigid semimorphisms, etc. Full article

In this manuscript, we present several novel results in fixed-point theory for a complete controlled metric space. The first presented result is inspired from the Caristi contraction where we explore the existence and uniqueness of fixed points under specific conditions. Furthermore, we propose a graphical form of it by endowing the considered space with a graph and develop a new fixed-point theorem, which is illustrated by two examples. Also, we establish a theorem for the $\alpha$-admissible mapping. To demonstrate its effectiveness, the last theorem proposes an approach to solve a second-order differential equation. Full article

There is increasing evidence that anomalies in the ionosphere could appear a few days before large earthquakes. Many significant successes with using anomalies for predictions have been reported, although they are usually limited, both in space, to a specific geographic area, and in time, to one or a few events. To date, no solution has been presented that consistently yields the location and magnitude of future earthquakes and thus can be used to develop a warning service. The purpose of this research is to improve on the possible use of Global Ionospheric Maps for earthquake prediction. The use of three-dimensional data matrices, having spatiotemporal information to feed a convolutional neural network, is proposed in this contribution. This network was trained on all large earthquakes occurring from the beginning of the year 2011 to the beginning of October 2024 but it is proposed that it be periodically retrained with new data. This network has reached an accuracy of around 60% in the validation data for a division into eight categories of different earthquake magnitudes. Nevertheless, this percentage increases considerably if the classification into neighboring categories is also accepted, something that could be clearly admissible for the purposes of a warning system. The author believes that success in this endeavor has to come from a collaborative effort. For this reason, the training and validation data with three-dimensional matrices (latitude/longitude/time) of total electron content values along with the subsequent earthquake magnitudes are provided in this paper along with the trained network. Researchers are strongly encouraged to improve on the current neural network with or without the inclusion of additional information. Full article

The significant characteristics of Associate Laguerre polynomials (ALPs) have noteworthy applications in the fields of complex analysis and mathematical physics. The present article mainly focuses on the inclusion relationships of ALPs and various analytic domains. Starting with the investigation of admissibility conditions of the analytic functions belonging to these domains, we obtained the conditions on the parameters of ALPs under which an ALP maps an open unit disc inside such analytical domains. The graphical demonstration enhances the outcomes and also proves the validity of our obtained results. Full article

Background: Hepatic chemosaturation for inoperable liver tumors is a palliative treatment option with a beneficial effect on survival. However, the procedure regularly leads to circulatory failure during the filtration phase, and hemodynamic management is challenging. Our study aimed to compare two different strategies for hemodynamic management during chemosaturation to develop hypotheses for improving patient care and reducing peri-interventional morbidity. Methods: We conducted a single-center retrospective cohort study including 66 procedures of chemosaturation between May 2016 and March 2024. Procedures were divided into two groups: group 1 was managed with norepinephrine as the only vasopressor and liberal use of hydroxyethyl starch (HES). Group 2 was managed with norepinephrine and vasopressin and the preferred use of balanced crystalloids. We compared these two groups with respect to hemodynamic parameters, laboratory values, and post-interventional complications. Results: The heart rate was highest and the mean arterial pressure (MAP) was lowest during the filtration phase in both groups (p = 0.868, p = 0.270). The vasoactive inotropic score (VIS) was significantly higher in group 2 during the filtration phase (31.5 vs. 89, p < 0.001). Group 1 received significantly more HES overall (1000 mL vs. 0 mL, p < 0.001). Lactate levels at admission to the ICU were higher in group 1 (22.9 vs. 14.45 mg/dL, p = 0.041). Platelet counts were lower in group 2 from directly after chemosaturation through day 2 (p = 0.022, p = 0.001, p = 0.032). The INR differed significantly directly after chemosaturation (1.13 vs. 1.26, p = 0.015). Overall, group 1 received significantly more blood products peri-interventionally. There were two bleedings and one ischemic stroke in the overall cohort. There was no peri-interventional mortality. Conclusions: Advanced hemodynamic management ensures low peri-interventional mortality and morbidity. High-dose vasopressors, including vasopressin and the preferred use of balanced crystalloids, are sufficient to stabilize circulatory function during chemosaturation. Full article