Search Results (10,485)

Active galactic nuclei (AGNs) often exhibit broad-line regions (BLRs), populated by high-velocity clouds in approximately Keplerian orbits around the central supermassive black hole (SMBH) at subparsec scales. During episodes of intense accretion at super-Eddington rates, the accretion disk can launch a powerful, radiation-driven wind. This wind may overtake the BLR clouds, forming bowshocks around them. Two strong shocks arise: one propagating into the wind, and the other into the cloud. If the shocks are adiabatic, electrons and protons can be efficiently accelerated via a Fermi-type mechanism to relativistic energies. In sufficiently dense winds, the resulting high-energy photons are absorbed and reprocessed within the photosphere, while neutrinos produced in inelastic $pp$ collisions escape. In this paper, we explore the potential of super-accreting AGNs as neutrino sources. We propose a new class of neutrino emitter: an AGN lacking jets and gamma-ray counterparts, but hosting a strong, opaque, disk-driven wind. As a case study, we consider a supermassive black hole with $M_{\mathrm{BH}}={10}^6{M}_{\odot }$ and accretion rates consistent with tidal disruption events (TDEs). We compute the relevant cooling processes for the relativistic particles under such conditions and show that super-Eddington accreting SMBHs can produce detectable neutrino fluxes with only weak electromagnetic counterparts. The neutrino flux may be observable by the next-generation IceCube Observatory (IceCube-Gen2) in nearby galaxies with a high BLR cloud filling factor. For galaxies hosting more massive black holes, detection is also possible with moderate filling factors if the source is sufficiently close, or at larger distances if the filling factor is high. Our model thus provides a new and plausible scenario for high-energy extragalactic neutrino sources, where both the flux and timescale of the emission are determined by the number of clouds orbiting the black hole and the duration of the super-accreting phase. Full article

This study evaluates the eco-efficiency and eco-productivity of 141 countries using data-driven analytical frameworks over the period 2018–2023, covering the pre-COVID, COVID, and post-COVID phases. We employ an input-oriented Slack-Based Measure Data Envelopment Analysis (SBM-DEA) under variable returns to scale (VRS), combined with the Malmquist Productivity Index (MPI), to assess both static and dynamic performance. The analysis incorporates three inputs—labor force, gross fixed capital formation, and energy consumption—one desirable output (gross domestic product, GDP), and one undesirable output (CO₂ emissions). Eco-efficiency (the joint performance of energy and carbon efficiency) and eco-productivity (labor and capital efficiency) are evaluated to capture complementary dimensions of sustainable performance. The results reveal significant but temporary gains in eco-efficiency during the peak pandemic years (2020–2021), followed by widespread post-crisis reversals, particularly in labor productivity, energy efficiency, and CO₂ emission efficiency. These reversals were often linked to institutional and structural barriers, such as rigid labor markets and outdated infrastructure, which limited the translation of technological progress into operational efficiency. The MPI decomposition indicates that, while technological change improved in many countries, efficiency change declined, leading to overall stagnation or regression in eco-productivity for most economies. Regression analysis shows that targeted policy stringency in 2022 was positively associated with eco-productivity, whereas broader restrictions in 2020–2021 were less effective. We conclude with differentiated policy recommendations, emphasizing green technology transfer and institutional capacity building for lower-income countries, and the integration of carbon pricing and innovation incentives for high-income economies. Full article

In modern shock absorber development, the fatigue durability of shim-based clamped valve systems remains a critical factor influencing both performance and operational safety. In this study, the authors extend their previous research achievements by developing a fatigue life prediction methodology that integrates an established finite element framework with a strength-based fatigue model incorporating experimentally derived and validated Wöhler characteristics of the metal alloy used in the valve shims. The focus of this work is the validation of the proposed methodology for hydraulic shock absorbers equipped with shim stack valve systems, supporting the virtual pre-selection of valve configurations during the OEM design process. This approach enables substantial reductions in experimental testing and facilitates cost-effective development under realistic operating conditions. To address random-amplitude loading scenarios, the rainflow-counting algorithm was employed to convert complex load histories into equivalent constant-amplitude cycles, thereby accurately capturing material memory effects associated with stress–strain hysteresis. Experimental validation was conducted using a high-performance servo-hydraulic load frame tester. The validated model demonstrated a prediction uncertainty of 46% for random-amplitude lifetime estimation. Full article

In this work, a unique approach was used to synthesise black coatings on aluminium alloys (AA) 6061 and 7075 for applications in the aerospace field. In detail, plasma electrolytic oxidation (PEO) technology was used, maintaining the voltage constant at a relatively low value (V_max ≤ 292 V) during the process. NaVO₃ additive was used in the silicate-based electrolyte to obtain a black colour. The coatings were characterised by SEM-EDS, XPS, XRD, VIS-NIR spectroscopy, and EIS. The presence of vanadium oxides in the PEO coatings was detected by EDS, XPS, and XRD analyses. PEO coatings on AA7075 produced with 10 g/L of NaVO₃ exhibited exceptional optical characteristics, with a solar absorptance value of 95.3% in the VIS-NIR spectrum (wavelength range of 400–2000 nm). All the coatings improved the corrosion performances of the tested AA6061 and AA7075 by two or three orders of magnitude in 3.5 wt. % aqueous NaCl. Moreover, there was no sign of delamination, cracks, or any visible changes on coatings after thermal shock, performed by cycling samples between two extreme temperatures, −196 °C and 150 °C, respectively. Full article

This study addresses the critical need to enhance productivity in industrial automatic systems by optimizing the mass of moving components. The primary challenge is determining the complex, dynamic loads on structural elements, a prerequisite for effective redesign, without access to physical prototypes for experimental measurement. This paper presents a solution through a case study of a load-bearing pylon in a fine blanking plant, which is subject to inertial loads and shocks from pneumatic actuators and shock absorbers. To overcome this challenge, a high-fidelity multibody simulation model is developed to accurately estimate the dynamic loads on the pylon. This data is given as input to the topology optimization (TO) process, following the Design for Additive Manufacturing (DfAM) framework, to redesign the pylon for mass reduction using a Powder Bed Fusion-Laser Beam (PBF-LB). Two materials, EOS Aluminum Al2139 AM and EOS Maraging Steel MS1, are evaluated. The findings demonstrate that the integrated simulation and redesign approach is highly effective. The redesigned pylon’s performance is verified within the same simulation environment, confirming the productivity gains before manufacturing. A cost analysis revealed that the additively manufactured solution is more expensive than traditional methods, and the final choice depends on the overall productivity increase. This research validates a powerful methodology that integrates dynamic multibody analysis with topology optimization for AM. This approach is recommended in the design phase of complex industrial machinery to evaluate and quantify performance improvements and make informed decisions on the cost-effectiveness of introducing AM components without the need for physical prototyping. Full article

Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS) are multifactorial and progressive neurodegenerative diseases (ND), which cause a functional capacity decline. Both diseases etiology remains unclear. They may have a hereditary genetic architecture, but they can also be due to a combination of genetic and environmental factors. Heat shock proteins (HSPs) play a crucial role in protein quality control, avoiding protein dysfunction and, consequently, cell apoptosis, which are well-known pathogenic mechanisms of ND. There are studies about chaperones physiology. However, research on their pathophysiology is scarce. Especially when it comes to their associated dysfunctions with Single nucleotide variants (SNV) on HSPs in ND. Thus, this review aimed to examine the role of genetic variants in genes encoding HSPs and their contribution to the pathophysiology of these sclerosis. We performed a qualitative and descriptive literature review, searching by the indexed terms “amyotrophic lateral sclerosis,” “genetic variants,” “heat shock proteins,” “Hsp40”, “Hsp70”, Hsp90”, “DNAJC7”, “multiple sclerosis,” “neurodegenerative diseases,” “protein quality control”, and “SNV” in the PubMed/NCBI, EMBASE and SciELo databases. Results described by a qualitative synthesis of the most significant studies. Despite the existence of studies with genetic variants in HSPs in patients with ND, we realize in this review the need for more specific research on this topic to demonstrate a significance as to the responsibility for deleterious effects in the modification in genes HSPs linked to sclerosis. Full article

Spilled hydrocarbons released from oil pipeline accidents can result in long-term environmental contamination and significant damage to habitats. In this regard, evaluating actions in response to vulnerability scenarios is fundamental to emergency management and groundwater integrity. To this end, understanding the trajectories and their influence on the various parameters and characteristics of the contaminant’s fate through accurate numerical simulations can aid in developing a rapid remediation strategy. This paper develops a numerical model using the CactusHydro code, which is based on a high-resolution shock-capturing (HRSC) conservative method that accurately follows sharp discontinuities and temporal dynamics for a three-phase fluid flow. We analyze nine different emergency scenarios that represent the breaking of a diesel oil onshore pipeline in a porous medium. These scenarios encompass conditions such as dry season rupture, rainfall-induced saturation, and varying pipeline failure pressures. The influence of the spilled oil pressure and water saturation in the unsaturated zone is analyzed by following the saturation contour profiles of the three-phase fluid flow. We follow with the high-accuracy formation of shock fronts of the advective part of the migration. Additionally, the mass distribution of the expelled contaminant along the porous medium during the emergency is analyzed and quantified for the various scenarios. The results obtained indicate that the aquifer contamination strongly depends on the pressure outflow in the vertical flow. For a fixed pressure value, as water saturation increases, the mass of contaminant decreases, while the contamination speed increases, allowing the contaminant to reach extended areas. This study suggests that, even for LNAPLs, the distribution of leaked oil depends strongly on the spill pressure. If the pressure reaches 20 atm at the time of pipeline failure, then contamination may extend as deep as two meters below the water table. Additionally, different seasonal conditions can influence the spread of contaminants. This insight could directly inform guidelines and remediation measures for spill accidents. The CactusHydro code is a valuable tool for such applications. Full article

This research investigates the responsiveness of climate and low-carbon (green) stock returns to oil prices and conventional energy stock returns, focusing on both contemporaneous and causal relationships, during an oil crisis. Two methodologies are used: vector auto-regressive (VAR) for testing the causal relationship, and ordinary least squares (OLS) for investigating the contemporaneous relationship. The main empirical results suggest that green stocks have a bidirectional positive contemporaneous relationship with oil prices and energy stock returns but no significant bidirectional causal relationship. The results reveal that oil prices and energy stock returns play a larger role in contemporaneous than causal relationships with green stock returns. In addition, green stock returns seem to have a stronger positive relationship with energy stock return than oil prices. Full article

Urban carbon reduction is instrumental in enabling cities to realize their developmental sustainability objectives. However, regional disparities in economic development pose significant challenges to low-carbon transitions. This study utilizes panel data from 282 cities in China spanning 2006–2021, considering the energy saving and emission reduction (ESER) fiscal policy as an external shock. Using a multi-period difference-in-differences approach, we assess how ESER impacts urban carbon emissions. Our findings indicate that ESER significantly reduces municipal carbon emissions by an average of 23.3% compared to non-pilot cities. Mechanism analyses suggest that this effect operates through reduced energy consumption, improved industrial structure, and enhanced green innovation. ESER’s impact exhibits heterogeneity across cities with different levels of economic development, population size, innovation capacity, and industrial composition. Moreover, we find evidence of spatial spillover effects, as ESER benefits extend to neighboring regions. These results confirm the effectiveness of ESER in promoting low-carbon development and offer practical implications for enhancing environmental governance through green fiscal instruments. Full article

Modeling risk evolution in financial networks presents both practical and theoretical challenges, particularly during periods of heightened systemic stress. This issue has gained urgency recently in China as it faces unprecedented financial strain, largely driven by structural shifts in the real estate sector and broader economic vulnerabilities. In this study, we combine Fractional-order Partial Differential Equations (FoPDEs) with network-based analysis methods, proposing a hybrid framework for capturing and modeling systemic financial risk, which is quantified using the $\Delta CoVaR$ algorithm. The FoPDEs model is formulated based on reaction–diffusion equations and discretized using the Caputo fractional derivative. Parameter estimation is conducted through a composite optimization strategy, and numerical simulations are carried out to investigate the underlying mechanisms and dynamic behavior encoded in the equations. For empirical evaluation, we utilize data from China’s financial and real estate sectors. The results demonstrate that our model achieves a Mean Relative Accuracy (MRA) of 95.5% for daily-frequency data, outperforming LSTM and XGBoost under the same conditions. For weekly-frequency data, the model attains an MRA of 91.7%, exceeding XGBoost’s performance of 90.25%. Further analysis of parameter dynamics and event studies reveals that the fractional-order parameter $\alpha$, which controls the memory effect of the model, tends to remain low when $\Delta CoVaR$ exhibits sudden surges. This suggests that the model assigns greater importance to past data during periods of financial shocks, capturing the persistence of risk dynamics more effectively. Full article

Small ruminant production is increasingly affected by heat stress, with recent heat waves highlighting growing economic and welfare-related challenges. Chronic exposure to elevated temperatures disrupts thermoregulation, reduces feed intake, slows growth, compromises meat quality, and increases mortality. This study evaluated the effects of chromium-yeast supplementation at different doses and timepoints on physiological and molecular stress biomarkers in heat-stressed lambs. Forty-eight clinically healthy 6-month-old Katahdin lambs (average weight 20 ± 2.9 kg) were assigned to a 2 × 4 factorial design, with two ambient temperature conditions (heat stress [HS] and thermoneutral [TN]) and four levels of dietary Cr-yeast (0, 0.2, 0.4, and 0.8 mg/kg of dry matter intake). Lambs were housed individually in pens (1.2 × 2.5 m), with ad libitum access to water, and fed a 50:50 corn silage and concentrate diet (excluding mineral premix) twice daily. Blood samples were collected at days 0, 30, and 60 to evaluate plasma cortisol and the expression of hsp60 and hsp70. Chromium bioavailability was assessed by blood levels using absorption chromatography, and glucose clearance was measured at the end of the experiment. Significant reductions in cortisol and hsp70 expression were observed after 30 days of Cr-yeast supplementation under HS conditions (p < 0.05), particularly at the highest dose. For hsp60, a significant reduction was observed at the highest dose on day 30 under HS (p < 0.05). These effects were not sustained on day 60 (p > 0.05). No significant differences were detected under TN conditions (p > 0.05). These findings suggest that Cr-yeast may offer short-term physiological and cellular protection against chronic heat stress in lambs. Full article

Alcohol Use Disorder (AUD) poses global health challenges, and causes hematological alterations such as macrocytosis and oxidative stress. Disruption of protein structures by alcohol and/or its metabolites may exacerbate AUDs; proteomics can elucidate the underlying biological mechanisms. This study examined the proteins differentially expressed in the cytosol and membrane fractions of erythrocytes obtained from 30 male patients with AUD, comparing them to samples from 15 age- and BMI-matched social drinkers (SDs) and 15 non-drinkers (control). The analysis aimed to identify the molecular differences related to alcohol consumption. The AUD patient subgrouping was based on mean corpuscular volume (MCV), with 16 individuals classified as having a normal MCV and 14 having a high MCV. Proteins were separated via two-dimensional(2D)-gel electrophoresis, digested with trypsin, and identified via Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (TOF) mass spectrometry (MALDI-TOF/TOF). Additionally, levels of malondialdehyde and 4-hydroxyalkenals (MDA + HAE), reduced glutathione (GSH), oxidized glutathione (GSSG), serum carbohydrate-deficient transferrin (%CDT), disialotransferrin (%DST), and sialic acid (SA) were analyzed. The results showed increased MDA + HAE and decreased total thiols in AUD patients, with GSSG elevated and the GSH/GSSG ratio reduced in the AUD MCV-high subgroup. Serum %CDT, %DST, and SA were significantly higher in AUD. Compared to the control profiles, the AUD group exhibited differential protein expression. Few proteins, such as bisphosphoglycerate mutase, were downregulated in AUD versus control and SD, as well as in the MCV-high AUD subgroup. Conversely, endoplasmin and gelsolin were upregulated in AUD relative to control. Cytoskeletal proteins, including spectrin-alpha chain, actin cytoplasmic 2, were overexpressed in the AUD group and MCV-high AUD subgroup. Several proteins, such as 14-3-3 isoforms, alpha-synuclein, translation initiation factors, heat shock proteins, and others, were upregulated in the MCV-high AUD subgroup. Under-expressed proteins in this subgroup include band 3 anion transport protein, bisphosphoglycerate mutase, tropomyosin alpha-3 chain, uroporphyrinogen decarboxylase, and WD repeat-containing protein 1. Our findings highlight the specific changes in protein expression associated with oxidative stress, cytoskeletal alterations, and metabolic dysregulation, specifically in AUD patients with an elevated MCV. Understanding these mechanisms is crucial for developing targeted interventions and identifying biomarkers of alcohol-induced cellular damage. The complex interplay between oxidative stress, membrane composition, and cellular function illustrates how chronic alcohol exposure affects cellular physiology. Full article

Background: Leber’s hereditary optic neuropathy (LHON) is the most common mitochondrial disorder and an inherited optic neuropathy. Recently, two different LHON inheritance types have been discovered: mitochondrially inherited LHON (mtLHON) and autosomal recessive LHON (arLHON). Our case report is the first diagnosed case of arLHON in a patient of Lithuanian descent and confirms the DnaJ Heat Shock Protein Family (Hsp40) Member C30 (DNAJC30) c.152A>G p.(Tyr51Cys) founder variant. Case Presentation: A 34-year-old Lithuanian man complained of headache and sudden, painless loss of central vision in his right eye. On examination, the visual acuity of the right and left eyes was 0.1 and 1.0, respectively. Visual-field examination revealed a central scotoma in the right eye, and visual evoked potentials (VEPs) showed prolonged latency in both eyes. Optical coherence tomography showed thickening of the retinal nerve fiber layer in the upper quadrant of the optic disk in the left eye. Magnetic resonance imaging of the head showed evidence of optic nerve inflammation in the right eye. Blood tests were within normal range and showed no signs of inflammation. Retrobulbar neuritis of the right eye was suspected, and the patient was treated with steroids, which did not improve visual acuity. He later developed visual loss in the left eye as well. A genetic origin of the optic neuropathy was suspected, and a complete mitochondrial DNA analysis was performed, but it did not reveal any pathologic mutations. Over time, the visual acuity of both eyes slowly deteriorated, and the retinal nerve fiber layer (RNFL) thinning of the optic disks progressed. A multidisciplinary team of specialists concluded that vasculitis or infectious disease was unlikely to be the cause of the vision loss, and a genetic cause for the disease was still suspected, although a first-stage genetic test did not yield the diagnosis. Thirty-three months after disease onset, whole-exome sequencing revealed a pathogenic variant in the DNAJC30 gene, leading to the diagnosis of arLHON. Treatment with Idebenone was started 35 months after the onset of the disease, resulting in no significant worsening of the patient’s condition. Conclusion: This case highlights the importance of considering arLHON as a possible diagnosis for patients with optic neuropathy, because the phenotype of arLHON appears to be identical to that of mtLHON and cannot be distinguished by clinicians. Full article

The extensive utilization of amorphous silica nanoparticles (SiNPs) has raised concerns regarding the potential health risks. Previous studies have indicated that SiNPs could trigger both the activation of heat shock proteins (HSPs) and epithelial–mesenchymal transition (EMT) in BEAS-2B cells; however, the underlying mechanisms require further elucidation. This study aimed to investigate how SiNPs activate the heat shock response (HSR) in BEAS-2B cells, which subsequently triggers EMT. Firstly, we observed that SiNPs were internalized by BEAS-2B cells and localized in the endoplasmic reticulum (ER), inducing ER stress. The ER stress led to the activation of SIRT1 by phosphorylation, which enhanced the nuclear transcriptional activity of HSF1 via deacetylation. HSF1 was found to upregulate the levels of HSP70 and HSP27 proteins, which further affected EMT-related genes and, ultimately, induced EMT. Additionally, 4-phenylbutyric acid (4-PBA) inhibited ER stress, which attenuated the SIRT1/HSF1 signaling pathway. The knockdown of SIRT1 and HSF1 using siRNA effectively suppressed the EMT progression. In summary, these results suggested that SiNPs activated the SIRT1/HSF1/HSPs pathway through ER stress, thereby triggering EMT in BEAS-2B cells. The present study identified a novel mechanism of SiNP-induced EMT, which has provided valuable insights for future toxicity studies and risk assessments of SiNPs. Full article

The US has undertaken both unconventional and conventional monetary policy stances in response to the COVID-19 pandemic and the Ukraine–Russia conflict, and there has been much debate on the effects of these various monetary policies on global financial markets. Our study considers the debate in the context of South Africa and uses the quantile–frequency connectedness approach to examine static and dynamic systemic spillover between the US shadow short rate (SSR) and South African equity, bond and currency markets between 1 December 2019 and 2 March 2023. The findings from the static analysis reveal that systemic connectedness is concentrated at their tail-end quantile distributions and US monetary policy plays a dominant role in transmitting these systemic shocks, albeit these shocks are mainly high frequency with very short cycles. However, the dynamic estimates further reveal that US monetary policy exerts longer-lasting spillover shocks to South African financial markets during periods corresponding to FOMC announcements of quantitative ‘easing’ or ‘tapering’ policies. Overall, these findings are useful for evaluating the effectiveness of the Reserve Bank’s macroprudential policies in ensuring market efficiency, as well as for enhancing investor decisions, portfolio allocation and risk management. Full article