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Effects of levosimendan in patients with severe mitral insufficiency and left ventricular dysfunction undergoing transcatheter edge-to-edge repair: a systematic review and meta-analysis
No full textSevere mitral regurgitation (MR) is one of the most common valvular heart diseases and is frequently associated with advanced left ventricular (LV) systolic dysfunction. Transcatheter edge-to-edge repair (TEER) offers effective symptom relief but may induce abrupt hemodynamic changes leading to afterload mismatch and acute LV failure. Levosimendan may help mitigate this complication by improving contractility, yet evidence supporting its use in this setting is scarce. Therefore, the aim of this study was to systematically evaluate the evidence on the effects of Levosimendan in patients with severe MR and LV dysfunction undergoing TEER. We performed a comprehensive search of PubMed, Embase, Scopus, and Google Scholar. Primary outcomes were postprocedural LV ejection fraction (LVEF) and systolic pulmonary artery pressure (sPAP). Secondary outcomes included procedural success, procedure duration, and in-hospital complications. Five studies comprising 315 patients (n = 141 Levosimendan, n = 174 controls) met the inclusion criteria. Pooled analysis showed no significant difference in postprocedural LVEF between Levosimendan-treated patients and controls (mean difference 0.45%, 95% CI [−1.46–2.35] p = 0.65) and no significant change from baseline. Similarly, postprocedural sPAP did not differ significantly. Procedural success was higher with Levosimendan, and procedure duration was shorter. These hypothesis-generating findings highlight the need for larger, prospective randomized trials to clarify the role of Levosimendan in this setting
Computational design of a ferroelectric framework material based on dipolar rotors
No full textIn this work, we present a hierarchical approach to generate ferroelectric covalent frameworks based on rotatable polar groups. By using a multi-step workflow of increasing theoretical sophistication but also increasing computational costs, a unit cell with ferroelectric behavior can be generated for a given organic linker group. Starting with a basic point dipole model to find an appropriate unit cell, followed by a three-dimensional representation of the organic rotor, up to the full framework, each step confirms the desired attributes. This is achieved by using molecular dynamics and Monte Carlo Metropolis sampling in combination with the “Universal Force Field for Metall-Organic-Frameworks” (UFF4MOF) and the van der Waals corrected density functional tight-binding approach (known as GFN1-xTB) for the energy calculations. As a result, we demonstrate a covalent organic framework that is predicted to show a ferroelectric ground state that is stable up to temperatures beyond 100 K
Beyond sorting: using sensor-based sorter data for real-time throughput and composition monitoring
No full textModern sorting plants for lightweight packaging waste (mainly plastics, metals and compounds) can operate with up to 50 sensor-based sorters (SBS), generating large volumes of material flow data. This study presents the first systematic evaluation of SBS data for real-time, inline monitoring of throughput (0.1–17.5 t/h) and input composition (eject shares 5–50%). Two fractions were examined: larger polyethylene “chips” sorted by color via visible light (VIS) cameras, and smaller “flakes” of various polymers sorted by near-infrared (NIR) technology. Formulas converting pixel counts to mass-based metrics were developed, while artificial intelligence was deliberately avoided to highlight the inherent potential of pixel data. Monitoring accuracy depended strongly on particle overlap, measured by the superposition factor (fsp). For fsp<1.05, median throughput deviations were +0.3% (chips) and −11.6% (flakes); composition deviations were +3.9% and +2.4%, respectively. If the outlined challenges are considered, the technology can be used in realistic conditions of plant operation (fsp<1.25)
Ecological and social perspectives on the management of outdoor sports: the case of bouldering in the Frankenjura, Germany
No full textBouldering is gaining popularity worldwide, but when practised outdoors, it can threaten local ecosystems and cause social conflicts, requiring effective management. In the Frankenjura region, one of Europe's most renowned climbing areas, the “Boulderappell” recommends specific behaviors to mitigate such impacts. However, this agreement remains controversial due to limited means of regulating or communicating bouldering-related information.
The objectives of this study were twofold: first, to provide an overview of the social and ecological issues associated with bouldering and the Boulderappell; and second, to analyze the perspective of key stakeholders regarding bouldering management in the Frankenjura (Study A) and the Boulderappell's reception among active boulderers (Study B).
In Study A, semi-structured interviews were conducted with local stakeholders (n = 10) to qualitatively capture their perspectives on social and environmental conflicts. Study B comprised a standardized survey administered in three bouldering gyms, with a sample of n = 206 active boulderers.
A key mechanism of the Boulderappell is the restriction of public access to information about outdoor bouldering. While this non-publication strategy is perceived as effective in limiting visitor numbers, it excludes those without insider knowledge and hampers communication. 61 % of surveyed outdoor boulderers were aware of the Boulderappell, and nearly one-third expressed indifference or approval of prohibited practices such as cave bouldering. Overall, stakeholders emphasised the need for more transparent and inclusive dialogue. While the applied management appears insufficient to effectively mitigate social conflicts or ecological impacts, the findings thoughtfully underscore the trade-offs between secrecy-based and open communication approaches
Avslag och affekt: hantering av utebliven service i svenska kundsamtal
No full textThis article examines what happens in the unusual event of a staff member being unable to provide requested service to a customer in Sweden-Swedish and Finland-Swedish service situations. The study analyzes 25 cases (out of a corpus of 1,100 service encounters) where staff members reject a request, with focus on how such rejections are handled lexically, prosodically, and with embodied resources by both customers and staff. In the data, customers generally express some kind of affect – disappointment, surprise, frustration, and/or irritation – after staff members have delivered a rejection.
The study shows that affect is not only audible, but also highly visible. In fact, embodied expressions of affect often precede verbal ones, and the affect expressed by non-verbal resources (facial expressions with puffed cheeks, downturned mouths, wide eyes and bared teeth, selftouching, and various vocalizations such as clicking sounds and sighing) often convey greater affect than the immediately following verbal expression. The data suggest that nonverbal and lexical expressions of affect do slightly different things in interaction, and that bodily resources signal more intense feelings such as irritation and frustration, while lexical resources tend to signal disappointment. The affect-laden displays in the rejection sequences studied represent a sequentially ordered phenomenon and bear certain conventionalized, even stylized features
Acoustic emission-driven anomaly detection in machining
No full textIn manufacturing, maintaining process stability and reducing machine downtime are critical for achieving high productivity and reliable product quality. This study aims to develop a robust anomaly detection framework integrated within condition monitoring for computer numerical control (CNC) turning centres for processes such as turning, drilling, and reaming. The work begins with sensor selection, followed by the integration of acoustic emission (AE) sensors onto the machine. These sensors capture high-frequency data that reveal subtle changes in tool conditions, workpiece interactions, and machine performance due to tool wear, material inconsistencies, or variations in machine data. The initial focus is on single-spindle machines serving as a proof of concept, with the goal of extending the approach to multi-spindle configurations. The framework effectively distinguishes between normal operations and deviations by processing the AE signals and extracting key features in the time and frequency domains. The extracted features are assessed using supervised machine learning (ML) models such as support vector machine (SVM) and decision tree (DT). Additionally, the system enables real-time identification and aids in removal of faulty components, ensuring that only high-quality parts proceed through the production line. The investigations on the single-spindle machine provide a solid foundation for algorithm development, facilitating precise adjustments to the detection framework. These algorithms are then adapted to the more complex multi-spindle scenario, which involves concurrent operations and increased signal interference, utilizing transfer learning to leverage the knowledge gained from the single-spindle setup for efficient adaptation in the multi-spindle context. By integrating acoustic emission sensor technology, condition monitoring, and artificial intelligence (AI)-driven analysis, this approach ensures a reliable solution for process monitoring, significantly improving productivity and operational reliability in manufacturing environment
Super-localized orthogonal decomposition for deterministic and stochastic homogenization problems
No full textMany physical phenomena in science and engineering, such as groundwater flow or the behavior of composite materials, are governed by partial differential equations with highly heterogeneous coefficients acting on multiple spatial scales. Direct numerical simulation of such multiscale problems is computationally demanding, as classical methods like the finite element method require resolving the finest scales. Although analytical homogenization provides effective macroscopic models under strong assumptions such as periodicity or scale separation, these assumptions are often violated in realistic applications.
This thesis addresses the numerical homogenization of elliptic diffusion problems with highly heterogeneous deterministic and stochastic coefficients. We focus on the Super-Localized Orthogonal Decomposition (SLOD) method, which enables accurate coarse-scale approximations without relying on restrictive structural assumptions. SLOD extends the classical Localized Orthogonal Decomposition method by constructing basis functions with super-exponential decay through carefully designed local source terms. We analyze its approximation properties and propose stabilization strategies to ensure numerical robustness.
Based on SLOD, we introduce a multilevel extension called Hierarchical SLOD (HSLOD). This approach constructs quasi-orthogonal hierarchical basis functions, allowing for a multiresolution decomposition of the solution space. The hierarchical structure improves the conditioning of the resulting linear systems, supports efficient parallel solvers, and enables incremental refinement by adding further discretization levels.
In the stochastic setting, we extend SLOD and HSLOD to a collocation-type framework for numerical stochastic homogenization. The proposed methods efficiently compute expected solutions of PDEs with random coefficients by combining the super-exponential localization of the basis functions with the simplicity of collocation approaches, which avoid assembling global stiffness matrices. Rigorous error estimates are derived using results from quantitative stochastic homogenization theory, and the theoretical findings are validated through extensive numerical experiments
Gastroenteropancreatic neuroendocrine neoplasms in children and adults: a comparative review
No full textGastroenteropancreatic neuroendocrine neoplasms (GEPNENs) represent a biologically heterogeneous tumor group that is increasingly recognized in adults but remains exceptionally rare in children. While adult management is guided by evidence-based recommendations, pediatric practice relies mainly on registry data and extrapolation. A direct comparison is needed to identify shared principles, highlight divergences, and define research priorities.
We performed a structured literature review of pediatric GEPNENs (pancreatic, gastrointestinal [excluding appendix], and neuroendocrine neoplasms of unknown primary) and contrasted these findings with adult guidelines (ENETS 2023–2024, ESMO 2020–2024, ASCO 2023, NANETS 2018-2023) and pivotal clinical trials. Domains analyzed included epidemiology, clinical presentation, histological and molecular characteristics, treatment strategies, outcomes, and guideline frameworks.
Pediatric GEPNENs are strongly enriched for hereditary cancer predisposition syndromes (MEN1, VHL, NF1, TSC) and show a predominance of well-differentiated NET G1–G2. In contrast, adults exhibit the full spectrum of NET G1–3 and NEC G3. Somatostatin receptor (SSTR) expression is frequent in both pediatric and adult NETs, supporting the use of somatostatin analogues (SSAs) and peptide receptor radionuclide therapy (PRRT) in advanced disease; SSTR expression declines with increasing grade. Surgical resection remains the only curative option in both populations, with pediatric practice prioritizing organ preservation and minimization of late effects. In adults, systemic therapy sequencing is structured by randomized trials, whereas pediatric use of systemic therapies is adapted case-by-case, with emerging but still limited evidence. Survival in localized pediatric NETs exceeds 90%, but remains poor in metastatic and high-grade disease, similar to adults.
Although histological frameworks are shared, pediatric GEPNENs differ from adult disease in genetics, site distribution, functional status, and survivorship challenges. Adult evidence may be cautiously adapted to pediatrics, but pediatric-specific guidelines and collaborative research are urgently needed to address unique biological and clinical features and to harmonize long-term care
Bilateral discoid medial menisci with a parameniscal cyst: a case report
No full textBilateral discoid medial menisci are an exceptionally rare anatomical variant, and their coexistence with a parameniscal cyst has only been described in isolated cases. We present the case of a 13-year-old male with activity-related medial knee pain initially affecting the right knee. Imaging confirmed an incomplete discoid medial meniscus associated with a parameniscal cyst, which was treated with arthroscopy, open cyst excision, and meniscocapsular repair. A subsequent symptomatic retear required revision saucerization and combined meniscal fixation techniques. Months later, the patient developed similar symptoms in the contralateral knee, where MRI revealed a discoid medial meniscus with a horizontal tear, successfully treated with saucerization and partial meniscectomy. At final follow-up, the patient remained pain-free and fully active. This case highlights the importance of early recognition and preservation-focused surgical treatment for this rare bilateral presentation