17315 research outputs found
Sort by
A diameter selective fullerene-mediated supramolecular self-assembly motif for single-walled carbon nanotube enrichment
No full textPost-synthetic diameter-selective separation of nanotubular structures has relied on exohedral interactions; a diameter-dependent enrichment via endohedral interactions for the purification of bulk single-walled carbon nanotubes (SWCNTs) remains unexplored. This paper describes a novel diameter-selective supramolecular self-assembly motif for nanotube enrichment via fullerene (C60) encapsulation by SWCNTs. C60-grafted silicon wafers and silica particles were used for the diameter-selective self-assembly and enrichment/separation of individualized SWCNTs, respectively. C60 grafting to silica substrates was performed via the addition of azide-terminated silane precursors, followed by the cycloaddition of azides with C60 to azafulleroids. Atomic force microscopy was used to determine the diameter dependency of the method. The diameter-sorted SWCNTs were further characterized via ultraviolet–visible–near-infrared spectroscopy and Raman spectroscopy. The method presented here was found to select SWCNTs with diameters of approximately 1.4–1.7 nm, with a central cavity matched to the diameter of C60. Self-assembly and enrichment/separation of other nanotubular structures are anticipated with this approach
Performance feedback, performance prospects, and firm search behavior: the role of institutional settings
No full textThe Behavioral Theory of the Firm (BTOF) posits that firms undertake R&D search when their current performance falls below their aspirations, reflecting a backward-looking driver of search, or when anticipated future performance is projected to fall short of targets, representing a forward-looking driver. However, little is known about how external contingencies influence the prominence of these search drivers. Drawing on the literature on institutions, we argue that financial systems in a country, a key aspect of firms’ institutional settings, influence the salience of forward- and backward-looking drivers by shaping firms’ temporal and cognitive orientations. Specifically, we propose that while firms in market-based financial systems are more responsive to performance expectations below targets, firms in bank-based financial systems are more responsive to performance below aspirations. We further argue that the influence of financial systems depends on firms’ slack resources and equity dependence. Our analyses on a sample of 3,908 manufacturing firms from 24 countries corroborate these hypotheses, stressing the central role of institutional settings in shaping firms’ R&D search behavior
How to fight Turkey's authoritarian turn
No full textThe arrest of Istanbul’s mayor, Ekrem İmamoğlu, marks the latest turn in Turkey’s prolonged autocratization process, signaling a possible shift from competitive to the hegemonic authoritarianism of Russia and Venezuela. Recep Tayyip Erdoğan’s regime intends to consolidate more power and weaken the ever-growing opposition using partisan courts and media. However, Erdoğan’s increasingly authoritarian regime may soon reach its material and coercive limits, inhibiting Turkey’s transition to hegemonic authoritarianism. Moreover, Turkey’s strong electoral traditions, diverse society, and popular resistance mobilized by the opposition render such a transition improbable. The Turkish case thus demonstrates how structural factors and political agency, in tandem, shape the prospects of deepening autocratization and re-democratization
Nutrient limitations on photosynthesis: from individual to combinational stresses
No full textLiebig's law of the minimum states that increasing photosynthetic productivity on nutrient-impoverished soils depends on addressing the most limiting nutrient. Research has identified the roles of different mineral nutrients in photosynthetic processes. However, diffusional and biochemical regulation of photosynthesis both feature patterns of cumulative effects that jointly determine photosynthetic capacity. More importantly, responses to multiple nutrient stresses are not simply additive and require a comprehensive understanding of how these stresses interact and impact photosynthetic performance. In this review we highlight key macroelements for photosynthesis – nitrogen, phosphorus, potassium, and magnesium – focusing on their unique functions and interactions in regulating carbon fixation under multiple nutrient deficiencies, with the goal of enhancing crop productivity through balanced nutrient applications
A longitudinal study of consumer animosity: the case of the US presidential elections
No full textPurpose This study investigates the longitudinal effects of animosity towards the US following the 2020 presidential election and provides insights into how political events influence consumer animosity and willingness to buy. Design/methodology/approach This study used a survey-based within-subjects design, collecting data in the UK and France across five waves before, during, and after the 2020 US presidential election. Linear panel regressions were performed to analyze temporal changes in political animosity, product judgments, and willingness to buy US products. Findings The study found a significant decrease in consumer animosity towards the US following the 2020 election, along with increased willingness to buy US products. The triggering event intensified animosity’s effect on willingness to buy, while its effect on product judgment remained unchanged. These results highlight the malleable and contextual nature of consumer animosity and purchasing behavior. Animosity-related events are particularly influential for ethnocentric consumers. Research limitations/implications The focus on two European countries may limit the generalizability of the findings to other regions. Future research could explore the longitudinal effects of consumer animosity across diverse cultural settings and events. Practical implications This study underscores the importance of monitoring political events and associated shifts in consumer animosity. The results identify those marketing-relevant indicators that are more sensitive to animosity-relevant events (willingness to buy) and those that are less sensitive (product judgments). Social implications The study uncovers the intricate relationship between political events and consumer behavior, demonstrating how geopolitical developments can affect attitudes towards a country and its products internationally. Originality/value This study offers a longitudinal perspective that has been largely missing in the field of con-sumer animosity
Displacement monitoring and damage diagnosis of a composite suspension control arm using inverse finite element method
No full textThe intermediate link that connects the chassis of a car to the body is called the 'control arm'. This component ensures the safety of the front suspension of motor vehicles, which is why monitoring its structural condition is a must. In this study, displacement monitoring (also known as 'shape sensing') and damage detection and localization of a twist beam are performed to ensure the high structural health of automotive components during operation. For this purpose, we use a superior sensing algorithm based on sensor data, the inverse finite element method (iFEM), which can predict shape changes in real time and perform damage diagnosis in the entire structural domain. The iFEM formulation is based on the most widely used inverse element in this field, the inverse four-node shell (iQS4). First, the sensor placement model of the composite control arm is investigated by numerical iFEM/iQS4 analysis to embed the fiber Bragg grating sensors at optimal positions in the laminate. Then an experimental iFEM analysis (with physical sensor data) is performed to verify the numerical iFEM results, and a damage identification analysis is performed with the verified numerical strain data. In the final step, the numerical and experimental results are compared holistically to investigate the applicability of iFEM for vehicle components. The results of this comparison show the high precision of the real-time iFEM / iQS4 deformation reconstruction of the control arm and demonstrate the superior capabilities of damage detection and localization
Edge ideals and their asymptotic syzygies
No full textLet G be a finite simple graph, and let I(G) denote its edge ideal. In this paper, we investigate the asymptotic behavior of the syzygies of powers of edge ideals through the lens of homological shift ideals HSi(I(G)k). We introduce the notion of the ith homological strong persistence property for monomial ideals I, providing an algebraic characterization that ensures the chain of inclusions AssHSi(I)⊆AssHSi(I2)⊆AssHSi(I3)⊆⋯. We prove that edge ideals possess both the 0th and 1st homological strong persistence properties. To this end, we explicitly describe the first homological shift algebra of I(G) and show that HS1(I(G)k+1)=I(G)⋅HS1(I(G)k) for all k≥1. Finally, we conjecture that if I(G) has a linear resolution, then HSi(I(G)k) also has a linear resolution for all k≫0, and we present partial results supporting this conjecture
High-performance and ultrafast symmetric supercapacitors based on cu(II)-doped SrSnO3 perovskites
Get PDFHerein, Cu(II)-doped SrSnO3perovskites (SrSn1–xCuxO3, namely SSO:Cux) were prepared by a modified Pechini method and applied as supercapacitors (SCs) for the first time. The effect of dopant concentration (x = 1, 2.5, and 5 mol %) was investigated to fine-tune the structural and electronic properties to design potential candidates as SCs. The SSO:Cux samples were characterized by conventional XRD and synchrotron XRD (S-XRD) combined with Rietveld refinements and spectroscopic analyses, such as Raman, FTIR, UV–vis, EPR, and XANES/NEXAFS. The electrochemical performance of the SSO:Cux samples was investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic cycling with potential limitation (GCPL). It was evidenced that incorporating 2.5 mol % Cu(II) into the SrSnO3perovskite lattice (SrSn0.975Cu0.025O3, SSO:Cu2.5) led to a significant change in structural disorder and electronic properties, which play an essential role in creating a mixture of point defects such as reduced Sn3+and Cu+cations, and oxygen vacancies (VO). The SC device constructed with the SSO:Cu2.5 material showed a specific capacitance of 613 F g–1at a scan rate of 1 mV s–1, with a remarkable specific energy density and specific energy power of 25.42 W h kg–1and 32678.57 W kg–1, respectively, which are higher than those observed for any other available perovskite-based SCs. This performance was primarily attributed to the formation of mixed Sn4+/Sn3+and Cu2+/Cu+cations, which alter the structural and electronic properties of SrSnO3. Our findings indicate that an improved capability to store high energy and power may be achieved by fine-tuning the Cu(II) dopant concentration in the lattice and controlling the formation of undesired phases. This offers experimental guidance to design other Cu-doped perovskites as alternative materials for energy storage applications
Big data analytics in supply chain management: uncovering emerging trends through a bibliometric network analysis and a systematic literature review
No full textInterpretable AI in cardiology: a real-world study on myocarditis and acute coronary syndrome
No full textMachine learning models have the potential to play a significant role in the diagnosis of cardiovascular diseases. However, for these models to be clinically reliable, they must be explainable. In this study, various machine learning algorithms were applied to distinguish between myocarditis and acute coronary syndrome (ACS), and the explainability of these models was evaluated. Logistic Regression, Support Vector Machines, and Random Forest models were trained using data obtained from Turkey's largest cardiology hospital. The obtained results were analyzed through global feature importance and SHAP values to explain the decision mechanisms of the models. The study aims to enhance physicians' trust in AI-based systems by illustrating how Explainable Artificial Intelligence (XAI) techniques can be applied in medical diagnosis settings