Terms Of Process Efficiency Research Articles

Efficient design of energy microgrid management system: A promoted Remora optimization algorithm-based approach

Microgrids are a promising solution for decentralized energy generation and distribution, offering reliability, efficiency, and resilience. These small-scale power systems can operate independently or connect to the main grid, providing greater reliability and resilience. However, integrating renewable energy into microgrids presents challenges due to their unpredictable nature and fluctuating load of electricity. Energy management strategies play a crucial role in optimizing the operation of microgrids, aiming to balance electricity supply and demand, maximize renewable energy utilization, and minimize operational costs. Various approaches have been proposed for energy management in microgrids, including optimization algorithms, machine learning techniques, and intelligent control systems. This study proposes an optimized and efficient strategy for microgrids operating in both independent and grid-connected modes, focusing on microgrids that utilize a combination of solar and green energy sources. The proposed approach, based on the Promoted Remora Optimization (PRO) algorithm, aims to meet load power requirements at the lowest possible cost while ensuring constant DC bus voltage and safeguarding batteries against overcharging and depletion. The CRO method effectively optimized the charging process, maintaining a consistent level of charge and achieving a final SoC of 33.37 %–33.60 %. It also demonstrated high system efficiency, with an average of 87.99 %, and a range of 87.80 %–88.03 %. The optimizer efficiency ranged from 83.12 % to 86.52 %, with an average of 86.46 %. The CRO method also achieved reasonable operating costs, with a cost per power of $0.1687/kW to $0.1699/kW and a daily cost of $1,379,595 to $1,479,998. Overall, the CRO method showed promise in optimizing the charging process in terms of efficiency and cost-effectiveness. Comparative analysis with existing literature is conducted to evaluate the effectiveness of the proposed approach, demonstrating its superior results compared to other energy management strategies for microgrids. This study contributes to the field of microgrid energy management by providing a novel approach based on the PRO algorithm and demonstrating its effectiveness through comparative analysis.

Effectiveness Analysis of Hydraulic Torque Wrench Machine Using Failure Mode and Effect Analysis (FMEA) and Logic Tree Analysis Study Case on Heavy Equipment Manufacturing

Production quality in terms of process efficiency and quality in the manufacturing industry must always be improved in order to maintain customer confidence. PT XYZ as a heavy equipment assembly company is one of the companies that depends on process reliability for a smooth production process. Based on this, the problems raised in this study focus on increasing the efficiency of the process of installing bolts on slew bearings. By using Overall Equipment Efficiency (OEE) and Process Capability (CpK) as the main benchmarks for measuring the quality of the production process where the latest data shows the average OEE value is at 18.53%, while the CpK value for the bolt tightening process is at 0 ,67. The OEE and CpK figures obtained show that the process quality is still not optimal and needs to be improved. The purpose of this research is to identify and prevent as many factors as possible that can lead to process failure. The methods used to evaluate processes and to identify where and how a process might fail are Failure Mode and Effect Analysis (FMEA) and Logic Tree Analysis (LTA). Both methods are used to identify and prevent as many factors as possible that can lead to a process failure. The results of research using the FMEA and LTA methods show that in the process of installing slew bearing bolts there is a process that needs to be improved because the RPN value is quite high, namely above 125. Some suggestions for improvement such as the use of a manipulator arm on a torque tool and the implementation of a manufacturing execution system (MES) can reduce the RPN value from above 125 to 28, where the process obtained is better than before.

Extraction of Caffeine from Spent Coffee Ground by Solid-liquid Extraction

The current research aims to utilize the spent coffee ground as a feedstock which is a waste material with a negative effect on the environment to extract natural bioactive valuable caffeine and determine the effective parameters of the extraction process efficiency in terms of caffeine concentration. The key studied parameters included extraction time 0- 150 min, temperature 25-55˚C, mixing speed (180-450 rpm), pH of suspension (4-9), and solvent type. The results of the experimental work showed that changing the pH of the suspension has a significant impact on the recovery rate of caffeine. When only water was used as a solvent, the concentration of caffeine increased from 135.061 (mg/L) to 2478.179 (mg/L) by increasing the pH of the suspension to 9. Another promising finding is that by changing the solvent type to an aqueous organic solvent, where the recovery of caffeine augmented remarkably. When 20% ethanol-water was utilized as a solvent and at the pH of 6 (the original pH) of the suspension, the concentration of obtained caffeine increased from 135 mg/L to 213 mg/L. Furthermore, increasing the ethanol percentage to 80%, rising the caffeine concentration to 464 mg/L at the same pH. adjusting the pH of the suspension to 7, resulted in rising the obtained caffeine concentration to 2386.13 mg/l with a solvent concentration of 80% ethanol.

Impact of ionic liquid's cation alkyl chain length and reaction time on cellulose nanocrystals preparation

Traditional methods to obtain cellulose nanocrystals typically involve mechanical and chemical processes and develop an improved process in terms of efficiency, sustainability, and the quality of CNCs produced are interesting. In this sense, we aimed to prepare cellulose nanocrystals (CNCs) from the hydrolysis of microcrystalline cellulose using protic ionic liquids (PILs), named 3-diethylamino-propylammonium hexanoate ([DEAPA][Hex]), 3-dimethylamino- 1-propylammonium hexanoate ([DMAPA][Hex]), and propylammonium hexanoate ([PA][Hex]) at different reaction times. The PILs demonstrated efficiency in producing cellulose nanocrystals, regardless of the cation size and reaction times. However, as expected the properties of the CNCs varied depending on the studied condition. The highest yield was observed in DMAPA[Hex], with a 34 % conversion. Crystalline indices decreased independent of the cation sizes and reaction times. Thermal stabilities were shifted to higher temperatures up to 92 ºC probably due to PILs cation sizes. In contrast, increasing reaction times decreased nanocrystals’ thermal stabilities up to 51ºC. So, protic ionic liquids (PILs) can be considered more environmentally friendly or sustainable solvents compared to traditional organic solvents for preparing cellulose nanocrystals. In the present work, it is reported an alternative method for obtaining CNCs and additionally provide the best preparation conditions for achieving important properties of this nanomaterial, with the potential for various applications.

From Roxy to Mini-Roxy: The Next Step Towards an Efficient Method for Oxygen Extraction from Regolith

Future exploration missions to the Moon and beyond will be dependent on the use of lunar regolith to produce metals/alloys and oxygen, provided they can be produced very efficiently such that their mass exceeds the mass of any needed consumables or spares to sustain the process. Among the many methods that have been studied so far, molten salt electrolysis with solid oxide membranes appears to be most promising since it meets all of the viability criteria. A specific implementation of this method to lunar applications called ROXY (Regolith to Oxygen and Metals) has been developed and tested, and the design and operations of related demonstration and production facilities have been investigated. As a next step, a miniaturized version of the ROXY cell has been developed, leading to the Mini-ROXY concept and further improvements in terms of process efficiency, and is a new starting point for upscaling the technology.

Drilling Sequence Optimization Using Evolutionary Algorithms to Reduce Heat Accumulation for Femtosecond Laser Drilling with Multi-Spot Beam Profiles.

We report on laser drilling borehole arrays using ultrashort pulsed lasers with a particular focus on reducing the inadvertent heat accumulation across the workpiece by optimizing the drilling sequence. For the optimization, evolutionary algorithms are used and their results are verified by thermal simulation using Comsol and experimentally evaluated using a thermal imaging camera. To enhance process efficiency in terms of boreholes drilled per second, multi-spot approaches are employed using a spatial light modulator. However, as higher temperatures occur across the workpiece when using simultaneous multi-spot drilling as compared to a single-spot process, a subtle spatial distribution and sequence of the multi-spot approach has to be selected in order to limit the resulting local heat input over the processing time. Different optimization approaches based on evolutionary algorithms aid to select those drilling sequences which allow for the combination of a high efficiency of multi-spot profiles, a low-generated process temperature and a high-component quality. In particular, using a 4 × 4 laser spot array allows for the drilling of 40,000 boreholes in less than 76 s (526 boreholes/s) with a reduced temperature increase by about 35%, as compared to a single spot process when employing an optimized drilling sequence.

Glycerol used for denitrification in full-scale wastewater treatment plants: nitrous oxide emissions, sludge acclimatization, and other insights.

Glycerol is commonly employed for denitrification purposes in full-scale wastewater treatment. In non-acclimatized biomass, the glycerol is very inefficient resulting in a high C/N ratio and low-standard denitrification rates. The acclimatization is driven by the microbial enrichment of Saccharimonadales and Propionibacteriales as found in different sampled municipal sludges flanking the dominant presence of Burkholderiales. The selective strategy is based on a very efficient process in terms of C/N ratios and standard denitrification rates, but it leads to nitrite accumulation. As a result, severe and unexpected nitrous oxide emissions were found in full-scale with emission factors up to 2.5% kgN2O (kgKJNremoved)-1. Simultaneous dosage of isobutirate in a full-scale experiment could counter the nitrous oxide emissions. As nitrous oxide emissions were found proportional to the dosed glycerol-based COD, the authors suggest that, in case of acclimatization of biomass to glycerol, an emission factor based on the dosed COD should substitute the general nitrous oxide emission factors based on incoming or removed nitrogen to the plant.

Recent Trends in Fermented Beverages Processing: The Use of Emerging Technologies

Since ancient times, fermentation has been one of the most utilized techniques for food preservation and for the development of natural products with functional properties at low cost. Nowadays, fermented foods and beverages are highly attractive to consumers since they are perceived as natural and potential sources of functional compounds. Research efforts conducted in this area over the years have allowed for an understanding of the main reactions occurring during fermentation related to microbial growth, enzyme activity, metabolite production, and physicochemical changes. As a result, scientists and technologists have been able to improve the fermentation process in terms of efficiency, safety, costs, and high-quality production of products. The aim of this review was to gather the most recent and relevant information about fermentation evolution during the last decades, focused on the application of emerging technologies for the development of fermented beverages as interesting products in the functional food market.

Towards the development of efficient, economic and environmentally friendly downstream processing for bio-based succinic acid

Succinic acid (SA) is among the top value-added platform chemicals that can be produced from renewable resources including organic wastes via microbial fermentation. Extensive studies have been witnessed in the last decades on the feedstock pretreatment and fermentation processes for SA production. However, the recovery and purification of SA from fermentation broth, dubbed downstream processing (DSP), has been overlooked. The major challenge in the DSP of bio-based SA is associated with the availability of low concentration of SA in the complex fermentation broth. Hence, the current study was systematically designed to assess recent efforts in the development of efficient, economic and sustainable DSP for bio-based SA ranging from small-scale to large-scale production schemes. This review presents a critical discussion of SA with regards to bio-based and petrochemical production routes, recent attempts of DSP, commercial-scale production, techno-economic analyses, as well as challenges and prospects in the DSP of SA. In general, the effectiveness the DSP of bio-based SA can be evaluated in terms of process efficiency, economics, and environmental aspects. To this end, the current review is believed to provide a comprehensive up-to-date insights to build a competitive SA bioproducing industries that could assist the quest towards the development of circular economy and sustainable future.

Large-Scale Experimental Simulations of In Situ Coal Gasification in Terms of Process Efficiency and Physicochemical Properties of Process By-Products

This paper presents a series of surface experiments simulating underground coal gasification (UCG). The main goal of the experiments was to investigate the influence of the gasification medium and the coal rank on the gasification process. Four multi-day trials were carried out using a laboratory gasification facility designed for the large-scale experimental simulations of UCG and located in the Experimental Mine “Barbara”, located at Mikołów, Poland. Two Polish bituminous coals were investigated: coal sourced from “Piast-Ziemowit” mine and coal sourced from “Wesoła” mine. Each of the two coals was gasified in two separate experiments using oxygen-enriched air (OEA) and pure oxygen as the respective gasifying agents. Gasification with oxygen resulted in significantly higher gas quality and higher process efficiency than gasification with OEA. Higher concentrations of hydrogen (23.2% and 25.5%) and carbon monoxide (31.8% and 33.4%) were obtained when oxygen was used as a gasifying reagent, while lower concentrations were obtained in the case of gasification with OEA (7.1% and 9.5% of hydrogen; 6.4% and 19.7% of carbon monoxide). Average gas calorific values were 7.96 MJ/Nm3 and 9.14 MJ/Nm3 for the oxygen experiments, compared to 2.25 MJ/Nm3 and 3.44 MJ/Nm3 for the OEA experiments (“Piast-Ziemowit” coal and “Wesoła” coal, respectively). The higher coalification degree of “Wesoła” coal (82.01% of carbon) compared to the “Piast-Ziemowit” coal (68.62% of carbon) definitely improves the gas quality and energy efficiency of the process. The rate of water condensate production was higher for the oxygen gasification process (5.01 kg/h and 3.63 kg/h) compared to the OEA gasification process (4.18 kg/h and 2.63 kg/h, respectively), regardless of the type of gasified coal. Additionally, the textural characteristics (porosity development) of the chars remaining after coal gasification experiments were analyzed. A noticeable development of pores larger than 0.7 nm was only observed for the less coalified “Piast-Ziemowit” coal when analyzed under the more reactive atmosphere of oxygen.

Drivers of exploitative and explorative innovation efficiency

In today's fast-changing world, it is essential not only to be innovative but also to innovate efficiently. The latter can be measured through the multi-faceted construct of innovation efficiency. While researchers recently have started investigating factors and practices fostering innovation efficiency, the fact that radical and incremental innovations require different structures and approaches has not been considered yet. This study, therefore, merges the innovation efficiency literature with the ambidexterity literature and divides innovation efficiency into exploitative and explorative innovation activities. As competition is an essential variable affecting innovation, this study explores its influence on explorative as well as exploitative innovation processes in terms of efficiency. Whereas exploitative and explorative innovation activities come together within general innovation efficiency to positively influence turnover growth, separately they have no effect on it. Data Envelopment Analysis is applied to determine the innovation efficiency, and ordinary linear and Tobit regressions are used to uncover different modes of operation of exploitative and explorative innovation activities. The results indicate that price competition hampers exploitative innovation efficiency, whereas explorative innovation efficiency might improve through outside pressure of product and quality competition. The results provide academics with a new perspective on explorative and exploitative innovation management, contribute to further detangling drivers and factors behind innovation efficiency, and help practitioners to better understand drivers of efficiency for the respective innovation processes.

Damage assessment of soybean and redroot amaranth plants in greenhouse through biomass estimation and deep learning-based symptom classification

Greenhouse plant assessment is key part in the process of developing and testing new herbicides as it serves to analyze the response of the species to those different products and doses in a controlled way. With that purpose, trials are carried out in greenhouse where the damage in the treated plants is daily assessed. This assessment of every pot is often performed in comparison with an untreated reference pot, also named as control pot. This assessment is currently done pot by pot through a time-consuming process which consists of visual assessments done by experts in the field. Digital tools to reduce time and to endow the experts with more objective and repetitive methods for establishing the damage in the plants are required.A novel solution based on image processing and deep learning techniques is proposed to estimate the damage in the plants in different growing stages in the greenhouse. Different damage types and in different stages are produced in plants and images of them are acquired to create a dataset. The available annotation is the damage estimation value provided by the experts. The proposed methodology tries to emulate the way the experts estimate the damage over the plants through a two-step procedure. First, the biomass reduction of the assessed plant compared to the corresponding control plant is calculated, and secondly, the possible disease symptoms in the plant are detected. The first part is done using classical image processing techniques and the second part relies on a deep learning based multi-label classification model for symptom classification.The algorithm has been tested over two species: Glycine max (soybean) and Amaranthus retroflexus (redroot amaranth). An R2 of 0.87 and 0.89 respectively is obtained for the damage estimation. The method improves the performance of the current manual process in terms of efficiency and objectivity.

The structural maintenance process of existing bridges integrated in BIM tools

The heritage of Italian bridges is very vast and varied be-cause of the geographical and orographic conformation of the territory. Existing national road and highway bridges are subjected to periodical inspections and, in some cases, urgent structural measures. The definition of a control and maintenance strategy is necessary to preserve and guarantee an acceptable level of safety and functionality of existing construction. Digital transformation is promoting new operating methods for the Facility Management due to the IoT, Big Data, Artificial Intelligence. The study aims to assess a new digital method supported by BIM tools that allow to improve structural maintenance processes in terms of efficiency, quality and speed. The method proposed is characterized by the use of the Building Condition Assessment to collect physical and performance information of the infrastructure. This information is digitalized in BIM and integrated with operational and maintenance attributes. Once the BIM model has been completed, the final purpose is to manage structural maintenance procedures.

Designing Process-based Chatbots in Enterprises: The Case of Business Travel Organization Considering the Users’ Perspective and Business Value

Chatbots have attracted much research attention in recent years, and organizations have increasingly begun applying them in everyday working life. However, researchers have rarely investigated how chatbots can support everyday tasks in enterprises. As such, we lack design knowledge for chatbots that support internal business processes since research has mostly examined customer-facing use cases. Notably, researchers have rarely considered chatbots’ economic and user-related effects, which, thus, remain unknown. To address this gap, we conducted a design science research study to survey a process-based chatbot application for business processes. From examining the scenario, we deduced design principles and implemented a software artifact. We evaluated the concept with 69 participants and surveyed the users’ perspective in terms of design and acceptance and the organizational perspective in terms of process efficiency and quality. In doing so, 1) we derived six design principles for process-based chatbots and implemented a respective chatbot, which enabled a user-adapted process and provided situational-dependent input options and support; 2) we found that users had a positive attitude towards using chatbots for business processes in terms of user experience and acceptance; and 3) the process performed at an economically efficient level that compared well with existing solutions and that IT affinity and prior experience had no influence on performance. Furthermore, our solution improved the process quality compared to the existing solution.

High Ion‐Selectivity of Garnet Solid Electrolyte Enabling Separation of Metallic Lithium

Ionic selectivity is of significant importance in both fundamental science and practical applications. For instance, an ion‐selective material allows the passage of a particular kind of ions while blocking the others, which could be used for purification of materials. Herein, the Li‐ion‐selectivity of a garnet‐type solid electrolyte is discussed by comparing the difference of activation energy between different ions migrating in solids. The high ion‐selectivity is confirmed by harvesting high‐purity metallic lithium (99.98 wt%) from low‐lithium‐purity sources (80 wt%) at a moderate temperature (190 °C). This gives it huge potential in separating lithium with impurities especially alkali and alkali‐earth elements. The cost of metallic lithium production is only 25% of the international lithium price. The proposed electrochemical metallic lithium separating method is advantageous compared with the traditional process in terms of efficiency, safety, and cost.

Green heterogeneous catalysts for cleaner solvent-free production of acetates

The development of new chemical synthetic methodologies that transform industrial chemical processes into more sustainable ones, constitutes one of the challenges and objectives of chemical research both in academia and in industry. The use of activated carbons as heterogeneous catalysts represents one of the most beneficial options for process efficiency in terms of reaction rate, yield, and ease of work-up. We have produced six new activated carbons by treatment of three affordable commercial carbons with either nitric acid, or with sulfuric acid. The complete characterization of these nine activated carbons has been carried out through the measurement of nitrogen adsorption capacity, porosimetry, elemental organic analysis, X-ray photoelectron spectroscopy, scanning electron microscopy and determination of the point of zero charge; transmission electron microscopy was also performed on two of them. The catalytic activity of these nine catalysts has been tested in the acetylation reaction of hydroxyl groups, undoubtedly one of the most versatile and widely used chemical transformations both at the laboratory and industrial scale. The results show that by means of a simple and affordable modification of commercial xerogel with sulfuric acid, a more efficient catalyst is formed. Acetylation with the best catalyst is completed in 90 min at room temperature and the product is easily isolated in quantitative yield. The system can be reutilized for five runs with only a small loss of catalytic activity.

High-throughput interspecies profiling of acidic plant hormones using miniaturised sample processing

BackgroundAcidic phytohormones are small molecules controlling many physiological functions in plants. A comprehensive picture of their profiles including the active forms, precursors and metabolites provides an important insight into ongoing physiological processes and is essential for many biological studies performed on plants.ResultsA high-throughput sample preparation method for liquid chromatography–tandem mass spectrometry determination of 25 acidic phytohormones classed as auxins, jasmonates, abscisates and salicylic acid was optimised. The method uses a small amount of plant tissue (less than 10 mg fresh weight) and acidic extraction in 1 mol/L formic acid in 10% aqueous methanol followed by miniaturised purification on reverse phase sorbent accommodated in pipette tips organised in a 3D printed 96-place interface, capable of processing 192 samples in one run. The method was evaluated in terms of process efficiency, recovery and matrix effects as well as establishing validation parameters such as accuracy and precision. The applicability of the method in relation to the amounts of sample collected from distantly related plant species was evaluated and the results for phytohormone profiles are discussed in the context of literature reports.ConclusionThe method developed enables high-throughput profiling of acidic phytohormones with minute amounts of plant material, and it is suitable for large scale interspecies studies.

Real-time prediction of the mechanical behavior of suction caisson during installation process using GA-BP neural network

Due to the short construction period, convenient transportation and strong geological adaptability, the suction caisson has received more and more attention in offshore geotechnical foundation engineering associated with oil and gas production platforms. A good understanding of the mechanical behaviors of soils, such as real-time effective stress and settlement, around the suction caisson during its installation is important for analyzing the stability and loading capacity of the platforms in deep water. The objective of this research is to develop a numerical model for predicting the mechanical behavior of soils around the suction caisson during installation based on the data including real-time settlement and effective stress produced from the centrifuge tests in the literature by using the genetic algorithm-back propagation (GA-BP) neural network method. Furthermore, the nonlinear relationship among the settlement, penetration pressure, effective stress, and suction required during the installation is thoroughly investigated. It is found that, compared with the experimental results, the relative error of the prediction results from the proposed model is −0.3%∼1.4% for settlement, 0.8%∼2.3% for effective lateral stress in a single clay layer, and −2.5%∼4.5% for normalized required suction in multilayered soils at the final stage. It can be concluded that the GA-BP neural network method can be used to predict the real-time hydromechanical behavior of the caisson foundation during the installation process in terms of efficiency and accuracy.

Experimental Investigation of a New Modular Crusher Machine Developed for Olive Oil Extraction Plants.

The crushing system is crucial in the virgin olive oil (VOO) mechanical extraction process. The use of different crusher machines can highly influence the quality of the final product, mainly due to the phenolic and volatile content responsible for VOO sensory and health properties. An experimental investigation was conducted to evaluate the effect of the geometric features of a new model of crusher machine for olives. The crusher machine consists of interchangeable rotors: a rotor with hammers and a rotor with knives. The evaluation was carried out with the same fixed grid in stainless steel with 6 mm diameter circular holes. An evaluation was carried out on the impact of the crusher tools on the pit particle size and on the distribution of energy and temperature. The performance of the plant was also assessed in terms of process efficiency and olive oil quality. The results showed that the specific energy released by the tool per unit of product, calculated through both energy conservation and comminution theory, is about 25–27% higher in the case of hammers. Since the impact energy is mainly dissipated in the product as heat, the temperature reached during milling operations with the hammer crusher was also higher by the same percentage with respect to the knife crusher. This has important consequences on the quality of the product: the new knife rotor used in the crushing phase produced an improvement in VOO quality, relating mainly to sensory attributes and the health-enhancing properties of the final product. The ability of the crusher to break cell walls and vacuoles, thus releasing the oil contained therein, is comparable for the two different rotors.

Synergistic effects on itaconic acid production in engineered Aspergillus niger expressing the two distinct biosynthesis clusters from Aspergillus terreus and Ustilago maydis

BackgroundItaconic acid (IA) is a versatile platform chemical widely used for the synthesis of various polymers and current methods for IA production based on Aspergillus terreus fermentation are limited in terms of process efficiency and productivity. To construct more efficient IA production strains, A. niger was used as a chassis for engineering IA production by assembling the key components of IA biosynthesis pathways from both A. terreus and Ustilago maydis.ResultsRecombinant A. niger S1596 overexpressing the A. terreus IA biosynthesis genes cadA, mttA, mfsA produced IA of 4.32 g/L, while A. niger S2120 overexpressing the U. maydis IA gene cluster adi1, tad1, mtt1, itp1 achieved IA of 3.02 g/L. Integration of the two IA production pathways led to the construction of A. niger S2083 with IA titers of 5.58 g/L. Increasing cadA copy number in strain S2083 created strain S2209 with titers of 7.99 g/L and deleting ictA to block IA degradation in S2209 created strain S2288 with IA titers of 8.70 g/L. Overexpressing acoA to enhance the supply of IA precursor in strain S2288 generated strain S2444 with IA titers of 9.08 g/L in shake flask.ConclusionRecombinant A. niger overexpressing the U. maydis IA biosynthesis pathway was capable of IA accumulation. Combined expression of the two IA biosynthesis pathways from A. terreus and U. maydis in A. niger resulted in much higher IA titers. Furthermore, increasing cadA copy number, deleting ictA to block IA degradation and overexpressing acoA to enhance IA precursor supply all showed beneficial effects on IA accumulation.