Demand High Cost Research Articles

THE SILK INDUSTRY: INDIA'S ROLE IN THE GLOBAL LANDSCAPE AND FINANCIAL DECISION-MAKING DYNAMICS

Silk industry is involved with this breeding of silk worms and manufacturer of the silk. India is the second largest producer of silk contributing to about 18% to the world production. What is however more not worthy is the fact that India is requirement of raw silk is much higher than it’s current production and present. It has a strong traditional and culture bound domestic market of silk. About 60 lakh persons are engaged in various sericulture activities in the country. It is estimated that sericulture can generate employment of 11 man days per kg of raw silk production throughout the year. This paper reviews recent research on silk industries by considering various SWOT analysis. The analysis revealed the strength on this industry, Silk industry region based, the sustaining Market demand high cost of raw silk and overview of the technology innovations on- farm experimentation. KEYWORDS: Silk industry, SWOT analysis, Industry analysis, Raw silk cost

Microheater with copper nanofiber network via electrospinning and electroless deposition

In this report, we present the development of a copper nanofiber network-based microheater, designed for applications in electron microscopes, gas sensing, and cell culture platforms. The seed layer, essential for electroless deposition, was fabricated through the electrospinning of a palladium-contained polyvinylpyrrolidone solution followed by a heat treatment. This process minimized the contact resistance between nanofibers. We successfully fabricated a microheater with evenly distributed temperature by controlling the electrospinning time, heat treatment conditions, and electroless deposition time. We assessed the electrical and thermal characteristics of the microheater by examining the nanofiber density, sheet resistance, and transmittance. The microheater’s performance was evaluated by applying current, and we verified its capacity to heat up to a maximum of 350 °C. We further observed the microheater’s temperature distribution at varying current levels through an infrared camera. The entire manufacturing procedure takes place under normal pressure, eliminating the need for masking or etching processes. This renders the method easily adaptable to the mass production of microdevices. The method is expected to be applicable to various materials and sizes and is cost-effective compared to commercially produced microheaters developed through microelectromechanical system processes, which demand complex facilities and high cost.

Multiscale Evaluation of Mechanical Properties for Metal-Coated Lattice Structures

With the combination of 3D printing and electroplating technique, metal-coated resin lattice is a viable way to achieve lightweight design with desirable responses. However, due to high structural complexity, mechanical analysis of the macroscopic lattice structure demands high experimental or numerical costs. To efficiently investigate the mechanical behaviors of such structure, in this paper a multiscale numerical method is proposed to study the effective properties of the metal-coated Body-Centered-Cubic (BCC) lattices. Unlike studies of a similar kind in which the effective parameters can be predicted from a single unit cell model, it is noticed that the size effect of representative volume element (RVE) is severe and an insensitive prediction can be only obtained from models containing multiple-unit-cells. To this end, the paper determines the minimum number of unit cells in single RVE. Based on the proposed method that is validated through the experimental comparison, parametric studies are conducted to estimate the impact of strut diameter and coating film thickness on structural responses. It is shown that the increase of volume fraction may improve the elastic modulus and specific modulus remarkably. In contrast, the increase of thickness of coating film only leads to monotonously increased elastic modulus. For this reason, there should be an optimal coating film thickness for the specific modulus of the lattice structure. This work provides an effective method for evaluating structural mechanical properties via the mesoscopic model.

친환경적 도시개발과 개발 갈등

Urban development and growth depends upon the ability of maintaining urban sustainability. In order to fit up such the ability, constant change is required. Environmentally-friendly urban development is an instrumental meaning for new urban changes. Environmentally-friendly urban development is a new urban development approach to remedy the existing reckless development to stabilize urban natural environment and living condition as well as social and economic domain. However, environmentally-friendly urban development presupposes the improvement of environmental aspects through green plan that demands high costs. While the high cost of development leads to the influx of economically relaxed upper-middle-income people, existing low-income natives are being displaced or kicked out that raises social inequality and unfairness. This phenomenon is pointed out as a result of urban gentrification, especially green gentrification that is accepted as one of the side effects of environmentally-friendly urban development. Green gentrification as one of the side effects of such environmentally-friendly urban development has brought a debate over its effects along with what factors have made the effects is also drawing attention. This study identifies the background of green gentrification due to environmentally-friendly urban development and the factors that led to green gentrification as well as analyze the controversial aspects of impact and effectiveness.

Bi-fidelity Kriging model for reliability analysis of the ultimate strength of stiffened panels

A method based on a Bi-fidelity Kriging model is proposed for structural reliability analysis. It is based on adding low-fidelity data samples to the model to predict high-fidelity values, thus saving computational effort. Distance Correlation develops the correlation between the low and high-fidelity functions, initially proposed to assess the correlation between two variables. The bi-fidelity Kriging response surface model's efficiency as a surrogate model will be assessed for structural reliability problems that demand high computational costs, such as nonlinear finite element analysis structural models. The efficiency assessment is performed by comparing the accuracy of the failure probability predictions based on the Subset Simulation and First-order reliability method using the Bi-fidelity Kriging model as a surrogate for the performance function. The idea is illustrated by considering a representative component of marine structures analyzed by finite element analysis to create bi-fidelity scenarios to assess structural reliability with many variables. The results show that the proposed multi-fidelity method can provide an accurate failure probability estimation with less computational cost.

Trends and predictors of incidence of hypospadias in a tertiary hospital in South Africa

BackgroundHypospadias is a penile congenital abnormality characterized by an ectopic urethral opening, ventral curvature and incomplete foreskin closure with a dorsal hooded prepuce. Management of the outcome demands high cost. The aim of this study was to determine the trends and predictors of hypospadias among babies born at Charlotte Maxeke Johannesburg Academic Hospital between 01 January 2014 and 31 December 2016.MethodsMothers’ files from the transfer unit of the labour ward were reviewed. A case–control study compared boys with hypospadias and those without born approximately at the same time. Data were retrospectively collected on data collection forms. EpiData version 3.1 and STATA version 15.1 were used for statistical analysis. The Mantel Haenszel method determined combined odds ratios for hypospadias outcome on boys whose mothers were exposed to certain conditions versus boys of unexposed mothers. Woolf’s method was used to compute confidence intervals of the odds ratios. Logistic regression analysis was used to assess the independent contributing maternal factors to the risk of hypospadias.ResultsRecords of 221 male babies were collected of which 73 were cases and 148 controls in the ratio of 1:2. Hypospadias was more frequent in boys born by Caesarean Section (p < 0.001), those with low birth weight (p < 0.001) and those small for gestational age (p < 0.002). Alcohol use (odds ratio 3.1), smoking (odds ratio 1.54), herbal use (odds ratio 2.05), medical history (odds ratio 2.8), multiple pregnancies (odds ratio 1.69) and maternal congenital abnormalities (odds ratio 3.03) indicated an increased risk of hypospadias. Surgical history (odds ratio 1.29), pre-natal vaccination (odds ratio 0.92), employment (odds ratio 0.85), and education (odds ratio 0.48) were not associated with the risk of hypospadias.ConclusionsMothers older than 36 years presented a stratifying effect on disease outcome. Our findings did not indicate major changes in trends of incidence of hypospadias. The years assessed did not have a significant effect on the number of cases.

Comparative Study of Materials used for Props and Scaffoldings in Southern Nigeria

The increase in demand and consequent high cost of steel props and scaffolds as a result of the desire to construct buildings with multiple floors in Nigeria has made many contractors use different materials. Thus, this study surveys and compares Steel, Timber and Bamboo scaffolds and props in Nigeria; it specifically investigated material preferences and their cost implications. It also determined installation techniques and the safety of props and scaffolds. Opinion surveys including questionnaire, visual inspections, interviews, and cost analyses were adopted as the research methodology. 50 ongoing building projects in Delta, Anambra, and Edo States were studied. The sample population was 30 site supervisors and 50 prop and scaffold installers. Purposive sampling was used to collect data. The findings reveal that contractors now prefer bamboo to other materials; the joinery systems depend on the material; nailing and tying for bamboo to bamboo while nailing and mechanical accessories were used for timber and steel respectively. Others are, all the materials are safe if properly fabricated and installed and the cost of scaffoldings and props decreases exponentially from steel to timber and then bamboo. Therefore, it was recommended among other materials that bamboo should be used in the production of prop and scaffold to save cost. Again, bamboo construction techniques should be included in the building construction curriculum, especially in scaffold and prop production.

Design and simulation of a User-Friendly solar operated grass cutting device

Conventional grass cutting devices are basically operated either by fuel or electrical energy. These are not environment-friendly and, furthermore, they demand high operational and maintenance costs. Encouraging the use of renewable energy resources is essential for sustainability. This paper proposes the design and fabrication of a solar operated lawn mower. Its blade cutting operation is based on the scotch yoke mechanism. The lawn mower components are presented. In addition, all necessary calculations of converting the solar energy into electrical energy are performed, as well as the calculations on the battery capacity needed and the time to charge. Moreover, structural analysis is done to check the strength of the developed frame and of the blades. The 3D CAD prototype is created, and the structural analysis of the lawn mower are performed by using SolidWorks© software. The design and calculations demonstrate that an efficient and sustainable solar operated lawn mower can be produced at minor costs.

Patient safety in differentiated (in-hospital) activation of the resuscitation room for severely injured patients

Providing trauma services demands high personnel resources and structural costs. The goal of this study was to show if the assignment of trauma patients to adefined A or B resuscitation room treatment as amodified management concept is safe and feasible. Between May 2020 and January 2021, all resuscitation room trauma patients were included in this single center prospective observational study. All patients admitted to the resuscitation room underwent aclassification according to the German S3 guidelines grade of recommendation GoRA and GoRB in polytrauma and the status of the ABCDE sequence to an A and B resuscitation room. The classification was performed by the senior consultant on call via telephone after consultation and discussion of clinical findings. All 135 resuscitation room patients were included in the study of whom 42trauma patients were assigned to the A resuscitation room (A-SR) and 93were assigned to the B resuscitation room (B-SR). The comparison of the two groups showed that patients in the A‑SR group are more likely to be accompanied by aprehospital emergency physician (80.5%) than patients in the B‑SR group (55.5%). Patients in the B‑SR group showed asignificantly higher Glasgow coma scale (GCS). Using the eFAST emergency ultrasound protocol, 2.4% of the A‑SR and 4.3% of the B‑SR patients had trauma-associated pathologies, 26% of the A‑SR and only 3.2% of the B‑SR patients had to be admitted to the ICU, 21.4% of the A‑SR and 1% of the B‑SR patients died within 30days after trauma. The injury severity scores (ISS) of the A‑SR patients were significantly higher than in the B‑SR group (ISS 28.3vs. 6.8). The study confirmed that the assignment by the emergency department consultant according to the German S3guideline in combination with the ABCDE sequence into resuscitation room A or B treatment is feasible, does not compromise the quality of care and is efficient in the use of the personnel resources.

Spark Ignition Engine Modeling Using Optimized Artificial Neural Network

The spark ignition engine is a complex multi-domain system that contains many variables to be controlled and managed with the aim of attending to performance requirements. The traditional method and workflow of the engine calibration comprise measure and calibration through the design of an experimental process that demands high time and costs on bench testing. For the growing use of virtualization through artificial neural networks for physical systems at the component and system level, we came up with a likely efficiency adoption of the same approach for the case of engine calibration that could bring much better cost reduction and efficiency. Therefore, we developed a workflow integrated into the development cycle that allows us to model an engine black-box model based on an auto-generated feedfoward Artificial Neural Network without needing the human expertise required by a hand-crafted process. The model’s structure and parameters are determined and optimized by a genetic algorithm. The proposed method was used to create an ANN model for injection parameters calibration purposes. The experimental results indicated that the method could reduce the time and costs of bench testing.

Validation of micro-chip based PCR assays for diagnosis of both Plasmodium falciparum and Plasmodium vivax

Microscopy is considered as the gold standard for malaria diagnosis, however sub-microscopic infections can only be detected by Polymerase chain reaction, which demands high cost and elaborate laboratory setup. The Micro-chip PCR based Truenat Malaria Pv-Pf and Pf assay is a portable solution for detection of sub-microscopic/asymptomatic cases of malaria in the field, three lots of which were evaluated for P. falciparum and P. vivax malaria. Three lots of Truenat® Malaria Pv-Pf and Pf assay (kits) were assessed using blood samples of P. vivax and P. falciparum as well as malaria negative blood samples. DNA was extracted from the blood samples using the Trueprep Auto v2 Universal Cartridge based sample prep device and real time qPCR was performed using Truelab DUO micro PCR Analyzer with three lots of Truenat® Malaria Pv-Pf and Pf Assays. Mean, Standard deviation and one-way analysis of variance (ANOVA) was used to assess the significance of inter-lot variability in Cycle threshold values. The Truenat® Malaria Pv-Pf and Pf assays identified the malaria parasites with 100% accuracy. Based on the test for variance (ANOVA) the inter-lot variability in cycle threshold values were not significant, indicating a high degree of precision. Based on high accuracy and precision between different lots, the Truenat® Malaria Pv-Pf and Pf assays were found to be suitable for the diagnosis of sub-microscopic infections in field conditions to provide support in elimination of malaria.

Split-GCN: Effective Interactive Annotation for Segmentation of Disconnected Instance.

Annotating object boundaries by humans demands high costs. Recently, polygon-based annotation methods with human interaction have shown successful performance. However, given the connected vertex topology, these methods exhibit difficulty predicting the disconnected components in an object. This article introduces Split-GCN, a novel architecture based on the polygon approach and self-attention mechanism. By offering the direction information, Split-GCN enables the polygon's vertices to move more precisely to the object boundary. Our model successfully predicts disconnected components of an object by transforming the initial topology using the context exchange about the dependencies of vertices. Split-GCN demonstrates competitive performance with the state-of-the-art models on Cityscapes and even higher performance with the baseline models. On four cross-domain datasets, we confirm our model's generalization ability.

Study on the parameterization response of probabilistic neural networks for seismic facies classification in the Gulf of Mexico

Nowadays, there are many unsupervised and supervised machine learning techniques available for performing seismic facies classification. However, those classification methods either demand high computational costs or do not provide an accurate measure of confidence. Probabilistic neural networks (PNNs) overcome these limitations and have demonstrated their superiority among other algorithms. PNNs have been extensively applied for some prediction tasks, but they have not been well studied regarding the prediction of seismic facies volumes using seismic attributes. We have explored the capability of the PNN algorithm when classifying large- and small-scale seismic facies. In addition, we evaluate the impact of user-chosen parameters on the final classification volumes. After performing seven tests, each with a parameter variation, we assess the impact of the parameter change on the resultant classification volumes. We find that the processing task can have a significant impact on the classification volumes, but we also find how the most geologically complex areas are the most challenging for the algorithm. Moreover, we determine that even if the PNN technique is performing and producing considerably accurate results, it is possible to overcome those limitations and significantly improve the final classification volumes by including the geologic insight provided by the geoscientist. We conclude by proposing a new workflow that can guide future geoscientists interested in applying PNNs, to obtain better seismic facies classification volumes by considering some initial steps and advice.

Biomass Derived Activated Carbon for Water Desalination by Capacitive Deionization

Growing population and industrialization is leading the shortage of clean potable water in the world. In this view, desalination of river and ground water can be a solution to produce drinking water for mankind. Reverse osmosis, distillation, ultrafiltration and electro-dialysis are some of the conventionally used techniques for water purification. However, the above- mentioned techniques demand high cost and energy consumption. Capacitive deionization (CDI) is a new type of cost as well as energy effective water desalination technology which involves the physical adsorption/desorption of ions on the electrode surface by applying a low potential difference (~1.2-1.5 V) across a pair of porous carbon electrodes. Herein, we report the synthesis of biomass-derived activated carbon by carbonization and post chemical activation method at high temperature, possessing high Brunauer-Emmet-Teller surface area of 1330 m2 g-1. The prepared activated carbon was characterized by various spectroscopic and microscopic techniques. The desalination performance was tested utilizing a laboratory batch model CDI unit with fixed voltage of 1.2 V and initial salt concentration of 500 ppm. The biomass-derived activated carbon showed an electro-adsorption capacity of ~100 mg g-1, which is very large as compared to the previous reports (~10-20 mg g-1) in comparable experimental conditions. Further, to check the recyclability and regeneration of electrodes, multiple adsorption/desorption cycles were carried out. Interestingly, even after ten continuous cycles, there was no loss in the adsorption capacity. These results illustrate that the present material can be used as an effective electrode material for making high performance and cost-effective real time water desalination unit.

Efficiency of microbial fuel cells in the treatment and energy recovery from food wastes: Trends and applications - A review

The rising global population and their food habits result in food wastage and cause an obstacle in its treatment and disposal. Due to the rapid shift in the lifestyle of the human population and urbanization, almost one-third of the food produced is wasted from various sectors like domestic sources, agricultural sectors, and industrial sectors. These food resources squandered are rich in organic biomolecules which can cause complications upon direct disposal in the environment. Conventional disposal methods like composting, landfills and incineration demand high costs besides causing severe environmental and health issues. To overcome these demerits of the conventional methods and to avoid the loss of rich organic food resources, there is an immediate need for a sustainable and eco-friendly solution for the valorization of the food wastes. Microbial fuel cells (MFCs) are gaining attention, due to their ideal approach in the production of electricity and parallel treatment of organic food wastes. The MFCs are significant as an innovative approach using microorganisms and oxidizing the organic food wastes into bio-electricity. In this review, the recent advancements and practices of the MFCs in the field of food waste treatment and management along with electricity production are discussed. The major outcome of this work highlights the setting up of MFC for the treatment of higher volumes of food waste residues and enhancing the bioelectricity production in an optimal condition. For further improvements in the food waste treatments using MFCs, greater understanding and more research needs are to be focused on the commercialization, different operational modes, operational types, and low-cost fabrication coupled with careful examination of scale-up factors.

Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization.

Coronary artery disease is a major cause of morbidity and mortality worldwide. Its underlying histopathology is the atherosclerotic plaque, which comprises lipid, fibrous and—when chronic—calcium components. Intravascular ultrasound (IVUS) and intravascular optical coherence tomography (IVOCT) performed during invasive coronary angiography are reference standards for characterizing the atherosclerotic plaque. Fine image spatial resolution attainable with contemporary coronary computed tomographic angiography (CCTA) has enabled noninvasive plaque assessment, including identifying features associated with vulnerable plaques known to presage acute coronary events. Manual interpretation of IVUS, IVOCT and CCTA images demands scarce physician expertise and high time cost. This has motivated recent research into and development of artificial intelligence (AI)-assisted methods for image processing, feature extraction, plaque identification and characterization. We performed parallel searches of the medical and technical literature from 1995 to 2021 focusing respectively on human plaque characterization using various imaging modalities and the use of AI-assisted computer aided diagnosis (CAD) to detect and classify atherosclerotic plaques, including their composition and the presence of high-risk features denoting vulnerable plaques. A total of 122 publications were selected for evaluation and the analysis was summarized in terms of data sources, methods—machine versus deep learning—and performance metrics. Trends in AI-assisted plaque characterization are detailed and prospective research challenges discussed. Future directions for the development of accurate and efficient CAD systems to characterize plaque noninvasively using CCTA are proposed.

Mechanistic Aspects of Microbe-Mediated Nanoparticle Synthesis.

In recent times, nanoparticles (NPs) have found increasing interest owing to their size, large surface areas, distinctive structures, and unique properties, making them suitable for various industrial and biomedical applications. Biogenic synthesis of NPs using microbes is a recent trend and a greener approach than physical and chemical methods of synthesis, which demand higher costs, greater energy consumption, and complex reaction conditions and ensue hazardous environmental impact. Several microorganisms are known to trap metals in situ and convert them into elemental NPs forms. They are found to accumulate inside and outside of the cell as well as in the periplasmic space. Despite the toxicity of NPs, the driving factor for the production of NPs inside microorganisms remains unelucidated. Several reports suggest that nanotization is a way of stress response and biodefense mechanism for the microbe, which involves metal excretion/accumulation across membranes, enzymatic action, efflux pump systems, binding at peptides, and precipitation. Moreover, genes also play an important role for microbial nanoparticle biosynthesis. The resistance of microbial cells to metal ions during inward and outward transportation leads to precipitation. Accordingly, it becomes pertinent to understand the interaction of the metal ions with proteins, DNA, organelles, membranes, and their subsequent cellular uptake. The elucidation of the mechanism also allows us to control the shape, size, and monodispersity of the NPs to develop large-scale production according to the required application. This article reviews different means in microbial synthesis of NPs focusing on understanding the cellular, biochemical, and molecular mechanisms of nanotization of metals.

Beneficial microbiomes for bioremediation of diverse contaminated environments for environmental sustainability: present status and future challenges.

Over the past few decades, the rapid development of agriculture and industries has resulted in contamination of the environment by diverse pollutants, including heavy metals, polychlorinated biphenyls, plastics, and various agrochemicals. Their presence in the environment is of great concern due to their toxicity and non-biodegradable nature. Their interaction with each other and coexistence in the environment greatly influence and threaten the ecological environment and human health. Furthermore, the presence of these pollutants affects the soil quality and fertility. Physicochemical techniques are used to remediate such environments, but they are less effective and demand high costs of operation. Bioremediation is an efficient, widespread, cost-effective, and eco-friendly cleanup tool. The use of microorganisms has received significant attention as an efficient biotechnological strategy to decontaminate the environment. Bioremediation through microorganisms appears to be an economically viable and efficient approach because it poses the lowest risk to the environment. This technique utilizes the metabolic potential of microorganisms to clean up contaminated environments. Many microbial genera have been known to be involved in bioremediation, including Alcaligenes, Arthrobacter, Aspergillus, Bacillus, Burkholderia, Mucor, Penicillium, Pseudomonas, Stenotrophomonas, Talaromyces, and Trichoderma. Archaea, including Natrialba and Haloferax, from extreme environments have also been reported as potent bioresources for biological remediation. Thus, utilizing microbes for managing environmental pollution is promising technology, and, in fact, the microbes provide a useful podium that can be used for an enhanced bioremediation model of diverse environmental pollutants.

Assessment of low-cost wireless sensors for structural health monitoring applications

Abstract Structural Health Monitoring (SHM) programs play an essential task in the field of civil engineering, especially for assessing safety conditions involving large structures such as viaducts, bridges, stadiums, and tall buildings. In fact, some of these structures are monitored 24 hours a day, 7 days a week, to supply dynamic measurements that can be used for the identification of structural problems, e.g., presence of cracks, excessive vibration, damage, among others. SHM programs may provide automated assessment of structural health by processing vibration data obtained from sensors attached to the structure. Frequently, SHM uses wired systems, which are usually expensive due to the necessity of continuous maintenance and are not always suitable for sensing remote structures. Conversely, commercial wireless systems often demand high implementation costs. Hence, this paper proposes the use of a low-cost wireless sensing system based on the single board computer Raspberry Pi, which significantly reduces implementation expenses while keeping data’s integrity. The wireless communication is performed in real-time through a local wireless network, responsible for sending and receiving vibration data. The proposed system is validated by comparing its results with a commercial wired system through a series of controlled experimental applications. The results suggest that the proposed system is suitable for civil SHM applications.

Experimental study of the temperature effect on two-phase flow properties in highly permeable porous media: Application to the remediation of dense non-aqueous phase liquids (DNAPLs) in polluted soil

The remediation of aquifers contaminated by viscous dense non-aqueous phase liquids (DNAPLs) is a challenging problem. Coal tars are the most abundant persistent DNAPLs due to their high viscosity and complexity. Pumping processes leave considerable volume fractions of DNAPLs in the soil and demand high operational costs to reach cleaning objectives. Thermally enhanced recovery focuses on decreasing DNAPL viscosity to reduce residual saturation. The oil industry has previously applied this technique with great success for enhanced oil recovery applications. However, in soil remediation, high porous media permeabilities and product densities may invalidate those techniques. Additionally, the impacts of temperature on coal tar's physical properties have not been thoroughly discussed in available literature. Here, we investigated how coal tar's physical properties, the capillary pressure-saturation curve and the relative permeability of two-phase flow in porous media depend on the temperature and flow rate experimentally. Drainage and imbibition experiments under quasi-static (steady-state) and dynamic (unsteady-state) conditions have been carried out at 293.15 K and 323.15 K in a 1D small cell filled with 1 mm homogeneous glass beads. Two different pairs of immiscible fluids have been investigated, coal tar-water and canola oil-ethanol. Results demonstrated similar trends for temperature effect and values of fluid properties for both liquid pairs, which backs up the use of canola oil-ethanol to model coal tar-water flow. It was found that there is no temperature effect on drainage-imbibition curves or residual saturation under quasi-static conditions. In dynamic conditions, the DNAPL residual saturation decreased by 16 % when the temperature changed from 293.15 K to 323.15 K. This drop was mainly linked to decreasing viscous fingering, as well as the appearance of wetting phase films around the glass beads. Both phenomena have been observed only in dynamic experiments. A high enough pumping flow rate is needed to generate dynamic effects in the porous medium. Ethanol and oil's relative permeabilities also increase with temperature under dynamic measurement conditions. Our findings indicate that flow rate is an important parameter to consider in thermal enhanced recovery processes. These effects are not taken into account in the classically used generalized Darcy's law for modeling two-phase flow in porous media with temperature variation.