Search Results (351)

We investigate whether a belief in trend continuation, often associated with the so-called “hot-hand effect,” can be endogenously triggered by personal performance feedback in a controlled financial experiment. Participants allocated funds across assets with randomly generated prices, under conditions of known probabilities and varying levels of risk. In a two-stage setup, participants were first exposed to random price sequences to learn the task and potentially develop perceptions of personal success. They then faced additional price paths under incentivized conditions. Our findings show that participants initially increased purchases following gains—consistent with a feedback-driven belief in momentum—but this pattern faded over time. When facing sustained losses, loss aversion dominated decision-making, overriding early optimism. These results highlight how cognitive heuristics and emotional biases interact dynamically, suggesting that belief in trend continuation is context-sensitive and constrained by the reluctance to realize losses. Full article

The Mediterranean region, identified by scientists as a ‘climate hot spot’, is experiencing warmer and drier conditions, along with an increase in the intensity and frequency of extreme weather events. One such extreme phenomena is droughts. The recent wildfires in this region are a concerning consequence of this phenomenon, causing severe environmental damage and transforming natural landscapes. However, droughts involve a two-way interaction: On the one hand, climate change and various human activities, such as urbanization and deforestation, influence the development and severity of droughts. On the other hand, droughts have a significant impact on various sectors, including ecology, agriculture, and the local economy. This study investigates drought dynamics in four Mediterranean countries, Greece, France, Italy, and Spain, each of which has experienced severe wildfire events in recent years. Using satellite-based Earth observation data, we monitored drought conditions across these regions over a five-year period that includes the dates of major wildfires. To support this analysis, we derived and assessed key indices: the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI). High-resolution satellite imagery processed within the Google Earth Engine (GEE) platform enabled the spatial and temporal analysis of these indicators. Our findings reveal that, in all four study areas, peak drought conditions, as reflected in elevated NDDI values, were observed in the months leading up to wildfire outbreaks. This pattern underscores the potential of satellite-derived indices for identifying regional drought patterns and providing early signals of heightened fire risk. The application of GEE offered significant advantages, as it allows efficient handling of long-term and large-scale datasets and facilitates comprehensive spatial analysis. Our methodological framework contributes to a deeper understanding of regional drought variability and its links to extreme events; thus, it could be a valuable tool for supporting the development of adaptive management strategies. Ultimately, such approaches are vital for enhancing resilience, guiding water resource planning, and implementing early warning systems in fire-prone Mediterranean landscapes. Full article

With their superior switching speed, GaN high-electron-mobility transistors (HEMTs) enable high power density, reduce energy losses, and increase power efficiency in a wide range of applications, such as power electronics, due to their high breakdown voltage. GaN-HEMT devices are subject to long-term reliability due to the self-heating effect and lattice mismatch between the SiC substrate and the GaN. Depletion-mode GaN HEMTs are utilized for radio frequency applications, and this work investigates three wide-bandgap (WBG) GaN HEMT fixed-frequency oscillators with output buffers. The first GaN-on-SiC HEMT oscillator consists of an HEMT amplifier with an LC feedback network. With the supply voltage of 0.8 V, the single-ended GaN oscillator can generate a signal at 8.85 GHz, and it also supplies output power of 2.4 dBm with a buffer supply of 3.0 V. At 1 MHz frequency offset from the carrier, the phase noise is −124.8 dBc/Hz, and the figure of merit (FOM) of the oscillator is −199.8 dBc/Hz. After the previous study, the hot-carrier stressed RF performance of the GaN oscillator is studied, and the oscillator was subject to a drain supply of 8 V for a stressing step time equal to 30 min and measured at the supply voltage of 0.8 V after the step operation for performance benchmark. Stress study indicates the power oscillator with buffer is a good structure for a reliable structure by operating the oscillator core at low supply and the buffer at high supply. The second balanced oscillator can generate a differential signal. The feedback filter consists of a left-handed transmission-line LC network by cascading three unit cells. At a 1 MHz frequency offset from the carrier of 3.818 GHz, the phase noise is −131.73 dBc/Hz, and the FOM of the 2nd oscillator is −188.4 dBc/Hz. High supply voltage operation shows phase noise degradation. The third GaN cross-coupled VCO uses 8-shaped inductors. The VCO uses a pair of drain inductors to improve the Q-factor of the LC tank, and it uses 8-shaped inductors for magnetic coupling noise suppression. At the VCO-core supply of 1.3 V and high buffer supply, the FOM at 6.397 GHz is −190.09 dBc/Hz. This work enhances the design techniques for reliable GaN HEMT oscillators and knowledge to design high-performance circuits. Full article

Thermomechanical processing has a significant impact on the porosity and mechanical properties of AISI 316L stainless steel produced by laser powder bed fusion (L-PBF). This work evaluated the effect of three heat treatment conditions: as-built (HT0), annealed at 650 °C for 3 h with air cooling (HT1), and annealed at 1050 °C for 1 h followed by water quenching (HT2), combined with cold and hot rolling at different strain levels. The most pronounced improvement was observed after 20% hot rolling followed by water quenching (HR + WQ), which reduced porosity to 0.05% and yielded the most spherical pores, with a circularity factor ($f_{circle}$) of 0.90 and an aspect ratio (AsR) of 1.57. At elevated temperatures, the matrix becomes more pliable, which promotes pore closure and helps reduce stress concentrations. On the other hand, applying heat treatment without causing deformation resulted in the pores growing and increasing porosity in the build direction. The fractography supported these findings, showing a transition from brittle to more ductile fracture surfaces. Heat treatment combined with plastic deformation effectively reduced internal defects and improved both structural integrity and strength. Full article

The rapid progress in additive manufacturing (AM) has unlocked significant possibilities for producing 316/316L stainless steel components, particularly in industries requiring high precision, enhanced mechanical properties, and intricate geometries. However, the widespread adoption of AM—specifically Directed energy deposition (DED), selective laser melting (SLM), and electron beam melting (EBM) remains challenged by inherent process-related defects such as residual stresses, porosity, anisotropy, and surface roughness. This review critically examines these AM techniques, focusing on optimizing key manufacturing parameters, mitigating defects, and implementing effective post-processing treatments. This review highlights how process parameters including laser power, energy density, scanning strategy, layer thickness, build orientation, and preheating conditions directly affect microstructural evolution, mechanical properties, and defect formation in AM-fabricated 316/316L stainless steel. Comparative analysis reveals that SLM excels in achieving refined microstructures and high precision, although it is prone to residual stress accumulation and porosity. DED, on the other hand, offers flexibility for large-scale manufacturing but struggles with surface finish and mechanical property consistency. EBM effectively reduces thermal-induced residual stresses due to its sustained high preheating temperatures (typically maintained between 700 °C and 850 °C throughout the build process) and vacuum environment, but it faces limitations related to resolution, cost-effectiveness, and material applicability. Additionally, this review aligns AM techniques with specific defect reduction strategies, emphasizing the importance of post-processing methods such as heat treatment and hot isostatic pressing (HIP). These approaches enhance structural integrity by refining microstructure, reducing residual stresses, and minimizing porosity. By providing a comprehensive framework that connects AM techniques optimization strategies, this review serves as a valuable resource for academic and industry professionals. It underscores the necessity of process standardization and real-time monitoring to improve the reliability and consistency of AM-produced 316/316L stainless steel components. A targeted approach to these challenges will be crucial in advancing AM technologies to meet the stringent performance requirements of various high-value industrial applications. Full article

Objectives: The aims of the presented study were to investigate and compare the effectiveness of Low-Level Laser Therapy (LLLT) and therapeutic ultrasound (US) on pain, function, emotional status, and sleep disturbances in patients with rotator cuff tendinopathy (RCT). Method: A total of 84 patients with RCT were included in the study and randomly divided into the US group (n = 42) and the LLLT group (n = 42). Hot-pack, transcutaneous electrical nerve stimulation, and a home-based exercise program were also administered to patients in each group. The patients were evaluated at baseline, and at 1st, 4th, and 12th weeks after treatment by Visual Analog Scale (VAS), Shoulder Pain and Disability Index (SPADI), Constant Murley Score (CMS), Disabilities of the Arm, Shoulder, and Hand Questionnaire (DASH), Hand Grip Strength (HGS), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Pittsburgh Sleep Quality Index (PSQI), and Short Form-36 (SF-36). Results: Significant improvements in VAS, SPADI, CMS, DASH, BDI, BAI, PSQI, and SF-36 scores were observed over time in both groups (p < 0.05 for all). The improvements in HGS scores were significantly greater in the US group compared to the LLLT group (p < 0.05 for all). There were no statistically significant differences between the groups in VAS, SPADI, CMS, DASH, BDI, BAI, PSQI, and SF-36 scores at each time point (p > 0.05 for all). Conclusions: Both therapeutic US and LLLT are effective and safe in the treatment of patients with RCT. However, our findings indicate no superiority of one treatment over the other in terms of pain relief or improvements in function, emotional status, sleep disturbances, or quality of life. Full article

In this paper, we present a stance detection model grounded in multi-task learning, specifically designed to address the intricate challenge of text stance analysis within social media comments. This model is structured with an embedding network, an encoder module, a sophisticated multi-task attention mechanism, an ensemble module, and a classification output layer. To augment the performance of stance detection, we employed sentiment analysis and toxicity language detection as auxiliary tasks. The sentiment analysis plays a pivotal role in enabling the model to capture the public opinion inclinations of both individual and collective users. By delving into these inclinations, our model can extract fine-grained stance elements, offering a more nuanced understanding of users’ positions. On the other hand, toxicity language detection aids in modeling the extreme tendencies of social media users towards specific events. It identifies manifestations of hatred, offensiveness, discrimination, and insult, thereby allowing the model to reconstruct users’ genuine stance information from these extreme expressions. Through the synergy of multi-task joint learning, the accuracy and reliability of the stance detection were significantly improved. To validate the efficacy of our proposed model, we selected two hot events as representative cases, one from the Chinese Weibo platform and the other from the English Twitter platform. A series of comprehensive tasks, including developing crawler programs, collecting data, performing data preprocessing, and conducting data annotation, were systematically executed. Subsequently, we applied our model to detect the stances within the comments related to these two events, categorizing them into three classes: support, opposition, and ambiguity. The experimental results demonstrate that our stance detection model, which integrates sentiment analysis and toxicity language detection, substantially improves the detection accuracy, outperforming traditional methods. Full article

The growing volume of plastic waste from end-of-life vehicles presents environmental concerns, driving efforts to integrate recycled plastics. This study investigates the possibility of using recycled plastic from automotive parts (painted and unpainted bumpers, fuel tanks) as a 10% filler in the core layer of three-layer particleboards (P) and evaluates its impact on physical properties (water absorption—WA and thickness swelling—TS), mechanical properties (internal bonding strength—IB, modulus of rupture—MOR, modulus of elasticity—MOE and screw driving torque—SDT) and volatile organic compounds—VOC emissions. The boards were produced using conventional hot-pressing technology and analyzed according to applicable standards. Based on the results, the density of the reference (P) was 0.72 g·cm⁻³, while wood–plastic composites ranged from 0.70 g·cm⁻³ to 0.72 g·cm⁻³. After 24 h, WA reached 40% for reference (P) and from 36.9% (for (P) containing unpainted bumpers) to 41.9% (for (P) containing fuel tanks). TS reached 18% for (P) and from 16.8% (for (P) containing unpainted bumpers and fuel tanks) to 18.1% (for (P) containing painted bumpers). Plastic is a hydrophobic material and it is assumed that by increasing the proportion of plastic filler in the particleboards, the WA and TS of prepared boards will decrease. From the point of view of mechanical properties, values for (P) containing plastic filler were slightly lower compared to reference (P). The lowest value of IB (0.39 MPa) were reached for (P) containing painted bumpers. Plastic surface treatment could interfere with adhesion between the plastic and adhesive, weakening the bond in the core layer. For this reason, is preferable to use unpainted fillers, which provide better adhesive properties and higher structural integrity. VOC emissions from wood components consisted primarily of monoterpenes such as α-pinene, 3-carene and limonene. Adding 10% plastic to the particleboard did not increase overall VOC emissions. On the other hand, combining wood and plastic particles resulted in a reduction in overall VOC emissions. The findings confirm that recycled automotive plastics can be effectively incorporated into particleboards, maintaining standard performance while reducing reliance on virgin wood materials, making them a viable and sustainable alternative for furniture and interior applications. Full article

This study investigates the germination ecology of three Lepidium species, including the invasive, indehiscent-fruited Lepidium appelianum and Lepidium draba, and the invasive, dehiscent-fruited Lepidium campestre. The ability of Lepidium species to germinate under a wide range of temperature conditions is significant for understanding their potential invasiveness and establishment in novel and extreme environments. This study aims to clarify the germination behavior of L. appelianum, L. draba, and L. campestre, thereby enhancing our understanding of their invasive potential and ecological implications in the context of a changing climate. The base (Tb), optimum (To), and maximum temperatures for 50% germination (Tc(50)) were determined across a broad thermal gradient following standard protocols. Freshly harvested seeds and fruits of L. appelianum are non-dormant. In contrast, L. draba exhibit pericarp-mediated chemical dormancy, while L. campestre demonstrates physiological dormancy, which is released through after-ripening. The results indicate that L. appelianum and L. draba seeds and fruits germinate at a base temperature (Tb) of 1 °C and 4 °C, respectively. On the other hand, L. campestre seeds germinate at a Tb of 5.8 °C. The optimum temperature (To) for the germination of seeds and fruits in L. appelianum and L. draba ranges from 23 °C to 25 °C, while the To for L. campestre seed germination is 16 °C to 18 °C. Additionally, the maximum temperature for 50% germination (Tc(50)) for L. appelianum fruits is 39.8 °C, for L. draba it is 34.4 °C, and L. campestre reports a (Tc(50)) ranging from 27.4 °C to 33.3 °C for freshly harvested and after-ripened seeds, respectively. These results demonstrated that L. appelianum and L. draba can germinate across a broad temperature range, from very cold to very hot, unlike L. campestre. These findings suggest that the unique reproductive strategy of indehiscent fruits, coupled with a wide thermal germination niche, may contribute to the invasive success of L. appelianum and L. draba. Given the projected climate warming, the results highlight the potential for increased invasiveness of these species and suggest the need for targeted management strategies. Full article

Semi-continuous casting is an important method for the large-scale production of high-strength conductive copper-iron (Cu-Fe) alloys in the future. However, serious peeling defects were found on the surface of cold-rolled strips during industrial trials. Due to the multi-step complexity of the manufacturing process (from casting to final product), identifying the root cause of defect formation remains challenging. X-ray computed tomography (X-CT) was used to quantitatively characterize the pores and defects in the horizontal continuous casting Cu-Ni-Sn slab, the semi-continuous casting Cu-Fe alloy slab, and the hot-rolled slab of Cu-Fe, and the relationship between the defect characteristics and processes was analyzed. The results showed that the internal defect sphericity distribution of the Cu-Fe alloy slab after hot rolling was similar to that of the reference Cu-Ni-Sn slab. The main difference lies in the low sphericity range (<0.4). The volume of pore defects inside the Cu-Fe alloy after hot rolling was significantly larger than in the reference sample, with a 52-fold volume difference. This phenomenon may be the source of surface-peeling defects in the subsequent cold-rolling process. The occurrence of internal defects in the Cu-Fe alloy is related to both the composition characteristics and casting processes of the Cu-Fe alloy; on the other hand, it is also related to the hot-rolling process. Full article

Fiber-reinforced polymer composites are exposed to severe environmental conditions throughout their intended lifespan. It is essential to investigate how they age when exposed to cold and hot water to increase the durability of fiber-reinforced polymer composites. This work uses a hand lay-up process to create composites with different weight percentages of glass fiber, nanoclay, and epoxy. ASTM guidelines are followed for performing tensile and flexural tests. The input parameters, varying wt.% of glass fiber and nanoclay, are continuous, and the aging condition is deemed a categorical factor. The mechanical properties are considered as response variables (output). The mechanical properties are optimized using Response Surface Methodology (RSM), while Artificial Neural Networks (ANNs) provide a reliable predictive model with high correlation coefficients. The findings demonstrate that ANNs outperform RSM in flexural strength prediction, whereas RSM offers greater accuracy for tensile strength modeling. SEM analysis of the fracture surfaces reveals the causes of specimen failure under tensile load, with distinct differences between dry, cold, and boiling water-soaked specimens. Full article

Changes in grassland vegetation coverage (GVC) and their causes in the China–Mongolia–Russia Economic Corridor (CMREC) region have been a hot button issue regarding the ecological environment and sustainable development. In this paper, multi-source remote sensing (RS) data were used to obtain GVC from 2000 to 2023 based on random forest (RF) regression inversion. The nonlinear characteristics such as the number of mutations, magnitude of mutations, and time of mutations were detected and analyzed using the BFAST model. Driving factors such as climatic factors were introduced to quantitatively explain the driving mechanism of GVC changes. The results showed that: (1) RF model is the optimal model for the inversion of GVC in this region. The R² of the RF training set reached 0.94, the RMSE of the test set was 12.86%, the correlation coefficient between the predicted and actual values was 0.76, and the CVRMSE was 18.07%. (2) During the period of 2000–2023, the number of mutations in GVC ranged from 0 to 5, and there were at least 1 mutation in 58.83% of the study area. The years with the largest proportion of mutations was 2010, followed by 2016, accounting for 14.57% and 11.60% of all mutations, respectively. The month with the highest percentage of mutations was October, and followed by June, accounting for 31.73% and 22.19% of all mutations, respectively. (3) The sustained and stable positive effect was shown by precipitation on GVC before and after the maximum mutation. Wind speed was a negative effect on GVC in areas with more severe desertification, such as Inner Mongolia, China and parts of Mongolia. On the other hand, GVC was reduced by the wind speed before and after the maximum mutations. Therefore, to guarantee the ecological security of the CMREC, governments should formulate new countermeasures to prevent desertification in the region according to the laws of nature and strengthen international cooperation. Full article

The groove parameters on the friction base of wet clutches significantly affect the temperature distribution of the steel plates. However, existing methods have not thoroughly investigated the mechanisms by which these parameters influence the thermoelastic instability of wet clutches. To address this gap, a comprehensive co-simulation model of the friction sub-multi-physical field was developed to systematically examine the effects of groove inclination, groove density, and groove depth on the surface temperature and mechanical response of the steel plates. The results indicate that both the tilt angle of the grooves and the number of grooves substantially influence the surface temperature distribution of the steel plates. Specifically, increasing the number of grooves leads to a more concentrated distribution of high-temperature hot spots in the circumferential direction, gradually transitioning the surface temperature–hot spot pattern from isolated hot spots to a more uniform high-temperature tropical distribution, which subsequently reduces the maximum surface temperature. On the other hand, increasing the groove inclination angle causes the high-temperature distribution to shift from localized hot spots to a more tropical pattern, with a relatively minor impact on the peak surface temperature. Furthermore, increasing the groove depth results in the dispersion of the high-temperature tropical zone in the circumferential direction, causing the maximum temperature to initially decrease and then increase. Full article

Integrating local, bio-sourced materials, such as earth and agricultural waste like dwarf hulls, is a sustainable solution to the challenges of climate change and increasing urbanization. The use of bio-based materials such as néré husk (Parkia biglobosa) in the manufacture of compressed earth bricks is a sustainable alternative for improving their thermal performance. This study assesses the impact of adding hulls in different forms (fine powder < 0.08 mm, aggregates from 2 mm to 5 mm, and aqueous maceration) on the thermal conductivity and effusivity of bricks. The tests were carried out using the asymmetric hot plane method, applying a constant heat flux and measuring the temperature variation via a thermocouple. Three samples of each formulation were analyzed to ensure the reliability of the results. The results show that the addition of fine powdered husk reduces the thermal conductivity of the bricks to 0.404 W/m.K and their effusivity to 922.2 W/(Km²) s¹/², compared with 0.557 W/m.K and 1000.32 W/(Km²) s¹/² for the control bricks. The addition of coarser aggregates (2 mm–5 mm) gives intermediate values (0.467 W/m.K and 907.99 W/(Km²) s¹/²). Aqueous maceration, on the other hand, results in an increase in thermal conductivity to 0.614 W/m.K. These results confirm that the shape and method of incorporation of the husk influence the thermal performance of the bricks, with fine powder offering the best thermal insulation. This approach highlights the potential of bio-based materials for eco-responsible construction. Full article

Carbon emissions are currently a hot topic in the international community. CO₂ reduction from heavy-duty commercial vehicles plays a significant role in slowing down the global greenhouse effect and promoting sustainable development. To control carbon emissions, many countries have tightened CO₂ emission regulations and policy requirements for heavy-duty commercial vehicles in recent years. Various CO₂ emission simulation models have been developed, such as the Greenhouse Gas Emissions Model (GEM) in the United States and the Vehicle Energy Consumption Calculation Tool (VECTO) in the European Union, to evaluate the real CO₂ emission levels of commercial vehicles and provide a scientific basis for formulating corresponding emission reduction policies and control measures. This paper systematically analyzes the CO₂ emission regulations and policy requirements for heavy-duty commercial vehicles in the United States, the European Union, China, and other developed countries. It also analyzes the GEM software in the United States, the VECTO software used in Europe, and the energy consumption simulation software for commercial vehicles in China. The influencing factors of CO₂ emission simulation are explored in detail. This study found that, although GEM and VECTO software are recognized for their high accuracy, their applications are still dependent on local policies. In other countries and regions, VECTO software has broader applicability. On the other hand, China’s commercial vehicle energy consumption simulation software and other reported studies have only been validated for specific vehicle types. The accuracy and generalizability of these models should be further promoted and verified. Full article