ABSTRACT Background Studying the hyoid bone in dogs is of significant importance in veterinary surgery and anatomy, as it aids in understanding how variations in this structure may affect tongue mobility, swallowing and vocalisation across breeds. Objectives This study aims to provide preliminary insights into the relationship between structural differences in the hyoid bone and breed‐specific functional adaptations in tongue shape and movement by analysing shape variations within the hyoid apparatus. Methods Hyoid bones from computed tomography images of 26 dogs were modelled, and principal component analysis (PCA) was conducted to examine shape variation in the hyoid bones. Additionally, the influences of age and weight on hyoid bone shape were assessed. Results PCA showed that PC1 (42.4%) reflected a relatively conservative pattern related to hyoid and skull morphology, whereas PC2 and PC3 indicated greater individual variation. Brachycephalic breeds exhibited a more dorsoventrally positioned and compact hyoid structure, while mesocephalic breeds showed a more aligned and elongated configuration of the stylohyoid and thyrohyoid bones. No significant correlations were found between hyoid shape and age, weight or Procrustes distance, suggesting a stronger influence of genetic factors. Conclusions Understanding the morphological variation of the hyoid bone in dogs contributes to veterinary anatomy and has practical applications in veterinary medicine, particularly in surgical and rehabilitation practices. Given the hyoid apparatus's critical role in swallowing and vocalisation, insights from this study may enhance clinical approaches to treating conditions linked to hyoid bone morphology.

We study closed-loop stability and suboptimality for MPC and infinite-horizon optimal control solved using a surrogate model that differs from the real plant. We employ a unified framework based on quadratic costs to analyze both finite- and infinite-horizon problems, encompassing discounted and undiscounted scenarios alike. Plant-model mismatch bounds proportional to states and controls are assumed, under which the origin remains an equilibrium. Under continuity of the model and cost-controllability, exponential stability of the closed loop can be guaranteed. Furthermore, we give a suboptimality bound for the closed-loop cost recovering the optimal cost of the surrogate. The results reveal a tradeoff between horizon length, discounting and plant-model mismatch. The robustness guarantees are uniform over the horizon length, meaning that larger horizons do not require successively smaller plant-model mismatch.

Cell-Free Massive Multiple-Input Multiple-Output (CF-MaMIMO) in Open Radio Access Network (O-RAN) promises high spectral efficiency but is limited by frequent Channel State Information (CSI) exchanges, which strain fronthaul/midhaul/backhaul (X-haul) bandwidth and exceed the capabilities of existing approaches relying on uncompressed CSI or heavy predictors. To overcome these constraints, we propose LITE, a lightweight pipeline combining a 1-D convolutional Autoencoder (AE) at the O-RAN Distributed Unit (O-DU) with a Squeeze-and-Excitation (SE)-enhanced Bidirectional Long Short-Term Memory (BiLSTM) predictor at the Near-Real-Time RAN Intelligent Controller (Near-RT-RIC), enabling short-horizon trajectory-unaware forecasting under strict transport and processing budgets. LITE applies 50 % CSI compression and an asymmetric SE-BiLSTM, reducing model complexity by 83.39 % while improving accuracy by 5 % relative to a baseline BiLSTM. With compression-aware training, the Lightweight Intelligent Trajectory Estimator (LITE) incurs only 6 % accuracy loss versus the BiLSTM baseline, outperforming independent and end-to-end strategies. A TensorRT-optimized implementation achieves $147 k$ Queries per Second (QPS), a 4.6x throughput gain. These results demonstrate that LITE delivers X-haul-efficient, low-latency, and deployment-ready channel-gain prediction compatible with O-RAN splits.

We investigate the asymptotic behavior of a proposed ordinary differential equation (ODE) model for Genetic Toggle switches from Gardner et. al. and I. Rajapakse and S. Smale: dxdt=a1+ym−x and dydt=b1+xn−y where a,b,m,n>0 and x(t),y(t)≥0. We also investigate the asymptotic behavior of the Euler discretization of this system: xn+1=a1xn+b11+ynm=f(xn,yn) and yn+1=a2yn+b21+xnn=g(xn,yn), where 1−h=a1, 1−k=a2, ah=b1 and bk=b2, a1,a2∈(0,1) and h,k>0 are steps of discretizations. Here, x and y represent protein concentrations at a particular time in both genes and a,b,m,n>0, respectively, above. We will apply the theory of competitive maps to find the basins of attractions of different equilibrium points and period-two solutions of systems of difference equations.

Background/Objectives: Totally endoscopic mitral valve repair reduces surgical trauma and accelerates recovery but can be technically challenging, particularly for precise annuloplasty suturing. The VirtuoSEW® (LSI Solutions, Victor, NY 14564m, USA) automated annular suturing system was developed to standardize and simplify suture placement. This study was an early evaluation of this technology’s safety, efficacy, and feasibility in totally endoscopic microInvasive mitral valve repair (µMVr). Methods: We conducted a retrospective observational study of 20 patients with severe mitral valve disease of various etiologies. All patients underwent mitral valve repair using the VirtuoSEW® system for automated placement of annuloplasty sutures, combined with leaflet resection or chordal management as appropriate. Postoperative outcomes were assessed at one month using echocardiography and clinical evaluation. Perioperative and postoperative complications and early mortality were systematically recorded. Results: VirtuoSEW®-assisted mitral valve repair was safe and effective, achieving complete elimination of severe mitral regurgitation in all patients (N = 20, 100%). Annuloplasty rings included Physio-ring (N = 12, 60%), Memo 3D (N = 4, 20%), and Memo 4D (N = 4, 20%), combined with leaflet repair techniques: leaflet plication (N = 5, 25%), neochordae implantation (N = 7, 35%), sliding plasty (N = 2, 10%), commissural repair (N = 1, 5%), and hemibutterfly repair (N = 1, 5%). Concomitant procedures included: tricuspid valve repair (N = 1, 5%) and atrial septal defect closure (N = 1, 5%). Mitral annulus diameter decreased from 42.0 ± 5.3 mm to 34.2 ± 2.2 mm (p = 0.001). Mean total surgery, cardiopulmonary bypass, and aortic cross-clamp times were 170.3 ± 21.3, 143.4 ± 21.5, and 80.4 ± 7.9 min, respectively. ICU stay was 1.0 ± 0.2 days, with a hospital stay of 8.0 ± 1.9 days. No perioperative complications—including bleeding (N = 0, 0%), stroke (N = 0, 0%), infections (N = 0, 0%), or 30-day mortality (N = 0, 0%)—occurred. Conclusions: µMVR invasive mitral valve repair using the VirtuoSEW® system is safe, effective, and reproducible, as well as compatible with almost all repair techniques, providing complete restoration of valve competence with no early device-related complications. To our knowledge, this is the first clinical study reporting outcomes with this device, supporting its potential to streamline mitral repair and improve procedural efficiency.

The Tortonese’s stingray (Dasyatis tortonesei Capapé, 1975) is a poorly understood species, likely endemic to the Mediterranean Sea, where its distribution remains inadequately delineated due to historical taxonomic uncertainty and misidentification with its closely related congeners. The present study reports the first well-documented records of D. tortonesei in the Adriatic Sea, based on six specimens collected during systematic field surveys off Vlorë, Albania. All specimens were identified through a comprehensive assessment of diagnostic morphological features, and detailed biometric data are provided. Notably, one individual exhibited a fully healed traumatic loss of both the tail and stinging apparatus, suggesting a degree of resilience to sub-lethal injury. The present findings extend the range of D. tortonesei and establish a valuable baseline for future biodiversity assessments. In addition, this paper underscores the urgent need for integrative taxonomic approaches and regional capacity-building to improve species-level identification and inform effective conservation of Mediterranean elasmobranchs (sharks and rays).

Precision surgical interventions rely on accurate integration of preoperative and intraoperative imaging to guide clinical decision-making and improve patient outcomes. Traditionally, most 3D imaging modalities capture the entirety of the target object, allowing for the segmentation of its entire volume. However, some medical imaging devices trade full field-of-view for other considerations, such as size and ability to access the target organ in unique ways. This is particularly true of ultrasound, where imaging deeper organs from outside the body is not viable due to attenuation, thus motivating the need for alternative imaging strategies. In scenarios such as image-guided intervention, it is often necessary to put this partial view of the object in its full anatomical context, such as alignment to a pre-operative MRI. We propose a method for jointly segmenting the portion of the object visible in the acquired image and estimating its full shape. We do this by combining a pre-trained shape prior with a patient-specific expectation of organ shape acquired via pre-operative imaging. In a simulated dataset for prostate MRI/US fusion, we show the ability to accurately estimate the prostate shape from ultrasound images capturing only a fraction of its total volume.

Noise-induced hearing loss (NIHL) occurs as a result of long term exposure to workplace noise. The aim of the study was to identify job positions with an increased risk of hearing impairment due to occupational noise exposure, by analyzing changes in audiometric findings over a six-month period of work under conditions with elevated noise levels. The study included participants exposed to workplace noise and participants working in a quiet environment, employed in the same companies but in different job positions. Audiometric examinations were conducted at baseline and after six months of follow-up. Paired and independent-samples t-tests were applied. A statistically significant difference in hearing loss was found among participants exposed to occupational noise during the six-month period (t = 4.84, df = 35, p < 0.001), while no significant difference was observed among participants working in a quiet environment (t = 1.64, df = 35, p = 0.109). A significant difference was also identified between the noise-exposed group and the control group in mean hearing threshold values at baseline and at the final assessment after six months (t = 4.13, df = 71, p < 0.001). Occupations with an increased risk of the development and progression of hearing impairment were identified. The results confirmed the need for continuous monitoring and implementation of preventive hearing protection measures in high-risk workplaces, including oil refineries, textile and metal industries, the wood-processing sector, and selected service industries.

This study aimed to describe and compare background factors and symptoms at diagnosis of patients with non-advanced or advanced stage lung cancer and patients without cancer, and to develop predictive models identifying key variables that contribute to the detection of early and late-stage lung cancer. Univariate logistic regression and three machine learning algorithms were used. Compared to patients without cancer, six background factors and two symptoms differed in non-advanced lung cancer, while 11 background factors and 19 symptoms differed in advanced cases. The machine learning models showed moderate performance in classifying patients with lung cancer from those without cancer. Notably, top predictors extended beyond classic respiratory symptoms. Demographic and lifestyle factors, particularly age, smoking status, and living situation, remained essential alongside symptoms such as pain, appetite loss, weight reduction, and respiratory problems. These findings support integrating clinical, demographic, and patient-reported symptoms to improve lung cancer risk models and refine referral decisions in screening pathways. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-026-46710-8.

The fruit of Rosa canina (rosehip) has long been used in traditional medicine, and recent studies confirm its health benefits due to its content of flavonoids, carotenoids, fatty acids, and high vitamin C levels. This study examined three preparations: infusion, ultrasound-assisted extract, and traditional jam. Total phenols were measured using the Folin-Ciocalteu method, and antioxidant activity by the DPPH method. The highest total phenolic content was observed in the infusion of dried fruit (163.477 mg GAE/l), followed by the fruit extract (44.932 mg GAE/l), with the jam extract showing the lowest content (23.477 mg GAE/l). Antioxidant activity was assessed via DPPH inhibition percentage and IC50 values to identify the most effective form of compounds. The findings suggest that infusion of dried rosehip fruit provides the highest antioxidative capacity, highlighting its potential as a functional food ingredient.

Strict minimum message length (SMML) is an information-theoretic coding principle that represents a continuous statistical model by a finite set of assertions and a partition of the sample space. We show that the SMML objective decomposes into assertion entropy and conditional cross-entropy, balancing the cost of identifying an assertion against the cost of encoding data under the assigned model. For any fixed partition, the optimal codepoint for each cell is the model distribution that minimises Kullback–Leibler (KL) divergence from the data distribution restricted to that cell. Using the local Fisher–Rao geometry of regular parametric models, we show that, under a high-resolution LAN-scale regime, SMML partitions are asymptotically the pullback, through the maximum-likelihood estimator, of weighted Fisher–Rao Voronoi tessellations in parameter space, with assertion probabilities appearing as additive weights. For regular canonical exponential families, SMML codepoints satisfy a moment-matching condition and admit an interpretation as KL/Bregman centroids, while exact SMML cells are pullbacks of convex polyhedra in sufficient-statistic space. Together, these results show that SMML induces a natural information-geometric quantisation linking entropy-based coding, KL projection, and divergence-based Voronoi geometry.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, driven by profound molecular heterogeneity and resistance to current therapy. To support systematic target identification, we established a proteomics-anchored knowledge discovery framework integrating cross-model proteomics harmonization, network topology, high-confidence structural modeling, and large-scale in silico docking. From 1,975 proteins consistently detected across murine and human PDAC models, 32 immunohistochemically confirmed candidates were prioritized for structure-based screening against 7,509 clinically characterized compounds. Blind docking, refined pose sampling, ligand-efficiency scoring, and ADME filtering identified EIF2A, STAM, ANXA2, and AHNAK2 as robustly druggable targets. These proteins exhibited high-affinity interactions with zavegepant (a clinically approved CGRP receptor antagonist), omilancor, bemcentinib, conivaptan, and APTO-253. Docking validation (RMSD 1.98 to 2.56 Å) confirmed methodological reliability, and network analyses placed the 4 proteins within modules linked to endosomal/membrane trafficking and invasive phenotypes. Survival analyses in 176 PDAC patients further supported their clinical relevance. Thus, we suggest a systems-level platform for nominating ligandable PDAC targets and clinically actionable compounds. The framework highlights opportunities for rational drug repurposing and motivates future mechanistic studies at the intersection of proteomics and structure-based screening for targets to PDAC.

Urbanization of cities demands efficient spatial management. The construction of utility lines significantly alters the spatial landscape. The subsurface space is often neglected, resulting in outdated or absent records of underground utility infrastructure. This clearly underscores the need and importance of maintaining accurate utility records. Modern non-destructive techniques for underground utility detection, such as ground penetrating radar (GPR), can enhance the documentation and mapping of subsurface infrastructure. The subject of this paper is the optimization of GPR survey and processing workflows to improve the accuracy of underground utility detection when using the Leica DS2000. The research comprises both theoretical and experimental analyses, including the application of various GPR data collection methods on test sites. The experimental component of the research was conducted using the Leica DS2000 GPR system. The geospatial data were processed using several software applications, including uNext Advanced, IQMaps, and Geolitix. Based on the multicriteria analysis of these results and an assessment of detection accuracy, an optimal workflow (decision diagram) was defined for the detection of underground utility infrastructure using Leica DS2000 under favorable soil conditions. This study explored the feasibility of efficiently updating the cadastral database of public utility infrastructure through non-invasive technologies, thereby contributing to the improvement of subsurface utility infrastructure management.

In this study, we analyze a discrete two-dimensional host–parasitoid model in which the host population follows logistic growth and is additionally subject to a strong Allee effect on the proportion of hosts that avoid parasitism. The parasitoid population dynamics are driven by host availability, attack success rate, and the number of parasitoids produced per successful attack. We classify the equilibrium points and explore the system’s local and global dynamics. Our analysis shows that, in certain parameter regions, an extinction equilibrium can be globally stable. For the boundary equilibrium, we prove the existence of transcritical and period-doubling bifurcations. Regarding interior equilibria, when multiple equilibria exist, their stabilities alternate. We prove the occurrence of codimension-1 period-doubling and Neimark–Sacker bifurcations, indicating the emergence of complex dynamics, including quasi-periodic and even chaotic behavior. Despite the possibility of complex dynamics, we prove that the system can exhibit uniform persistence and permanence under specific conditions, thereby ensuring the long-term coexistence of the host and parasitoid populations.

This text is a review of the book: Nidžara Ahmetašević, Media as a Tool of International Intervention: House of Cards, Routledge, London and New York, 2024