Effective Channel Research Articles

Experimental study of fluid displacement and viscous fingering in fractured porous media: effect of viscosity ratio

Abstract Viscous fingering instability has been analyzed through empirical studies using miscible flow displacement in fractured porous media. While significant research has been conducted on viscous fingering, limited information is available regarding its behavior in fractured porous structures. The experiments were conducted in rectangular porous models with fractures oriented at $${0}^\circ $$ 0 ∘ , $${45}^\circ $$ 45 ∘ , and $${90}^\circ $$ 90 ∘ , to investigate how fracture orientation influences fluid displacement, where both channeling and fingering mechanisms play significant roles. This paper, which is the second part of a previous study, places particular emphasis on the impact of the viscosity ratio, a crucial parameter in determining the complexity of the fingering patterns. Quantitative parameters such as sweep efficiency, tip location, and breakthrough time were evaluated and analyzed using image processing techniques. The results indicate that increasing the viscosity ratio leads to more complex finger formations. Additionally, as the injection rate increases, the size of the finger patterns slightly increases, while the channeling effect becomes less pronounced. Notably, fractures aligned at $${0}^\circ $$ 0 ∘ had the most significant impact on the rate of sweep efficiency and tip location, increasing the tip velocity of the fingers by up to 90%.

Tunable 1D-2D Carbon Nanomaterials for Broadband and High-Performance Microwave Absorption via Ultrasonic Spray Ice Template.

Polymer-based one- and two-dimensional (1D-2D) carbon nanomaterials are considered promising microwave-absorbing materials (MAMs) due to their high atomic utilization efficiency and tunable microscopic/macroscopic morphology. The tunable design of 1D-2D carbon nanomaterials through a facile method to meet the requirements of advanced MAMs remains a challenge. In this work, the environmentally friendly processing method of ultrasonic spray ice template (USIT) is employed to fabricate porous carbon nanomaterials based on Kapton-type polyimide, which exhibit the intriguing morphology of both 1D nanowires and 2D nanosheets. Under subsequent carbonization at 700 and 800 °C, the obtained carbon nanomaterials inherit the original morphology. Furthermore, the 1D or 2D nanomorphology can be readily controlled by adjusting the concentration of the precursor solution. For samples fabricated with lower precursor concentrations (0.1%), 1D nanowire structures are predominant. Interconnected conductive networks and heterogeneous interfaces are formed by intertwining and stacking nanowires, thereby enhancing the conductivity loss. Additionally, the abundant porous structure provides an effective channel for electromagnetic wave entrance, significantly improving the impedance matching ability. The results show that the 1D nanowire-dominated samples (700 °C carbonization) show excellent electromagnetic microwave absorption performance. The reflection loss minimum (RLmin) is -67.2 dB at 8.1 GHz and 4.65 mm, and the maximum effective absorption bandwidth (<-10 dB) is 7.7 GHz at 3.03 mm. Exemplified by MAMs, the USIT strategy has broad prospects, providing enormous potential for various practical applications and bridging the gap between polymer precursors and 1D/2D tunable carbon nanomaterials.

Optimizing Bandwidth Allocation in Converged Networks Using Hybrid Deep Learning Model

The demand for high-speed network services and the increasing development of network traffic have led to the popularity of converged networks, which mix various services over a single infrastructure. However, because of the variety of application requirements and resource constraints, ensuring quality of service (QoS) in these networks is difficult. Conventional methods for allocating bandwidth are frequently static, reactive, and inefficient, which results in less-than-ideal network performance. We provide a unique deep learning method to optimize bandwidth allocation in convergent networks in order to overcome this. We create and use three deep learning models: Deep Q-Networks (DQN), Generative Adversarial Networks (GAN), and a special LSTM-based DQN model. We assess each model's performance using an extensive dataset. Our results show that the Novel DQN model performs better than the other models in terms of minimum packet loss, increased accuracy, decreased latency, throughput maximization, spectral efficiency optimization, bit error rate reduction, fairness assurance, and effective channel resource use. Better service quality is the outcome of these upgrades, which also significantly increase upload and download speeds. Our empirical studies demonstrate our methodology's usefulness in real-world scenarios and open the door to intelligent network management solutions that facilitate better QoS, efficient bandwidth allocation, and improved user experiences in converged networks.

Passive exposure to opioid crisis information and public attitudes: Effects on local policy support, discrimination, and stigma in a United States national survey.

To examine associations between passive exposure to opioid crisis information and public attitudes toward opioid use disorder (OUD) policies and stigma among United States (US) adults. A nationally representative survey of 6543 US adults was conducted from December 2023 to January 2024. Participants reported passive exposure to opioid crisis information from various sources. Outcome measures included preferences for national and local harm-reduction policies, discriminatory practices, carceral approaches, and OUD stigma. Multivariable regression analyses were performed, controlling for demographic factors. Over half (n=3863, 59.4%) of participants reported passive exposure to opioid crisis information. Exposure from medical professionals (b=0.143, p=0.001), family/friends (b=0.118, p=0.013), print media (b=0.135, p=0.019), and web searches (b=0.164, p=0.002) was associated with increased support for local harm-reduction policies. Social media exposure was negatively associated with support for discriminatory practices (b=-0.101, p=0.043). Exposure from medical professionals was negatively associated with OUD stigma (b=-0.090, p=0.014). No significant associations were found between information exposure and support for national harm-reduction policies or carceral approaches. Despite widespread media coverage of the opioid crisis, passive information exposure was only associated with increased support for local, not national, harm-reduction policies. The modest exposure rate (59.4%) suggests an attention gap between information availability and public engagement. The differential effectiveness of information channels suggests that communication strategies emphasizing community-level initiatives and leveraging specific sources like healthcare providers and interpersonal networks may be particularly important for building public support for evidence-based OUD prevention policies.

Particle transport and finite-size effects in Lorentz channels with finite horizons

Particle transport and finite-size effects in Lorentz channels with finite horizons

Percolation theory-based KMC simulation for scaled Fe-FET based multi-bit computing-in-memory with temperature compensation strategy

In this letter, we investigate the impact of percolation transport mechanisms on ferroelectric field effect transistor (FeFET) multi-value storage with kinetic Monte-Carlo (KMC) simulation considering aspect ratio and temperature dependencies. It is found that the portion of the ferroelectric polarization, which dominates the threshold voltage shift of the FeFET, increases when aspect ratio of device decreases. Moreover, randomness of percolation path formation and variations of equivalent conductance can be suppressed, indicating mitigation of device-to-device variations and enhancement of separation of individual states. Besides, to further investigate an amorphous channel promising in multi-bit applications, disorder effects in channel contribute to intrinsic percolation transport, coupling with multi-domain dynamics in Fe-layer, are studied by the high temperature characterization. On this basis, the KMC scheme is further modified to predict multi-value distribution from 300 K to 400 K. To tackle such critical reliability issues induced inaccuracy for in-memory computing (CIM), an efficient write-verify scheme is proposed to mitigate state overlapping and provide in-depth insights for co-design of device reliability and multi-bit CIM performances.

Comparative Study on Customer Experience in Digital Banking and Physical Banking in Sri Lanka: A Special Reference to Sri Lankan Commercial Banks

With the increasing adoption of digital banking in Sri Lanka, the convenience and accessibility of online platforms have transformed how customers manage their financial activities. However, customer experiences across digital banking channels may vary considerably from those in traditional, physical bank branches. This study aims to explore the customer experience within Sri Lankan commercial banks, focusing on both digital and physical banking channels. The key research problem involves understanding customer performances and expectations while evaluating the effectiveness of these banking channels. This research seeks to provide actionable insights for the improvement of service delivery. The study specifically investigates customer experiences in terms of perceived ease of use, efficiency, control, and security, while considering the consistency of service quality and the emotional responses of the customers. The primary objectives are to compare the customer experience in digital verses physical banking channels, and to assess the influence of demographic factors, such as age, gender, income, marital status, province, and employment sector, on the choice of banking channels. A comparative quantitative analysis was conducted, utilizing demographic factors and customer variables drawn from existing literature. Two models were developed to analyse customer preferences: one for digital banking and one for physical branch banking, with outcomes categorized as ‘indifferent’, ‘prefer digital’, or ‘prefer both’. The hypotheses were tested using probit regression analysis. The findings revealed that level of education significantly affects the performance for digital banking, with perceived control and security being critical factors influencing digital banking experiences. For physical bank branches, customer age, education level, and income were found to be significant predictors of preference. Based on the analysis, this study provides policy recommendations aimed at enhancing customer experience and satisfaction in Sri Lanka commercial banks by aligning service delivery with customer expectations across both banking platforms.

Optimal channel and feature selection for automatic prediction of functional brain age of preterm infant based on EEG

IntroductionApproximately 15 million premature infants are born each year, many of whom face risks of neurological impairments. Accurate assessment of brain maturity is crucial for timely intervention and treatment planning. Electroencephalography (EEG) is a noninvasive method commonly used for this purpose. However, using all channels and features for brain maturity assessment can lead to high computational burden and overfitting, which can decrease the performance of the prediction system.MethodsIn this study, we propose an automatic prediction framework based on EEG to predict functional brain age (FBA) for assessing brain maturity in preterm infants. To optimize channel selection, we combine Binary Particle Swarm Optimization (BPSO) with Forward Addition (FA) and Backward Elimination (BE) methods. For feature selection, we combine the Pearson Correlation Coefficient (PCC), Recursive Feature Elimination (RFE), and Support Vector Regression (SVR) model.ResultsThe proposed framework achieved a prediction accuracy of 76.71% within ±1 week and 94.52% within ±2 weeks. Effective channel and feature selection significantly improved model performance while reducing computational costs.DiscussionThese results demonstrate that optimizing channel and feature selection can enhance the performance of FBA prediction in preterm infants, offering a more efficient and accurate tool for brain maturity assessment.

Compact SPICE Model for TeraFET Resonant Detectors

This paper presents an improved compact model for TeraFETs employing a nonlinear transmission line approach to describe the non-uniform carrier density oscillations and electron inertia effects in the TeraFET channels. By calculating the equivalent components for each segment of the channel—conductance, capacitance, and inductance—based on the voltages at the segment’s nodes, our model accommodates non-uniform variations along the channel. We validate the efficacy of this approach by comparing terahertz (THz) response simulations with experimental data and MOSA1 and EKV TeraFET SPICE models, analytical theories, and Multiphysics simulations.

Straightening trajectory of hooked fibers in the fiber transport channel of rotor spinning investigated by fluid solid coupled simulation

The airflow in the transport channel contributes to the accelerated straightening of the hooked fibers, which greatly influences the structural properties of the yarn. To study the straightening process of hooked fiber in the fiber transport channel, Altair EDEM 2022 software was used to establish flexible fiber models, and combined with ANSYS Fluent 2022R1 simulation software, the fluid-solid coupling method was used to simulate the air velocity distribution in the fiber transport channel and the straightening process of the hooked fibers in the airflow field. The numerical simulated air flow is verified by Hagen-Poissuille pipe flow equation. The effects of different fiber transport channels on the straightening of various hooked fibers were discussed. The results show that the straightening effect of leading hooked fiber in the airflow field is better than that of trailing hooked fiber with significant straight. In the case of the fiber transport channel with a circular cross-section outlet, the straightening of trailing hooked fiber can be slightly enhanced. Considering the feeding position of fibers transferred from carding roller to inlet of fiber transport channel, the collision of hooked fibers with the wall influences straightening of hook part or even reduces the straightness. Through the comparision on straightness between simulated and the experimental fibers, it is verified the better straightening of leading hooked fiber in the fiber sliver in the channel. The straightening process of hooked fibers influenced by airflow field and input location of fiber transport channel are simulated, which provides a reference for optimizing fiber transport channel structure and spinning prameters.

Magnetized peristaltic flow of Sisko nanofluid under thermal radiation and double-diffusive convection with viscous dissipation and slip effects in an asymmetric channel

The phenomenon of peristalsis has gathered significant attention from researchers due to its wide-ranging applications in fields such as biological sciences, industries, and biomechanics. Its practical relevance can be observed in various processes, including blending food in the digestive tract, flow in small blood vessels and the movement of cilia. Inspired by such useful applications, this theoretical study applies an analytical model that examines the movement of magnetically induced Sisko nanofluid in an asymmetric channel considering the factors like viscous dissipation, multiple slip, thermal radiation, and double diffusive convection. The fluid flow was administered using partial differential equations (PDE’s), transformed into a set of interconnected ordinary differential equations. These non-linear equations were further numerically solved by the NDSolve function in Mathematica. According to our outcomes, the temperature profile increases as the thermal slip factor rises. Moreover, the concentration and nanoparticle profile decrease with increasing values of the concentration slip and nanoparticle slip parameters. It can also determine that when the impact of thermal radiation increases, the temperature profile drops. Such a model has practical applications in simulating the small vessel transportation of particle in hemodynamics as well as in the field of biomedical and medical engineering for nanofluid peristaltic pumps.

Community Engagement as an Engine for School Performance: The Case of Secondary Schools of Kamonyi District, Rwanda

This study investigates the effects of community engagement on school performance in secondary schools in Kamonyi District, Rwanda. The study specifically focused on evaluating the extent of parental involvement in secondary schools in Kamonyi District and its influence on academic achievement, student attendance, and teacher performance, examining the effectiveness of community communication channels in promoting school performance in secondary schools in Kamonyi District and investigating the role of local community support in enhancing school performance in secondary schools in Kamonyi District. Guided by Epstein’s Theory of Overlapping Spheres of Influence, the research explores the roles of parental involvement, community communication channels, and local community support in enhancing academic achievement, student attendance, and teacher performance. Using a correlational research design, quantitative data were collected from a sample of 530 respondents. The study utilized a total sample size of 530 respondents drawn from a target population of 2,014 individuals. A census approach was applied to head teachers and members of the school parents’ committee, each consisting of 101 individuals, ensuring full inclusion of these groups. For secondary school teachers, stratified random sampling was used to select 328 participants from a total population of 1,812. Secondary data were gathered from reports, policy documents, and other relevant records from the Ministry of Education and Kamonyi District’s Education Office and primary data were collected through structured questionnaires. After data collection, the responses from the questionnaires were coded and entered into SPSS, for analysis. Descriptive statistics were used to summarize the data, including means, frequencies, and percentages. Correlation analysis was performed to examine the relationship between community engagement and school performance. The study found a strong and statistically significant relationship between community engagement and school performance in Kamonyi District (r = 0.874, p &lt; 0.01). Parental involvement positively correlates with teacher performance (r = 0.803, p &lt; 0.01) and student attendance (r = 0.735, p &lt; 0.01), highlighting its role in enhancing teaching effectiveness and student presence. Effective community communication also improves student attendance (r = 0.757, p &lt; 0.01) and teacher performance (r = 0.816, p &lt; 0.01). Additionally, local community support shows the strongest correlation with academic achievement (r = 0.969, p &lt; 0.01) and student attendance (r = 0.818, p &lt; 0.01), emphasizing the importance of community contributions to school success. In conclusion, the study emphasizes that strong community engagement—through active parental involvement, effective communication, and local community support—significantly enhances school performance in Kamonyi District. To address the gaps identified, the study recommends that the Ministry of Education (MINEDUC) develop and implement guidelines encouraging parental involvement in school governance, decision-making, and educational activities. Strengthened policies on community engagement and investments in digital and traditional communication platforms are also essential to foster effective communication between schools and stakeholders.

Quasi-vertically asymmetric channels of graphene oxide membrane for ultrafast ion sieving

The high performance of two-dimensional (2D) channel membranes is generally achieved by preparing ultrathin or forming short channels with less tortuous transport through self-assembly of small flakes, demonstrating potential for highly efficient water desalination and purification, gas and ion separation, and organic solvent waste treatment. Here, we report the construction of vertical channels in graphene oxide (GO) membrane based on a substrate template with asymmetric pores. The membranes achieved water permeance of 2647 L m−2 h−1 bar−1 while still maintaining an ultrahigh rejection rate of 99.9% for heavy metal ions, which is superior to the state-of-the-art 2D membranes reported. Furthermore, the membranes exhibited excellent stability during long-term filtration experiments for at least 48 h, as well as resistance to ultrasonic treatment for over 100 minutes. The vertical channels possess very short pathway for almost direct water transport and a highly effective channel area, meanwhile the asymmetric porous template enhances the packing of the inserted GO nanosheets to avoid the swelling effect of membrane. Our work provides a simple way to fabricate vertical channels of 2D nanofiltration membranes with high water purification performance.

Ultranarrow Semiconductor WS2 Nanoribbon Field-Effect Transistors.

Semiconducting transition metal dichalcogenides (TMDs) have attracted significant attention for their potential to develop high-performance, energy-efficient, and nanoscale electronic devices. Despite notable advancements in scaling down the gate and channel length of TMD field-effect transistors (FETs), the fabrication of sub-30 nm narrow channels and devices with atomic-scale edge control still poses challenges. Here, we demonstrate a crystallography-controlled nanostructuring technique to fabricate ultranarrow tungsten disulfide (WS2) nanoribbons as small as sub-10 nm in width. The WS2 nanoribbon junctions having different widths display diodic current-voltage characteristics, providing a way to create and tune nanoscale device properties by controlling the size of the structures. The transport properties of the nanoribbon FETs are primarily governed by narrow channel effects, where the mobility in the narrow channels is limited by edge scattering. Our findings on nanoribbon devices hold potential for developing future-generation nanometer-scale van der Waals semiconductor-based devices and circuits.

Dynamics of Contaminant Flow Through Porous Media Containing Random Adsorbers

Many porous media are mixtures of inert and reactive materials, manifesting spatio-chemical heterogeneity. We study the evolution of scalar transport in a chemically heterogeneous material that mimics a green roof soil substrate, fractionally composed of inert and reactive adsorbing particles. These adsorbing particles are equivalent to biochar within a real soil substrate. The scalar transport evolution is determined using experiments and simulations calibrated from experimental data. Experiment 1 is used to determine the equilibrium capacity and adsorption rate of two biochar types when immersed in a methylene blue solution. Breakthrough curves of a packed bed of glass beads with randomly interspersed biochar are determined in experiment 2. Simulations are then run to investigate the solute transport and adsorption dynamics at the pore-scale. An analytical model is proposed to capture the behavior of the biochar adsorption capacity, and the simulation results are compared with experiment 2. A pore-scale analysis showed that uniformly sized beds are superior in contaminant breakthrough reduction, which is related to the adsorptive surface area and the rate at which adsorption capacity is reached. Cases using the adsorption capacity model display a tight distribution of particle surface concentration at later simulation times, indicating maximum possible adsorption. The beds with dissimilar particle sizes create more channeling effects which reduce adsorptive particle efficiency and consequently higher breakthrough concentration profiles. Comparison between experiments and simulations show good agreement. Improved biochar performance can be achieved by maintaining particle size uniformity alongside high adsorption capacity and adsorption rates appropriate to the rainfall intensity.

Measurements of decay branching fractions of the Higgs boson to hadronic final states at the CEPC

Abstract The Circular Electron Positron Collider (CEPC) is a large-scale particle accelerator designed to collide electrons and positrons at high energies. One of the primary goals of the CEPC is to achieve high-precision measurements of the properties of the Higgs boson, facilitated by the large number of Higgs bosons that can be produced with significantly low contamination. The measurements of Higgs boson branching fractions into bb/cc/gg and tautau/WW*/ZZ*, where the W or Z bosons decay hadronically, are presented in the context of the CEPC experiment, assuming a scenario with 5600 fb-1 of collision data at a center-of-mass energy of 240 GeV. In this study the Higgs bosons are produced in association with a Z boson, with the Z boson decaying into a pair of muons (μ+μ-), which have high efficiency and high resolution. In order to separate all decay channels simultaneously with high accuracy, the Particle Flow Network (PFN), a graph-based machine learning model, is considered. The precise classification provided by the PFN is employed in measuring the branching fractions using the migration matrix method, which accurately corrects for detector effects in each decay channel. The statistical uncertainty of the measured branching ratio is estimated to be 0.55% in H → bb final state, and approximately 1.5%-16% in H → cc/gg/tautau/WW*/ZZ* final states. In addition, the main sources of systematic uncertainties to the measurement of the branching fractions are discussed. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Article funded by SCOAP3 and published under licence by Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Science and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd.

The Pseudo-Bilayer Bulk Heterojunction Active Layer of Polymer Solar Cells in Green Solvent with 18.48% Efficiency

Planar heterojunction (PHJ) is employed to obtain proper vertical phase separation for highly efficient polymer solar cells (PSCs). However, it heavily relies on the choice of orthogonal solvent in the production process. Here, we fabricated a pseudo-bilayer bulk heterojunction (PBHJ) PSC with cross-distribution in the vertical direction by preparing two layers of PM6 and BTP-eC9 blends in an o-XY solution with different dilution ratios to study the morphological evolution of PBHJ film. We found that the PBHJ film exhibits more uniform and suitable continuous interpenetrating network morphology and proper phase separation in the vertical direction for the formation of p-i-n structure. This provides an effective channel for exciton dissociation and charge transport, which is confirmed by both exciton generation simulations and charge dynamics measurements. The PBHJ devices can effectively inhibit trap recombination and accelerate charge separation and transfer. Based on good active layer morphology and balanced charge mobility, all-green solvent-processed PSCs with champion power conversion efficiencies (PCEs) of 18.48% and 16.83% are obtained in PM6:BTP-eC9 and PTQ10:BTP-eC9 systems, respectively. This work reveals the potential mechanism of morphological evolution induced by the PBHJ structure and provides an alternative approach for developing solution processing PSCs.

The Digital Duo: Exploring The Impact of AI Chatbots and Digital Marketing Strategies on Consumer Purchase Intentions in Pakistan’s E-Commerce Sector

The rise of e-commerce in Pakistan has stimulated businesses. It has turned to new tools like AI chatbots and digital marketing strategies for increasing consumer participation and stimulating purchasing intent. The aim of this study is to inspect the purchase intention of consumers in the e-commerce sector of Pakistan. On the other hand, the impact of the factors of AI chatbot i.e. responsiveness, usability, perceived trust, responsiveness is explained. Satisfaction illustrates the mediating role of the customer. In the study, data were gathered from 254 respondents through an online survey. Data was analyzed for assessing structural relationships within the model by utilizing SmartPLS 4. The results of the study show that AI chatbots significantly influence purchase intentions of consume with perceived trust, responsiveness, and usability being the most influential factors. Among the strategies of digital marketing, social media is considered the most effective channel for nurturing purchase intent followed by content marketing. On the contrary, marketing through emails did not show a significant impact. Customer satisfaction mediates the relationship between the factors of AI chatbot and strategies of digital marketing with purchase intent. Particularly, through perceived trust and response to AI chatbots and social media for content marketing and digital strategies, however, usage and email marketing did not show any mediation effects. This research provides effective insights for e-commerce businesses in Pakistan. It sheds light on the essentialism of leveraging AI chatbot capabilities and tailored digital marketing approaches for increase customer satisfaction and ultimately purchase intent. As the sector of e-commerce continues to expand, businesses need to focus on such critical areas to remain competitive and meet evolving demands of consumers.

Anticonvulsant Effects of Synthetic N-(3-Methoxybenzyl)oleamide and N-(3-Methoxybenzyl)linoleamide Macamides: An In Silico and In Vivo Study.

Epilepsy is a chronic neurological disorder that affects nearly 50 million people worldwide. Experimental evidence suggests that epileptic neurons are linked to the endocannabinoid system and that inhibition of the FAAH enzyme could have neuroprotective effects by increasing the levels of endogenous endocannabinoid anandamide. In this context, the use of macamides as therapeutic agents in neurological diseases has increased in recent years. With a similar structure to anandamide, several theories point to the FAAH-macamide interaction as a possible cause of FAAH enzymatic inhibition. In this work, we used in silico and in vivo techniques to analyze the potential therapeutic effect of three synthetic macamides in the treatment of epilepsy: N-3-methoxybenzyl-oleamide (3-MBO), N-3-methoxybenzyl-linoleamide (3-MBL), and N-3-methoxybenzyl-linolenamide (3-MBN). In the first stage, an in silico analysis was conducted to explore the energetic affinity of these macamides with rFAAH and their potential inhibitory effect. MD simulations, molecular docking, and MM/PBSA calculations were used for these purposes. Based on our results, we selected the two best macamides and performed an in vivo study to analyze their therapeutic effect in male Sprague Dawley rat models. Rats were subjected to an in vivo induction of epileptic status by the intraperitoneal injection of pilocarpine and analyzed according to the Racine scale. In silico results showed an energetic affinity of three macamides and a possible "plugging" effect of the membrane access channel to the active site as a potential cause of FAAH inhibition. On the other hand, the in vivo results showed an anticonvulsant effect of both macamides, with 3-MBL being the most active, resulting in a higher survival probability in the rats. This work represents one of the first studies on the use of macamides for the treatment of epilepsy.

The Effects of International Technology Spillover Channels on Innovation Performance: An Application on Turkish Manufacturing Industry

Abstract The increasing pressure of competition in a globalizing world forces the countries to strengthen their market shares in order to grow rapidly. This requires to have technological innovation, and scientific knowledge, as the primary sources. Hence, the main aim of this study is to investigate the effects of international technology spillover channels on the innovation performance of firms operating in the Turkish manufacturing industry. For the aim of the study, the System Generalized Moments Method (SGMM) was used for the estimation of the models. Micro data of the 311 firms covering the period of 2011–2015 were obtained from the Turkish Statistical Institute (TURKSTAT). The results of the study show that domestic R&amp;D stock and especially technology absorptive capacity have significant and strong positive effects on the new product sales of the firms. Also, the findings indicate that the international technology spillover channels which have the most important impact on the innovation performance is foreign direct investments (FDI), and this is followed by the export channel. Depending on the conditional values of technology absorptive capacity in the manufacturing industry, the marginal effects of international technology spillover channels on new product sales differ. As a matter of the fact, when the share of technology absorptive capacity increases, the marginal effects of FDI on new product sales decrease, while the marginal effects of export and technology transfer expenditures increase. As a result, the government should increase the sales of new products of firms by encouraging domestic R&amp;D activities and FDI, thus laying the groundwork for the high and stable economic growth rates.