Search

The melting of Antarctic glaciers has become a significant issue as a result of global climate change. Algae on the Antarctic ice/snow is an important part of terrestrial photosynthetic organisms. Monitoring and tracking these algal blooms is crucial for understanding the melting of glaciers in the region. Due to the climatic and natural conditions of the region, traveling to and arranging logistics for monitoring and observing snow algae in the Antarctic continent becomes extremely challenging. To overcome these challenges, a novel algorithm has been developed and designed to automatically detect and analyze green algae (Chlorella sp.) from satellite images. Leveraging the vast and free available data from the Sentinel-2 satellite, the algorithm utilizes its high spectral resolution capabilities, capturing invaluable information from various spectral bands. The algorithm was formulated based on the image obtained on February 28, 2017, where green algae formations were intensively seen in the Ryder Bay. The algorithm was developed based on rule-based detection of algae, with the usage of reflection values from the areas where ground truth was established on this date. The developed algorithm was coded and tested using Python version 3.9. The accuracy analysis of the algorithm was conducted using overall accuracy (OA), F1 score, and Kappa statistical test. As a result of the analysis, the OA, F1 score, and Kappa statistic values were calculated as %91, %88.82-%95.27, and 0.901, respectively. [ABSTRACT FROM AUTHOR]

Repaglinide (RPG) belongs to the class of drugs known as meglitinides and is used for improving and maintaining glycemic control in the treatment of patients with Type 2 diabetes. RPG is a Class II drug (BCS) because of its high permeability and low water solubility. It also undergoes hepatic first-pass metabolism. The oral bioavailability of RPG is low (about 56 %) due to these drawbacks. Our aim in this study is to prepare two different nano-sized drug carrier systems containing RPG (nanoparticle: RPG-PLGA-Zein-NPs or nanoemulsion: RPG-NE) and to carry out a pharmacokinetic study for these formulations. We prepared NPs using PLGA and Zein. In addition, a single NE formulation was developed using Tween 80 and Pluronic F68 as surfactants and Labrasol as co-surfactant. The droplet size values of the blank-NE and RPG-NE formulations were found to be less than 120 nm. The mean particle sizes of blank-Zein-PLGA-NPs and RPG-Zein-PLGA-NPs were less than 260 nm. The C max and t max values of RPG-Zein-PLGA-NPs and RPG-NE (523 ± 65 ng/mL and 770 ± 91 ng/mL; 1.41 ± 0.46 h and 1.61 ± 0.37 h, respectively) were meaningfully higher than those of free RPG (280 ± 33 ng/mL; 0.72 ± 0.28 h) (p < 0.05). The AUC 0-∞ values calculated for RPG-Zein-PLGA-NPs and RPG-NE were approximately 4.04 and 5.05 times higher than that calculated for free RPG. These nanosized drug delivery systems were useful in increasing the oral bioavailability of RPG. Moreover, the NE formulation was more effective than the NP formulation in improving the oral bioavailability of RPG (p < 0.05). [Display omitted] [ABSTRACT FROM AUTHOR]

A growing number of adversaries are targeting space missions, and as such, there have been increasing academic and industrial efforts in identifying threats and risks through modelling techniques. In parallel, the research communities are collaborating to lower the entry barriers for space activities to deliver more innovative and cost-effective space missions. This evolution has been termed as New Space. However, this transformation of the space ecosystem has led to changes in the threat landscape, introducing new threat vectors and threat actors intent on compromising space systems and missions. As a result, it is expected that cyber threats could increase against space systems. Furthermore, teleoperation, a significant use case for building extraterrestrial habitats, has already been shown vulnerable in other domains as well. For example, teleoperated robots developed for remote surgery have been shown to be vulnerable to threats, such as malicious control due to an elevation-of-privilege attack. Threat modelling is a systematic and structured method to determine associated system vulnerabilities, possible attack entry points and vectors, and potential impacts on the system. In this work, we examine the efficacy of the de facto threat modelling methods such as STRIDE/DREAD in capturing highly adaptive security requirements and threats from a system-centric perspective for the teleoperation mission scenario. Understanding and protecting these hardware-software assets and their interaction in the mission is of foremost importance since security breaches threaten human safety across the broader New Space ecosystem. This research presents the limitations of existing threat modelling approaches in capturing hardware-software interaction in space systems, which is an open area for scientific enquiry. Moreover, research challenges are raised to improve the safety and security of the teleoperation mission. The output of this work can then be used to develop more appropriate threat modelling approaches to support security requirement engineering for different New Space mission scenarios. [ABSTRACT FROM AUTHOR]

High-dynamic range (HDR) video reconstruction using conventional single-exposure sensors can be achieved by temporally alternating exposures. This, in turn, requires computing exposure alignment which is difficult to achieve due to the exposure differences that notoriously creates problems for moving content, in particular, in larger saturated and dis-occluded regions. An attractive alternative are dual-exposure sensors that capture, in a single-shot, differently exposed and spatially interleaved half-frames, so that they are perfectly spatially and temporally (up to varying motion blur) aligned by construction. In this work, we demonstrate that we successfully compensate for reduced spatial resolution and aliasing in such sensors, and we improve overall the quality and dynamic range of reconstructed HDR video with respect to single-exposure sensors for a given number of alternating exposures. Specifically, we consider low, mid, and high exposures, and we propose that the mid exposure is captured for every frame, and serves as a spatial and temporal reference. We capitalize here on neural networks for denoising, deblurring, and upsampling tasks, so that effectively we obtain two clean, sharp, and full-resolution exposures for every frame, which are then complemented by warping a missing third exposure. High-quality warping is achieved by learning optical flow that merges the individual flows found for each specific exposure. Such flow merging is instrumental in handling saturated/dis-occluded image regions, while dense temporal sampling of mid exposure improves motion quality reproduction between more sparsely sampled exposures. We demonstrate that by capturing only a limited amount of sensor-specific data and a novel use of histograms, instead of common parametric noise statistics, we are able to generate synthetic training data that lead to a better denoising and deblurring quality than can be achieved by existing state-of-the-art methods. As there is not enough high-quality HDR video available, we devise a method to learn from LDR video instead. Our approach compares favorably to several strong baselines, and can boost existing HDR image and video methods when they are re-trained on our data. [Display omitted] • High Dynamic Range Video. • Denoising and Deblurring. • Noise Simulation. • Optical Flow. • High Dynamic Range Sensors. [ABSTRACT FROM AUTHOR]

While the phase angle of any of the bus voltages can be chosen as the angular reference in the state estimation formulation of positive sequence networks, the same approach does not readily extend to three-phase network state estimation problem. It is commonly assumed that there is at least one bus where the bus voltages are perfectly balanced with phase angles displaced ± 120 ° and these balanced three phase voltages are used as the three-phase reference in solving the three-phase state estimation problem. This assumption may be quite realistic in transmission networks, and for distribution networks with a strong transmission system connection. However, it might not be realistic to assume existence of a perfectly balanced reference bus in today's distribution systems with ever increasing penetration of renewable sources or for isolated operation of microgrids. In this paper, a novel state estimation formulation will be presented which facilitates correct solution irrespective of the existence of buses with perfectly balanced voltages. The new formulation is general, and lends itself to bad data processing. It yields accurate results in any three-phase power system irrespective of its operating conditions (balanced or highly unbalanced), configuration (isolated microgrid, connected to transmission system, etc.) and whether or not it contains any synchronous generators. The performance of the method is validated using the IEEE 123 bus three-phase system. • Novel state estimation formulation to obtain accurate three phase angular reference. • A generalized estimation method for the highly unbalanced three phase systems. • Robust state estimation formulation against the measurement sets with bad data. [ABSTRACT FROM AUTHOR]

Light Emitting Diodes (LEDs) have emerged as a tool with great potential in the field of phytoremediation, offering a novel approach to enhance the efficiency of plant-based remediation techniques. In this work investigated the influence of LEDs on the phytoremediation of arsenic (As) and mercury (Hg) by Ceratophyllum demersum L., propagated using tissue culture methods. In addition, the biochemical properties of the plants exposed to metal toxicity were examined. Phytoremediation experiments employed concentrations of As (0.01–1.0 mg/L) and Hg (0.002–0.2 mg/L), with application periods set at 1, 7, 14, and 21 days. In addition to white, red and blue LEDs, white fluorescent light was used for control purposes in the investigations. A positive correlation was observed between higher metal concentrations, extended exposure times, and increased metal accumulation in the plants. Red LED light yielded the highest level of heavy metal accumulation, while white fluorescent light resulted in the lowest accumulation level. Examination of the biochemical parameters of the plants, including photosynthetic pigment levels, protein quantities, and lipid peroxidation, revealed a pronouncedly enhanced performance in specimens subjected to red and blue LED illumination, surpassing outcomes observed in other light treatments. The findings of this study introduce innovative avenues for the effective utilization of red and blue LED lights in the realm of phytoremediation research. Thus, the interaction between LEDs, tissue culture, and the phytoremediation process could lead to synergistic effects that contribute to more effective and sustainable remediation strategies. [Display omitted] • LED lights are very effective for phytoremediation of As and Hg. • Heavy metal accumulation values of plants increase under Red and Blue LEDs. • Red LED application reduces the effects of heavy metal stress in plants. • Tissue culture is a great advantage for effective and sustainable phytoremediation. • A highly efficient remediation system can be created with LEDs and tissue culture. [ABSTRACT FROM AUTHOR]

Countries have been aiming to reduce dependence on fossil fuel energy and increase the use of clean energy. In this context, energy security has become one of the most important issues for countries, especially in light of the recent energy crisis that threatens energy security. The financial structure of the countries can be also influential in ensuring energy security. By taking higher fossil fuel energy dependence resulting in higher energy security risk (ESR) and higher financial development (FD) into consideration, the study analyzes how FD affects energy security in South Korea, which is an important case and neglected in the current literature. To do so, the study considers the ESR index as the dependent variable, uses disaggregated level FD indicators as explanatory variables, conducts a novel cross-quantilogram method to account for the quantile dependence, and uses data between 1980/Q2 and 2018/Q4. The findings reveal that (i) disaggregated level FD indicators are powerful estimators of ESR; (ii) the financial markets component has a much stronger effect on ESR than the financial institutions component; (iii) the effect of FD sub-components on ESR varies across quantiles; (vi) the predictive power of the FD indicators on ESR weakens as time (lag) passes. The study emphasizes the critical role of FD on ESR, which implies that South Korean policymakers should consider the significant effect of FD and its sub-components as well as changing structure across quantiles and time-lags in shaping policy framework to ensure energy security. Based on the outcomes, South Korea can benefit from FD to mitigate ESR and ensure economic and environmental sustainability. [Display omitted] • The study analyzes the effect of financial development on energy security risk. • The study examines South Korea case for the period 1980/Q2–2018/Q2. • The study applies the novel cross-quantilogram method. • Financial markets have a powerful effect on energy security risk. • Financial institutions have a relatively weaker effect on energy security risk. [ABSTRACT FROM AUTHOR]

Performance forecasting of aeroengines is crucial for achieving better operational efficiency, ensuring safety, reducing costs, and minimizing environmental impact in the aviation industry. It enables engineers and researchers to make informed decisions, leading to advancements in technology and the overall evolution of aviation. This study is focused on the effects of flight conditions on the performance of a turbojet, which in consequence affects the environmental aspect of operation. By investigating the relationships between aeroengine efficiency and performance indicators such as thrust, shaft speed, and exhaust gas temperature (EGT), and flight characteristics expressed in terms of environmental and operational conditions, the study seeks to elucidate these connections. The article's significance lies in its successful application of Long Short-Term Memory (LSTM) networks to predict thrust, shaft speed, and EGT variations in turbojet engines under varying flight conditions. Experimental data from a turbojet test bench is processed with deep learning, specifically LSTM recurrent neural networks that are developed based on Matrix Laboratory (MATLAB). The model inputs are free stream air speed, compressor inlet pressure, combustor inlet temperature, combustor inlet pressure, turbine inlet temperature, turbine inlet pressure, nozzle inlet pressure and fuel flow, and the outputs are thrust, shaft speed and EGT. Predicted thrust closely aligns with actual thrust values, though with minor discrepancies. Shaft speed predictions exhibit a similar trend, while EGT predictions showcase a comparable pattern with slight variations. Despite the prediction errors, a thorough evaluation of median values, box plots, and probability density functions confirms that the models effectively capture available information, though discrepancies may arise from measurement inaccuracies and initial engine conditions. These results show that it is possible to accurately predict turbojet performance using LSTM recurrent neural network. This research paves the way for enhanced aeroengine performance prediction, particularly in scenarios requiring off-board or high-performance applications. • Uses SR-30 turbojet engine data set based on the experimental process. • Evaluates the efficiency and performance of the developed models. • Describes the effects of the fuel flow and free-stream airspeed. • Focuses on the effects of flight conditions in the performance of a turbojet. • Analyzes the nexus of thrust, shaft speed, and exhaust gas temperature to flight characteristics. [ABSTRACT FROM AUTHOR]

Desig n and fabrication of biologically active cryogels using novel biopolymer(s) are still of great importance at regenerating bone defects such as traumatic bone injuries, maxillofacial surgery, osteomyelitis, and osteoporosis. Nowadays, plant mucilage, an herbal biomaterial, has been drawn attention by scientists due to their marvelous potential to fabricate 3-dimensional (3D) physical constructs for the field of regenerative medicine. Herein, a 3D cryogel from silicon-integrated quince seed mucilage (QSM) is constructed using microwave-assisted sol–gel reaction, characterized in-depth by attenuated total reflectance Fourier transform-infrared spectroscopy (ATR-FTIR), solid-state silicon cross-polarization magic-angle nuclear magnetic resonance (29Si-CP-MAS NMR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), differential scanning calorimeter (DSC), micro-mechanical testing, porosity, and swelling tests, contact angle measurements, Brunauer-Emmet-Teller and Barret-Joyner-Halenda (BET-BJH) analysis, enzymatic biodegradation test, and field emission-scanning electron microscopy-energy dispersive X-ray spectroscopy (FE-SEM-EDX) mapping. The osteobiologic capacity of the cryogels is determined using human adipose-derived mesenchymal stem cells (hAMSCs) under in vitro conditions. Osteogenic differentiation of hAMSCs on both QSM and silica-modified QSM (Si-QSM) cryogels is analyzed by histochemistry, immunohistochemistry, and quantitative-real time (q-RT) PCR techniques. The results obtained from in vitro experiments demonstrate that the upregulation of osteogenesis-related genes in Si-QSM cryogels presents a stronger and earlier development over QSM cryogels throughout the culture period, which in turn reveals the great potential of this novel Si-incorporated QSM cryogels for bone tissue engineering applications. • Mucilage was extracted in UPW via a rotary evaporator. Si-QSM was fabricated by microwave-assisted sol-gel reaction. • Cryogels were characterized by ATR-FTIR, 29Si-CP-MAS NMR, XRD, TGA, DSC, BET-BJH analyses and contact angle measurements. • Cryogels were tested with hAMSCs. To evaluate the osteogenesis, HC & IHC stainings and qRT-PCR analyses were fulfilled. • The Si-QSM cryogels upregulated osteogenesis-related genes in hAMSCs significantly more and earlier than QSM cryogels. [ABSTRACT FROM AUTHOR]

The evolutionarily conserved VPS13 family proteins have been implicated in several cellular processes. Mutations in each of the four human VPS13s cause neurodevelopmental or neurodegenerative disorders. Until recently, the molecular function of VPS13 remained elusive. Genetic, functional and structural studies have now revealed that VPS13 acts at contact sites between intracellular organelles to transport lipids by a novel mechanism: direct transfer between bilayers via a hydrophobic channel that spans its entire rod-like N-terminal half. Predicted similarities to the autophagy protein ATG2 suggested a similar role for ATG2 that has now been confirmed by structural and functional studies. Here, after a brief review of this evidence, we discuss what is known of human VPS13 proteins in physiology and disease. [ABSTRACT FROM AUTHOR]

Background: Although dendritic cell (DC)—based cancer vaccines represent a promising treatment strategy, its exploration in the clinic is hampered due to the need for Good Manufacturing Practice (GMP) facilities and associated trained staff for the generation of large numbers of DCs. The Quantum bioreactor system offered by Terumo BCT represents a hollow-fiber platform integrating GMP-compliant manufacturing steps in a closed system for automated cultivation of cellular products. In the respective established protocols, the hollow libers are coated with fibronectin and trypsin is used to harvest the final cell product, which in the case of DCs allows processing of only one tenth of an apheresis product. Materials and Results: We successfully developed a new protocol that circumvents the need for fibronectin coating and trypsin digestion, and makes the Quantum bioreactor system now suitable for generating large numbers of mature human monocyte-derived DCs (Mo-DCs) by processing a complete apheresis product at once. To achieve that, it needed a step-by-step optimization of DC-differentiation, e.g., the varying of media exchange rates and cytokine concentration until the total yield (% of input CD14+ monocytes), as well as the phenotype and functionality of mature Mo-DCs, became equivalent to those generated by our established standard production of Mo-DCs in cell culture bags. Conclusions: By using this new protocol for the Food and Drug Administration-approved Quantum system, it is now possible for the first time to process one complete apheresis to automatically generate large numbers of human Mo-DCs, making it much more feasible to exploit the potential of individualized DC-based immunotherapy. [ABSTRACT FROM AUTHOR]

The OECD community consumes excessive amounts of raw materials and materials, which leads to pollution and increases the material footprint. The material footprint is directly linked to the Sustainable Development Goals (SDGs)-8 and 12. The main reason for the material footprint is the usage of fossil fuels, and the dependence of OECD countries on fossil fuels continues to this day. By expanding renewable energy utilization due to rising energy security risk, a community can take steps to improve ecological quality and reduce its material footprint. In this context, the paper focuses to examine the impact of energy security, green innovation, economic policy stringency and income on the fossil fuel material footprint for 24 OECD countries over the period 1995–2018. To this end, the paper uses the Augmented Mean Group (AMG) method and novel Half Panel Jackknife (HPJ) causality and estimation approach. The study adds value to existing knowledge by empirically testing the determinants of fossil fuel material footprint for OECD countries for the first time using the novel HPJ approach. The results of the AMG show that increasing energy security risk index reduces the material footprint, while green innovation and economic policy stringency have no impact on environmental degradation. The environmental Kuznets curve (EKC) in the form of an inverted U and an inverted N are valid for OECD countries. The HPJ approach also illustrates that there is a causality from green innovation and energy security risk to material footprint, and innovation and risk are support footprint reduction. Based on these results, the study recommends that OECD policymakers pay attention to ensuring energy security to reduce the material footprint by expanding renewable resources and allocate more economic resources to green innovations with higher returns, considering the validity of the EKC. [Display omitted] • Applies second-generation panel data methods. • Investigates the fossil fuel material footprint for 24 OECD countries. • The EKC hypothesis holds for the fossil fuel material footprint of OECD countries. • Green innovation and energy security risk reduce fossil fuel material footprint. • Increasing risks and technological development contribute to SDGs 8 and 12. [ABSTRACT FROM AUTHOR]

Accurate and detailed maps of irrigation and drainage networks in plains are imperative for efficient water management. Conducting field surveys of these networks proves to be expensive and labor-intensive. Besides, manual extraction of this information from remote sensing data lacks the necessary speed and accuracy. While LiDAR data offers highly detailed insights into terrain morphology, extracting water channels from it is not a straightforward task. The commonly employed slope-based algorithms, primarily reliant on elevation gradients, falter in plains due to minimal height variations such as local depressions or sinks, which can lead to misinterpretations. The primary goal of this study is to automate the extraction of the network using high-resolution Digital Terrain Models (DTMs) derived from LiDAR. Though the number of parameters is limited, users have the flexibility to finely adjust hydrologically relevant and intuitive parameters based on their specific channel preferences. The algorithm commences with a curvature analysis of the surface. Random seed points are strategically chosen from locations where the local curvature is categorized as 'valley.' A cross-section of the DTM is then extracted aligned with the direction of maximum curvature. The section's morphology is thoroughly evaluated to determine its validity as a water channel section. If deemed valid, points on both sides of the thalweg point along the zero-curvature direction undergo testing. The channel is traced in both directions, as long as the cross-sections maintain their validity. Upon the cessation of tracking, new hypotheses are examined until all 'valley' type points have been exhausted. The study demonstrates that the algorithm can also calculate channel capacity or perform channel classification using the acquired channel thalweg points and cross-sections. To validate the algorithm's effectiveness, tests are conducted across three distinct areas within the Bergama Plain in Turkey. Manual markings establish the ground truth for the channels. The precision and recall values achieve 100%, with the exception of Test Area 2 (77% precision). Additionally, the outcomes surpass those of flow-based algorithm implemented in the same areas. The proposed method proves its utility in plains and remains open to further refinement and development. • Water channels are detected from high-resolution DEMs in plains. • The morphologies of cross-sections are analyzed to distinguish true channels. • A detected channel point is tracked in both directions. • The algorithm's performance is superior to that of gradient-based methods. [ABSTRACT FROM AUTHOR]

Environmental regulations have emerged as a critical policy tool for promoting environmental sustainability worldwide. However, there is a dearth of literature that investigates the impact of environmental regulations on load capacity factor in Asia-Pacific Economic Cooperation (APEC) economies. This study aims to address this gap by examining the role of renewable energy consumption, human capital, and environmental regulations in improving load capacity factor. In doing so, the paper covers 14 APEC economies; applies second generations panel data models (i.e., CUP-FM (continuously updated fully modified) as the base model and CUP-BC (continuously-updated and bias-corrected) for the robustness); and runs data between 1992 and 2018. The empirical findings present that: i) renewable energy consumption and human capital contribute to improving load capacity factor; ii) environmental regulations are not at a level to increase load capacity factor; iii) economic growth and trade openness significantly reduce load capacity factor. Considering empirical outcomes, this study suggests that APEC should tighten environmental regulations to achieve sustainable environment. In addition, this study offers important sustainable environmental policies for APEC within the framework of empirical findings. • CUP-FM and CUP-BC methods are applied over the spanning from 1992 to 2018. • Examines relationship between renewable energy, environmental regulations, and human capital with load capacity factor. • Renewable energy and human capital significantly increase the level of environmental quality. • Environmental regulations are insufficient for APEC countries. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

International initiatives, such as the Paris Climate Conference and the COP26 conference, have highlighted the role of technology in fighting environmental problems. However, it is uncertain whether technologies are beneficial in curbing carbon dioxide (CO 2) emissions. To find an answer to this question, the study focuses on four technologically advanced countries (United Kingdom, Switzerland, Norway, Denmark), considers information and communication technologies (ICT), renewable energy technologies (RRD), and economic growth in relation to environmental degradation, and tests the validity of the environmental Kuznets curve (EKC). The study applies Fourier approaches and uses data for the period 1989–2020. In this way, the study defines that (i) ICT and RRD are cointegrated with CO 2 emissions; (ii) ICT mitigates environmental degradation in the United Kingdom, Denmark, Switzerland, and Norway; (iii) RRD expenditures, however, are not effective in reducing CO 2 emissions; (iv) the EKC hypothesis is also validated for the countries studied. Thus, the study highlights the need for countries to rely on further use of ICT and income growth as effective policy instruments to mitigate CO 2 emissions rather than RRD. [Display omitted] • Investigates the impact of ICT and renewable energy R&D on CO 2 emissions. • Focuses on technologically advanced countries for the period 1989–2020. • Applies novel Fourier-based approaches. • ICT help to CO 2 reduction, but renewable R&D does not. • The EKC hypothesis is validated. [ABSTRACT FROM AUTHOR]

This study investigates the tensile behavior of ductile and brittle epoxy polymers reinforced by graphene nanoplatelets (GNPs) dispersed by various methodologies. Dispersion of GNPs into the epoxy matrix using sonication or sonication in combination with high shear mixing was investigated. Also, the effectiveness of the dispersion of GNPs into epoxy resin or hardener was assessed. Then, the effect of GNP concentration on the tensile properties of GNP/epoxy composites fabricated by three selected dispersion techniques was explored. A large number of specimens were tested under uniaxial tensile loading and the results were analyzed in terms of tensile strength, fracture elongation, and tensile modulus. Finally, scanning electron microscopy imaging was used to assess the fractured surface of the selected specimens. Results indicate that the addition of GNPs into brittle epoxy does not provide significant improvements in tensile properties. On the other hand, up to 41% increase in tensile strength and 19% increase in tensile modulus were observed for ductile epoxy with 1 wt% GNPs. However, the addition of GNPs into either brittle or ductile epoxy reduces the fracture elongation of the developed composites. • Effective dispersion of GNPs into a brittle and a ductile epoxy polymer using sonication and high shear mixing was explored. • The effect of GNP concentration on tensile properties of epoxy nanocomposites was investigated. • Dispersing GNPs into epoxy resin first 30 min sonication and then 60 min shear mixing provided better results. • Using only sonication for the dispersion of GNPs leads considerable decreases in fracture elongation. • The use of 1 wt% of GNP in ductile epoxy increases the tensile strength by 41% and tensile modulus by 19%. [ABSTRACT FROM AUTHOR]

• Multilayers of poly(2-alkyl-2-oxazoline)s with varying side chains were constructed. • Surface properties of films were affected by the chemical nature of PAOX side chain. • Multilayers released different amount of Ciprofloxacin at acidic pH and 37 °C. • Surface properties were correlated with biological properties of the films. Multilayers of poly(2-alkyl-2-oxazoline)s (PAOX) with varying side chains were constructed through layer-by-layer (LbL) self-assembly using Tannic Acid (TA). Surface morphology, stability, wettability and stimuli-responsive drug release properties of the films were correlated with antiadhesive and antibacterial properties of the multilayers. Thickness, roughness, wettability and stability of multilayers were affected by the chemical nature of PAOX side chain, phase behaviour of PAOX and the binding strength between the layers. PAOX-multilayers released remarkably different amounts of Ciprofloxacin (CIP) especially at acidic pH and 37 °C. Antibacterial activity of the films against S. aureus was in good agreement with the amounts of CIP released from multilayers. Despite the differences in the released CIP amount, PAOX-multilayers showed similar antibacterial activity against E. coli under all conditions. Multilayers with greater wettability exhibited greater resistance against Bovine Serum Albumin (BSA) adsorption and were more effective to reduce adherence of E. coli. None of the PAOX-films exhibited antiadhesiveness against S. aureus. [ABSTRACT FROM AUTHOR]

Abstract This paper presents computational analysis of the inverse Stefan type free boundary problem, where information on the boundary heat flux is missing and must be found along with the temperature and the free boundary. We pursue optimal control framework introduced in Abdulla (2013, 2016), where boundary heat flux and free boundary are components of the control vector, and optimality criteria consist of the minimization of the quadratic declinations from the available measurements of the temperature distribution at the final moment, phase transition temperature on the free boundary, and the final position of the free boundary. We develop gradient descent algorithm based on Fréchet differentiability in Hilbert–Besov spaces complemented with preconditioning or increase of regularity of the Fréchet gradient through implementation of the Riesz representation theorem. Three model examples with various levels of complexity are considered. Extensive comparative analysis through implementation of preconditioning and Tikhonov regularization, calibration of preconditioning and regularization parameters, effect of noisy data, comparison of simultaneous identification of control parameters vs. nested optimization is pursued. [ABSTRACT FROM AUTHOR]

With its strong ties to the European Union, Germany is well-positioned to assist many countries achieve sustainability goals. Therefore, the main objective of this paper is to examine how renewable energy intensity and renewable energy share improve environmental sustainability, the load capacity factor (LCF) in Germany from 1970 to 2018. To this end, the study uses the autoregressive distributed lag model, with the effects of the Kyoto Protocol included as a dummy variable. The study contributes to the literature by considering and testing for the first time the impact of renewables on the LCF in terms of intensity and share for Germany. The empirical results show that (i) economic growth lowers the LCF faster in the early stages of economic development than in later periods; therefore, the environmental Kuznets curve hypothesis is valid in Germany. (ii) A 1% upsurge in renewable energy intensity has no statistically significant effect on the LCF, while a 1% rise in the share of renewables in the total energy mix increases LCF by 0.48%. (iii) A 1% rise in urbanization reduces the LCF by 6.52%. (iv) A 1% augment in human capital enhances the LCF by 3.49%. These outcomes suggest that the German government should use human capital development and increasing the share of renewable energy as policy instruments to achieve the sustainable development goals. [Display omitted] • The EKC hypothesis is valid for Germany. • Renewable energy intensity has no influence on the load capacity factor. • A higher renewable share in the energy mix is associated with an improvement in LCF. • Human capital plays a key role in solving environmental challenges. • The urbanization process has a devastating effect on the environment. [ABSTRACT FROM AUTHOR]

In environmental economics, the load capacity factor has recently been empirically studied to demonstrate how human actions degrade the environment and how nature compensates for this damage. Therefore, the improvement of the load capacity factor by countries is a critical indicator for achieving Sustainable Development Goals. The study therefore examines the environmental effects of research and development investments in renewable and nuclear energy. In doing so, the study covers Japan; applies Fourier-based time series models (i.e., FMOLS as the base model and DOLS and CCR for the robustness); and uses data between 1974 and 2018. The estimation results present that (i) renewable energy research and development investments support the environment; (ii) economic growth and financial development degrade the environment; and (iii) nuclear energy research and development investments have no effect on the environment. Thus, the study recommends that Japan should contribute to the achievement of the Sustainable Development Goals by concentrating its research and development investments on renewable energy sources instead of nuclear energy. [Display omitted] • The study focuses on renewable and nuclear energy R&D expenditures on the LCF. • The study examines Japan for the period 1974–2018. • The study applies Fourier-based approaches. • Renewable energy R&D expenditures have an evolving effect on the environment. • Nuclear energy R&D expenditures have no significant effect on the environment. [ABSTRACT FROM AUTHOR]

Abstract The Drug often binds to more than one targets defined as polypharmacology, one application of which is drug repurposing also referred as drug repositioning or therapeutic switching. The traditional drug discovery and development is a high-priced and tedious process, thus making drug repurposing a popular alternate strategy. We proposed an integrative method based on similarity scheme that predicts approved and novel Drug targets with new disease associations. We combined PPI, biological pathways, binding site structural similarities and disease-disease similarity measures. The results showed 94% Accuracy with 0.93 Recall and 0.94 Precision measure in predicting the approved and novel targets surpassing the existing methods. All these parameters help in elucidating the unknown associations between drug and diseases for finding the new uses for old drugs. Graphical abstract Image 1 Highlights • Building a computational model to propose a drug repurposing strategy that predicts approved and novel drug disease associations. • We combined PPI, biological pathways, binding site structural similarities and disease-disease similarity measures together. • Features like binding site structural similarity was analyzed in particular. • The model showed 94% Accuracy with 0.93 Recall and 0.94 Precision measure in predicting the approved and novel targets surpassing the existing methods. [ABSTRACT FROM AUTHOR]

Abstract This paper presents results from a series of numerical modeling tests conducted with the objective of developing a computational framework for studying rock burst events. A commercially available distinct element code with its explicit time-stepping scheme is adopted for modeling the initial quasi-static and the subsequent dynamic response of rock burst in compression and shear. Ground reaction curves are introduced to discuss criteria for stability of a failure through stress analyses. Energy balance equations are analyzed for assessing the rock burst intensity by estimating radiated seismic energy once conditions of instability emerge. Two methods are discussed for estimating radiated seismic energy: tracking of the energy conversion during failure; recording the kinetic energy that is damped by mechanical damping schemes. Modeling approach and methodologies for studying compressive-type rock burst are developed and calibrated against available analytical solutions with respect to radiated seismic energy and excavation convergence. Factors participating in the intensity of rock burst in compression are examined by modeling a rectangular tabular excavation supported by a single pillar with ductile, semi-brittle, and brittle failure responses under different compressive loading. A shear-type rock burst along a strike-slip fault model is simulated and modeling approach is calibrated by checking the resulting slip distribution, radiated seismic energy, and seismic moment against analytical solutions. Factors contributing to the occurrence and intensity of shear-type rock burst are explored by simulating different slip scenarios under different loading conditions. With presented analyses, this paper provides a computational framework calibrated for studying rock burst events and, as a reference for treatment of more complex cases, shows how Young's modulus of the rock, failure stress drop, rock brittleness, and slip-weakening behaviors of faults govern the rock burst occurrence and intensity. [ABSTRACT FROM AUTHOR]

In this study, the short- and long-run dynamic relationship between per capita GDP, per capita carbon dioxide (CO 2 ) emissions, financial development, per capita total renewable energy consumption, hydropower consumption, alternative energy consumption and urbanization was investigated by using ARDL bounds testing approach, Gregory-Hansen and Hatemi-J cointegration tests for Turkey during 1974–2014. The results of three cointegration test indicated that there was a long-run relationship between these variables. The coefficients obtained from the ARDL, fully modified least squares (FMOLS) and canonical cointegrating regression (CCR) estimators showed that economic growth, financial development, and urbanization increase environmental degradation, while total renewable energy consumption, hydropower consumption, and alternative energy consumption had no effect on CO 2 emissions. The findings showed that economic growth caused the greatest increases in CO 2 emissions, followed by urbanization and financial development. However, renewable energy consumption was not at a desirable level to reduce CO 2 emissions. The study also support environmental Kuznets curve (EKC) hypothesis, which establishes an inverted U-shaped relationship between economic growth and CO 2 emissions. The turning points of per capita GDP obtained from long-run regressions were found to be around 13523–14077 US Dollars, outside the sample period. The overall results indicated that Turkey has not reached the level of per capita GDP that can reduce environmental pollution and renewable energy consumption is not a solution to reduce CO 2 emissions. [ABSTRACT FROM AUTHOR]

In this study, esterification of propionic acid with ethanol over a tungstophosphoric acid catalyst was conducted in a batch reactor and in a pervaporation membrane reactor (MR). The performance of the esterification was determined in terms of the propionic acid conversion. Effects of the reaction temperature within the range of 50 °C–70 °C, the initial molar ratio of reactants (1:1, 2:1, 3:1), and the catalyst concentration (10–20 g cat/kg reactant) on the propionic acid conversion were investigated. A poly(vinyl alcohol) membrane was prepared and used to remove the water from the reaction media simultaneously. Conversion results of the batch reactor (BR) and the MR were compared. Results showed that the conversion of the reaction was improved by using MR. As the highest conversion of 80.7% was obtained in the BR, 92.9% of acid conversion was achieved in the MR at 70 °C when the alcohol:acid molar ratio was 3:1. The conversion of the propionic acid-ethanol esterification was enhanced between the values from 15% to 27% by using MR. Activation energy of the reaction carried out in the MR was found as 39.6 kJ/mol. [ABSTRACT FROM AUTHOR]

In Photosystem II (PSII), the Mn 4 CaO 5 -cluster of the active site advances through five sequential oxidation states (S 0 to S 4 ) before water is oxidized and O 2 is generated. Here, we have studied the transition between the low spin (LS) and high spin (HS) configurations of S 2 using EPR spectroscopy, quantum chemical calculations using Density Functional Theory (DFT), and time-resolved UV-visible absorption spectroscopy. The EPR experiments show that the equilibrium between S 2 LS and S 2 HS is pH dependent, with a p K a  ≈ 8.3 ( n  ≈ 4) for the native Mn 4 CaO 5 and p K a  ≈ 7.5 ( n  ≈ 1) for Mn 4 SrO 5 . The DFT results suggest that exchanging Ca with Sr modifies the electronic structure of several titratable groups within the active site, including groups that are not direct ligands to Ca/Sr, e . g ., W1/W2, Asp61, His332 and His337. This is consistent with the complex modification of the p K a upon the Ca/Sr exchange. EPR also showed that NH 3 addition reversed the effect of high pH, NH 3 -S 2 LS being present at all pH values studied. Absorption spectroscopy indicates that NH 3 is no longer bound in the S 3 Tyr Z state, consistent with EPR data showing minor or no NH 3 -induced modification of S 3 and S 0 . In both Ca-PSII and Sr-PSII, S 2 HS was capable of advancing to S 3 at low temperature (198 K). This is an experimental demonstration that the S 2 LS is formed first and advances to S 3 via the S 2 HS state without detectable intermediates. We discuss the nature of the changes occurring in the S 2 LS to S 2 HS transition which allow the S 2 HS to S 3 transition to occur below 200 K. This work also provides a protocol for generating S 3 in concentrated samples without the need for saturating flashes. [ABSTRACT FROM AUTHOR]

• Examines the environmental impact of renewable and nuclear energy R&D expenditures. • Focuses on Germany using three environmental indicators from 1974 to 2018. • Nuclear energy-related R&D expenditures are not effective on the environment. • Renewable energy-related R&D expenditures reduce CO 2 emissions. • The EKC hypothesis is valid, whereas the LCC hypothesis is not. This study analyzes the effect of renewable energy research & development (RRD) and nuclear energy research & development (NRD) expenditures on environmental quality by considering Germany's goal of achieving carbon neutrality until 2045. Hence, the study uses various environmental indicators (carbon dioxide (CO 2) emissions, ecological footprint-EF, and load capacity factor-LCF) to investigate the effects of RRD and NRD on the environmental quality controlling also a gross domestic product (GDP) and test the validity of the environmental Kuznets curve (EKC) and recently proposed load capacity curve (LCC) hypotheses. Also, the study includes yearly data from 1974 to 2018, uses fractional frequency Fourier autoregressive distributive lag (FADL) based FMOLS approach as the main model, and applies FADL based DOLS approach and Fourier wavelet causality test for the robustness. The empirical results reveal that (i) the explanatory variables have a cointegration link with CO 2 emissions and EF; (ii) the EKC hypothesis is valid for Germany, while the LCC hypothesis is invalid; (iii) RRD expenditures are effective only in reducing CO 2 emissions; (iv) RRD and NRD expenditures have no significant effect on the EF. Considering the results, German policymakers could utilize RRD more effectively and efficiently to improve environmental quality and reduce the EF. In this way, Germany could achieve its carbon neutrality goal until the middle of the century by benefiting from RRD facilities. [ABSTRACT FROM AUTHOR]

This study evaluates the effects of military expenditures (MEX) on environmental pollution, as well as the moderating role of factors such as financial development and technological progress for 15 NATO member countries under the environmental Kuznets curve (EKC) hypothesis. Using the CS-ARDL estimator, the study analyzes the effects of MEX, income, energy consumption, financial development, and technical progress on carbon emissions spanning the period from 1991 to 2018. Additionally, interaction terms are employed to regularize the moderating effects of financial development and technical advancement. The results show that income, energy consumption, and MEX all contribute to a rise in emissions. It is also found that the financial sector does not eradicate the detrimental ramifications of MEX on the environment, but that technological progress has a moderating effect. A 1% increase in the interaction of technological progress with the military sector reduces environmental degradation by 0.36, but a 1% augment in the interaction of the financial sector with the military sector increases carbon emissions by 0.41%. For this reason, it is imperative to evaluate and revise the financing of MEX of NATO countries from an environmental perspective for sustainable development. Furthermore, as long-run income elasticity in NATO countries is lower than the short-run one, the EKC hypothesis is valid. Based on the overall findings, the study suggests that NATO allies should incorporate the benefits of income growth and technological development into their environmental policies to offset the negative effects of MEX. [Display omitted] • Employs second-generation panel data approaches for NATO countries. • Examines the moderating role of technological progress and financial development. • NATO countries damage the environment with their military expenditures. • Technological progress has an environmental moderating role in the military sector. [ABSTRACT FROM AUTHOR]

• In our approach, three primary energy absorption mechanisms are considered; in-plane tensile deformation energy, shear plugging energy and friction energy. • Since the impact is a short time duration and dynamic physical event, in order to simplify the analysis, an equation that defines the impact duration is presented. • In our approach, energy absorption due to friction is calculated with poisson effect. Composite behaviour under ballistic impact is a challenging engineering problem due to its nonlinear nature, besides the ballistic impact itself is a dynamic and complex phenomenon. This study presents a novel analytical formulation for the speed reduction of impacts of bullet-type projectiles based on in-plane tensile failure energy absorption, including a new approach representing the energy absorption due to friction. Since for low-velocity impacts, energy absorption mechanisms are drastically different from high-velocity impacts, limitation algorithms are developed to accommodate for low-velocity impact cases. The developed formulations are applied to real and virtual ballistic impact test cases to predict the residual velocities. A satisfying correlation between results is observed. [ABSTRACT FROM AUTHOR]

• The IP and OOP seismic performance of bed-joint reinforced AAC infills were evaluated through full-scale tests. • The IP drift limit of 0.005 given in several seismic codes results in major OOP performance degradation. • The use of bed-joint reinforcement significantly enhanced the OOP performance of infills. • The specimens with bed-joint reinforcement exhibited smaller residual crack widths after the IP tests. The infill walls made of Autoclaved Aerated Concrete (AAC), which is a lightweight, fire resistant and energy efficient material, provide effective insulation solutions for building types of structures and becoming more and more popular in earthquake prone regions. Although the number of experimental tests examining the seismic response of clay brick infills is extensive, the amount of prior research on infill walls built of AAC blocks is rather limited. Past research revealed that the use of bed-joint reinforcement is one of the promising solutions to improve the global seismic response of masonry walls by enhancing strength and displacement capacity. In this study, the out-of-plane (OOP) seismic performance of AAC infill walls with flat-truss and innovative cord-type bed-joint reinforcement is experimentally evaluated. Also, consideration is given to the prior in-plane (IP) damage, which was found to degrade the seismic performance of infills in OOP direction. For this purpose, three IP and four OOP, in total, seven experimental tests were performed on four full-scale AAC infill wall specimens. The test parameters were selected in such a way as to make it possible to parametrically compare the OOP performance of AAC infills with flat-truss and cord-type bed-joint reinforcements with unreinforced AAC infill walls, together with the effect of prior IP damage on the OOP response of unreinforced AAC infill walls. It was found that the use of innovative cord-type bed-joint reinforcement improved the OOP strength to a similar extent to what was obtained from the truss-type reinforced specimen. In terms of ultimate displacement and energy dissipation capacity enhancement, the specimen with cord-type reinforcement performed better. In addition, the damages formed due to IP cyclic displacement reversals up to 0.005 drift ratio, which is defined as the drift limit for buildings with brittle infill walls in certain design codes, resulted in a significant reduction in the OOP strength and stiffness properties of AAC infills. The theoretical OOP strength calculations were found to provide unconservative strength values for the IP-damaged specimens. [ABSTRACT FROM AUTHOR]

[Display omitted] • This study evaluates energy consumption options in France using dynamic ARDL. • Explores the impact of changes in disaggregated energy consumption on CO 2 emissions. • The results show that nuclear energy can be a real option for France against gas supply cuts. • The KRLS approach validates the robustness of the dynamic ARDL simulations outcomes. The study explores the influences of potential changes in energy consumption on carbon dioxide (CO 2) emissions, focusing on disaggregated energy consumption sources. In this manner, the study considers France as the leading nuclear energy-consuming country in Europe, includes yearly data between 1970 and 2021, and performs the dynamic autoregressive distributed lag (DYNARDL) model. In addition, the Kernel-based regularized least squares (KRLS) is used for robustness check. The results reveal that (i) cointegration exists between the disaggregated energy consumption indicators and CO 2 emissions; (ii) nuclear, natural gas, oil, and coal energy have a statistically significant effect on CO 2 emissions, while renewable energy is not statistically significant; (iii) nuclear power has a decreasing effect on CO 2 emissions; (iv) positive (i.e., increasing) shocks to nuclear reduce CO 2 emissions, even if they are 300 % in the case of counterfactual shocks; (v) any positive (i.e., increasing) shocks to coal have a drastically increasing effect on CO 2 emissions, even if they are 25 % in the case of counterfactual shocks; (vi) the KRLS approach confirms the robustness of the results. Thus, this study suggests that France should continue to rely on nuclear power for electricity generation and that French policymakers should reduce electricity exports to European Union countries to provide an alternative against the Russian natural gas shock by preventing a reduction in energy supply. [ABSTRACT FROM AUTHOR]

In today's world, environmental concerns are at the forefront of countries' considerations, along with economic priorities. In this context, countries face the challenge of developing and directing their investments in clean energy technologies to achieve the Sustainable Development Goals, particularly affordable and clean energy. Does the development and diffusion of clean energy technologies contribute to improving environmental quality? This study addresses this question by examining the effects of clean energy technologies on sustainable environmental quality as expressed by the load capacity factor (LCF). In this context, the study explores the United States (US), as the largest economy and one of the leading countries investing in clean energy, considering the role of human capital, urbanization, and economic growth. To this end, this paper applies the novel augmented autoregressive distributed lag (ARDL) model to annual data from 1974 to 2018. The long-term empirical results show that (i) Clean energy technologies have no effect on the LCF; (iii) human capital supports environmental quality; (iv) urbanization has an adverse effect on environmental quality; (v) increasing economic growth worsens environmental quality. Overall, the empirical results suggest that while clean energy technologies should support sustainable environmental quality, this is unfortunately not the case in the US. Therefore, the US policymakers need to take improvement actions to ensure that clean energy technologies contribute to sustainable environmental quality and that the community reaps the environmental benefits of human capital. [Display omitted] • Applies the Augmented ARDL approach with smooth structural shifts. • Tests the impact of clean energy technologies on environmental quality. • Clean energy technologies do not affect the environmental quality. • Income and urbanization reduce the load capacity factor. • Human capital improves environmental quality. [ABSTRACT FROM AUTHOR]

This is the first prospective study of a combination therapy involving a cardenolide and a MEK inhibitor for metastatic melanoma. Whereas BRAF mutant melanomas can exhibit profound responses to treatment with BRAF and MEK inhibitors, there are fewer options for BRAF wild-typemelanomas. In preclinical studies, we discovered that cardenolides synergize with MEK inhibitor to promote the regression of patient-derived xenografts irrespective of BRAF mutation status. We therefore conducted a phase 1B study of digoxin 0.25 mg and trametinib 2 mg given orally once daily in 20 patients with advanced, refractory, BRAF wild-typemelanomas. The most common adverse events were rash, diarrhea, nausea, and fatigue. The response rate was 4/20 or 20% with response durations of 2, 4, 6, and 8 months. The disease control rate (including partial responses and stable disease) was 13/20 or 65% of patients, including 5/6 or 83% of patients with NRASmutant melanomas and 8/14 or57%ofNRAS wild-typemelanomas. Patients with stable disease had disease control for 2, 2, 2, 4, 5, 6, 7, 10, and 10 months. Xenografts from four patients recapitulated the treatment responses observed in patients. Based on these pilot results, an expansion armof digoxin plusMEKinhibitor is warranted for NRAS mutant metastatic melanoma patients who are refractory or intolerant of immunotherapy. [ABSTRACT FROM AUTHOR]

A one-dimensional vertical (1DV) turbulence-closure flow model, coupled with sediment transport capabilities, is extended to incorporate graded sediment mixtures. The hydrodynamic model solves the horizontal component of the incompressible Reynolds-averaged Navier–Stokes (RANS) equations coupled with k – ω turbulence closure. The sediment transport description includes both bed and suspended load descriptions. So-called high-concentration effects (turbulence damping and hindered settling velocities) are likewise included. The sediment transport model treats the bed and suspended load individually for each grain fraction, including effects associated with increased exposure of larger particles within a mixture. The suspended sediment transport model also makes use of modified reference concentration approach, wherein reference concentrations computed individually for each fraction are translated to a common level, conveniently enabling use of a single computational grid for the simulation of suspended sediments. Parametric study shows that these two effects combine to help alleviate an otherwise systematic tendency towards over- (under-) predicted transport rates for fine (coarse) sand fractions. The sediment transport model is validated against sheet-flow experimental oscillatory tunnel measurements beneath velocity-skewed wave signals, and demonstrates similar accuracy (transport rates generally within a factor of two) for both graded and uniform sands. The model is likewise validated against an extensive data set involving sheet-flow transport beneath acceleration-skewed wave signals (limited to uniform sands). It is then utilized to study potential effects of gradation on the net transport beneath such flows. The simulations suggest that gradation effects can both increase, as well as decrease, the total transport rate, depending largely on the behavior of the fine sand fraction. The model is implemented within the Matlab environment, and is freely available upon request to the corresponding author. [ABSTRACT FROM AUTHOR]

The present study reports for the first time the preparation of poly(2-ethyl-2-oxazoline)/clay nanocomposites. The tosyl-functionalized montmorillonite clay is utilized as initiator for the living cationic ring-opening polymerization of 2-ethyl-2-oxazoline, which triggers the delamination of silicate layers in the polymer matrix and leading to nanocomposite formation. The living nature of the polymerization has been confirmed by kinetic studies. The morphology and thermal properties of nanocomposite have been evaluated using X-ray diffraction, transmission electron microscopy, differential scanning calorimeter and thermogravimetric analysis. All nanocomposite samples have a mixed exfoliated/intercalated silicate layers and an improved thermal stability compared to pure poly(2-ethyl-2-oxazoline). [ABSTRACT FROM AUTHOR]

• Examines the determinants of energy efficiency in 27 OECD countries. • Applies the novel half panel jackknife estimator. • Renewable energy and human capital improve energy efficiency. • Economic growth and CO 2 emissions lower energy efficiency. • OECD countries should give importance to renewable energies and human capital. OECD countries are aware of the need to transform the energy sector for green growth. As energy requirements are estimated to increase by 80% by 2050, humanity must develop the ability to produce more with less energy. In this regard, both economic and environmental benefits can be achieved by increasing energy efficiency, which is why it is important to study the determinants of energy efficiency. The aim of this study is to provide new insights into the link between energy efficiency and various leading factors such as GDP, industrial structure, carbon emissions, renewable energy, human capital and green innovation. To this end, the study analyzes 27 OECD countries for the period 2000 to 2019 using the novel half panel jackknife estimator and various panel data methods. The findings of the study show that renewable energy and human capital increase energy efficiency, while economic growth and carbon emissions decrease. However, industrial structure and green innovation do not have a statistically significant effect on energy efficiency. Based on the outcomes, OECD countries are recommended to promote human capital development and renewable energy rather than regulating industrial structure and increasing investment in green innovation to improve energy efficiency. [ABSTRACT FROM AUTHOR]

This study reports the particle size effects on the film formation behavior of pyrene labeled polystyrene (PS) latexes by a combination of steady state fluorescence (SSF), UV–vis (UVV) and atomic force microscopy (AFM) techniques. For this purpose, PS latex dispersions of same molecular weight but different particle size were used. Four different latex films were prepared from dispersions of 203, 320, 400 and 900 nm PS particles by drop casting at room temperature and annealed at elevated temperatures in the range of 100–250 °C for 10 min time intervals above the glass transition ( T g ) temperature of PS. Scattered light intensity (I sc ) and fluorescence intensity (I P ) from P were measured after each annealing step to monitor the stages of film formation. Evolution of transparency of latex films were monitored using photon transmission intensity, I tr . Atomic force microscopy (AFM) was used to detect variation in the physical structure of annealed films. Onset temperatures for minimum film formation (T 0 ), void closure (T v ), and healing (T h ) processes were determined. The film formation stages (void closure and interdiffusion) were modeled and related activation energies were determined. It is found that both T v and T h ) shifted to lower temperatures as PS particle size decreases. In addition, void closure (ΔH) and interdiffusion (ΔE) energy values also decreased with decreasing the particle size. These results showed that the PS particles undergo complete film formation at much lower temperatures and requiring less energy as the particle size decreases. AFM images were also verified these results produced from optical data. [ABSTRACT FROM AUTHOR]

Thrombotic episodes are far less common than bleeding complications after hematopoietic stem cell transplantation (HSCT). However, they lead to significant morbidity and mortality. These complications are classified into four groups, including venous thromboembolic events (VTE), catheter-induced thrombosis (CIT), transplant-associated thrombotic microangiopathy (TA-TMA) and sinusoidal obstruction syndrome (SOS) or veno-occlusive disease (VOD). The frequency of VTE is increased among patients undergoing HSCT due to some acquired conditions including underlying malignancy, infections, administration of myeloablative conditioning regimens and/or total body irradiation, prolonged hospitalizations leading to immobility and presence of central venous catheters. Central venous catheters provide a convenient long-term venous access during HSCT. But they may lead to VTE and related complications such as pulmonary embolism or post-thrombotic syndrome by inducing endothelial trauma and inflammation. TA-TMA is a heterogeneous, fatal disorder seen within 100 days post-transplant and presents with thrombocytopenia, hemolysis, acute renal failure, mental status changes and involvement of other organs. SOS or VOD is another life threatening complication occuring within the first 35–40 days following a myeloablative regimen and presents with painful hepatomegaly, weight gain and elevated serum bilirubin levels. In this review, we aimed to define the epidemiology, specific risk factors, prevention and management of each group of complications in view of the recent relevant literature. [ABSTRACT FROM AUTHOR]

Intense anthropogenic air, water, and soil pollution motivates researchers and this study to analyze the determinants of pollution and propose solutions to ensure environmental sustainability. By using the load capacity factor to examine the factors that determine environmental quality and by proposing the load capability curve (LCC) hypothesis, this study adds to the existing environmental literature. The load capacity factor allows for comprehensive environmental quality monitoring of environmental quality by comparing ecological footprint and biocapacity. This study evaluates the load capacity factor in relation to information and communication technology (ICT), research and development (R&D), renewable energy consumption, and income. In doing so, the study applies the cross-sectionally augmented autoregressive distributed lag estimator and the Durbin-Haussman cointegration test from 1986 to 2017 for the G7 countries. The empirical results show that renewable energy, R&D spending, and ICT positively affect environmental quality. Moreover, since there is a U-shaped relationship between environmental quality and income, this study confirms the LCC hypothesis, implying that income initially deteriorates ecological conditions but helps improve environmental quality after crossing a certain threshold. The bottom turning point is around US$ 46660–47909, where G7 countries such as Canada, Germany, Japan, and the United States have reached income levels that improve load capacity factor. Based on the overall results, G7 governments should promote economic development, disseminate renewable energy, direct R&D spending to areas of greatest benefit, and support the deployment of green ICT infrastructure as part of their environmental policies. [Display omitted] • CS-ARDL and AMG methods are used to estimate long run elasticities. • The LCC hypothesis is valid for G7 countries. • R&D spending, ICT, income and renewable energy improve environmental quality. • Canada, Germany, Japan and the United States have reached the bottom turning point. [ABSTRACT FROM AUTHOR]

In this study, Peridynamic (PD) theory is used to model mode-I delamination in unidirectional and multidirectional laminated composites. Experiments are conducted to determine mode-I fracture toughness in a unidirectional carbon-epoxy Double Cantilever Beam (DCB) specimen where the crack propagation remains on the original notch plane. The PD model of the DCB geometry is generated using an in-house pre-processor code in MATLAB and implemented in ABAQUS software. The brittle damage law in the original PD model is modified to a bilinear law to capture progressive softening. PD results are found to be in good agreement with the experimental results in terms of force–displacement curves and crack length. Next, this PD approach is applied to a multidirectional angle-ply DCB specimen. The PD model shows that delamination path jumps between the layers as the delamination grows. Force–displacement behaviour and delamination patterns obtained using PD model are compared with the corresponding experimental results from Gong et al. (2018). As a result, PD theory with bilinear softening law is found to successfully capture force–displacement relations and delamination migration in multidirectional laminated composites under mode-I loading conditions. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel family of multivariate fuzzy neural network interpolation operators activated by sigmoidal functions belonging to the new class of multivariate sigmoidal functions. To present an alternative way to the well-known shortcomings of the Hukuhara difference, we use a proper function defined on a set of fuzzy n -cell numbers. Moreover, we construct the Kantorovich variant of fuzzy NN interpolation operators, and also achieve approximation properties via L p -type metric with respect to both modulus of continuity and L p -modulus of continuity in fuzzy sense. Various special examples for the class of multivariate sigmoidal functions are presented. Also, we give some illustrative examples to demonstrate the approximation performances of all the above operators. Finally, we give a novel interpolation algorithm involving a multidimensional fuzzy inference system with applications in color image resizing and inpainting. • A novel family of multivariate fuzzy neural network interpolation. • Alternative ways to overcome the drawbacks of Hukuhara difference. • Kantorovich variant of fuzzy NN interpolation operators. • Special examples for the class of multivariate sigmoidal functions. • A novel interpolation algorithm for the color image process. [ABSTRACT FROM AUTHOR]

Globally, the leather industry is currently undergoing radical transformation due to pollution and discharge legislations. The present study is based on the investigation of performance of a hybrid electrocoagulation/electrodialysis process for the removal of COD, NH 3 -N, Cr and color in tannery wastewater. Effects of current density and electrolysis time were analyzed to optimize the electrocoagulation process with aluminum either iron electrodes. The optimized electrocoagulation process was then integrated with electrodialysis (ED) for the treatment of tannery effluents and was found that the hybrid process was capable of promoting the quality of the treated tannery wastewater. In case of treated tannery by EC with aluminum electrodes, ED process was effectiveness where the removal efficiency of COD, NH 3 -N, Cr and color were 92,100,100,100% respectively corresponds to conductivity value of 0.371 mS/cm at 45 minute. While, in the case of treated tannery by EC with iron electrodes, ED process was also efficient for removal pollutants, the removal efficiency of COD, NH 3 -N, Cr and color were 87,100,100,100% respectively corresponds to conductivity value of 1.5 mS/cm at 75 minute. It is noticeable that the effluent treated with combined EC-ED techniques presents very similar values for the same parameter as the ones presented by normal feed water. [ABSTRACT FROM AUTHOR]

Photosystem II (PSII) catalyzes light-driven water splitting in nature and is the key enzyme for energy input into the biosphere. Important details of its mechanism are not well understood. In order to understand the mechanism of water splitting, we perform here large-scale density functional theory (DFT) calculations on the active site of PSII in different oxidation, spin and ligand states. Prior to formation of the O-O bond, we find that all manganese atoms are oxidized to Mn(IV) in the S 3 state, consistent with earlier studies. We find here, however, that the formation of the S 3 state is coupled to the movement of a calcium-bound hydroxide (W3) from the Ca to a Mn (Mn1 or Mn4) in a process that is triggered by the formation of a tyrosyl radical (Tyr-161) and its protonated base, His-190. We find that subsequent oxidation and deprotonation of this hydroxide on Mn1 result in formation of an oxyl-radical that can exergonically couple with one of the oxo-bridges (O5), forming an O-O bond. When O 2 leaves the active site, a second Ca-bound water molecule reorients to bridge the gap between the manganese ions Mn1 and Mn4, forming a new oxo-bridge for the next reaction cycle. Our findings are consistent with experimental data, and suggest that the calcium ion may control substrate water access to the water oxidation sites. [ABSTRACT FROM AUTHOR]

For this study, seamless square tubes of aluminum alloys EN AW-6060 and EN AW-6082 were extruded with axial variable wall thickness by applying an axial moveable stepped mandrel. The microstructures in thick-walled and thin-walled sections of these tubes were investigated and correlated to the extrusion conditions. The results for EN AW-6060 revealed fibrous grains at low ram velocity ( v ram = 0.8 mm/s) and thus low strain rate. In these cases, peripheral coarse grains were also observed on the tube surfaces. Applying a higher v ram = 3.3 mm/s lead to a fully recrystallized microstructure. For EN AW-6082 the fibrous microstructure was predominant. This was attributed to the Mn-content of this alloy, which acts as an inhibitor for recrystallization. Only at the highest values of strain, strain rate and temperature a recrystallized microstructure was observed for this alloy. EBSD analyzes of boundary misorientation angles indicate that geometric dynamic recrystallization seems to be the predominant mechanism at low strain rates. The facts that the amount of low angle boundaries significantly decreased as subgrains were removed and the amount of high angle grain boundaries is increased revealed that recrystallization occurred at higher strain rates and strains. Furthermore, the transition areas, where the wall thickness was gradually reduced were investigated. Due to increasing strain and thus increasing strain rate, thin-walled tube segments show lower grain size than thick-walled sections. It was also revealed that the PCG layer thickness remained about constant with increased strain, but since the tube wall thickness was reduced, the recrystallized fraction increased for higher strains. [ABSTRACT FROM AUTHOR]

Selection of the process input parameters that would produce a sintered ceramic tile with high flexural strength, low water absorption and shrinkage is the main challenge. Generally, multiple parameters such as temperature, constituent content and type, either independently or interactively affect the efficiency of sintering process. Therefore, response surface methodology (RSM) was used to optimize the responses of these three input variables. Analysis of variance (ANOVA) showed the results of the test of significance of factors and interactions for the responses. The temperature and fly ash (FA) contents are the factors most associated with the output parameters. However, the FA type is the factor that has insignificant effect on responses. RSM demonstrated that predicted values were reasonably close to the experimental values confirming the validity and reliability of the suggested models. [ABSTRACT FROM AUTHOR]

The influence of leg dimensions and spacing on power-generation and thermo-mechanical performance of thermoelectric devices was investigated using numerical and statistical analyses tools. Bismuth-telluride based thermoelectric device models with rectangular-prism and cylindrical legs were simulated for a temperature range of 20–120 °C and various leg heights between 1 and 5 mm, widths/diameters between 1 and 2 mm, and spacing between 0.5 and 1.5 mm. Predicted power output, conversion efficiencies, and thermal stresses were validated with less than 8.9%, 1.2%, and 6.6% variations respectively. It is found that both leg width and height have a significant effect on power generation and thermal stresses: The relationship between power generation performance and thermal stress levels is inverse. Although leg spacing has effect on thermal stress and conversion efficiency, its effect on power output is negligible. [ABSTRACT FROM AUTHOR]

In this study, we consider the theoretical structure and classification of two-dimensional (2D) three-state uniform cellular automata (CA) based on their visual behavior. The basic features of a CA comprise their discrete dynamic structure and the fact that they are modeled locally, but their behavior can be similar to a continuous system at large time and spatial scales. The geometrical structures of the patterns produced by iterating CA can be considered according to some basic properties. After applying the rules iteratively, it has been shown that CA are capable of producing complex behaviors. Some types of CA exhibit remarkably regular behavior with finite configurations. With simple initial configurations, the patterns generated may be self-replicating (SR), self-similar (SS), or mixed. In this study, we consider the theory of 2D uniform periodic boundary (PB), adiabatic boundary (AB), and reflexive boundary (RB) CA with a von Neumann neighborhood, and applications of image analysis for generating patterns. We investigate a 2D CA under these boundary restrictions for three-state cases, i.e., the ternary field Z 3 . We also study the applications of SR and SS patterns that correspond to the linear CA rules of 2D uniform CA with different boundary cases over Z 3 . The von Neumann neighborhood CA rule (i.e., Rule 2460) is classified into SR and SS types depending on the non-zero boundary values a , b , c , d of the neighboring cells that influence the cells under consideration. Based on the visual appearance of the patterns, we also show that Rule 2460 is sometimes sensitive, depending on the boundary conditions and chaotic behavior. Finally, we conclude by analyzing some results in detail for CA defined by Rules 2460NB, 2460PB, 2460AB, and 2460RB for non-symmetric figures. [ABSTRACT FROM AUTHOR]

We describe a planning algorithm, NDP2, that finds strong-cyclic solutions to nondeterministic planning problems by using a classical planner to solve a sequence of classical planning problems. NDP2 is provably correct, and fixes several problems with prior work. We also describe two preprocessing algorithms that can provide a restricted version of the symbolic abstraction capabilities of the well-known MBP planner. The preprocessing algorithms accomplish this by rewriting the planning problems, hence do not require any modifications to NDP2 or its classical planner. In our experimental comparisons of NDP2 (using FF as the classical planner) to MBP in six different planning domains, each planner outperformed the other in some domains but not others. Which planner did better depended on three things: the amount of nondeterminism in the planning domain, domain characteristics that affected how well the abstraction techniques worked, and whether the domain contained unsolvable states. [ABSTRACT FROM AUTHOR]