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In this study, Batem Pınarı, Interdonato, Meyer, and Ak Limon lemon cultivars were studied. Lemon peel's essential oils were obtained by two different methods (hydrodistillation and cold pressing) during four different harvest periods for each cultivar. Essential oil content, density, refractive index, optical activity, and composition were evaluated. The highest essential oil amount was found in the Interdonato cultivar (2.54%) and the lowest in Ak Limon (1.37%). The highest density value was 0.8471 g/mL (Ak Limon) and the lowest was 0.8423 g/mL (Meyer). Essential oil densities obtained by cold pressing were higher than those obtained by hydrodistillation. The highest refractive index values were determined for Batem Pınarı and Meyer (1.4747), and the lowest were determined for Ak Limon (1.4740). The refractive index values obtained by cold pressing were higher than those obtained by hydrodistillation. Optical activity values were found to be highest in Ak Limon and lowest in Batem Pınarı, and higher following hydrodistillation than cold pressing. The essential oil compositions of the samples showed significant differences depending on the cultivar and isolation method. Limonene, the highest component proportionally, composed 76.0%–89.0% of samples. The highest limonene content was determined for Ak Limon (88.7%), and the lowest for Batem Pınarı (76.7%). Limonene content did not change significantly between hydrodistillation (82.2%) and cold press (82.2%) isolation methods. Findings show that there is significant variation in quality parameters of lemon peel essential oils.

Objective The aim of this study was to determine the plasma pharmacokinetics of oxytetracycline (OTC) in rainbow trout (Oncorhynchus mykiss) of different body sizes. Methods The research was carried out on three groups as small (30–50 g), medium (90–110 g) and large (185–215 g) body sizes at 8 ± 0.5 °C. OTC was administered orally at a dose of 60 mg/kg to all groups. Blood samples were taken at 19 different sampling times until the 384 h after oxytetracycline administration. The plasma concentrations of OTC were measured using high pressure liquid chromatography-ultraviolet and pharmacokinetic parameters were evaluated using non-compartmental analysis. Results OTC was detected in small-body sized fish until the 336 h and in medium and large-body sized fish until the 384 h. The elimination half-life of OTC was 85.46, 87.24 and 86.98 h in the small, medium and large body size groups, respectively. The peak plasma concentration increased from 0.66 to 1.11 µg/mL, and the area under the plasma concentration-versus time curve from zero (0) h to infinity (∞) increased from 87.86 to 151.52 h*µg/mL, in tandem with the increase in fish body size. As fish body size increased, volume of distribution and total body clearance decreased. Conclusion These results show that the pharmacokinetics of OTC vary depending on fish size. Therefore, there is a need to reveal the pharmacodynamic activity of OTC in rainbow trout of different body sizes.

Celem badań było odkrycie znaczeń symboliki kolorów użytych na rysunkach o tematyce lęku. Objęliśmy nimi 482 dzieci z Polski i Turcji w wieku 6-10 lat narodowości polskiej i tureckiej (dobór celowy, metoda kuli śnieżnej). Badania polegały na porównaniu kolorystyki rysunków dzieci obu narodowości oraz ich interpretacji uwzględniającej kontekst kulturowy. Na potrzeby przedstawionej w artykule analizy sformułowaliśmy następujące pytania: Jakie kolory dominują na rysunkach dzieci obu narodowości? Jakie podobieństwa, a jakie różnice występują w kolorystyce badanych rysunków? Jak można interpretować użyte kolory, uwzględniając ich znaczenie symboliczne i funkcję w kulturze? Zauważono, że wśród użytych kolorów dominujące były czarny, czerwony i niebieski. Na podstawie przeprowadzonych badań stawiamy hipotezę, że użycie tych kolorów przez dzieci na rysunkach o tematyce lęku nie jest przypadkowe. Można je potraktować jako tzw. kolory lęku, czyli takie, które mają symboliczny związek z tą emocją. W przypadku koloru czarnego może być to lęk przed śmiercią, czerwonego lęk przed zranieniem. Użycie czerwonego i niebieskiego koloru można też interpretować jako potrzebę ochrony przed niebezpieczeństwem (apotropeiczne znaczenie kolorów).

Emotions are pervasive in Economics. The spillover effect of Central Bank's interest decision is a crucial topic not only to economies but also to individuals. Twitter is a useful source of data for social and economic research as data provides public available and accessible easily. The study aims to determine the emotions with longitudinal research by analyzing tweets about the interest decision of the Central Bank in Turkiye. Within the study emotions expressed by tweets about interest rate decision are analyzed using Plutchik’s Wheel of Emotions. The 2873 tweets about the interest decision cut on 29 November 2022 were examined by the Maxqda qualitative data analysis program. According to findings, the emotion of "anger" is mostly concentrated under the heading of interest rate decision. Also the analysis indicated that majority of tweets emphasized inflation and foreign exchange among macroeconomic variables and reducing interest indicates negative effects on economy especially by means of inflation. The study contains the classification of emotions regarding interest rate decision and provides evidence that economic decisions affect emotions and they are not independent from each other. Also study aims to provide comprehensive data for researchers who want to use Twitter with economics and emotions together.

This study delves into the exploration of the fatigue performance of a structure that has been spot-welded and is being loaded with torsional fatigue. The extended finite element method (XFEM) was applied to simulate the intricate interaction of spot welds in response to cyclic loading. The developed model was validated through experiments. The influences of different parameters, such as the number of spot welds used to join the adherends, the diameters of the spot welds, and the load ratio applied, on the fatigue performance of the box were investigated. The first two parameters studied had a significant influence on the extent of the fatigue failure-affected spot welds, where the crack propagation rate can be decreased by more than 700%.

Abstract. Vasovagal syncope is the most likely cause of syncope in the young. Head-up tilt-table test (HUT) provides the ability to provoke vasovagal syncope under controlled laboratory settings. In adult [...]

Abstract Objective Doxycycline (DO) has been used in fish for a long time, but there are some factors that have not yet been clarified regarding its pharmacokinetic (PK) and pharmacodynamic (PD) properties. Therefore, the aim of this study was to investigate the PK and PK/PD targets of DO after 20 mg/kg intravascular (IV), intramuscular (IM) and oral (OR) gavage administration in rainbow trout (Oncorhynchus mykiss). Methods Plasma samples were collected at specific time points and subsequently analysed by HPLC‐ultraviolet. The PK/PD indices were calculated based on the MIC90 (Aeromonas hydrophila and Aeromonas sobria) values obtained for the respective bacteria and the PK parameters obtained for DO following both IM and OR administration. Results After IV administration, the elimination half‐life (t1/2ʎz), area under the concentration vs. time curve (AUC), apparent volume of distribution at steady‐state and total body clearance of DO were 34.81 h, 723.82 h µg/mL, 1.24 L/kg and 0.03 L/kg/h, respectively. The t1/2λz of the DO was found to be 37.39 and 39.78 h after IM, and OR administration, respectively. The bioavailability was calculated 57.02% and 32.29%, respectively, after IM and OR administration. The MIC90 of DO against A. hydrophila and A. sobria was 4 µg/mL. The PK/PD integration showed that DO (20 mg/kg dose) for A. hydrophila and A. sobria with MIC90 ≤4 µg/mL achieved target AUC/MIC value after IM administration. Conclusions These results suggest that when rainbow trout was treated with 20 mg/kg IV and IM administered DO, therapeutically effective concentrations were reached in the control of infections caused by A. hydrophila and A. sobria.

Objective:Breast-conserving surgery (BCS) followed by radiotherapy (RT) is the standard treatment for early-stage breast cancer. The use of an additional RT dose (boost) to the tumour bed improves local control but may worsen quality of life (QOL) and cosmetic results. Multifocal/multicentric tumours (MMTs) pose a challenge as they require larger boost volumes. This study investigated the impact of RT volumes on late-term cosmetic outcomes and QOL in patients with unifocal and MMTs who underwent adjuvant RT after BCS.Materials and Methods:Retrospective data of 367 patients who underwent BCS between 2012 and 2014 were reviewed. A cohort of 121 patients with at least six months of completed RT were prospectively included in the study. Cosmetic results were evaluated using a modified scoring system, and QOL was assessed using The European Cancer Treatment and Organization Committee tools.Results:The results showed that the inclusion of regional lymphatics in the RT treatment field significantly affected QOL, particularly in terms of role functioning and social functioning. Higher boost volume ratios were associated with increased pain-related symptoms. However, the presence of MMTs did not significantly affect cosmetic outcomes compared to unifocal tumours.Conclusion:The size of the boost and inclusion of regional lymphatics in RT significantly impact QOL in patients undergoing BCS. Tumour foci number does not affect cosmetic outcomes. These findings emphasize the need for careful consideration of RT volumes to minimize long-term adverse effects on QOL. Future prospective studies should evaluate early side effects and baseline QOL scores to provide a comprehensive assessment.

The nonductile reinforced concrete building (NDRCB) stock—typically, pre-1974 structures in the U.S.—is a well-known high-risk group for seismic hazards. Prior studies indicate that there are approximately 1500 NDRCBs in Los Angeles. Through various ordinances, the owners are currently required to choose between demolition and, when appropriate, seismic retrofitting. Because fulfilling these ordinances will take decades, the potential risk of major losses will persist. In this study, a method for automated development of structural analysis models and damage fragilities for non-ductile moment-resisting frames is established. This capability enables seismic risk assessment at a regional scale using relatively limited building metadata and the era-specific seismic design code. The approach is used first to develop archetypal models in OpenSees, verified through static pushover and nonlinear time-history analyses against prior detailed studies. Fragility curves for discrete damage states are developed through a probabilistic seismic demand model. Additional investigations are carried out to consider the influence of soil-structural interaction effects and to determine the most suitable seismic intensity measures to quantify the seismic damage levels of NDRCB frames. The sensitivity of the proposed modeling method to variations/uncertainties in building configurations and properties is also examined through parametric studies. The method is limited to a particular subcategory of NDRBCs—namely, moment-resisting frames—but extensions to other types appear straightforward.

Since its initial report in the Philippines in 1981, ice-ice disease (IID) remains a substantial threat to the sustainability of eucheumatoid seaweed production. However, comprehensive investigations into the prevalence, intensity, and potential relationships with physicochemical and meteorological parameters are limited, particularly in open-sea farms. This is the first study to conduct a 12-month monitoring of IID prevalence and intensity in eucheumatoid seaweed farms in Tawi-Tawi, Philippines. The research aimed to elucidate seasonal variations and potential associations with physicochemical and meteorological parameters. The findings revealed significant seasonal variations in IID prevalence, with a higher incidence observed during the dry season compared to the wet season. Additionally, deep-water farms exhibited significantly higher prevalence and ice-ice spot numbers per bundle compared to shallow-water farms. Furthermore, Kappaphycus striatus displayed a significantly greater ice-ice spot length per bundle compared to K. alvarezii. Notably, no interaction effects were observed among season, species, and depth. Interestingly, while no correlations were found between ice-ice disease and most measured physicochemical and meteorological parameters (temperature, salinity, pH, water current velocity, wind speed) or nutrient concentrations (phosphate, nitrate, nitrite), an inverse correlation (p < 0.05) emerged between ammonium levels and IID intensity parameters (number and length of ice-ice spot per bundle). Moreover, a positive correlation was observed between monthly rainfall and IID intensity. These findings offer valuable insights into the dynamics of IID in open-sea eucheumatoid seaweed (Kappaphycus) farming, highlighting the influence of seasonality, depth, and species susceptibility, as well as the relationship between IID severity and ammonium levels and rainfall.

The Internet of Things (IoT) is playing a pivotal role in transforming various industries, and Wireless Sensor Networks (WSNs) are emerging as the key drivers of this innovation. This research explores the utilization of a heterogeneous network model to optimize the deployment of sensors in agricultural settings. The primary objective is to strategically position sensor nodes for efficient energy consumption, prolonged network lifetime, and dependable data transmission. The proposed strategy incorporates an offline model for placing sensor nodes within the target region, taking into account the coverage requirements and network connectivity. We propose a two-stage centralized control model that ensures cohesive decision making, grouping sensor nodes into protective boxes. This grouping facilitates shared resource utilization, including batteries and bandwidth, while minimizing box number for cost-effectiveness. Noteworthy contributions of this research encompass addressing connectivity and coverage challenges through an offline deployment model in the first stage, and resolving real-time adaptability concerns using an online energy optimization model in the second stage. Emphasis is placed on the energy efficiency, achieved through the sensor consolidation within boxes, minimizing data transmission hops, and considering energy expenditures in sensing, transmitting, and active/sleep modes. Our simulations on an agricultural farmland highlights its practicality, particularly focusing on the sensor placement for measuring soil temperature and humidity. Hardware tests validate the proposed model, incorporating parameters from the real-world implementation to enhance calculation accuracy. This study provides not only theoretical insights but also extends its relevance to smart farming practices, illustrating the potential of WSNs in revolutionizing sustainable agriculture.

The aim of this study was to compare the pharmacokinetics of oxytetracycline (OTC) following single- (60 mg/kg) and multiple-dose oral administrations (60 mg/kg, every 24 h for 7 days) in rainbow trout. It also aimed to determine bioavailability after a single dose and tissue residues and withdrawal times after multiple doses. This study was carried out on 420 rainbow trout at 9 ± 0.8 °C. This study was carried out in two stages: single-dose (intravascular and oral) and multiple-dose treatment. The OTC concentrations in plasma and tissues were measured by high-performance liquid chromatography and analyzed by a non-compartmental method. The withdrawal time (WT) was estimated using the WT 1.4 software. OTC exhibited a long terminal elimination half-life (t1/2ʎz) after IV and oral administration. The oral bioavailability of OTC was very low (2.80%). In multiple-dose treatment, t1/2ʎz, the area under the plasma concentration–time curve and peak plasma concentration increased significantly after the last day compared to the first day. OTC showed strong accumulation after multiple doses with a value of 5.33. OTC concentrations were obtained in the order liver > kidney > muscle+skin > plasma. At 9 ± 0.8 °C, the WT calculated for muscle+skin was 56 days for Europe and 50 days for China, respectively. The t1/2ʎz (68.94 h) and time (68 h) above the 1 µg/mL MIC following a single OTC dose may support the extension of the 24 h dosing interval following multiple dosing. However, further studies are required to determine the optimal dosage regimen in multiple-dose OTC treatment in the treatment of infections caused by susceptible pathogens.

Brush seals are leakage performance systems that are operating against turbine shafts and bucket tips. Flexible bristle structure can compensate the rotor interference during transients, which enables closer clearance control in turbine and turbo-engine applications. During turbomachinery transients, contacting bristles exert force on turbine shaft, which in turn result in wear, frictional heat generation, counter torque and power loss. Brush seal design with proper stiffness has crucial importance since high bristle tip force levels during rotor contact may result in rotor instability, bristle tip melting or thermo-mechanical fatigue due to large amount of local frictional heat input. Counter torque applied by the contacting brush seal with improperly excessive tip force may result in turbine stall and overall efficiency losses. High levels of bristle contact forces may induce elevated wear rates, which degrades the leakage performance of the brush seal during its life cycle. Brush seal contact force evaluation under operating conditions has critical importance and has to be conducted before turbine integration to avoid performance losses and possible turbine failure in some extreme cases. In this paper, ‘Bristle Contact Force Theory’ is developed and closed form bristle tip force (BTF) function is derived where rotor-bristle, inter-bristle and bristle-back plate interactions are included. BTF measurements under pressurized and unpressurized air environment are conducted for the selected test seals by using the custom ‘Rotary Test Rig’. BTF function of bristle contact force theory show high level of correlation with the test data. The effect of cant angle manufacturing tolerance on bristle tip force levels is also examined through bristle tip contact force theory, and compared with the test seal measurements. Methodology for number of bristle row calculation and comparison with the geometric inspection of test seals are also detailed within the content of this paper.

Due to their effective and affordable joining capabilities, resistance spot-welded (RSW) structures are widely used in many industries, including the automotive, aerospace, and manufacturing sectors. Because spot-welded structures are frequently subjected to cyclic stress conditions while in service, fatigue failure is a serious concern. It is essential to comprehend and predict their fatigue behavior in order to guarantee the dependability and durability of the relevant engineering products. The analysis of fatigue failure in spot-welded structures is the main topic of this paper, along with the prediction of fatigue life (Nf) and identification of failure mechanisms. Also, the effects of parameters such as the amount of cyclic load applied, the load ratio, and size of the spot-welding on the Nf were investigated. To achieve this, the fatigue performance of spot-welded joints was simulated using the extended finite element method (XFEM). The XFEM method is particularly suited for capturing intricate crack patterns in spot-welded structures because it allows for the modeling of crack propagation without the need for remeshing. It was observed that when the cycling load was decreased by 20%, Nf increased by around 250%. On the other hand, the fatigue life of the structure, and, hence, the crack propagation rate, was significantly affected by the load ratio and diameter of the spot-welding. This paper presents the details of the novel approach to studying spot-weld fatigue characterization using XFEMs to simulate crack propagation.

In this study, the effect of inlet air cooling on greenhouse gas (GHG) emissions and engine performance for a land-based gas turbine engine was investigated under varying ambient temperatures (15–55 °C). The study aimed to reduce GHG emissions while improving output power and fuel efficiency during hot weather operating conditions. For illustrative purposes, a representative gas turbine engine model, approximating the 250 MW class General Electric (GE) engine, was analyzed in a simple cycle. A refrigeration process was integrated with a turboshaft gas turbine engine to chill the incoming air, and the power required for cooling was extracted from the gas turbine’s output power. This mechanical chiller was assumed to provide a 15 °C inlet air temperature. Without inlet air cooling, at 55 °C ambient temperature, the engine’s power output was calculated to decrease by 15.06%, while power-specific fuel consumption and GHG emissions increased by 6.09% and 5.84%, respectively. However, activating the refrigeration or cooling system in the inlet made it possible to mitigate most of the adverse effects of hot weather on the engine’s performance and GHG emissions. Therefore, with inlet air cooling, the power output loss reduces to 3.28%, indicating an 11.78% recovery compared to the 15.06% loss without cooling. Similarly, the rise in power-specific fuel consumption caused by high ambient temperature decreases from 6.09% to 3.43%, reflecting a 2.66% improvement. An important finding of the study is that with inlet air cooling, the increase in GHG emissions reduces from 5.84% to 3.41%, signifying a 2.43% improvement on a hot day with a temperature of 55 °C.

Transportation networks play a crucial role in society by enabling the smooth movement of people and goods during regular times and acting as arteries for evacuations during catastrophes and natural disasters. Identifying the critical road segments in a large and complex network is essential for planners and emergency managers to enhance the network's efficiency, robustness, and resilience to such stressors. We propose a novel approach to rapidly identify critical and vital network components (road segments in a transportation network) for resilience improvement or post-disaster recovery. We pose the transportation network as a graph with roads as edges and intersections as nodes and deploy a Graph Neural Network (GNN) trained on a broad range of network parameter changes and disruption events to rank the importance of road segments. The trained GNN model can rapidly estimate the criticality rank of individual road segments in the modified network resulting from an interruption. We address two main limitations in the existing literature that can arise in capital planning or during emergencies: ranking a complete network after changes to components and addressing situations in post-disaster recovery sequencing where some critical segments cannot be recovered. Importantly, our approach overcomes the computational overhead associated with the repeated calculation of network performance metrics, which can limit its use in large networks. To highlight scenarios where our method can prove beneficial, we present examples of synthetic graphs and two real-world transportation networks. Through these examples, we show how our method can support planners and emergency managers in undertaking rapid decisions for planning infrastructure hardening measures in large networks or during emergencies, which otherwise would require repeated ranking calculations for the entire network.

Vibration analysis of bridges induced by train loads is a crucial aspect of railway design, particularly considering the complexity of vehicle components such as bogie-suspension systems. Consequently, railway engineers have endeavored to improve the computational efficiency and applicability of train models using the finite-element method. This paper introduces a toolbox implemented in ABAQUS through a user-defined element (UEL) subroutine, which incorporates the vehicle–bridge interaction (VBI) element theory. This toolbox effectively handles diverse vehicle–bridge interaction systems. In the proposed theory, the wheel-track contact force is derived based on the bridge response, eliminating the need for an iterative process and significantly reducing computational workload compared to classical physics-based analysis. The presented approach is validated through a moving sprung mass model and a moving rigid bar model. Furthermore, a case study is conducted on a three-dimensional finite-element model of a high-speed railway bridge in China, based on a design sketch, to showcase the capabilities of the developed scheme. The study demonstrates the practical application of the proposed methodology in analyzing vehicle–bridge structures with high complexity.

The purpose of this study was to compare the pharmacokinetics, tissue residues, and withdrawal times of doxycycline after oral administration in rainbow trout reared at 10 and 17 °C. Fish received a 20 mg/kg oral dose of doxycycline after a single or 5-day administration. Six rainbow trout were used at each sampling time point for plasma and tissue samples, including liver, kidney, and muscle and skin. The doxycycline concentration in the samples was determined using high-performance liquid chromatography with ultraviolet detector. The pharmacokinetic data were evaluated by non-compartmental kinetic analysis. The WT 1.4 software program was used to estimate the withdrawal times. The increase of temperature from 10 to 17 °C shortened the elimination half-life from 41.72 to 28.87 h, increased the area under the concentration–time curve from 173.23 to 240.96 h * μg/mL, and increased the peak plasma concentration from 3.48 to 5.50 μg/mL. At 10 and 17 °C, the doxycycline concentration was obtained in liver > kidney > plasma > muscle and skin. According to the MRL values stated for muscle and skin in Europe and China (100 μg/kg) and in Japan (50 μg/kg), the withdrawal times of doxycycline at 10 and 17 °C were 35 and 31 days, respectively, for Europe and China and 43 and 35 days, respectively, for Japan. Since temperature significantly affected pharmacokinetic behavior and withdrawal times of doxycycline in rainbow trout, temperature-dependent dosing regimens and withdrawal times of doxycycline might be necessary.

Near-fault earthquakes (NFEs), characterized by high peak ground velocity (PGV) and long period pulses, show different properties from far-field ones [...]

Objective: To determine the anti-inflammatory effects of mucus obtained from different fish species on the carrageenan-induced acute paw edema in rats. Methods: Forty-two rats were randomly divided into seven groups. Acute paw edema was induced by 0.1 mL of 1% carrageenan, and a single dose of diclofenac and lyophilized mucus (25 mg/kg) of rainbow trout, brook trout, European sea bass, and gilthead sea bream were administered to rats through gastric gavage 1 h before carrageenan treatment. Rat paws were measured before and 1-4 h after carrageenan treatment. The mRNA expressions of cytokines (TNF-α, IL-1β, IL-6, IL-10, and TGF-β), antioxidant markers (catalase and superoxide dismutase), and COX-2 were investigated using quantitative polymerase chain reaction. The histopathological changes were evaluated by hematoxylin and eosin staining. Results: The inhibition percentage of carrageenan-induced paw edema by different fish mucus ranged from 52.46% to 74.86% at 4 h. Histopathological evaluation showed that all fish mucus diminished carrageenan-induced edema and inflammatory cell infiltration. The upregulation of IL-1β mRNA induced by carrageenan was decreased by the mucus of rainbow trout and gilthead sea bream while an increase in the expression of IL-6 mRNA was reduced by the mucus of rainbow trout, brook trout, and gilthead sea bream. In addition, the mRNA expression of superoxide dismutase was higher in the rainbow trout mucus group than the carrageenan group. Conclusions: Mucus obtained from different fish species may have anti-inflammatory effects.

This study presents a two-step FE model updating approach for health monitoring and damage identification of prestressed concrete girder bridges. To reduce the effects of modeling error in the model updating process, in the first step, modal-based model updating is used to estimate linear model parameters mainly related to the stiffness of boundary conditions and material properties. In the second step, a time-domain model updating is carried out using acceleration data to refine parameters accounting for the nonlinear response behavior of the bridge. In this step, boundary conditions are fixed at their final estimates using modal-based model updating. To prevent the convergence of updating algorithm to local solutions, the initial estimates for nonlinear material properties are selected based on the first-step model updating results. To validate the applicability of the two-step FE model updating approach, a series of forced-vibration experiments are designed and carried out on a pair of full-scale decommissioned and deteriorated prestressed bridge I-girders. In the first step, parameters related to boundary conditions, including stiffness of supports and coupling beams, as well as material properties, including initial stiffness of concrete material, are estimated. In the second step, concrete compressive strength and damping properties are updated. The final estimates of the concrete compressive strength are used to infer the extent of damage in the girders. The obtained results agree with the literature regarding the extent of reduction in concrete compressive strength in deteriorated concrete structures.

Accurate estimation of fuels is essential for wildland fire simulations as well as decision-making related to land management. Numerous research efforts have leveraged remote sensing and machine learning for classifying land cover and mapping forest vegetation species. In most cases that focused on surface fuel mapping, the spatial scale of interest was smaller than a few hundred square kilometers; thus, many small-scale site-specific models had to be created to cover the landscape at the national scale. The present work aims to develop a large-scale surface fuel identification model using a custom deep learning framework that can ingest multimodal data. Specifically, we use deep learning to extract information from multispectral signatures, high-resolution imagery, and biophysical climate and terrain data in a way that facilitates their end-to-end training on labeled data. A multi-layer neural network is used with spectral and biophysical data, and a convolutional neural network backbone is used to extract the visual features from high-resolution imagery. A Monte Carlo dropout mechanism was also devised to create a stochastic ensemble of models that can capture classification uncertainties while boosting the prediction performance. To train the system as a proof-of-concept, fuel pseudo-labels were created by a random geospatial sampling of existing fuel maps across California. Application results on independent test sets showed promising fuel identification performance with an overall accuracy ranging from 55% to 75%, depending on the level of granularity of the included fuel types. As expected, including the rare—and possibly less consequential—fuel types reduced the accuracy. On the other hand, the addition of high-resolution imagery improved classification performance at all levels.

EEG signals are interpreted, analyzed and classified by many researchers for use in brain–computer interfaces. Although there are many different EEG signal acquisition methods, one of the most interesting is motor imagery signals. Many different signal processing methods, machine learning and deep learning models have been developed for the classification of motor imagery signals. Among these, Convolutional Neural Network models generally achieve better results than other models. Because the size and shape of the data is important for training Convolutional Neural Network models and discovering the right relationships, researchers have designed and experimented with many different input shape structures. However, no study has been found in the literature evaluating the effect of different input shapes on model performance and accuracy. In this study, the effects of different input shapes on model performance and accuracy in the classification of EEG motor imagery signals were investigated, which had not been specifically studied before. In addition, signal preprocessing methods, which take a long time before classification, were not used; rather, two CNN models were developed for training and classification using raw data. Two different datasets, BCI Competition IV 2A and 2B, were used in classification processes. For different input shapes, 53.03–89.29% classification accuracy and 2–23 s epoch time were obtained for 2A dataset, 64.84–84.94% classification accuracy and 4–10 s epoch time were obtained for 2B dataset. This study showed that the input shape has a significant effect on the classification performance, and when the correct input shape is selected and the correct CNN architecture is developed, feature extraction and classification can be done well by the CNN architecture without any signal preprocessing.

An accurate seismic response simulation of civil structures requires accounting for the nonlinear soil response behavior. This, in turn, requires understanding the nonlinear material behavior of in situ soils under earthquake excitations. System identification methods applied to data recorded during earthquakes provide an opportunity to identify the nonlinear material properties of in situ soils. In this study, we use a Bayesian inference framework for nonlinear model updating to estimate the nonlinear soil properties from recorded downhole array data. For this purpose, a one-dimensional finite element model of the geotechnical site with nonlinear soil material constitutive model is updated to estimate the parameters of the soil model as well as the input excitations, including incident, bedrock, or within motions. The seismic inversion method is first verified by using several synthetic case studies. It is then validated by using measurements from a centrifuge test and with data recorded at the Lotung experimental site in Taiwan. The site inversion method is then applied to the Benicia–Martinez geotechnical array in California, using the seismic data recorded during the 2014 South Napa earthquake. The results show the promising application of the proposed seismic inversion approach using Bayesian model updating to identify the nonlinear material parameters of in situ soil by using recorded downhole array data.

We present a finite element model updating technique for soil–structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and updated using a sequential Bayesian estimation approach for joint parameter and input identification. A two-step system identification approach is devised. First, the fixed-base structural model is updated to estimate the structural model parameters (including effective elastic modulus of structural components, distributed floor mass, and Rayleigh damping parameters) and some uncertain components of the foundation-level motion. Then, the identified structural model is used for soil–structure model updating wherein the Rayleigh damping parameters, the stiffness and viscosity of the soil subsystem (modeled using a substructure approach), and the foundation input motions (FIMs) are estimated. The identified model parameters are compared with state-of-practice recommendations. While a specific application is made for the Millikan Library, the present work offers a framework for integrating large-scale FE models with measurement data for model inversion. By utilizing this framework for different civil structures and earthquake records, key structural model parameters can be estimated from the real-world recorded data, which can subsequently be used for assessing and improving, as necessary, state-of-the-art seismic analysis and structural modeling techniques. This paper presents an effort towards using real-world measurements for large-scale FE model updating in the soil and structure, uniform soil time domain for joint parameter and input estimation, and thus paves the way for future applications in system identification, health monitoring, and diagnosis of civil structures.

Earthquakes threaten humanity globally in complex ways that mainly include various socioeconomic consequences of life and property losses. Resilience against seismic risks is of high importance in the modern world and needs to be sustainable. Sustainable earthquake resilience (SER) from the perspective of structural engineering means equipping the built environment with appropriate aseismic systems. Shape memory alloys (SMAs) are a class of advanced materials well suited for fulfilling the SER demand of the built environment. This article explores how this capability can be realized by the innovative SMA-based superelasticity-assisted slider (SSS), recently proposed for next-generation seismic protection of structures. The versatility of SSS is first discussed as a critical advantage for an effective SER. Alternative configurations and implementation styles of the system are presented, and other advantageous features of this high-tech isolation system (IS) are studied. Results of shaking table experiments, focused on investigating the expected usefulness of SSS for seismic protection in hospitals and conducted at the structural earthquake engineering laboratory of the University of Bonab, are then reported. SSS is compared with currently used ISs, and it is shown that SSS provides the required SER for the built environments and outperforms other ISs by benefitting from the pioneered utilization of SMAs in a novel approach.

Fish oil has a cardioprotective effect in adults with ischemic heart disease. The authors examined the effects of fish oil in children with idiopathic dilated cardiomyopathy (DCM). Eighteen DCM patients [...]

Due to technical developments and wider range of applications in the steel structures, significance of the research on structural stability problems become forward. Lateral torsional buckling is a major problem especially for doubly symmetric I-shaped steel members subjected to flexure about their strong axis. If these members are not appropriately braced against lateral deflection and twisting, they are under the risk of failure by lateral torsional buckling prior to the reach their load carrying capacity. In this study, elastic lateral torsional buckling behavior of doubly symmetric I-shaped steel members under linear moment gradient is investigated considering a proposed method, several design standards and codes, approaches from the literature and finite element analysis. Proposed method herein is based on finite difference solution of lateral torsional buckling differential equation considering linear moment gradient. Different unbraced member lengths and various end moment values are considered in order to compare and evaluate these approaches in terms of critical moment and moment modification factor. Analysis results show that lateral torsional buckling is a key issue for doubly symmetric I-shaped steel members that are under flexure and it is reflected satisfactorily with the proposed method considering the design codes and standards, approaches from the literature and finite element analysis results.

Çelik yapılardaki teknik gelişmeler ve daha geniş uygulama alanları nedeniyle yapısal stabilite problemleri üzerine yapılan araştırmaların önemi artmaktadır. Yanal burulmalı burkulma, özellikle kuvvetli eksenlerinde eğilmeye maruz kalmış çift simetri eksenli I-kesitli çelik elemanlar için önemli bir sorundur. Bu elemanlar yatay yer değiştirme ve dönmeye karşı uygun bir şekilde desteklenmezlerse, yük taşıma kapasitelerine ulaşamadan önce yanal burulmalı burkulma riski altındadırlar. Bu çalışmada, farklı uç moment etkisi altındaki çift simetri eksenli I-kesitli çelik elamanların elastik yanal burulmalı burkulma davranışı, önerilen bir yöntem ile birlikte çeşitli tasarım standartları, literatürdeki yaklaşımlar ve sonlu eleman analizleri dikkate alınarak incelenmiştir. Burada önerilen yöntem, doğrusal değişen moment etkisi altında yanal burulmalı burkulma davranışını temsil eden diferansiyel denklemin sonlu farklar yöntemi ile çözümüne dayanır. Kritik moment ve moment düzeltme faktörü açısından bu yaklaşımları karşılaştırmak ve değerlendirebilmek için farklı yatay yönde tutulma uzunlukları ve çeşitli uç moment değerleri dikkate alınmıştır. Analiz sonuçları, yanal burulmalı burkulmanın, eğilme altında bulunan çift simetri eksenli I-kesitli çelik elemanlar için önemli bir konu olduğu ve önerilen yöntem ile tasarım standartları, literatürdeki yaklaşımlar ve sonlu elemanlar sonuçları ile karşılaştırıldığında sonuçların tatmin edici bir şekilde yansıtıldığını göstermektedir.

Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The described process is a practice of digital twinning and the updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Objective:Obesity is a chronic metabolic disorder that leads to the increased risk of cardiovascular diseases. This study aims to investigate the effect of weight loss on the platelet count and volume, which is associated with cardiovascular diseases.Methods:In total, 56 obese patients were recruited for the study. The parameters were retrospectively evaluated before and after 6 months of surgery.Results:The mean weight of the patients was 126.2±23.1 kg before surgery and 91.8±20.5 kg after surgery (p

Objective:Some previous studies have shown that low-dose radiotherapy (RT) can increase tumor invasion and metastasis. Multiple RT fields are usually used to prevent the damage to the organs at risk. We performed a clinical study with a concern that low-dose RT might increase invasion or metastasis. Ionizing radiation (IR) can enhance the potential tumor micro-environment by modifying the host micro-metastatic cancer cells.Methods:We conducted a retrospective study on 50 patients aged between 45 and 87 years, who were applied RT and/or chemotherapy, had the Eastern Cooperative Oncology Group performance status (ECOG) between 1 and 3 and stage II–III lung cancer, and were without any metastasis. RT was applied at daily fractions of 180–200 cGy (5 days/week) and a 54–66 Gy total dose. V5, V10, V20, V40, V50, and V60 values of the lung in a disease-free life, and general life effects statistically analysed with Mann-Whitney U and L Par testS.Results:A lower RT dose range, which produced V5, V10, and V20 volume values of the lung, was analyzed. It was observed that the V5, V10, and V20 RT volumes of the lung provided a minimal positive effect on relapse-free and general survival according to the R-correlation values.Conclusion:Larger studies are necessary according to these results to evaluate the impact of low-dose radiation and to increase the survival rates.

Abstract Objective Several studies have shown that low‐dose radiotherapy (RT) might increase tumor invasion and metastases. Whereas multiple RT fields that increase low‐dose RT areas are often used to prevent damage to organs at risk. We carried out a clinical trial with the concern that low‐dose RT sites could increase invasions or metastases when multiple sites were used. Methods A clinical retrospective study was carried out on 50 lung cancer patients with stage II–IIIB cancer, who underwent RT and/or chemotherapy, had Eastern Cooperative Oncology Group performances 1–3, were aged 45–87 years, and without metastases. RT was carried out for 5 days with 180–200 cGy fractions per day with a total dose of 54–66 Gy. The radiation dose volume areas V5, V10, V20, V40, V50, and V60 of lung were calculated and analyzed by Mann–Whitney U‐test and L par test on disease‐free and overall survival statistically. Results It was determined that V5, V10, and V20, which constitute the low RT dose areas of the lung, positively affected the recurrence‐free and overall survival minimally according to r correlation values. Conclusion Low‐dose RT volumes were positively affected minimally by recurrence‐free survival and overall survival in the present study. The effects of low‐dose radiation must be evaluated more clearly in studies.

Neo-liberal eğitim anlayışının üniversiteleri öğrenci odaklı, küresel kalkınmaya uygun eğitimi amaçlayan, girişimci ve yaratıcı insan kaynağı üreten ve buna uygun eğitim programları geliştiren birer kuruma dönüştürdüğü gözlenmektedir. Bu bağlamda üniversitelerin girişimci bir yapıya sahip olup olmadığı yönünden ölçümler yapıldığı da dikkat çekmektedir. Bu ölçümlerin birçok amacı bulunmakla birlikte, öncelikle tüm paydaşların beklentilerini karşılayan rekabetçi, girişimci ve yenilikçi bir üniversite yönetişim sistemi kurularak bu sistemin geliştirilmesini sağlamaktır. Buna paralel olarak yine tüm paydaşların beklentilerini karşılayacak ve bu sistemin geliştirilmesine katkı verecek Girişimci ve Yenilikçi Üniversite İndeksleri oluşturma çabaları da artış eğilimindedir. Üniversite girişimciliğinin ölçümlenmesinin yararlılığı konusunda genel olarak uzlaşı bulunduğu söylenebilir. Bu amaçla Türkiye’de sadece TÜBİTAK tarafından geliştirilen ve yürütülen Girişimci ve Yenilikçi Üniversite İndeksi olarak adlandırılan bir adet İndeks 2012 yılından bu yana kullanılmaktadır. Bu konuda farklı ölçüm araçlarının olması bilimsel olarak yararlı olacaktır. Bu düşünceden hareketle bu araştırmanın amacı, Üniversite girişimciliği konusunda yeni bir indeks geliştirmektir.Ölçek geliştirme aşamasında literatürde yer alan üç fazlı on adımlı yaklaşım benimsenmiştir. Ölçekte yer alabilecek ifadeler literatür ve uzman görüşleri doğrultusunda oluşturulmuştur. Bu aşamada 53 maddelik taslak bir form elde edilmiştir. Bu taslak indeks, alandan uzmanlara gönderilerek uzman görüşü istenmiştir. Elde edilen uzman görüşleri sonrasında Kapsam Geçerlik İndeksi KGİ çalışması yapılmış ve 50 maddenin aday ölçekte kaldığı tespit edilmiştir. Yapı geçerliği açısından Faktör analizi öncesinde Kaiser-Meyer-Olkin katsayısı ve Bartlett testi yapılmış ve Bartlett testi sonucu P

The pharmacokinetic of enrofloxacin was investigated in brown trout (Salmo trutta) following oral administration of 10, 20, and 40 mg/kg doses at 11 ± 1.5 °C. Furthermore, MICs of enrofloxacin against Aeromonas hydrophila and A. sobria were determined. The plasma concentrations of enrofloxacin and ciprofloxacin were determined using HPLC–UV and analyzed by non-compartmental method. Following oral administration at dose of 10 mg/kg, total clearance (CL/F), area under the concentration–time curve (AUC0−∞) and peak plasma concentrations (Cmax) were 41.32 mL/h/kg, 242.02 h*μg/mL and 4.63 μg/mL, respectively. When compared to 10 mg/kg dose, the dose-normalized AUC0–∞ and Cmax were increased by 56.30% and 30.08%, respectively, while CL/F decreased by 38.4% at 40 mg/kg dose, suggesting the non-linearity. Ciprofloxacin was not detected in the all of plasma samples. The MIC values of enrofloxacin were ranged 0.0625–4 μg/mL for A. hydrophila and 0.0625–2 μg/mL for A. sobria. The oral administration of enrofloxacin at 10 (for 192 h) and 20 (for 240 h) mg/kg doses provided the AUC of enrofloxacin equal to 1.23 and 1.96-fold MICs, respectively, for A. hydrophila and A. sobria with the MIC90 values of 1 µg/mL. However, further researches are needed on the PK/PD study of enrofloxacin for the successful treatment of infections caused by A. hydrophila and A. sobria in brown trout.

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The aim of this study was to determine the pharmacokinetics of carprofen following intravenous (IV), intramuscular (IM) and oral routes to rainbow trout (Oncorhynchus mykiss) broodstock at temperatures of 10 ± 1.5 °C. In this study, thirty-six healthy rainbow trout broodstock (body weight, 1.45 ± 0.30 kg) were used. The plasma concentrations of carprofen were determined using high-performance liquid chromatography and pharmacokinetic parameters were calculated using non-compartmental analysis. Carprofen was measured up to 192 h for IV route and 240 h for IM, and oral routes in plasma. The elimination half-life (t1/2λz) was 30.66, 46.11, and 41.08 h for IV, IM and oral routes, respectively. Carprofen for the IV route showed the total clearance of 0.02 L/h/kg and volume of distribution at steady state of 0.60 L/kg. For IM and oral routes, the peak plasma concentration (Cmax) was 3.96 and 2.52 μg/mL with the time to reach Cmax of 2 and 4 h, respectively. The bioavailability was 121.89% for IM route and 78.66% for oral route. The favorable pharmacokinetic properties such as the good bioavailability and long t1/2λz for IM and oral route of carprofen suggest the possibility of its effective use for the treatment of various conditions in broodstock.

The present article introduces an algorithm for path planning and assembly of infinitesimal and real-sized particles by using a distance and path based permutation algorithm. The main objective is to define non-overlapping particle paths subject to minimal total path length during particles positioning and assembly. Thus, a local minimum is sought with a low computational cost. For this reason, an assignment problem, to be specific Euclidean bipartite matching problem, is presented, where the particles in the initial (random selection) and final (particle assembly) configurations are in one-to-one correspondence. The cost function for particle paths is defined through Euclidean distance of each particle between the initial and final configurations. Principally, a cost flow problem is formed and solved by determining an optimal permutation subject to the total Euclidean distance of the particles and their non-overlapping paths. Monte Carlo simulations are carried out for non-overlapping paths; thus, non-colliding particles, and then total path distances of the obtained sets are minimized, resulting in an optimal solution which may not be necessarily the global optimum. Case studies on basic and complex shaped infinitesimal and real-sized particle assemblies are shown with their total costs, i.e., path lengths. It is believed that the present study contributes to the current efforts in optical trapping automation for particle assemblies with possible applications, e.g., in the areas of micro-manufacturing, microfluidics, regenerative medicine and biotechnology.

Purpose. We aimed to investigate whether the accuracy of the Plusoptix A09 photorefractor in children with ametropia is enhanced by cycloplegia with 1% tropicamide. Methods. A total of 70 eyes (70 children) were retrospectively reviewed. Noncycloplegic photorefraction, cycloplegia with 1% tropicamide, cycloplegic photorefraction, and cycloplegic refraction with a tabletop autorefractometer were performed on all subjects in this order. Measurements were compared statistically. Results. The mean age was 45.9 ± 11.4 months. The mean spherical equivalent (0.61 ± 1.03 diopters (D); range, −2.38 to 3.63 D) and mean spherical power (1.16 ± 0.92 D; range, −1.25 to 3.75 D) values that were acquired from the photorefraction without cycloplegia showed statistically significant differences from those of the autorefraction with cycloplegia (mean spherical equivalent = 1.00 ± 1.27 D; range, −1.50 to 4.25 D, mean spherical power = 1.60 ± 1.14; range, −1.25 to 4.50 D). The mean difference for the spherical equivalent was −0.39 ± 0.93 D (P=0.021; 95% limits of agreement (LoA) = −2.22 D to 1.44 D) and for spherical power was −0.44 ± 1.02 D (P=0.016; LoA = −2.44 D to 1.56 D). Without cycloplegia, Plusoptix A09 showed myopic shift, while after cycloplegia, it showed hyperopic shift. Spherical equivalent (mean difference (MD) ± SD = 0.78 ± 1.00 D, P0.05). Conclusion. Cycloplegia with 1% tropicamide did not improve the accuracy of photorefraction using Plusoptix A09 in preschool children. The spherical equivalent and spherical power values obtained by photorefraction with cycloplegia were significantly higher from those obtained by autorefraction with cycloplegia.

Effects of Common sour orange and Troyer citrange rootstocks on fruit quality properties were researched for Fina and Clemanules varieties and 64, 68, 90 Clementine types. These varieties and types grafted on Sour orange and Troyer citrange rootstocks were planted in 1996. Common sour orange and Troyer citrange affected similarly on the fruit quality of Clementine varieties and types. It could be suggested that, these rootstocks should be used for Clementine mandarin cultivars.