Laboratory Experiments Research Articles

Knowledge graph-guided data-driven design of ultra-high-performance concrete (UHPC) with interpretability and physicochemical reaction discovery capability

Traditional methods for designing concrete materials typically rely on labor-intensive laboratory experiments, resulting in time and cost inefficiencies. Recently, designing concrete using artificial intelligence (AI) methods has shown high efficiency, but existing AI methods often rely solely on data, which can lead to violation with scientific principles and result in models lacking reasoning abilities. To overcome these challenges, this paper presents an interpretable knowledge graph-guided data-driven design approach. By integrating advanced computing techniques with domain knowledge via knowledge graphs, this approach enables the interpretation of data-driven models and uncovers the underlying mechanisms behind predictions. This approach is applied to ultra-high-performance concrete (UHPC) involving complex physicochemical reactions. The domain knowledge about UHPC is imparted using a knowledge graph, and UHPC properties are predicted using a machine learning model considering mixing proportions, processing methods, and physiochemical properties of materials via natural language processing. The results show that the knowledge graph displays crucial design variables and their effects on UHPC properties, aiding in selecting variables for machine learning models and interpreting their results. The prediction accuracy of the machine learning model reached 0.95. The research paves the way for more transparent and scientific AI models for material design and AI-enabled discovery of scientific knowledge.

Synergizing Solar Power with Enhanced Oil Recovery: Integrating Solar-Assisted Methods into Existing EOR Techniques

This study investigates the utilization of solar energy to enhance the efficiency of oil recovery processes, known as Solar Assist-Enhanced Oil Recovery (SA-EOR). The project objectives involve assessing the feasibility and effectiveness of integrating solar technologies with traditional oil recovery methods, such as steam injection or water flooding, to improve oil production rates and reduce operational costs. Methods employed include computational modeling, laboratory experiments, and field trials to evaluate various solar-assisted techniques and their impact on oil recovery. Key findings suggest that solar integration can enhance oil recovery by optimizing thermal processes, improving fluid mobility, and reducing environmental footprint. Additionally, the study underscores the economic viability and sustainability of SA-EOR solutions in the context of evolving energy landscapes. Overall, this research contributes valuable insights into the potential of solar technologies to revolutionize conventional oil recovery practices and advance towards more efficient and environmentally friendly energy production methods. Methods, termed Solar Assist-Enhanced Oil Recovery (SA-EOR). The objective is to investigate the efficacy of utilizing solar power to optimize thermal processes in oil extraction, such as steam injection or water flooding. Through computational modeling, laboratory experiments, and field trials, various SA-EOR techniques are evaluated for their potential to enhance oil recovery rates and reduce environmental impact. Findings indicate promising opportunities for leveraging solar energy to improve fluid mobility, optimize reservoir conditions, and ultimately increase oil production efficiency. This research underscores the significance of SA-EOR methods in advancing sustainable energy practices within the oil industry while addressing pressing environmental concerns.

Determination Of Drag And Inertia Coefficients By An Analytical Model

Hard structures like dykes or groins have been recognized for their negative environmental impact and limited durability in the face of climate change (Sutton-Grier et al., 2015). The concept of Shore Soft Engineering (SSE) has allowed ecological considerations to be embedded in the design of coastal protection (Hartig et al., 2011). Among emerging defense structures, nature-based solutions are built with natural materials and rely on physical properties and mechanisms observed in nature. They aim to protect, manage and restore ecosystems while providing some benefit to the human-being and biodiversity (Cohen-Shacham et al., 2016); they offer an interesting alternative to hard structures. However, implementing these solutions in urbanized coastal areas where ecosystems are vulnerable can be challenging. Another alternative approach is using biomimetic solutions, which can provide the functions of natural systems like seagrass, dunes, or coral through robust human-made constructions. Natural habitats exist in a variety of more or less complex forms, ranging from rigid (mangroves, coral) to flexible (seagrass) (Mullarney and Henderson, 2018); and they drive changes in the current profile, in wave dissipation or in sediment motion. Understanding how to mimic these systems, in particular their internal geometry and hydrodynamic effects, is challenging. This complexity makes the development of biomimetic solutions difficult (Perricone et al., 2023). In this context, this study strictly focuses on wave dissipation by flexible systems. Wave dissipation by natural habitats has been extensively studied through laboratory experiments (Houser et al., 2015) and in-situ measurements (Bradley and Houser, 2009). The pioneer analytical model (Dalrymple et al., 1984) depicted aquatic vegetation as rigid cylinders; however, the rigidity assumption fails to capture the inherent flexibility of plants. Alternative strategies emerged to account for this flexibility, such as using an empirical drag coefficient (Mendez and Losada, 2004) or introducing an effective length, representing the length that a rigid cylinder would have to dissipate the same wave height as flexible cylinders (Luhar and Nepf, 2016). However, to define this effective length or an empirical drag coefficient, it is necessary to carry out in-situ measurements. Numerous analytical models based on force balance (Luhar and Nepf, 2016; Leclercq and de Langre, 2018) have been developed to represent the movement of flexible vegetation like seagrass. These models depict the flexible vegetation as a series of segmented rigid stems attached to each other and subjected to oscillating flows. Some models attempt to link stem motion with wave dissipation to integrate this coupling into numerical models (Yin et al., 2022). However, these models still require unknown quantities such as drag and inertial coefficients. The present study aims to develop an analytical model for determining drag and inertial coefficients based solely on the geometry, the structure flexibility and wave forcing. At last, the method could help better represent the dissipation into numerical simulations without the need for prior parametrization.

Study of the engineering performance of pipes buried in the soil

This paper investigates the response of a flexible buried pipe to traffic load using laboratory experiments and numerical analysis. A series of laboratory tests and numerical simulations were performed to examine the effect of surface pressure, loading width, pipe type, pipe thickness, and burial depth on model response. In the experiments, a load was applied to the surface of a tank in which a pipe was buried. To gain a better understanding of the pipe's behavior, numerical simulations were performed using the finite element method; PLAXIS 2-D software. The results show that there is a good agreement between numerical and experimental test results. Furthermore, experimental and numerical analysis show that increasing burial depth reduces pipe deflection, increases soil surface settlement, and decreases pipe pressure, whereas increasing surface pressure increases all of the above parameters. Finally, equations were developed based on all numerical and experimental results to predict maximum stress on the pipe crown.

Assessment of Insecticide Resistance in Spodoptera litura (Fabricius) in Vegetable Crop Ecosystem

One of the most prevalent insect pests is the tobacco caterpillar or Spodoptera litura (Fabricius), which results in significant crop losses developed resistance against different insecticides over time. This laboratory experiment was carried out in the Department of Entomology, College of Agriculture, Rajendranagar, Professor Jayashankar Telangana State Agricultural University (PJTSAU), Hyderabad during Karif, 2022. The susceptible population was reared in laboratory continuously for ten generation without exposing it to insecticides. The susceptibility of field populations of S. litura that were collected from many vegetable crops in the intense vegetable crop cultivating mandals i.e., Chevella and Maheshwaram of Rangareddy district to commonly used insecticides viz., chlorantraniliprole, emamectin benzoate and flubendamide was then compared with a laboratory reared susceptible population The bioassay studies revealed that the LC50 values of these insecticides were significantly higher in the field population collected from Chevella and Maheshwaram compared to the susceptible laboratory population. Based on the LC50 values the Resistant ratio (RR) was calculated for the field populations. It was found that Chevella population developed 35.34 folds resistance and Maheshwaram population also developed nearly 34.90-fold resistance against emamectin benzoate. Both Chevella and Maheshwaram populations were found to develop moderate resistance of 28.23 and 27.35-fold against flubendamide and comparatively lower resistance of 21.05 and 23.44-fold resistance against chlorantraniliprole when compared to susceptible population. These findings further helps in developing better IRM strategies.

A Cost-Effective and Simplified Integration of Simulations and Hands-on Experiments in the Teaching of Electronic Instrumentation and Measurement Laboratory Course

To develop students into effective engineers upon graduation, it is important to bridge the gap between theory and practice. This is achieved through hands-on laboratory experiments, which form an important part of engineering education especially electronic circuits-related courses within the undergraduate level of education. Hence, it is important to develop well-outlined laboratory experiments that reflect the theoretical part of a course. Equally important is comparing simulation and measurement data, to better appreciate the theory. This work presents integrated simulation and hands-on experiments in teaching electronic instrumentation and measurement laboratory course, using low-cost off-the-shelf components. A no-cost circuit simulator software (LTspice) and low-cost breadboard with readily available off-the-shelf circuit components can be used both at home (self-paced) and in the laboratory to motivate students and align results for an improved learning approach. The advantage of this integrated laboratory is that no specialized or expensive teaching kit is required, which improves accessibility and course delivery. In addition, based on the feedback received, students are satisfied with this simplified and low-cost integrated laboratory.

Video-based measurements of the entrainment, speed and mass flux in a wind-blown eruption column

On May 4 2010 a wind-blown ash plume issued from Eyjafjallajökull volcano in Iceland. Analysis of a 17-minute-long video recording of the eruption suggests that, within 2–2.5 km of the vent, the flow was moving with the wind and rising under buoyancy, following a trajectory directly analogous with laboratory experiments of turbulent buoyant plumes in a cross-flow. The radius of the time-averaged ash cloud grew with height z at a rate r = 0.48 z, corresponding to an entrainment coefficient 0.4, again consistent with laboratory experiments. By analysing the frames in the video and comparing the shape of the plume to that predicted by the model, we estimate that during the 17 minutes recorded, the eruption rate gradually decreased by about 43% from an initial rate of 1.11 × 104 kg s−1 to 0.63 × 104 kg s−1. The analysis reported herein opens the way to assess eruption rates and eruption column processes from video recordings during explosive volcanic eruptions.

Lagrangian Measurements Of Surface Water Waves: Relation Between Drift Velocities And Set-Down

Since the work of Stokes on steady progressive surface waves (Stokes, 1847), there has been interest in fluid particle trajectories and associated mass flux. The original result obtained by Stokes was based on linear theory, and implied that there is a net forward drift in the fluid beneath a propagating surface wave. In the non-dimensional case, the drift velocity for a sinusoidal wave on a fluid of depth h is given by Recent works suggest that in many cases, particularly in waves propagating over a shear flow, a net Eulerian flow may develop, which is opposed to the Stokes drift. Monismith et al. (2007) suggested that in a deep-water setting, the net Eulerian backflow may cancel the Lagrangian Stokes drift on a pointwise basis. Further, Grue & Kolaas (2017) found good agreement with the theoretical findings of Longuet-Higgins (1953), except near the bottom and near the free surface, where boundary layers have a discernable impact on the induced flow. In recent field measurements, it was observed that the drift velocity correlates positively with the local average fluid depth (Bjørnestad et al., 2021). In other words, a wave with a set-up features a large forward drift, while a wave with a set-down features a negative net drift. The present work aims at investigating what observed in the field by means of laboratory experiments carried out in a wave flume, where monochromatic and bichromatic waves of different characteristics have been run.

Effect of topography and hydrological change on solute transport at the sediment-water interface in seasonal lakes

Study regionThe Poyang Lake is located in northern Jiangxi Province, which is the largest fresh water in China. The upstream connection with rivers and downstream access to the Yangtze River create seasonal hydrological regimes, resulting in over 100 seasonal lakes within the floodplain. These lakes provide important habitats for migratory birds to forage and nest during dry seasons, and contribute to floodwater regulation during wet seasons, maintaining lake ecosystem. Study focusThis study has combined laboratory experiments and numerical simulations to mechanically analyze the effect of the depth, width, slope of seasonal lakes, water level amplitude and dry season periods on water recharge patterns, exchange fluxes and solute transport characteristics at the sediment-water interface. New hydrological insights for the regionReducing the lake area by 33% through adjustments in depth or slope significantly reduces solute transport range (12.81% and 6.5% within 120 min) and high velocity area. The sensitivity of the solute amount in the lakebed to depth is the highest, followed by slope and width. Decreasing water level amplitude during dry seasons increases the flow velocity within the beach, facilitating short-term solute transport towards the lakebed. Extending the duration of dry periods increases cumulative flux of solutes entering the lakebed. These findings contribute to the ecological restoration efforts in floodplains and water pollution control measures.

The Sequential estimation of generalized linear model coefficients

Generalized LinearModels (GLM) allows us to model the relationship between a response variable and one or more predictor variables while taking into account the distribution of the response variable. It is a useful tool for modeling data that do not follow a normal distribution and can be applied to a wide range of data types and problem settings. As data becomes increasingly relevant in our daily lives, the use of these models is becoming more important. However, this increase in importance also implies an increase in the complexity of estimation due to the volume of data that must be processed. In contrast, when dealing with laboratory experiments or other situations, we may have limited observations making it challenging to obtain robust estimates. To address these challenges, this paper proposes a simple and efficient method for estimating the coefficients of GLM and provides mathematical proof for the almost sure convergence of this method towards the desired solution. The proposed method is also validated on real-world data, reinforcing its utility and effectiveness.

The impact of doctors' facial attractiveness on users' choices in online health communities: A stereotype content and social role perspective

This study examines the impact of doctors' facial attractiveness on users' choices in online health communities (OHCs). We conducted a field study using a sample of 14,897 doctors registered on a Chinese OHC. The results indicate a significant negative relationship between the facial attractiveness of doctors and the number of visits to their homepage by users. However, this relationship only holds true for male surgeons and female internal medicine doctors, not for female surgeons or male internal medicine doctors. These findings suggest the possible presence of gender-specialty bias in the influence of facial attractiveness on patients' decision-making. To further investigate how facial attractiveness influences users' inclination to choose a particular doctor, we develop our research model drawing upon the stereotype content and social role perspective. Through a laboratory experiment, we found that OHC users' perceptions of doctors' warmth and competence act as mediating factors in the relationship between facial attractiveness and user choice. Additionally, this relationship is influenced by stereotypical gender-specialty fit.

Generation of bidirectional shear horizontal guided waves by size optimization of face-shear piezoelectric transducers

Generating directional guided waves helps to avoid unwanted reflections while providing location information for defects. Bidirectional waves focus wave beams in two opposite directions, which can be applied for generating circumferential zero-order shear horizontal (SH0) waves for large-diameter pipe inspection. In this paper, a novel method for generating bidirectional SH0 waves through size optimization using face-shear (d24) lead zirconate titanate (PZT) transducer is proposed. A theoretical model is established based on the shear-lag model and the Huygens principle, which describes the generation and propagation of SH0 waves in thin plate by bonded d24 PZT transducer. The theoretical model is validated by multi-physics finite element (FE) simulation results in terms of SH0 displacement wavefield. Based on the theoretical model, the performance of bidirectional SH0 wave generation is studied. The maximum bidirectional ratio that can be achieved by d24 PZT within a size range (1–25 mm) under a five-cycle sinusoid tone-burst excitation at a center frequency range (50–300 kHz) is studied. Results show that over 20 dB effect can be achieved at the PZT with a specific aspect ratio. Laboratory experiments are conducted using d24 PZT transducers at 50–300 kHz to validate the effect of bidirectional wave generation in practical detection scenarios. Experimental results show effects of over 20 dB within a certain frequency range can be achieved when using a PZT with a large aspect ratio, which agree well with the theoretical predictions.

Beaconet: A Reference-Free Method for Integrating Multiple Batches of Single-Cell Transcriptomic Data in Original Molecular Space.

Integrating multiple single-cell datasets is essential for the comprehensive understanding of cell heterogeneity. Batch effect is the undesired systematic variations among technologies or experimental laboratories that distort biological signals and hinder the integration of single-cell datasets. However, existing methods typically rely on a selected dataset as a reference, leading to inconsistent integration performance using different references, or embed cells into uninterpretable low-dimensional feature space. To overcome these limitations, a reference-free method, Beaconet, for integrating multiple single-cell transcriptomic datasets in original molecular space by aligning the global distribution of each batch using an adversarial correction network is presented. Through extensive comparisons with 13 state-of-the-art methods, it is demonstrated that Beaconet can effectively remove batch effect while preserving biological variations and is superior to existing unsupervised methods using all possible references in overall performance. Furthermore, Beaconet performs integration in the original molecular feature space, enabling the characterization of cell types and downstream differential expression analysis directly using integrated data with gene-expression features. Additionally, when applying to large-scale atlas data integration, Beaconet shows notable advantages in both time- and space-efficiencies. In summary, Beaconet serves as an effective and efficient batch effect removal tool that can facilitate the integration of single-cell datasets in a reference-free and molecular feature-preserved mode.

Greenhouse gas mitigation and soil carbon stabilization potential of forest biochar varied with biochar type and characteristics

Biochar is increasingly used in climate-smart agriculture, yet its impact on greenhouse gas (GHG) emissions and soil carbon (C) sequestration remains poorly understood. This study examined biochar-mediated changes in soil properties and their contribution to C stabilization and GHG mitigation by evaluating four types of biochar. Soil carbon dioxide (CO2) and nitrous oxide (N2O) emissions, soil chemical and biological properties, and soil organic carbon (SOC) mineralization kinetics were monitored using greenhouse, laboratory, and modeling experiments. Three pine wood biochars pyrolyzed at 460 °C (PB-460), 500 °C (PB-500), 700 °C (PB-700), and one pine bark biochar from gasification at 760 °C (GB-760) were added into soil at 1 % w/w basis. Soils amended with biochar were used to cultivate sorghum for three months in a greenhouse, followed by three months of laboratory incubation. Data obtained from laboratory incubation was modeled using various statistical approaches. The PB-500 and PB-700 reduced cumulative N2O-N emissions by 68.5 % and 73.9 % and CO2 equivalent C emissions by 66.9 % and 72.4 %, respectively, compared to unamended control. The N2O emissions were positively associated with soil nitrate N, available P, and biochar ash content while negatively associated with SOC. The CO2 emission was negatively related to biochar C:N ratio and volatile matter content. Biochar amended soils had 49.2 % (PB-500) to 87.7 % (PB-700) greater SOC and 22.9 % (PB-700) to 48.1 % (GB-760) greater sorghum yield than the control. While PB-700 had more saprophytes than the control, the GB-760 yielded a greater yield than biochars prepared by pyrolysis. Microbial biomass C was 7.23 to 23.3 % greater in biochar amended soils than in control. The double exponential decay model best explained the dynamics of C mineralization, which was associated with initial soil nitrate N and available P positively and total fungi and protozoa biomass negatively. Biochar amendment could be a climate smart agricultural strategy. Pyrolysis pine wood biochar showed the greatest potential to reduce GHG emissions and enhance SOC storage and stability, and gasification biochar contributed more to SOC storage and increased crop yield.

Effects of Impact Energy and Aspect Ratio on the Motion of Particle Clouds in Stagnant Water

Abstract A series of laboratory experiments was conducted to investigate the effects of impact energy and other initial controlling parameters on the motion of particle clouds in stagnant water. Experiments were performed for two median sand diameters of D50 = 0.52 mm and 0.74 mm and nozzle diameters of do = 6 mm and 8 mm. Sand masses were converted to an equivalent pipe length with the same diameter as the nozzle, Lo, and a wide range of aspect ratios, Lo/do, between 2 and 93 was tested. The impact energy of sand particles was controlled by the release height of sand particles, and it was quantified by the non-dimensional release height, η, ranging from 1 to 21.5. It was found that particle clouds with higher impact energy had smaller concentration and velocity decay rates. This indicated that by increasing the release height, the momentum transfer between sand particles and the ambient water decreases. The time-series of instantaneous sand velocity were used to determine velocity fluctuations and turbulence intensity of sand particles and a direct correlation was found between sand velocity fluctuations and aspect ratio in particle clouds. The effects of impact energy on the anatomy of the resulted particle clouds were examined in this study. It was found that the cloud width increased dramatically when the impact energy of sand particles with high aspect ratios (i.e., Lo/do > 39) increased. Furthermore, the dispersion of sand particle began earlier as the kinetic energy of sand particles increased at the water surface.

Enhancing complex bioprocess learning through simulation technology and hybrid teaching: A case study in university education.

The utilization of computer simulators in university education is progressively being embraced to offer students a practical exposure to industrial bioprocesses. Bioreactor computer simulators hold various advantages over conventional laboratory experiments, such as cost-effectiveness and enhanced safety. The research objective is to assess the effectiveness of integrating bioreactor computer simulators into hybrid teaching to promote active and collaborative learning experiences and evaluate their impact on student participation and understanding. A hybrid strategy combining synchronous, face-to-face, and online teaching has been implemented to enhance the teaching-learning processes in the Industrial Bioprocesses course for Biochemistry students. The simulation software BIOSTAT®T Yeast was used. This software models the production of ethanol with Saccharomyces cerevisiae through batch cultivation and the determination of the kLa value of a bioreactor. In the first simulation activity, students analyzed the software response based on parameter values input by the instructor, while in the second simulation activity, students autonomously used the computer simulator under the primary oversight of the instructor. The survey results indicate that the pedagogical innovation was positively received and significantly motivating for the students. Comparing student satisfaction surveys between the two simulation activities suggests that fostering student autonomy and engagement through simulation technology can improve satisfaction and learning outcomes in bioprocess education.

Kurt Lewin: The Foundations of an Academic Life

For most of his working life, Kurt Lewin was known as a pioneering child psychologist. In 1939, Lewin appears suddenly to move his focus from children to adults and from laboratory experiments to changing behavior in the real world. This paper examines when and how, as a supposedly laboratory-based child psychologist, he developed the motivation, skills, knowledge and tools necessary to become the “intellectual father” of social and organizational change. It investigates Lewin's formative years, his education - especially his doctoral studies at the University of Berlin, and his military service in WW1. The paper concludes that rather than seeing Lewin as a pioneering child psychologist, we need to see him as a pioneering and campaigning psychologist, who had been studying human behavior (adult and child) and how to change it since beginning his doctoral studies in 1911, and applying this knowledge to organizations for almost as long.

Fairness in markets and market experiments: insights from a field‐plus‐lab study and a failed replication

AbstractWe investigate how fairness in a laboratory experiment framed as a market exchange relates to preferences for fair trade products elicited before and at the end of the experiment. We collected two samples, 10 years apart. In the original sample, fairness in the market experiment measured by the willingness to buy at a higher price when higher wages are paid to the worker correlates both with the choice of a fair trade product and with the willingness to pay a positive fair trade premium. These correlations are not significant in the replication experiment, which indicates at best a weak relationship.

Do Dominant Native Ants Outcompete the Invasive Argentine Ant in Mediterranean Citrus Ecosystems? A Laboratory Test

The invasive Argentine ant (Linepithema humile) poses a significant threat to ecosystem stability worldwide. In Mediterranean citrus ecosystems, its spread may be limited by interactions with dominant native ant species. We conducted laboratory experiments to investigate the competitive dynamics between Argentine ants and two major native species, Tapinoma nigerrimum and Lasius grandis. At the individual level, both native species exhibited superior competitive performance, attributed to their larger body sizes and potential differences in chemical defences. At the colony level, T. nigerrimum demonstrated efficiency in interference competition, successfully defending food resources from Argentine ants. However, the Argentine ant exhibited higher recruitment capacity, albeit it was density-dependent. Our findings support the hypothesis that dominant native ants can serve as barriers against Argentine ant invasion in citrus ecosystems, highlighting the importance of interspecific competition in shaping community dynamics and invasive species management. This study underscores the potential role of native ant species in mitigating the impacts of invasive ants on ecosystem functioning and biodiversity conservation in agricultural landscapes, offering valuable insights for invasive species management strategies in Mediterranean citrus ecosystems.

Physical Modelling Of The Wave Field Around An Array Of Centrally Controlled Wave Energy Converters

Stepped revetments have shown to be effective in limiting wave overtopping and wave run-up compared to sloped revetments. However, literature on wave impact pressures and comprehensive design guidelines for these structures is scarce. Laboratory experiments support establishing design recommendations. So far, studies for wave impacts at stepped revetments were mainly performed at small scales. Results from these tests are likely to be subjected to scale effects and therefore inaccurately replicate the wave-structure interaction at full scale. This study quantifies scale effects of wave impact characteristics for design cases based on a comparison to small-scale tests (Kerpen et al., 2018). Full-scale flume experiments were studied with a slope of 1:3 and uniform step heights of 0.17 m and 0.50 m in the Large Wave Flume (GWK) in Hannover, Germany. Horizontal and vertical wave impacts were measured at 15 locations in the plunging region of the revetment for a range of wave steepnesses (). The results show that previous small-scale tests underestimate design wave impact pressures by a factor of up to 7.7. Impact loadings occur considerably faster than at small scale with relative peak rising times decreasing by a factor of up to 5.6. Prediction formulae are derived for the vertical distribution of horizontal impact pressures (Figure 1b) as well as for temporal characteristics of these pressures at stepped revetments.