Search Results (376)

Pinyon–juniper (PJ) woodlands, one of the most extensive mature and old-growth woodland types in the Western United States, provide critical ecological, cultural, and economic benefits but face increasing threats from climate change, altered disturbance regimes, invasive species, and pests. We developed the PJ Woodland Climate Adaptation Management Menu, a decision support tool designed to guide adaptive, climate-informed management of PJ ecosystems, particularly within the Colorado Plateau ecoregion. The menu was created through an iterative, collaborative process involving literature review, integration of strategies from existing adaptation frameworks, and extensive input from scientists, land managers, and community partners during workshops and focus groups. The menu links specific, evidence-based approaches to each of six broad strategies, including soliciting community input, mitigating disturbance, enhancing and maintaining biodiversity, conserving ecotones, timing actions for optimal outcomes, and accepting climate-driven changes when appropriate. It is intended for use with the Adaptation Workbook to help managers connect local goals and climate vulnerabilities to tailored management tactics. Hypothetical scenarios demonstrate the menu’s application to contrasting PJ woodland conditions, from die-off events to old-growth maintenance. Lessons learned during development underscore the value of early stakeholder engagement, cross-sector collaboration, and balancing diverse ecological objectives. This menu offers a flexible, transferable framework to strengthen climate resilience in PJ woodlands and serves as a model that could improve adaptation planning in other dryland forest ecosystems. Full article

The aim of this study was to assess long-term outcomes in patients with different vascular types of childhood stroke. Methods: Data for children with childhood stroke (aged 29 days to 18 years) were collected from the Estonian Pediatric Stroke Database. Outcomes (death, recurrent stroke, epilepsy, neurodevelopmental outcome by pediatric stroke outcome measure (PSOM)) were assessed at a minimum of two years after stroke. Results: Long-term outcome data were available for 44 patients with childhood stroke (including three patients who died of stroke). According to the PSOM, based on gender, age, location of stroke and epilepsy, there were no differences in outcomes, but patients with a Pediatric NIH Stroke Scale (PedNIHSS) score of ≥6 had worse outcomes compared to patients with a score of <6. Children with arterial hemorrhagic stroke (AHS) were more likely to die, suffer from epilepsy and develop problems in the cognition/behavior PSOM subscale compared to children with arterial ischemic stroke (AIS). Combined poor outcomes (epilepsy, PSOM ≥ 1, recurrent stroke, mortality) occurred in 75% (33/44) of all patients with long-term outcome data. Conclusions: Combined poor outcomes occurred in 75% of the patients with childhood stroke. Patients with AHS showed higher mortality and worse long-term outcomes compared to patients with AIS in certain neurodevelopmental domains. Full article

The discrete-form control of the Stewart platform is essential for digital implementation in intelligent manufacturing and robotic systems under the context of Industry 4.0, yet its performance is often degraded by unavoidable discrete disturbances. This challenge motivates the development of algorithms with strong disturbance suppression capability. To address this issue, a continuous-form double-integration-enhanced recurrent neural network (CF-DIE-RNN) algorithm incorporating a novel double-integration-enhanced design concept is first developed to improve robustness against time-varying disturbances. For digital hardware applications, a discrete-form double-integration-enhanced RNN (DF-DIE-RNN) algorithm is then constructed by discretizing the CF-DIE-RNN algorithm using a general four-step discretization formula and a one-step forward difference formula based on Taylor expansion. Rigorous theoretical analysis establishes the convergence properties of the proposed algorithm and characterizes its steady-state residual bounds under different disturbance types, revealing its capability to suppress discrete quadratic time-varying disturbances. Numerical and simulation experiments demonstrate that the DF-DIE-RNN algorithm achieves superior disturbance suppression and more accurate trajectory tracking than existing discrete-form RNN algorithms, confirming its effectiveness for discrete-form Stewart platform control. Full article

Rising temperatures and droughts are triggering forest die-off in climate warming hotspots such as the Mediterranean Basin. UAVs equipped with LiDAR and multispectral sensors offer a powerful tool for surveys of tree vigor at landscape level. We used UAV-acquired LiDAR data and multispectral camera imagery to segment individual tree crowns, classify species, and assess the health status in two drought-affected forests in northeastern Spain: a mixed Pinus pinaster–Quercus ilex forest and a Pinus halepensis forest. Individual trees were segmented and classified using object-based image analysis with the Random Forest algorithm incorporating spectral, structural, and topographic variables. Greenness indices (NDVI and EVI) were analyzed in relation to crown height, topography (slope and elevation) and solar radiation, and their interactions. Analyses showed satisfactory crown segmentation (F-Score = 0.85–0.86) and species classification (Overall accuracy = 0.86–0.99), though distinguishing spectrally similar classes remained challenging. Taller P. pinaster trees exhibited higher NDVI, while taller P. halepensis displayed higher NDVI values in dense neighborhoods and on gentle slopes. These findings highlight the potential of high-resolution UAV-based remote sensing for effective near-real-time detection and attribution of forest die-off. Future research should aim to improve algorithm accuracy and better integrate field-based validation across different forest types. Full article

In the field of structural health monitoring systems, sensors serve as the fundamental components for assessing infrastructure integrity. The rationality of their spatial configuration significantly influences the precision of structural performance assessment, the efficacy of damage detection algorithms, and the operational reliability of the system throughout its designated lifecycle. A robust optimization methodology for the placement of multi-type sensors is proposed in this study, explicitly formulated to mitigate the negative impact of sensor malfunctions during long-term operation. First, a rigorous evaluation framework for sensor placement schemes is established based on Bayesian inference and the minimization of information entropy, thereby quantifying the uncertainty inherent in parameter identification. Then, a probabilistic model of sensor failure is developed utilizing the Weibull distribution to capture time-dependent reliability characteristics, combined with a modified information entropy calculation method that mathematically assimilates these failure probabilities into the optimization objective. Finally, a heuristic search strategy is employed to achieve the robust optimal placement of multi-type sensors, efficiently navigating the complex combinatorial search space. In contrast to deterministic information entropy (DIE) methodologies, which assume ideal sensor functionality, the robust information entropy (RIE) approach comprehensively accounts for the stochastic nature of sensor failures and their impact on the information content of the monitoring network, thereby significantly augmenting the robustness and redundancy of the sensor configuration. Validations utilizing a numerical frame structure and a finite element bridge model demonstrate that the RIE method effectively integrates the sensor failure probability model to yield robust optimal placement schemes, minimizing the risk of information loss and ensuring reliable structural health monitoring throughout the engineering lifecycle. Full article

The thermal dissipation performance of the radiator is crucial for the stable operation of power electronic devices. Due to excellent thermal performance, copper pin-type heat sink substrates are widely adopted. However, the cold extrusion process for heat sink substrates suffers from low material utilization and high forming loads. To improve material utilization and reduce cold extrusion forming load, four blank shapes (rectangular, trapezoidal, trapezoidal cap, and stepped) were designed using finite-element simulation to investigate the effects of blank shape and placement method with orientation relative to the die cavity on forming quality. Further dimensional optimization was conducted to determine the optimal configuration. The results show that the stepped blank with front orientation exhibits the optimal forming performance, featuring the lowest forming load and the most sufficient pin-fin filling. Compared with back orientation, front orientation achieves higher and more uniform material flow velocity, and significantly reduces forming load. Through dimension optimization, the 7 mm-thick stepped blank is determined as the optimal solution, with the forming load reduced to 15,000 kN (a 35.3% decrease compared to the initial 7.5 mm stepped blank), and both the substrate thickness and pin-fin height meet the design requirements (4.5 mm and 6.5 mm). Experiments verify the feasibility of the optimized scheme, providing technical support for the low-cost, high-quality mass production of copper pin-type heat sink substrates. Full article

Wafer map defect classification plays a critical role in yield monitoring and root-cause analysis in semiconductor manufacturing. Although recent convolutional neural network (CNN)-based approaches have achieved high classification accuracy, most existing models are evaluated primarily on clean datasets and remain vulnerable to unseen perturbations and representation-level variability at test time. In this paper, we propose a hybrid CNN–echo state network (ESN) architecture that integrates spatial feature extraction with sequential aggregation to enhance robustness under input perturbations. The CNN backbone extracts two-dimensional feature maps, which are converted into ordered sequences using a multidirectional scanline strategy and processed by an ESN reservoir. The resulting sequential representations are combined with CNN features through a class-specific adaptive fusion mechanism. Using the defect-only eight-class version of the WM-811K dataset, we systematically evaluate robustness under multiple perturbation scenarios, with particular focus on the clean train/noisy test (CT-NT) setting. To ensure a controlled robustness evaluation aligned with the binary nature of wafer map data, we introduce binary-consistent die-flip perturbations and additionally employ additive Gaussian perturbations as a representation-level stress test. Under clean-data conditions, the proposed model showed a 0.61 pp improvement in test accuracy compared to the ResNet34-based CNN, with notably larger gains for rare classes and defect types exhibiting strong structural patterns. In the clean train/noisy test scenario, where the model was trained on clean wafer map data and evaluated under controlled test-time perturbations, the accuracy of the CNN baseline dropped to 77.59% at $\sigma$ = 0.10, whereas the proposed hybrid model maintained an accuracy of 87.30%, resulting in an absolute improvement of 9.71 pp. Per-class analysis reveals that the robustness gain is class-dependent, with pronounced improvements for defect types exhibiting clear and repetitive structural patterns, such as Loc and Edge-Ring. Further mechanistic analysis demonstrates that the robustness improvement arises from enhanced representation stability and bounded reservoir dynamics, rather than from changes in CNN feature extraction or training regularization. These results demonstrate that the proposed CNN-ESN hybrid architecture provides meaningful advantages in terms of robustness under noisy evaluation conditions without requiring noise-aware training or prior knowledge of perturbation characteristics. Full article

Nowadays, Additive Manufacturing for Electronics (AME) is gaining ground in device fabrication for the numerous advantages of these types of manufacturing technologies, such as fast production processes, freeform design, and low-cost prototyping. In this scenario, the proposed research work is focused on evaluating an innovative strategy for a common issue in power electronics, which is related to the generation of hotspots. To face this problem, the 3D printing of ceramic substrates with different high surface areas was studied to improve thermal dissipation. Together with improved thermal management, the upper surface of the devices enabled the deposition of a desired conductive pattern and the bonding of bare die components for device fabrication. Finally, thermal exchange was monitored to verify the efficacy and efficiency of the devices’ dissipation capabilities. The proposed models exhibited a 70% temperature reduction upon transitioning from air to water. Furthermore, the operating temperature remained stable for 10 min, meeting the specific requirements of the intended application. Full article

The survival and activation of both effector and regulatory CD4⁺T cells are promoted by cytokines in a complex series of interactions. Alloantigen-specific Regulatory T cells (Treg) constitutively express IL-2 receptor (CD25) and Foxp3. This discovery arose as the cells that transfer the alloantigen-specific transplant tolerance die in culture with specific alloantigens, unless the cultures are supplemented with cytokines from activated lymphocytes. One such cytokine was IL-2, but other cytokines are essential. We describe how the activation of Treg by antigens depends on cytokines produced by antigen-activated effector T cells. These cytokines also drive in parallel the activation of Treg. The Treg are induced to express similar transcription factors and chemokine receptors and have a similar cytokine responsiveness to the activated T effector cells. The activation of Treg by antigens is a two-step process: the first requires cytokines produced by effector T cells early in their activation, and the second step is driven by cytokines produced later by effector T cells during activation. Cytokines from Type 1 responses promote the induction of Th1-like Treg. Likewise, cytokines produced in Type 2, Type 3, and Tfh responses induce different pathways of Treg activation. Understanding the pathways for the activation and expansion of potent antigen-specific Treg will help produce Treg to control allograft rejection or autoimmunity. Currently, the complexity of the numerous potential pathways of activation of Treg remains incompletely understood. The dogma that IL-2 is the only driver of Treg activation may have hindered the development of highly potent antigen-specific Treg for therapy. Full article

Cold forging backward extrusion is mainly employed in the manufacturing of axisymmetric cup-like components used extensively in automotive and aerospace assemblies due to the process-induced strength that has a pivotal role in such applications. Although cold forging backward extrusion yields mechanically robust components, it demands high forces, subjecting tooling to immense stress, thereby restricting process capacity. The process encounters hindrances in gaining widespread industrial acceptance due to frequent failures of die elements, necessitating proper die design and control of major influencing factors for process viability and cost-effectiveness. The punches in backward extrusion are often susceptible to failures when processing steel billets. The punch service life is significantly affected by geometrical attributes, the type of steel undergoing deformation, and tool manufacturing aspects. Hence, the present study evaluates punch performance in cold forging backward extrusion using optimized geometrical attributes, manufactured through a design of an experimental approach comprising an L9 orthogonal array. The manufacturing factors considered are punch material, hardness, and advanced surface coating. Punches were designed for two industrial components using powder metallurgy (PM) steels—S600, S290, and S590, heat treated to 60–66 HRC, and coated via physical vapor deposition with TiN, AlTiN, and TiAlCN. Punch performance was analyzed against existing industry practices, and the strategy demonstrated improved productivity. Punch performance was determined based on the number of forgings produced before wear- and fatigue-induced failures. Significant improvements in punch performance were witnessed in both high-speed steel (HSS) and PM punches with optimized geometries. Fractographic investigations were carried out on fractured punches and analyzed, focusing on the coating’s effect on the thermal aspects of the punches. The proposed study will assist the cold-forging industry in determining appropriate variables to minimize forming responses, thereby enhancing tool life. The research also benefits industries by enhancing process robustness and improving process efficiency with respect to cost and time. Full article

Annual killifishes of the genus Nothobranchius live in seasonal water bodies in Eastern Africa. Adults die at the end of the rainy season when seasonal pools desiccate but diapaused embryos persist in the sediments and hatch in subsequent rainy seasons. Embryos use environmental cues to determine optimal hatching conditions to begin a new generation. We simulated a predation event by crushing Nothobranchius embryos and tested if embryos of N. eggersi and N. foerschi adjust time of hatching in response to these chemical cues. We placed individual diapause III embryos in cups of dechlorinated water dosed with either (1) blank water, (2) odor of crushed chironomids, or (3) odor of crushed Nothobranchius embryos. Although N. eggersi Red embryos hatched at a significantly faster rate than embryos from N. eggersi Solid blue or N. foerschi, the effect of the cue was consistent for all three types of Nothobranchius embryos used in this study. The odor of crushed Nothobranchius embryos caused a significant delay in time to hatch relative to the two control treatments. These data suggest that Nothobranchius embryos attend to chemical alarm cues derived from crushed conspecific embryos and delay hatching as a bet-hedging strategy to avoid hatching when they detect risk of predation. Full article

Raw and minimally processed berries are not subjected to any processing kill steps and are stored under cold conditions to extend shelf-life. This study evaluated the growth and survival of high and low populations of L. monocytogenes on blueberries and raspberries stored under refrigerated and frozen temperatures. Fresh berries (10 g) were inoculated with a five-strain cocktail of L. monocytogenes to target 5.5 or 2 log CFU/g, stored at 4 and −18 ± 2 °C, and enumerated for up to 14 days post inoculation (dpi) at 4 °C and 168 dpi at −18 °C. Significant differences were evaluated (p ≤ 0.05), and die-off was modeled, using Davies test to determine breakpoints. No significant changes (p > 0.05) in L. monocytogenes populations were observed over time on berries stored at 4 °C, regardless of inoculation level. At −18 °C, significant reductions were observed over 168 dpi, with greater declines for high-inoculated blueberries and raspberries (2.63 and 2.13 log CFU/g, respectively), compared to those that were low-inoculated (0.67 and 0.46 log CFU/g, respectively). Die-off modeling indicated linear decay for both low-inoculated berry types and biphasic patterns for both high-inoculated frozen blueberries and high-inoculated raspberries stored at 4 °C. Results suggest that while L. monocytogenes does not grow, blueberries and raspberries support survival during refrigerated and frozen storage, emphasizing the need for stringent pre- and postharvest practices to limit contamination. Full article

Background: Deep infiltrating endometriosis (DIE) and, in particular, bowel endometriosis stand out for their complexity. While surgery for bowel endometriosis has proven to be effective, there is a lack of standardization concerning the technique used and the reported outcomes. Objectives: The objective is to perform a review aiming to summarize the state of the art of bowel endometriosis and to point out the gaps to be addressed by future research. We also propose a novel classification of surgical procedures to fill these gaps and improve management. Methods: A literature search was performed on PubMed from inception to October 2025. Results: The following three major procedures for the excision of bowel endometriosis have been proposed: the nodule shaving, the discoid excision, and the segmental intestinal resection. One further technique, NOSE (natural orifice specimen extraction), can be applied for the removal of the specimen in cases of discoid or segmental resection. To reduce surgical morbidity, current data support the choice of most conservative surgical options, namely nodule dissection and discoid resection, as well as the use of nerve-sparing techniques in case of segmental resection. Nonetheless, there is little evidence concerning the indication and the most appropriate technique to be used, including their relative risks and benefits in terms of pain control, urinary and gastrointestinal function, risk of future relapse, and fertility outcomes. Conclusions: Significant barriers in comparing surgical outcomes due to unclear definitions, lack of standardization, and incomplete reporting are some of the most relevant issues frequently encountered. To fill these gaps, we propose a new classification system for bowel surgery that describes the dimension and the number of the lesions, as well as the type of surgical technique used, supplemented by the information if vaginal opening was necessary for complete lesion resection. This proposition aims to open a discussion on this topic and boost focused research to evaluate the utility of a new classification in clinical practice. Full article

The cerebellar cortex presents a repetitive structure, but the main projecting neurons of this tissue, the Purkinje cells, are not identical and behave differently to various types of injury. Common patterns of neurodegeneration exist, where certain Purkinje cells die earlier than others. By contrast, lobe X of the cerebellum is a particularly resistant structure, independently of the cerebellar disease or damage. However, the mechanisms underlying the survival capability of these especially resistant Purkinje cells are still unknown. In this work, we have used the Purkinje Cell Degeneration (PCD) mouse, a model of severe cerebellar degeneration that also reproduces the human disease called childhood-onset neurodegeneration with cerebellar atrophy, to study Purkinje cell resistance. After an exhaustive immunochemical analysis of the different subpopulations of Purkinje cells, the Heat Shock Protein 25 (HSP25) and its phosphorylated version HSP25-P-Ser15 were found to be especially induced in lobe X of PCD mice. As this protein has neuroprotective properties, it may be responsible for resistance against cerebellar neurodegeneration. Taking into account the constant resistance of lobe X, the use of HSP25 may lead to new possibilities for achieving natural protection both in cerebellum and in other brain structures, or even for developing future neuroprotective therapies. Full article

Cancer remains one of the most prominent global health concerns, posing a substantial threat to public health. Millions of people die from cancer each year, and many cancer types remain incurable at present. Conventional cancer treatments, including surgery, chemotherapy, radiotherapy, and immunotherapy, often fail to achieve optimal clinical outcomes and are frequently associated with severe trauma and adverse effects. Consequently, there is an urgent need to develop novel therapeutic strategies to address these limitations. Hydrogels have been widely utilised as platforms for loading drugs, proteins, DNA, and stem cells in biomedical tissue repair and cancer therapy. Through modification of their physicochemical properties and functions, hydrogels can be endowed with responsiveness to multiple stimuli. In recent years, stimuli-responsive hydrogels (also known as smart-responsive hydrogels), as novel drug delivery systems, have demonstrated remarkable efficacy in cancer treatment. Stimuli-responsive hydrogels are capable of altering their mechanical properties, swelling behaviour, hydrophilicity, bioactivity, and molecular permeability in response to endogenous stimuli (including pH, ROS, and temperature) and exogenous stimuli (including light, ultrasound, and magnetic fields). This review highlights recent advances and applications of responsive hydrogels triggered by endogenous stimuli (including pH, ROS, and temperature) and exogenous stimuli (including light, ultrasound, and magnetic force) in cancer drug delivery and treatment. Finally, the current application limitations and future prospects of smart-responsive hydrogels are summarised. Full article