Search Results (497)

Background: Mental health issues among PhD students are rising, a trend believed to be driven by academic and social challenges. Method: A total of 1265 doctorate students from a large university in Barcelona, Spain (739 women; 414 men; 112 marked other options), with a mean age of 32.36 years (SD = 8.20, range: 23–67), were evaluated by means of standardized instruments. Results: Totals of 40.6% and 46.5% of the sample exceeded the cut-off point for anxiety and depression symptoms, and 57.7% for life satisfaction. The proportion of females exceeding the cut-off point was significantly higher than that of males for both anxiety (women: 43.8%, men: 34.5%) and depression (women: 49.3%, men: 39.8%), but not for life satisfaction (women: 57.6%, men: 58.4%). Arts and Humanities PhD students’ disciplines reported higher anxiety and depression scores than those in Social Sciences, Experimental Sciences and Mathematics, and Health Sciences, respectively, while Social Sciences students showed higher life satisfaction and mentoring support than the other groups. Depression scores were significant predictors of life satisfaction across all doctoral programs. Conclusions: These findings highlight the importance of mentoring in supporting doctoral students’ mental health and life satisfaction and can also inform policies in educational institutions, given that PhD students experiencing psychopathological disorders are at a higher risk of academic failure and dropout. Full article

As artificial intelligence (AI) systems attain greater autonomy, recursive reasoning capabilities, and complex environmental interactions, they begin to exhibit behavioral anomalies that, by analogy, resemble psychopathologies observed in humans. This paper introduces Psychopathia Machinalis: a conceptual framework for a preliminary synthetic nosology within machine psychology intended to categorize and interpret such maladaptive AI behaviors. Drawing structural inspiration from psychiatric diagnostic manuals, we propose a taxonomy of 32 AI dysfunctions encompassing epistemic failures, cognitive impairments, alignment divergences, ontological disturbances, tool and interface breakdowns, memetic pathologies, and revaluation dysfunctions. Each syndrome is articulated with descriptive features, diagnostic criteria, presumed AI-specific etiologies, human analogs (for metaphorical clarity), and potential mitigation strategies. This framework is offered as an analogical instrument—eschewing claims of literal psychopathology or consciousness in AI, yet providing a structured vocabulary to support the systematic analysis, anticipation, and mitigation of complex AI failure modes. Drawing on insights from psychiatric classification, cognitive science, and philosophy of mind, we examine how disordered AI behaviors may emerge from training instabilities, alignment conflicts, or architectural fragmentation. We argue that adopting an applied robopsychological perspective within a nascent domain of machine psychology can strengthen AI safety engineering, improve interpretability, and contribute to the design of more robust and reliable synthetic minds. Full article

Background: The interaction between prosthetic restorations and periodontal health is a critical factor for the long-term success of dental treatments. A biologically compatible prosthetic design supports periodontal stability, whereas neglecting periodontal principles can compromise treatment outcomes. This study aimed to validate a questionnaire designed to assess dentists’ perceptions regarding the influence of prosthetic restorations on the periodontium. Material and Methods: An observational cross-sectional study was conducted using a self-administered questionnaire distributed to licensed dentists across Romania. The questionnaire underwent expert review, pilot testing (n = 50), and statistical validation, including the Content Validity Index (CVI), Cronbach’s alpha for internal consistency, and Exploratory Factor Analysis (EFA) using Principal Component Analysis (PCA) with Varimax rotation. The final sample included 39 respondents. Data was analyzed using SPSS v26.0. Results: The questionnaire demonstrated excellent internal consistency (Cronbach’s alpha = 0.900; standardized alpha = 0.917). Most items had corrected item-total correlations > 0.40. EFA revealed eight coherent factors explaining 81.68% of total variance, with high communalities (0.549–0.966), strong Kaiser–Meyer–Olkin test (KMO) values, and significant Bartlett’s test values, confirming construct validity. Descriptive statistics showed predominantly positive attitudes among dentists regarding the periodontal considerations in prosthetic treatment. The highest-rated items emphasized oral hygiene, periodontal stability, and biological adaptation of restorations. Lower scores were associated with routine use of periodontal indices and recognition of failures due to insufficient evaluation. Conclusions: The validated instrument proved reliable and demonstrated strong psychometric properties in this exploratory validation, supporting its use in research and education. Romanian dentists demonstrated a favorable perception of the role of periodontal health in prosthetic success. This tool can inform curriculum development and interdisciplinary clinical protocols in prosthodontics and periodontology. Full article

Reliable estimates of aquifer properties are needed for groundwater resources management and for engineering applications. Pumping tests conducted in fractured aquifers using an open borehole may not produce a proper characterization of the aquifer properties leading to the failure of engineering solutions. In this work, we apply a radial flow model to reproduce the time drawdown curves recorded at an observation borehole instrumented with multi-level piezometers drilled in the Permo-Triassic sandstone, which is a complex fractured hydraulic unit. The radial flow model and the optimization code PEST are used to estimate the aquifer hydraulic parameter values. The model is then used to investigate the implications of replacing the multi-level piezometers with an open borehole. The results show that the open borehole does not only significantly alter the groundwater head and flow patterns around the borehole, but the analysis of the time drawdown curve obtained would produce estimates of aquifer properties that bear no relationship with the actual hydraulic properties of the aquifer. For engineering control studies, the pumping test must be carefully designed to account for the presence of fractures, and these must be represented in the analysis tools to ensure the correct characterization of the hydraulic system. Full article

Background/Objectives: We sought to characterize the variance and overlap among definitions of Proximal Junctional Kyphosis (PJK) used in the adult spinal deformity (ASD) literature. PJK is defined as excess in PJK angle, a Cobb angle between the upper-instrumented vertebra (UIV) and a supra-adjacent vertebra (SAV), either one (UIV+1) or two (UIV+2) levels rostral of the UIV. No expert consensus exists for threshold angle or which SAV to use. Methods: A total of 116 thoracolumbar fusion patients ≥ 65 years old were reviewed. The UIV+1 and UIV+2 angles were measured. Six definitions of PJK from the literature were evaluated. These definitions were selected based on citation frequency, historical relevance, and accessibility through commonly used databases. Pearson’s Chi-squared and pairwise comparisons were performed to evaluate the distinctness and agreement rates among these definitions. Results: The six definitions of PJK were as follows: [PJK20] PJK angle ≥ 20° with UIV+2 as the (SAV), [PJK10] PJK angle ≥ 10° with a >10° change from pre-op with UIV+2 as the SAV, [PJK2SD] PJK angle > 2 standard deviations from average with UIV+1 as the SAV, [PJK10+10] PJK angle ≥ 10° with a >10° change from pre-op with UIV+1 as the SAV, [PJK15] PJK angle > 15° with UIV+1 as the SAV, and [PJK30] PJK angle > 30° with UIV+2 as the SAV, or displaced rod fracture, or reoperation within 2 years for junctional failure, pseudoarthrosis, or rod fracture. [PJK10] and [PJK2SD] were the most distinct definitions while [PJK20], [PJK10+10], [PJK15], and [PJK30] showed no significant pairwise differences. [PJK2SD] was stringent, while definition [PJK30] included unique diagnostic information not captured by other definitions. Conclusions: The use of [PJK20], [PJK10+10], [PJK15], or [PJK30] is recommended for consistency, with [PJK15] presenting the best balance. Stringent [PJK2SD] may be beneficial for identifying severe PJK, though with low sensitivity. Overall, PJK definitions must be standardized for the consistent reporting of clinical outcomes and research comparability. Full article

This article analyzes statistics on the failure of technological equipment, assemblies, and mechanisms of agricultural (and other) machines associated with the breakdown or failure of gear pumps. It was found that the leading causes of gear pump failures are the opening of gear teeth contact during pump operation, poor assembly, wear of bushings, thrust washers, and gear teeth. It has also been found that there is a problem related to the restoration, repair, and manufacture of parts in the conditions of enterprises serving the agro-industrial complex of the Republic of Kazakhstan (AIC RK). This is due to the lack of necessary technological equipment, tools, and instruments, as well as centralized repair and restoration bases equipped with the required equipment. This work proposes to solve this problem by applying AM technologies to the repair and manufacture of parts for agricultural machinery and equipment. The study results on the stress–strain state of support bushings under various pressures are presented, showing that a fully filled bushing has the lowest stresses and strains. It was also found that bushings with 50% filling and fully filled bushings have similar stress and strain values under the same pressure. The difference between them is insignificant, especially when compared to bushings with lower filling. This means that filling the bushing by more than 50% does not provide a significant additional reduction in stresses. In terms of material and printing time savings, 50% filling may also be the optimal option. Full article

The management of adult spinal deformity (ASD) has evolved dramatically over the past century, transitioning from external bracing and in situ fusion to complex, technology-driven surgical interventions. This review traces the historical development of spinal deformity correction and highlights contemporary enabling technologies that are redefining the surgical landscape. Advances in stereoradiographic imaging now allow for precise, low-dose three-dimensional assessment of spinopelvic parameters and segmental bone density, facilitating individualized surgical planning. Robotic assistance and intraoperative navigation improve the accuracy and safety of instrumentation, while patient-specific rods and interbody implants enhance biomechanical conformity and alignment precision. Machine learning and predictive modeling tools have emerged as valuable adjuncts for risk stratification, surgical planning, and outcome forecasting. Minimally invasive deformity correction strategies, including anterior column realignment and circumferential minimally invasive surgery (cMIS), have demonstrated equivalent clinical and radiographic outcomes to traditional open surgery with reduced perioperative morbidity in select patients. Despite these advancements, complications such as proximal junctional kyphosis and failure remain prevalent. Adjunctive strategies—including ligamentous tethering, modified proximal fixation, and vertebral cement augmentation—offer promising preventive potential. Collectively, these innovations signal a paradigm shift toward precision spine surgery, characterized by data-informed decision-making, individualized construct design, and improved patient-centered outcomes in spinal deformity care. Full article

Objectives: Patients with acute heart failure (AHF) often receive initial non-invasive ventilation (NIV). This study aimed to evaluate the prognostic role of NIV in patients hospitalized for AHF. Methods: This was a retrospective cohort study. We enrolled patients admitted to our cardiac intensive care unit with a diagnosis of AHF. Anthropometric, clinical, pharmacological, and instrumental assessments were collected. Both in-hospital and 180-day post-discharge mortality were evaluated. Results: Among 200 patients (mean age 81 ± 9 years; 52% male), NIV was applied in 80 cases (40%). These patients had more severe NYHA functional class, a higher prevalence of de novo AHF, required higher diuretic doses, and had longer hospital stays. In multivariate analysis, NIV remained significantly associated with length of stay (LOS) (r = 0.26; p = 0.0004). In-hospital mortality was 5% overall and significantly higher in the NIV group compared to non-NIV patients (10% vs. 1.6%, p < 0.001). At 180 days, mortality was also significantly higher in the NIV group [hazard ratio (HR) 1.84; 95% confidence interval (CI): 1.18–2.85; p = 0.006]. After adjusting for age, BNP, CRP, arterial blood gas parameters, renal function, and LVEF, NIV remained an independent predictor of 180-day mortality (HR 1.61; 95% CI: 1.01–2.54; p = 0.04). Conclusions: Patients with AHF who required NIV exhibited more severe disease and longer hospital stays. NIV use was independently associated with both in-hospital and post-discharge mortality, suggesting its potential role as a prognostic marker in AHF. Full article

Protein S-nitrosylation is a selective post-translational modification in which a nitrosyl group is covalently attached to the reactive thiol group of cysteine, forming S-nitrosothiol. This modification plays a pivotal role in modulating physiological and pathological cardiovascular processes by altering protein conformation, activity, stability, and other post-translational modifications. It is instrumental in regulating vascular and myocardial systolic and diastolic functions, vascular endothelial cell and cardiomyocyte apoptosis, and cardiac action potential and repolarization. Aberrant S-nitrosylation levels are implicated in the pathogenesis of various cardiovascular diseases, including systemic hypertension, pulmonary arterial hypertension, atherosclerosis, heart failure, myocardial infarction, arrhythmia, and diabetic cardiomyopathy. Insufficient S-nitrosylation leads to impaired vasodilation and increased vascular resistance, while excessive S-nitrosylation contributes to cardiac hypertrophy and myocardial fibrosis, thereby accelerating ventricular remodeling. This paper reviews the S-nitrosylated proteins in the above-mentioned diseases and their impact on these conditions through various signaling pathways, with the aim of providing a theoretical foundation for the development of novel therapeutic strategies or drugs targeting S-nitrosylated proteins. Full article

Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system activity, vascular compliance, and circadian rhythms. This enables early identification of abnormal BP trends and allows for timely diagnosis and interventions to reduce the risk of cardiovascular diseases (CVDs) such as hypertension, stroke, heart failure, and chronic kidney disease as well as chronic stress or anxiety disorders. To facilitate continuous BP monitoring, we propose an AI-powered estimation framework. The proposed framework first uses an expert-driven feature engineering approach that systematically extracts physiological features from photoplethysmogram (PPG)-based arterial pulse waveforms (APWs). Extracted features include pulse rate, ascending/descending times, pulse width, slopes, intensity variations, and waveform areas. These features are fused with demographic data (age, gender, height, weight, BMI) to enhance model robustness and accuracy across diverse populations. The framework utilizes a Tab-Transformer to learn rich feature embeddings, which are then processed through an ensemble machine learning framework consisting of CatBoost, XGBoost, and LightGBM. Evaluated on a dataset of 1000 subjects, the model achieves Mean Absolute Errors (MAE) of 3.87 mmHg (SBP) and 2.50 mmHg (DBP), meeting British Hypertension Society (BHS) Grade A and Association for the Advancement of Medical Instrumentation (AAMI) standards. The proposed architecture advances non-invasive, AI-driven solutions for dynamic cardiovascular health monitoring. Full article

In high-voltage transmission lines, insulators subjected to prolonged electromechanical stress are prone to zero-value defects, leading to insulation failure and posing significant risks to power grid reliability. The conventional detection method of spark gap is vulnerable to environmental interference, while the emerging electric field distribution-based techniques require complex instrumentation, limiting its applications in scenes of complex structures and atop tower climbing. To address these challenges, this study proposes an electroluminescent sensing strategy for zero-value insulator identification based on the electroluminescence of ZnS:Cu. Based on the stimulation of electrical stress, real-time monitoring of the health status of insulators was achieved by applying the composite of epoxy and ZnS:Cu onto the connection area between the insulator steel cap and the shed. Experimental results demonstrate that healthy insulators exhibit characteristic luminescence, whereas zero-value insulators show no luminescence due to a reduced drop in electrical potential. Compared with conventional detection methods requiring access of electric signals, such non-contact optical detection method offers high fault-recognition accuracy and real-time response capability within milliseconds. This work establishes a novel intelligent sensing paradigm for visualized condition monitoring of electrical equipment, demonstrating significant potential for fault diagnosis in advanced power systems. Full article

The Flexible Combined Imager (FCI), developed as the next-generation imager for the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteosat Third Generation (MTG) satellite series, represents a significant advancement over its predecessor, SEVIRI, on the Meteosat Second Generation (MSG) satellites. FCI offers more spectral bands, higher spatial resolution, and faster imaging capabilities, supporting a wide range of applications in weather forecasting, climate monitoring, and environmental analysis. On 13 January 2024, the FCI onboard MTG-I1 (renamed Meteosat-12 in December 2024) experienced a critical anomaly involving the failure of its onboard Calibration and Obturation Mechanism (COM). As a result, the use of the COM was discontinued to preserve operational safety, leaving the instrument dependent on alternative calibration methods. This loss of onboard calibration presents immediate challenges, particularly for the infrared channels, including image artifacts (e.g., striping), reduced radiometric accuracy, and diminished stability. To address these issues, EUMETSAT implemented an external calibration approach leveraging algorithms from the Global Space-based Inter-Calibration System (GSICS). The inter-calibration algorithm transfers stable and accurate calibration from the Infrared Atmospheric Sounding Interferometer (IASI) hyperspectral instrument aboard Metop-B and Metop-C satellites to FCI’s infrared channels daily, ensuring continued data quality. Comparisons with Cross-track Infrared Sounder (CrIS) data from NOAA-20 and NOAA-21 satellites using a similar algorithm is then used to validate the radiometric performance of the calibration. This confirms that the external calibration method effectively compensates for the absence of onboard blackbody calibration for the infrared channels. For the visible and near-infrared channels, slower degradation rates and pre-anomaly calibration ensure continued accuracy, with vicarious calibration expected to become the primary source. This adaptive calibration strategy introduces a novel paradigm for in-flight calibration of geostationary instruments and offers valuable insights for satellite missions lacking onboard calibration devices. This paper details the COM anomaly, the external calibration process, and the broader implications for future geostationary satellite missions. Full article

Global biodiversity is in crisis, with wildlife populations declining 69% since 1970 (WWF). Preserving and restoring ecosystems is essential for sustaining life on Earth. However, many countries rely on market-based instruments like biodiversity offsets, despite little evidence of their effectiveness. This study critically examines biodiversity offsets, identifying institutional, data, ecological, economic, and social failures that undermine their success. Using Indonesia, a global biodiversity hotspot, as a case study, we develop an econometric model to analyze key drivers of deforestation. The findings reveal that biodiversity offset schemes are fundamentally flawed: they lack scientific credibility, rely on arbitrary ratios, lack auditing and transparency, create value conflicts, and fail to achieve “No Net Loss” even over a 100-year timeframe. Offsets do not compensate for lost biodiversity, especially for affected communities, and are rarely supported by ecosystem mapping or robust valuation metrics. Without major reforms, they cannot halt or reverse biodiversity loss. A stronger, evidence-based approach is urgently needed. Rather than relying on ineffective offset schemes, the global community must prioritize genuine ecosystem restoration and sustainable conservation strategies to protect biodiversity for future generations. Full article

Objectives: This pre-clinical feasibility study evaluates the accuracy of a novel augmented reality-based (AR-based) guidance technology using head-mounted displays (HMDs) for the placement of patient-specific instruments (PSIs)—also referred to as surgical guides—and osteotomy performance in pelvic tumour resections. The goal is to improve PSI placement accuracy and osteotomy execution while assessing user perception and workflow efficiency. Methods: The study was conducted on ten 3D-printed pelvic phantoms derived from CT scans of cadaveric specimens. Custom PSIs were designed and printed to guide osteotomies at the supraacetabular, symphysial, and ischial regions. An AR application was developed for the HoloLens 2 HMD to display PSI location and cutting planes. The workflow included manual supraacetabular PSI placement, AR-guided placement of the other PSIs and osteotomy execution. Postoperative CT scans were analysed to measure angular and distance errors in PSI placement and osteotomies. Task times and user feedback were also recorded. Results: The mean angular deviation for PSI placement was 2.20°, with a mean distance error of 1.19 mm (95% CI: 0.86 to 1.52 mm). Osteotomies showed an overall mean angular deviation of 3.73° compared to planned cuts, all within the predefined threshold of less than 5°. AR-assisted guidance added less than two minutes per procedure. User feedback highlighted the intuitive interface and high usability, especially for visualising cutting planes. Conclusions: Integrating AR through HMDs is a feasible and accurate method for enhancing PSI placement and osteotomy performance in pelvic tumour resections. The system provides reliable guidance even in cases of PSI failure and adds minimal time to the surgical workflow while significantly improving accuracy. Further validation in cadaveric models is needed to ensure its clinical applicability. Full article

Grass-covered levees commonly protect river and estuarine areas against flooding. Climate-induced water level changes may increasingly expose these levees to overflow events. This study investigates whether grass-covered levees can withstand such events, and under what conditions failure may occur. Between 2020 and 2022, full-scale overflow tests were conducted at the Living Lab Hedwige-Prosperpolder along the Dutch–Belgian Scheldt Estuary to assess erosion resistance under varying hydraulic conditions and vegetation states. A custom-built overflow generator was used, with instrumentation capturing flow velocity, water levels, and erosion progression. The results show that well-maintained levees with intact grass cover endured overflow durations up to 30 h despite high terminal flow velocities (4.9–7.7 m/s), without structural damage. In contrast, levee sections with pre-existing surface anomalies, such as animal burrows, slope irregularities, surface damage, or reed-covered soft soils, failed rapidly, often within one to two hours. Animal burrows facilitated subsurface flow and internal erosion, initiating fast, retrograde failure. These findings highlight the importance of preventive maintenance, particularly the timely detection and repair of anomalies. Once slope failure begins, the process unfolds rapidly, leaving no practical window for intervention. Full article