Laboratory Experiments Research Articles

Timber–Encased-Steel Beams: Laboratory Experimentation and Analytical Modeling

Timber–Encased-Steel Beams: Laboratory Experimentation and Analytical Modeling

Cross-correlation adjustment full-waveform inversion with source encoding in ultrasound computed tomography

Full-waveform inversion (FWI) is one of the leading-edge techniques in ultrasound computed tomography (USCT). FWI reconstructs the images of sound speed by iteratively minimizing the difference between the predicted and measured signals. The challenges of FWI are to improve its stability and reduce its computational cost. In this paper, a new USCT algorithm based on cross-correlation adjustment FWI with source encoding (CCAFWI-SE) is proposed. In this algorithm, the gradient is adjusted using the intermediate signals as the inversion target rather than the measured signals during iteration. The intermediate signals are generated using the travel time difference calculated by cross-correlation. In the case of conventional FWI failure, using the proposed algorithm, the estimated sound speed can converge toward the ground truth. To reduce the computational cost, an intermittent update strategy is implemented. This strategy only requires one time for the calculation of the travel time difference per stage, so that the source encoding can be used. Simulation and laboratory experiments are implemented to validate this approach. The experiment results show it has successfully recovered the sound speed model, while conventional FWI failed when the initial model greatly differed from the ground truth. This verifies that our approach improves the stability of the reconstruction in USCT. In practice, additional computational costs can be reduced by combining our approach with existing methods. The proposed approach increases the robustness of the FWI and expands its application.

Investigating the effectiveness of carbon nanotubes for the compressive strength of concrete using AI-aided tools

Sustainable development in the building industry can be achieved through the use of versatile cementitious composites. Thus, incorporating nanoparticles into cement composites can create materials with enhanced performance and numerous applications. The utilization of carbon nanotubes (CNTs) in the construction industry has great promise for developing efficient solutions to establish a sustainable ecosystem with diverse characteristics. However, forecasting the characteristics of these composites is a significant challenge due to their intricate composite structure and nonlinear behavior. Designing and conducting laboratory experiments on diverse samples and across multiple age groups is challenging, time-consuming, and costly. Moreover, there is presently a lack of a forecasting model that can predict concrete's compressive strength (fc') with nanoparticles. Three machine learning (ML) techniques, K-nearest neighbor (KNN), linear regression (LR), and artificial neural network (ANN), were used to predict the fc' of nanocomposites containing CNTs in this research. A thorough database consisting of 282 data entities for the CNTs-based concrete and the model's reliability was assessed using the R2 test and statistical error analysis. The ANN model had the most outstanding R2 value of 0.885, while the KNN and LR models had R2 values of 0.838 and 0.744, respectively. Moreover, RReliefF analysis is utilized to evaluate the primary components in predicting concrete outcomes. This research shows that the properties of CNT-based concrete composites are greatly affected by the water-to-binder ratio, followed by the proportions of cement and coarse aggregates. The ML algorithms exhibited superior generalization capabilities, suggesting their enhanced potential for accurate predictions of CNTs-based concrete properties.

How Live Marketing Affects Green Purchase in the Age of Artificial Intelligence?

ABSTRACT With the rise of artificial intelligence and the public’s attention to environmental issues, live online promotion of green products has become a new marketing method. It has become a key issue for enterprises to choose the appropriate information framework to motivate consumers’ green purchasing behavior through different forms of live broadcasting. Combined with laboratory experiments, this study analyses the interaction between the type of live streaming and message framing on green purchase intention based on explanation level theory. Three experiments results show that using loss-framing message real anchors are more likely to promote consumers’ green purchase intentions, and AI anchors are more suitable for using gain frames. Besides, consumer innovativeness moderates the influence of message framing and live streaming form on green purchase intention, and green perceived value plays a mediating role in this process. Our findings can not only guide the formulation of enterprise marketing strategy, but also provide countermeasures and suggestions for the future development of live marketing.

Генотипни различия в растежната активност на семената от сортове зимен ечемик

At the Institute of Agriculture - Karnobat, Bulgaria, laboratory research was conducted on 5 varieties of two-row and 5 varieties of multi-row winter barley. The aim of the research is to determine the genotypic differences in the initial growth of winter barley varieties. The varieties were studied in a laboratory experiment using the roll method. Number of indicators number of roots (number), length of roots (cm), length of the first leaf (cm) were recorded. 20 seeds of each variety were placed on filter paper in 3 replicates. The rolls are immersed in water and after 10 days the length of the first leaf, the number of roots and their length are counted. The results of the analysis show that Zahir and Alexan varieties form the largest number of roots. The Lardeya and Bozhin varieties form the smallest number of roots. The Kuber and Siela varieties have the longest root length and the first leaf. The varieties Zahir and Achinora have the smallest root length, and Lardea and Zemela have the smallest length of the first leaf. To improve the length of the first leaf, good combinations are expected when crossing the varieties Daria, Bozhin with Alexan, Achinora. Siela, Zemela, Alexan and Achinora varieties are genetically the most distant from Lardea, Kuber and Zahir in terms of length and number of roots. It is recommended to use them for crosses in order to create a better root system.

Sediment source and dose influence the larval performance of the threatened coral Orbicella faveolata.

The effects of turbidity and sedimentation stress on early life stages of corals are poorly understood, particularly in Atlantic species. Dredging operations, beach nourishment, and other coastal construction activities can increase sedimentation and turbidity in nearby coral reef habitats and have the potential to negatively affect coral larval development and metamorphosis, reducing sexual reproduction success. In this study, we investigated the performance of larvae of the threatened Caribbean coral species Orbicella faveolata exposed to suspended sediments collected from a reef site in southeast Florida recently impacted by dredging (Port of Miami), and compared it to the performance of larvae exposed to sediments collected from the offshore, natal reef of the parent colonies. In a laboratory experiment, we tested whether low and high doses of each of these sediment types affected the survival, settlement, and respiration of coral larvae compared to a no-sediment control treatment. In addition, we analyzed the sediments used in the experiments with 16S rRNA gene amplicon sequencing to assess differences in the microbial communities present in the Port versus Reef sediments, and their potential impact on coral performance. Overall, only O. faveolata larvae exposed to the high-dose Port sediment treatment had significantly lower survival rates compared to the control treatment, suggesting an initial tolerance to elevated suspended sediments. However, significantly lower settlement rates were observed in both Port treatments (low- and high-dose) compared to the control treatment one week after exposure, suggesting strong latent effects. Sediments collected near the Port also contained different microbial communities than Reef sediments, and higher relative abundances of the bacteria Desulfobacterales, which has been associated with coral disease. We hypothesize that differences in microbial communities between the two sediments may be a contributing factor in explaining the observed differences in larval performance. Together, these results suggest that the settlement success and survival of O. faveolata larvae are more readily compromised by encountering port inlet sediments compared to reef sediments, with potentially important consequences for the recruitment success of this species in affected areas.

Measuring gravitational attraction with a lattice atom interferometer.

Despite being the dominant force of nature on large scales, gravity remains relatively elusive to precision laboratory experiments. Atom interferometers are powerful tools for investigating, for example, Earth's gravity1, the gravitational constant2, deviations from Newtonian gravity3-6 and general relativity7. However, using atoms in free fall limits measurement time to a few seconds8, and much less when measuring interactions with a small source mass2,5,6,9. Recently, interferometers with atoms suspended for 70 s in an optical-lattice mode filtered by an optical cavity have been demonstrated10-14. However, the optical lattice must balance Earth's gravity by applying forces that are a billionfold stronger than the putative signals, so even tiny imperfections may generate complex systematic effects. Thus, lattice interferometers have yet to be used for precision tests of gravity. Here we optimize the gravitational sensitivity of a lattice interferometer and use a system of signal inversions to suppress and quantify systematic effects. We measure the attraction of a miniature source mass to be amass = 33.3 ± 5.6stat ± 2.7syst nm s-2, consistent with Newtonian gravity, ruling out 'screened fifth force' theories3,15,16 over their natural parameter space. The overall accuracy of 6.2 nm s-2 surpasses by more than a factor of four the best similar measurements with atoms in free fall5,6. Improved atom cooling and tilt-noise suppression may further increase sensitivity for investigating forces at sub-millimetre ranges17,18, compact gravimetry19-22, measuring the gravitational Aharonov-Bohm effect9,23 and the gravitational constant2, and testing whether the gravitational field has quantum properties24.

THE POTENTIAL OF PATIN FISH (Pangasius hypophthalmus) PROTEIN CONCENTRATE IN ADDRESSING OF STUNTING

Background: Stunting has become a health problem in developing countries such as Indonesia. This can provide an effect on body composition, decreasing albumin levels and immunity status. Patin fish is well-known to have a high level of protein concentration and has a positive-effect on stunting. Objectives: The present study aimed to investigate the nutrient compound of Patin fish protein concentrate. Methods: The research method used is experimental laboratories. The test was carried out by Association of Official Agricultural Chemists method (AOAC) 2012. Results: The results showed that Patin Fish Protein Concentrate have high protein contain. A comprehensive literature review was conducted to gather scientific evidence regarding the effects of height protein intake on improving nutritional status, linear growth, and health outcomes in children with stunting. The literature review findings indicate that Patin Fish protein concentrate holds promise as a good protein source in enhancing the nutritional status and growth of stunting children. Additionally, Patin Fish protein concentrate may provide supplementary benefits in increasing intake of omega-3 fatty acids crucial for brain development and cognitive function in children. Conclusion: However, further experimental research is warranted to validate the findings of this literature review and assess the potential of Patin Fish protein concentrate in nutritional intervention programs for effectively addressing stunting.

Design and Implementation of a Low-Power Device for Non-Invasive Blood Glucose

Glucose is a simple sugar molecule. The chemical formula of this sugar molecule is C6H12O6. This means that the glucose molecule contains six carbon atoms (C), twelve hydrogen atoms (H), and six oxygen atoms (O). In human blood, the molecule glucose circulates as blood sugar. Normally, after eating or drinking, our bodies break down the sugars in food and use them to obtain energy for our cells. To execute this process, our pancreas produces insulin. Insulin “pulls” sugar from the blood and puts it into the cells for use. If someone has diabetes, their pancreas cannot produce enough insulin. As a result, the level of glucose in their blood rises. This can lead to many potential complications, including blindness, disease, nerve damage, amputation, stroke, heart attack, damage to blood vessels, etc. In this study, a non-invasive and therefore easily usable method for monitoring blood glucose was developed. With the experiment carried out, it was possible to measure glucose levels continuously, thus eliminating the disadvantages of invasive systems. Near-IR sensors (optical sensors) were used to estimate the concentration of glucose in blood; these sensors have a wavelength of 940 nm. The sensor was placed on a small black parallelepiped-shaped box on the tip of the finger and the output of the optical sensor was then connected to a microcontroller at the analogue input. Another sensor used, but only to provide more medical information, was the heartbeat sensor, inserted into an armband (along with the microprocessor). After processing and linear regression analysis, the glucose level was predicted, and data were sent via the Bluetooth network to a developed APP. The results of the implemented device were compared with available invasive methods (commercial products). The hardware consisted of a microcontroller, a near-IR optical sensor, a heartbeat sensor, and a Bluetooth module. Another objective of this experiment using low-cost and low-power hardware was to not carry out complex processing of data from the sensors. Our practical laboratory experiment resulted in an error of 2.86 per cent when compared to a commercial product, with a hardware cost of EUR 8 and a consumption of 50 mA.

Integrating particle packing approach with ML techniques to optimise the compressive strength of RCA based concrete mixes

The present study focusses on predicting and optimizing the compressive strength of recycled concrete aggregate (RCA) based concrete mixes using machine learning algorithms. The issues with the gradation of irregular shape of recycled aggregates is leveraged using particle packing approach. Integration of the packing density into analysis of 466 data sets of RCA based concretes using ML techniques is the novelty of this work. Input variables water-to-binder ratio, binder content, natural fine aggregate, natural coarse aggregates, RCA percentage replacement (ranging from 0 % to 100 %), packing density, and output variable compressive strength (in MPa) are considered. Random Forest Regressor (RFR) algorithm demonstrated significant accuracy in predicting the RCA based concrete mixes. Validation through k-fold analysis reinforced robustness of the predictive model, revealing an average R2 of 0.99 with low predictive errors. Overall, ML-based regression analysis has come in handy to accurately predict the strength in RCA-based concrete mixes, offering a valuable alternative, avoiding, extensive laboratory experiments for strength optimization.

Rhizobacterial Bacillus enrichment in soil enhances smoke tree resistance to Verticillium wilt.

Verticillium wilt, caused by the soilborne fungus Verticillium dahliae, poses a serious threat to the health of more than 200 plant species worldwide. Although plant rhizosphere-associated microbiota can influence plant resistance to V. dahliae, empirical evidence underlying Verticillium wilt resistance of perennial trees is scarce. In this study, we systemically investigated the effect of the soil microbiota on the resistance of smoke trees (Cotinus coggygria) to Verticillium wilt using field, greenhouse and laboratory experiments. Comparative analysis of the soil microbiota in the two stands of smoke trees suggested that Bacillus represented the most abundant and key microbial genus related to potential disease suppression. Smoke tree seedlings were inoculated with isolated Bacillus strains, which exhibited disease suppressiveness and plant growth-promoting properties. Furthermore, repletion of Bacillus agents to disease conducive soil significantly resulted in reduced incidence of smoke tree wilt and increased resistance of the soil microbiota to V. dahliae. Finally, we explored a more effective combination of Bacillus agents with the fungicide propiconazole to combat Verticillium wilt. The results establish a foundation for the development of an effective control for this disease. Overall, this work provides a direct link between Bacillus enrichment and disease resistance of smoke trees, facilitating the development of green control strategies and measurements of soil-borne diseases.

Point-to-point virtual model control of a flexible joint robotic manipulator using trajectories of motion

This paper considers the use of trajectories of motion as a means of addressing the problem of unwanted oscillations and improving steady-state accuracy in the point-to-point motion of a flexible joint robotic manipulator using a novel third-order Poynting–Thomson virtual model control. A differentially flat model of the manipulator was exploited for classical controller design. The trajectories of motion were generated through a Newton interpolation procedure. The conditions for motion from rest to rest were derived and used to generate the trajectories required to steer the manipulator from one static point to another. Simulation and laboratory experiments confirmed that with the use of the trajectories of motion, rest-to-rest displacement is achieved without the unwanted swings about the final position. A marginal improvement in trajectory tracking performance was also verified by comparing it with the classical controller and state feedback controller. Moreover, the new controller showed better external disturbance rejection than the classical flat controller.

Lab-scale validation and parametric numerical investigation on hydrogen production in a porous media as a byproduct of in-situ combustion

A numerical 1D model was developed and validated using the measured data on a porous tube lab experiment for hydrogen generation as an in-situ combustion (ISC) byproduct, and a detailed parametric numerical study was performed. This work explores the impacts of various water injection parameters on the generation of hydrogen, the oil recovery factor (ORF), and carbon monoxide using a thorough parametric analysis. The methodology included simulating the injection of mutually enriched air and water into the combustion tube, focusing on parameters such as water temperature, quality, and flow rates. Key findings reveal that the oxygen ratio in the oxidizer substantially influences hydrogen production and ORF, with hydrogen generation increasing from 1.65 × 103 cm3 to 3.0 × 103 cm3, which is around 82 % when the oxygen percentage is raised from 50 % to 95 %. The results showed that employing wet combustion instead of dry combustion increased the hydrogen production rate by roughly four times. Variable water temperature has insignificant impacts on the hydrogen production rate and ORF. Increasing the steam quality has an opposed effect on the hydrogen generation rate. Additionally, escalating the injected water flow rate from 3000 cm³/day to 15000 cm³/day boosts hydrogen production from 10000 cm³ to 53400 cm³, respectively.

Synergizing computer‐aided design, commercial software, and cutting‐edge technologies in an innovative nozzle test apparatus for an engineering laboratory course

AbstractThis study explores compressible flow, a field reliant on mathematical models for effective teaching. Using laboratory experiments as pedagogical tools, we introduce a compact nozzle test apparatus that integrates cutting‐edge technologies—additive manufacturing (AM), pressure‐sensitive paint, the Schlieren system, image processing, and computational fluid dynamics (CFD)—in a compressible flow laboratory course. Commercial software, including MATLAB, SOLIDWORKS, ANSYS Fluent, and LabVIEW, facilitates the incorporation of these technologies. The research outlines the course structure, objectives, and details of student projects. Through a comparative analysis of experimental results, analytical calculations, and CFD simulations, we showcase the successful integration of AM in pedagogical practices for compressible flow, addressing critical concerns like nozzle strength and surface roughness. Statistical data from student projects offer practical insights, ensuring accuracy in experimental applications. The laboratory's design and detailed lists of components and costs provide a meaningful comparison with a supersonic wind tunnel, considering manufacturing expenses, operational costs, spatial requirements, and noise levels. The assessment of lab report grades underscores the approach's efficacy in conveying compressible flow concepts successfully, facilitated by modern computers. In summary, our study presents a comprehensive, efficient, and technologically advanced approach to teaching compressible flow within a concise framework.

Microplastics Uptake by Four Filter Feeders

Microplastics (MPs) are insidious plastic particles with sizes ranging from 1 to 5000 µm. Their presence has been reported all over the world. Recently, bioremediation to remove MPs from water columns using filter feeders as biofilters has been proposed. In a previous lab experiment, the MP bioremediation potential of four fouling organisms from a mariculture facility (Mytilus galloprovincialis, Sabella spallanzanii, Phallusia mammillata, Paraleucilla magna) was separately assessed in single-species experiment. Herein, a follow-up of the work is presented using a multi-species approach. The four organisms were placed together in the same 5 L beaker and fed with a concentration of 250 p/L 6 µm red polystyrene discernible particles. After digesting the organisms and counting the MPs in both the water and the organisms, the results of the two experiments were compared. In the previous experiment, S. spallanzanii had the highest particle retention (PR) value (PR = 88.01%), while in this experiment, P. mammillata has the lowest PR value (PR = 31%). The multi-species approach resulted in a higher number of plastics being removed from the water (88%) compared to the single-species experiments. These fouling organisms naturally exist as a community, acting as an efficient filter with complex morphologies and hydrodynamic features. Here, this simple marine animal forest is re-evaluated by exploiting the ecosystem services provided by these organisms as a solution to MP pollution problem in a mariculture environment.

Animal Experiments and Laboratory Safety within the Scope of Occupational Health and Biosafety

Occupational health and biosecurity terms include scientific approaches regarding ethical values, reliable methods, and a series of precautions to be taken against risks and hazards for employees and the living material being studied. Research and development activities carried out within the scope of biotechnology involve many risks under laboratory conditions, which are their own physical area. Many precautions and practices have been defined to analyze these risks and take precautions before they occur, and laboratory guides have been created in line with these definitions. During studies carried out with experimental animals under laboratory conditions, safe working rules may be violated due to physical conditions, equipment and materials, treatments applied to the subjects, negligence, or faulty practices caused by the researcher or expert. Biosafety in animal experiments consists of a set of ethical conditions and practices declared in the guidelines of specialized laboratories at their own level, protecting employees, subjects, and life outside the laboratory. In this review, possible risks and dangers that may arise at different biosafety levels and the precautions and practices that can be taken against them are evaluated. In this way, it was aimed to contribute to the development of laboratory and biosafety criteria in animal experiments.

Sonic gravimeter for determining the acceleration of gravity: A laboratory experiment for undergraduate students

Sonic gravimeter for determining the acceleration of gravity: A laboratory experiment for undergraduate students

Exploring the Inductive Effect through Computational Modeling: A General and Organic Chemistry Lab Experiment

Exploring the Inductive Effect through Computational Modeling: A General and Organic Chemistry Lab Experiment

Direct numerical simulation of the 7-7-7 film cooling at a range of compound angles

Film cooling is essential for protecting substrate materials from the hot gases in turbomachines. Recent experiments have explored the effects of compound angles for the 7-7-7 film cooling hole, a baseline shaped film cooling hole developed at the START lab. However, differences in facility conditions, manufacturing process uncertainties, uncertainties in flow conditions, and the absence of internal cooling hole measurements necessitate further investigation to fully understand the impact of compound angles and the associated flow physics. This study presents direct numerical simulations (DNS) for the baseline 7-7-7 shaped film cooling hole, examining a range of compound angles and flow conditions paralleling those in prior lab experiments. The data gleaned offers insights into the flow dynamics within and in the vicinity of the cooling hole, particularly in areas proximate to the wall. Our findings indicate that increasing the compound angle adversely affects adiabatic cooling efficiency. A detailed analysis reveals that this decline in efficiency is primarily due to hot gas intrusion into the cooling hole, the elevation of the cooling jet from the wall, and intensified secondary flows at higher compound angles. Additionally, the DNS data reveals a logarithmic scaling in the laterally averaged mean velocity profile and a self-similarity in temperature profiles beyond a certain distance from the cooling hole.

Efficacy Of Ultraviolet Irradiation For Sterilization Of Dental Instrumen Against Oral Microbiome Growth

Background: Oral microbiome bacteria can attach to a variety of surfaces including oral diagnostic devices. Oral diagnostic tools that are not properly cleaned and sterilized can be used as a place for bacteria to multiply and cause cross-infection. Objective: This research aims to test the success of sterilization equipment using Ultraviolet light to sterilize dental instruments when used for dental examination activities in the field. Methods: Randomized Experimental laboratory Pretest Posttest with Control Group Design. The subject of the study was the mouth glasses used after dental examination at UKGS. The intervention of the mouth glass was sterilized using Ultraviolet-c at three different times, namely 20 minutes, 25 minutes, and 30 minutes. Results: The results of Ultraviolet-c with One Way Anova test results showed a p-value of 0.000 (p0.05) indicating a significant difference in the number of oral microbiome bacteria between sterilization time and the number of oral microbiome bacterial colonies. Pearson correlation test p-value (p0.05) it can be concluded that there is a significant relationship between sterilization time and the number of oral microbiome colonies with a correlation coefficient of -0.850 which means that the longer the sterilization time, the number of oral microbiome bacteria decreases. Conclusion: Ultraviolet-c for 30 minutes is effective for sterilization of oral microbiome bacteria.