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Globally, up to 10% of the total annual rice production is wasted due to excessively high moisture content during storage. Mechanized drying of rice is an important measure to reduce this loss. However, traditional hot-air rice dryers have issues such as low drying rates and high energy consumption. This paper introduces a new type of gas-catalytic infrared rice dryer, including its working principle and components. By using drying rate and fissuring rate as evaluation indicators before and after drying, the performance of this dryer is compared with that of traditional hot-air dryers. Further, a three-factor, three-level orthogonal experimental method was employed. Batch processing capacity, conveyor belt speed, and tempering time were selected as variables to calculate the optimal operating conditions of the gas-catalytic infrared rice dryer using the comprehensive balance method. Experimental results show that under nine different operating conditions, the gas-catalytic infrared rice dryer outperforms the traditional hot-air dryer. The drying rate of the gas-catalytic infrared dryer increased by 215.15% compared to the traditional hot-air dryer, and the fissuring rate decreased by 86%. The orthogonal experimental results indicate that, based on a comprehensive evaluation of moisture content difference and fissuring rate, the gas-catalytic infrared dryer achieves the best drying effect when the conveyor belt speed is 1.92 m/min and the tempering time is 40 minutes. These research findings provide important references for further optimization of rice drying technology.

Background The diauxic growth of Saccharomyces cerevisiae on glucose and xylose during cellulose-to-ethanol processes extends the duration of the fermentation and reduces productivity. Despite the remarkable advances in strain engineering, the co-consumption of glucose and xylose is still limited due to catabolite repression. This work addresses this challenge by developing a closed-loop controller that is capable of maintaining the glucose concentration at a steady set-point during fed-batch fermentation. The suggested controller uses a data-driven model to measure the concentration of glucose from ‘real-time’ spectroscopic data. The concentration of glucose is then automatically controlled using a control scheme that consists of a proportional, integral, differential (PID) algorithm and a supervisory layer that manipulates the feed-rates to the reactor accounting for the changing dynamics of fermentation. Results The PID parameters and the supervisory layer were progressively improved throughout four fed-batch lignocellulosic-to-ethanol fermentations to attain a robust controller able of maintaining the glucose concentration at the pre-defined set-points. The results showed an increased co-consumption of glucose and xylose that resulted in volumetric productivities that are 20–33% higher than the reference batch processes. It was also observed that fermentations operated at a glucose concentration of 10 g/L were faster than those operated at 4 g/L, indicating that there is an optimal glucose concentration that maximises the overall productivity. Conclusions Promoting the simultaneous consumption of glucose and xylose in S. cerevisiae is critical to increase the productivity of lignocellulosic ethanol processes, but also challenging due to the strong catabolite repression of glucose on the uptake of xylose. Operating the fermentation at low concentrations of glucose allows reducing the effects of the catabolite repression to promote the co-consumption of the two carbon sources. However, S. cerevisiae is very sensitive to changes in the glucose concentration and deviations from a set-point result in notable productivity losses. The controller structure developed and implemented in this work illustrates how combining data-driven measurements of the glucose concentration and a robust yet effective PID-based supervisory control allowed tight control of the concentration of glucose to adjust it to the metabolic requirements of the cell culture that can unlock tangible gains in productivities.

Global demand for poultry and associated feed are projected to double over the next 30 years. Insect meal is a sustainable alternative to traditional feeds when produced on low-value high-volume agricultural byproducts. Black soldier fly (BSF) larvae ( Hermetia illucens L.) are high in protein and contain methionine, an essential amino acid that is critical to poultry health. BSF larvae can be grown on many organic residues, however, larvae growth and quality vary based on feedstock and cultivation processes. Experiments were completed to monitor temporal changes in BSF larvae growth and composition using almond hulls as a growth substrate under batch and semi-batch processes and with varying substrate carbon to nitrogen ratio (C/N). A logistic kinetic growth model was developed to predict larval biomass and methionine accumulations during batch production. Estimated ranges of model parameters for larvae maximum specific growth rate and carrying capacity were 0.017–0.021 h −1 and 9.7–10.7 g larvae kg −1 hulls dry weight, respectively. Methionine content in larvae increased from 11.1 to 17.1 g kg −1 dry weight over a 30-day batch incubation period. Larvae-specific growth and yield increased by 168% and 268%, respectively, when cultivated in a semi-batch compared to a batch process. Increasing C/N ratio from 26 to 40 increased density of methionine content in larvae per unit feedstock by 25%. The findings demonstrate a logistic model can predict larvae biomass accumulation, harvest time can achieve specific methionine contents, and a semi-batch process is more favorable for larvae biomass accumulation compared to a batch process.

Continuous cell culture-based influenza vaccine production could significantly reduce footprint and manufacturing costs compared to current batch processing. However, yields of influenza virus in continuous mode can be affected by oscillations in virus titers caused by periodic accumulation of defective interfering particles. The generation of such particles has also been observed previously in cascades of continuous stirred tank reactors (CSTRs) and is known as the \"von Magnus effect\". To improve virus yields and to avoid these oscillations, we have developed a novel continuous tubular bioreactor system for influenza A virus production. It was built using a 500 mL CSTR for cell growth linked to a 105 m long tubular plug-flow bioreactor (PFBR). Virus propagation took place only in the PFBR with a nominal residence time of 20 h and a production capacity of 0.2 mL/min. The bioreactor was first tested with suspension MDCK cells at different multiplicities of infection (MOI), and then with suspension avian AGE1.CR.pIX cells at a fixed nominal MOI of 0.02. Maximum hemagglutinin (HA) titers of 2.4 and 1.6 log10(HA units/100 μL) for suspension MDCK cells and AGE1.CR.pIX cells, respectively, were obtained. Flow cytometric analysis demonstrated that 100% infected cells with batch-like HA titers can be obtained at a MOI of at least 0.1. Stable HA and TCID50 titers over 18 days of production were confirmed using the AGE1.CR.pIX cell line, and PCR analysis demonstrated stable production of full-length genome. The contamination level of segments with deletions (potentially defective interfering particles), already present in the virus seed, was low and did not increase. Control experiments using batch and semi-continuous cultures confirmed these findings. A comparison showed that influenza virus production can be achieved with the tubular bioreactor system in about half the time with a space-time-yield up to two times higher than for typical batch cultures. In summary, a novel continuous tubular bioreactor system for cell culture-based influenza virus production was developed. One main advantage, an essentially single-passage amplification of viruses, should enable efficient production of vaccines as well as vectors for gene and cancer therapy.

The bullwhip effect, or demand information distortion, has been a subject of both theoretical and empirical studies in the operations management literature. In this paper, we develop a simple set of formulas that describe the traditional bullwhip measure as a combined outcome of several important drivers, such as finite capacity, batch-ordering, and seasonality. Our modeling framework is descriptive in nature as it features certain plausible approximations that are commonly employed in practical inventory systems. The results are nonetheless compelling and can be used to explain various conflicting observations in previous empirical studies. Building on the theoretical framework, we discuss the managerial implications of the bullwhip measurement. We show that the measurement can be completely noninformative about the underlying supply chain cost performance if it is not linked to the operational details (such as decision intervals and leadtimes). Specifically, we show that an aggregated measurement over relatively long time periods can mask the operational-level bullwhip. In addition, we show that masking also exists under product or location aggregation in some illustrative cases.

In multi-class telecommunications or manufacturing systems, customers belonging to the same class can often be processed together. This results in a service capacity that depends on the classes of the customers in the queue. In this paper, we analyse a discrete-time batch-service queue with two customer classes. The single batch server can group all same-class customers at the head of the queue up to a constant class-dependent maximum service capacity. We focus on the analysis of the system occupancy at service initiation opportunities, and also compute both a light- and heavy traffic approximation in order to reduce the numerical complexity introduced by the maximum service capacities. Additionally, we propose a method for interpolating between these approximations in order to study the behaviour in the intermediate region. We also deduce the system occupancy and its approximations at random slot boundaries. In the numerical experiments, we examine the conditions under which these proposed approximations are accurate.

A wooden matched-die mold was manufactured to develop wood-based corrugated panels. Wood veneers brushed with resin were cold pressed between the mold halves and formed into a corrugated geometry. The corrugated panels were used as a core and bonded to flat veneer-based facesheets to develop sandwich panels. The whole manufacturing process involved a cold-forming technique that allowed panels to be produced with no heat. Specimens cut from both corrugated and sandwich panels were submitted to a four-point bending test to evaluate their structural performance. Adopting the same number of layers used to make the sandwich panels, flat panels were fabricated and tested to find the effect of this corrugated geometry and cold-forming process on the load-carrying capacity of the sandwich structures. A comparison with flat panels made with the same stacking of veneers showed an increase of 272% of the bending stiffness of the sandwich panels, which is known as the sandwich effect. Comparison between the bending results of the panels developed in this study with those manufactured using thermoset resin and hot-pressing technique indicated that the cold-forming process using the wooden mold is an effective and inexpensive method to develop wood-based corrugated sandwich panels.

Background The degradation of cellulose and hemicellulose molecules into simpler sugars such as glucose is part of the second generation biofuel production process. Hydrolysis of lignocellulosic substrates is usually performed by enzymes produced and secreted by the fungus Trichoderma reesei . Studies identifying transcription factors involved in the regulation of cellulase production have been conducted but no overview of the whole regulation network is available. A transcriptomic approach with mixtures of glucose and lactose, used as a substrate for cellulase induction, was used to help us decipher missing parts in the network of T. reesei Rut-C30. Results Experimental results on the Rut-C30 hyperproducing strain confirmed the impact of sugar mixtures on the enzymatic cocktail composition. The transcriptomic study shows a temporal regulation of the main transcription factors and a lactose concentration impact on the transcriptional profile. A gene regulatory network built using BRANE Cut software reveals three sub-networks related to i ) a positive correlation between lactose concentration and cellulase production, i i ) a particular dependence of the lactose onto the β -glucosidase regulation and i i i ) a negative regulation of the development process and growth. Conclusions This work is the first investigating a transcriptomic study regarding the effects of pure and mixed carbon sources in a fed-batch mode. Our study expose a co-orchestration of xyr1 , clr2 and ace3 for cellulase and hemicellulase induction and production, a fine regulation of the β -glucosidase and a decrease of growth in favor of cellulase production. These conclusions provide us with potential targets for further genetic engineering leading to better cellulase-producing strains in industry-like conditions.

Green seaweed Ulva spp. contains dietary fiber and bioactive compounds and can be used as raw material for biscuit products. People from toddlers widely consume biscuits to the elderly. The technique of making biscuits is easy and does not require significant capital. The addition of 1% Ulva flour in biscuit formulations reported could control blood sugar levels. This study aimed to calculate the feasibility of Ulva biscuits production on a household scale with variations in 1 and 2 kg production capacity in 3 replications. The results showed that the yields were 74.94 to 77.02% and were not significantly different. The nutritional contents were also not significantly different, i.e., 2.89 to 3.53% of water content, 2.84 to 3.14% of protein content, 42.61 to 45.03% of fat content, 46.80 to 49.59% of total carbohydrates, and 41.71 to 45.57% of reducing sugar. Based on the calculation of business feasibility with a financial approach, the break-even point (BEP) value will be achieved if a minimum production of 2 batch processes per day is carried out with a production capacity of 15 kg of flour per batch and a working period of 25 days per month. The net present value (NPV) will be reached 85.9 million rupiahs, and the payback period (PP) will be achieved in 14 months.

With the remarkable development and progress of earth-observation techniques, remote sensing data keep growing rapidly and their volume has reached exabyte scale. However, it’s still a big challenge to manage and process such huge amounts of remote sensing data with complex and diverse structures. This paper designs and realizes a distributed storage system for large-scale remote sensing data storage, access, and retrieval, called RSIMS (remote sensing images management system), which is composed of three sub-modules: RSIAPI, RSIMeta, RSIData. Structured text metadata of different remote sensing images are all stored in RSIMeta based on a set of uniform models, and then indexed by the distributed multi-level Hilbert grids for high spatiotemporal retrieval performance. Unstructured binary image files are stored in RSIData, which provides large scalable storage capacity and efficient GDAL (Geospatial Data Abstraction Library) compatible I/O interfaces. Popular GIS software and tools (e.g., QGIS, ArcGIS, rasterio) can access data stored in RSIData directly. RSIAPI provides users a set of uniform interfaces for data access and retrieval, hiding the complex inner structures of RSIMS. The test results show that RSIMS can store and manage large amounts of remote sensing images from various sources with high and stable performance, and is easy to deploy and use.