Processing Capacity Research Articles

Goal-directed attention transforms both working and long-term memory representations in the human parietal cortex.

The abundance of distractors in the world poses a major challenge to our brain's limited processing capacity, but little is known about how selective attention modulates stimulus representations in the brain to reduce interference and support durable target memory. Here, we collected functional magnetic resonance imaging (fMRI) data in a selective attention task in which target and distractor pictures of different visual categories were simultaneously presented. Participants were asked to selectively process the target according to the effective cue, either before the encoding period (i.e., perceptual attention) or the maintenance period (i.e., reflective attention). On the next day, participants were asked to perform a memory recognition task in the scanner in which the targets, distractors, and novel items were presented in a pseudorandom order. Behavioral results showed that perceptual attention was better at enhancing target memory and reducing distractor memory than reflective attention, although the overall memory capacity (memory for both target and distractor) was comparable. Using multiple-voxel pattern analysis of the neural data, we found more robust target representation and weaker distractor representation in working memory for perceptual attention than for reflective attention. Interestingly, perceptual attention partially shifted the regions involved in maintaining the target representation from the visual cortex to the parietal cortex. Furthermore, the targets and distractors simultaneously presented in the perceptual attention condition showed reduced pattern similarity in the parietal cortex during retrieval compared to items not presented together. This neural pattern repulsion positively correlated with individuals' recognition of both targets and distractors. These results emphasize the critical role of selective attention in transforming memory representations to reduce interference and improve long-term memory performance.

Techno-economic assessment and carbon pricing analysis for economic feasibility of epoxidized sucrose soyate: A biobased thermoset resin

The substantial environmental issues associated with plastic production have prompted researchers to accelerate the development of environmentally friendly biobased alternatives to reduce reliance on petroleum-based resources and mitigate emissions. Epoxidized Sucrose Soyate (ESS), a high-performance biobased epoxy resin obtained from soybean oil and sucrose, has shown promising potential in polymers and coatings applications. The success of ESS performance necessitates further investigations into its industrial-scale production and viability as an environmentally sustainable alternative to conventional petroleum-based resins. This study consists of a comprehensive techno-economic analysis (TEA) and cradle-to-gate life cycle assessment (LCA) to evaluate the technical, economic, and environmental feasibility of industrial-scale ESS production. The minimum selling price (MSP) of ESS at various production scales was estimated which offers insights into cost optimization. The MSP for 0.1, 1.0, and 10 ton/h processing capacity of sucrose soyate was calculated to be $9.57, $6.74, and $6.62 per kg of ESS, respectively. Relative to a comparable petroleum-based epoxy resin with similar functionality, such as bisphenol A diglycidyl ether (with a price range of $1.8 to $5.2 per kg), larger scales of ESS production have the potential to compete economically. The LCA results demonstrated the superior environmental performance of ESS, especially in the global warming potential category, indicating its potential as a compelling sustainable choice for replacing petroleum-based resins. This combined TEA and LCA study demonstrated the economic viability and environmental benefits of ESS, highlighting its promise as a sustainable alternative for industrial applications.

Bioprocess Design and Technoeconomic Analysis of 2,3-Butanediol Production in Wood-Based Biorefineries

2,3-Butanediol (BDO) is a crucial precursor in various industries, traditionally derived from fossil resources, raising environmental concerns. This study evaluates the techno-economic feasibility of producing BDO from wood residues, a sustainable resource abundantly available in Nordic countries. By modeling a biorefinery plant with a daily capacity of 100 metric tons of wood chips, three scenarios (Sc.) were explored: Sc. 1, where BDO is the sole product; Sc. 2, where BDO is produced alongside methane and biofertilizer; and Sc. 3, which incorporates a combined heat and power system using biogas from the waste stream. The analysis emphasizes the minimum selling price (MSP) of BDO, revealing it to be lowest in Sc. 1 at USD2.97/kg, compared to USD3.20/kg and USD3.48/kg for Sc. 2 and Sc. 3, respectively. Notably, sensitivity analysis highlighted the impact of processing capacity on economic performance, suggesting a potential for higher scalability and profitability in Sc. 2. This study contributes novel insights into the role of processing capacity and fermentation yield in optimizing BDO production, providing a valuable framework for technology developers aiming to establish wood-based biorefineries. These findings not only enhance understanding of economic thresholds but also underscore the importance of resource efficiency and strategic planning in bio-based production setups.Graphical abstract

STUDYING THE IMPACT OF THE VOLUME OF WORK AT THE RAILCAR TRANSFER POINT ON THE NEED FOR TRACK STORAGE CAPACITY FOR BOGIES

Purpose. In the context of military aggression by moscow, export cargo flows, which were largely transported by sea from Ukraine's Black Sea ports, were directed towards western land crossings. At the same time, exporters were trying not only to find new logistics routes but also to increase exports to European countries. This resulted in longer queues at land borders, both road and rail, and the turnover of railcars and their individual components became uncontrollable and unpredictable. The reason for the downtime of cargo in railroad cars at the borders was the limited processing capacity of railcar interchange points and the transshipment capacity of cargo terminals at border stations. One of the elements of the cargo border crossing system, the increase of which will increase the volume of export cargo flow, is the points of change of wagons from 1435 mm gauge to 1520 mm gauge. Therefore, the aim of this study is to determine the required track capacity for storing 1520 mm and 1435 mm gauge bogies under conditions of daily uneven transportation and the stochastic nature of the turnover of cars on the territory of European railways. Methodology. Simulation modeling, mathematical statistics, and inventory management methods were used to study the impact of the workload of a railcar transfer point on track capacity. Results. As a result of the research, the numerical characteristics of a random variable of the number of cars transferred to the transfer point during the day, as well as the value of car turnover in Europe, were obtained. A methodology for determining the required track capacity for storing bogies based on simulation modeling of the operation of the railcar interchange points was developed. The dependence of the guaranteed stock of bogies of 1435 mm gauge at the station on the daily number of cars serviced at the railroad car transfer point was obtained. Practical significance. The obtained dependences of the required capacity of the tracks for storing bogies on the daily number of cars arriving at the transfer point will allow us to check and, if necessary, bring the existing track development of border stations into line with the calculated volumes of work.

Effect of β-glucans on rainbow trout (Oncorhynchus mykiss) IgM+ B cells

β-glucans are carbohydrates present in the cell wall of many fungi, which are often used as immunostimulants in feeds for farmed species. Their capacity to activate innate immune responses directly acting on innate cell populations has been widely documented in fish. However, whether they can affect the functionality of adaptive immune cells has been scarcely explored. In this context, in the current work, we have determined the effects of β-glucans on rainbow trout blood IgM+ B cells in the presence or absence of 2,4,6-trinitrophenyl hapten conjugated to lipopolysaccharide (TNP-LPS), a model antigen. For this, rainbow trout peripheral blood leukocytes were incubated with different doses of β-glucans or media alone in the presence or absence of TNP-LPS for 48 h. The size, levels of expression of surface MHC II, antigen processing and phagocytic capacities and proliferation of IgM+ B cells were then studied by flow cytometry. The number of IgM-secreting cells in the cultures was also estimated by ELISpot. β-glucans significantly decreased the levels of surface MHC II expression and the antigen processing capacities of these cells, especially in the presence of TNP-LPS, while they increased their phagocytic activity. On their own, β-glucans slightly activated the proliferation of IgM+ B cells but reduced that induced by TNP-LPS. In contrast, β-glucans significantly increased the number of cells secreting IgM in the cultures. This effect of β-glucans on the IgM-secreting capacity of B cells was also confirmed through a feeding experiment, in which the IgM-secreting capacity of blood leukocytes obtained from fish fed a β-glucan-supplemented diet for one month was compared to that of leukocytes obtained from fish fed a control diet. Altogether, these findings contribute to increase our knowledge regarding the effects of β-glucans on fish adaptive responses.

Optimization of catalyst service cycle and start-up considering the reactor-distillation-HEN integration and climate

Considering the catalyst deactivation and seasonal temperature variation, a systematic method is proposed for clarifying the dynamic variation of system operating parameters and targeting the optimal catalyst regeneration cycle and start-up date. Relationships between catalyst activity, reactor inlet and outlet temperatures, reactor heat load, and running time are deduced, as well as that between column temperatures, pressures, energy demands, processing capacity, and production month. Diagrams are constructed to illustrate the parameter variations. With the energy consumption and processing capacity combined, an evaluation index is introduced for integrating the reactor-separator-heat exchanger network (HEN) and optimizing the production start-up date. The proposed method is intuitive and efficient and can be used for system design, guiding production, or fault diagnosis. A benzene alkylation process is studied; the optimal regeneration cycle of the ZSM-5 catalyst is 11 months, and the best start-up date is August, saving 2.32 × 105 kgce (kg standard coal) per production cycle.

High-dimensional two-photon quantum controlled phase-flip gate

High-dimensional quantum systems have been used to reveal interesting fundamental physics and to improve information capacity and noise resilience in quantum information processing. However, it remains a significant challenge to realize universal two-photon quantum gates in high dimensions with high success probability. Here, by considering an ion-cavity QED system, we theoretically propose, to the best of our knowledge, the first high-dimensional, deterministic, and universal two-photon quantum gate. By using an optical cavity embedded with a single trapped Ca+40 ion, we achieve a high average fidelity larger than 98% for a quantum controlled phase-flip gate in four-dimensional space, spanned by photonic spin angular momenta and orbital angular momenta. Our proposed system can be an essential building block for high-dimensional quantum information processing, and also provides a platform for studying high-dimensional cavity QED. Published by the American Physical Society 2024

The technical, economic, and environmental assessment of solvothermal liquefaction processes: An experimental and simulation study on the influence of solvent reichardt parameter

This study explored solvothermal liquefaction (STL) as a viable method for repurposing food waste (FW). Various solvents with different Reichardt parameters were used to facilitate liquefaction, and their impacts on biocrude yields were analyzed. Notably, among the solvents investigated, water and ethanol yielded the highest biocrude yields of 24.7 wt% and 23.6 wt%, respectively. Synergistic effects from combining these solvents were also observed, resulting in enhanced biocrude yields. The STL process was simulated using ASPEN Plus to evaluate its economic feasibility, including sensitivity analysis on input data. Additionally, a negative non-linear correlation was found between net greenhouse emissions and processing capacity. The study determined that the environmental performance of STL becomes less competitive compared to FW landfilling when process capacity falls below a minimum level. Overall, these findings highlight the potential of STL technology for FW management, offering both economic and environmental benefits.

A Review of Key Technologies for Environment Sensing in Driverless Vehicles

Environment perception technology is the most important part of driverless technology, and driverless vehicles need to realize decision planning and control by virtue of perception feedback. This paper summarizes the most promising technology methods in the field of perception, namely visual perception technology, radar perception technology, state perception technology, and information fusion technology. Regarding the current development status in the field, the development of the main perception technology is mainly the innovation of information fusion technology and the optimization of algorithms. Multimodal perception and deep learning are becoming popular. The future of the field can be transformed by intelligent sensors, promote edge computing and cloud collaboration, improve system data processing capacity, and reduce the burden of data transmission. Regarding driverless vehicles as a future development trend, the corresponding technology will become a research hotspot.

Aircraft Accident and Crash Images Processing with Machine Learning

The aviation industry is in constant need of innovations in terms of safety and operational efficiency. In this context, low-light image enhancement technologies play an important role in a numerous areas of disciplines, from night flights to accident and collision investigations. Machine learning, deep learning methods and traditional methods not only provide the aviation industry with an effective image processing and improvement capacity in low light conditions, but also reveal important information by analysing the data of low-light images of crashed and destroyed aircraft. Within the scope of the study, traditional methods, deep learning method and machine learning are combined in order to enhance and process low-light ambient images of crashed and destroyed aircraft. By using Swish and Tanh activation functions together in the deep learning model, the performance of the neural networks used in the process of improving low-light environment images was improved and the image quality was increased. The enhanced images were evaluated and compared using PSNR and MSE as objective quality assessment measures. According to the PSNR and MSE criteria, the numerical results obtained from the image enhancement studies of the deep learning model were calculated as 29.85 and 100.44, respectively. The results introduce that the deep learning model provides better image enhancement than traditional methods. In conclusion, improvement of low-light image and processing is an important technological advancement in the aviation industry, enabling safer and more efficient operations. The successful of machine learning include deep learning and traditional methods shows that the aviation industry will achieve a safer and innovative structure in the future.

Modeling a hybrid solar- gas dehydrating plant for agro-industrial products

The article presents the development of a mathematical model for a dehydrating plant with a processing capacity of 100 to 200 kg of fresh product with both solar and gas thermal sources. The comprehensive plant model is based on mass and energy balances that consider the impact of real environmental conditions into the process. The model reproduces an experimental pineapple dehydration process with a maximum relative error of 7 %. According to our simulation results, reducing infiltration rate into the drying tunnel from 20 % to 0 % leads to a 7 °C increase in air drying temperature. This represents a reduction in drying time of 24 min. A 30 min reduction in drying time was observed when the drying airflow was decreased by 50 %. While increasing the airflow by 70 % results in 10 min longer drying time. When the minimum drying air temperature was increased from 40 °C to 70 °C, the drying time was reduced by 90 min. This reduces the use of electrical energy but increases the use of gas. Therefore, we estimated a energy total cost of $12.20 per 100 kg batch. Given the limited number of hybrid plant models in the literature, the integral dynamic modeling strategy offers an interesting option due to its flexibility, as it can be extended to the analysis of different plants and products. Furthermore, it enables the potential establishment of design, operation, and control strategies that could result in the process intensification.

Lean Inventory Management and Performance of Milk Processors in Kenya

Dairy is a key contributor to the Kenyan economy and it helps in poverty alleviation and food nutrition in rural and urban areas. Dairy processing acts as a link between dairy farmers and the consumers in Kenya. However, milk processors have been facing numerous challenges that consequently affect their performance. Poor quality of milk, post-harvest losses resulting from inadequate cooling plants and seasonality of milk production in the country are among the problems the milk processors face. Raw milk, the main inventory for milk processors, is highly perishable and requires processing immediately after collection. However, this has not been the case. In fact, 54% of the invested capacities of milk processors remain underutilized. This calls for leanness in inventory that will ultimately reduce waste and improve firms’ performance through reduced complaints. This study was guided by resource orchestration and lean theory. The study was a census and the unit of analysis was all milk processors in Kenya licensed by the Kenya Dairy Board. A pilot study was conducted to enhance the questionnaire’s quality. A Cronbach Alpha of 0.8 was used. Before the regression was run, diagnostic tests were conducted to check for assumptions of linearity. An analysis of variance was conducted to test the variables’ significance and, ultimately, a multiple regression analysis was run. Maintain zero inventory and use of technology to order inventory and maintain zero inventory had positive and significant coefficients while collaboration with suppliers and members in a supply chain had a negative insignificant coefficient. The study concludes that zero inventory and use of technology to order have significant positive correlation coefficients. This implies that the two can help a firm reduce customer complaints and in return improve performance.

Secure and Swift: A Proactive Approach to Defend Lightweight Key Exchange Mechanisms Against Replay, Masquerade, and Message Forgery Attacks in Cloud-IoT Communication

The Internet of Things (IoT) has rapidly advanced, making it feasible to connect numerous embedded devices to the internet for data sharing. Since the embedded devices have limited power, storage, and processing capacity, it is necessary to integrate embedded devices with a big resource pool, like the cloud. This technological integration is anticipated to bring about a remarkable expansion in the present and future exciting uses of IoT. Security concerns such as device data privacy and authentication are important ones in this regard. The goal of the current study is to develop a lightweight key establishment for safe mutual authentication system for cloud servers and the Internet of Things. Lightweight key establishment are used in our approach for authentication, while advanced encryption standard is used for confidentiality and integrity. The suggested plan achieves efficiency in performance analysis as well as security aspects including confidentiality, integrity, and authentication in security analysis. Proposed mechanism additionally, does an informal analysis and comparison of the security attributes, including replay attack, masquerade attack, message forgery attack.

Variations in dietary patterns of living sloths revealed by finite element analysis of jaws.

Although extinct sloths exhibited a wide range of dietary habits, modes of locomotion, and occupied various niches across the Americas, modern sloths are considered quite similar in their habits. The dietary habits of living sloths can be directly observed in the wild, and understanding the mechanical behavior of their jaws during chewing through finite element analysis (FEA) provides a valuable validation tool for comparative analysis with their extinct counterparts. In this study, we used FEA to simulate the mechanical behavior of sloth mandibles under lateral mastication loads, using it as a proxy for oral processing. Our research focused on the six extant sloth species to better understand their diets and validate the use of FEA for studying their extinct relatives. We found that all living sloths have the predominancy of low-stress areas in their mandibles but with significant differences. Choloepus didactylus had larger high-stress areas, which could be linked to a reduced need for processing tougher foods as an opportunistic generalist. Bradypus variegatus and Choloepus hoffmanni are shown to be similar, displaying large low-stress areas, indicating greater oral processing capacity in a seasonal and more competitive environment. Bradypus torquatus, Bradypus pygmaeus, and Bradypus tridactylus exhibited intermediary processing patterns, which can be linked to a stable food supply in more stable environments and a reduced requirement for extensive oral processing capacity. This study sheds light on extant sloths' dietary adaptations and has implications for understanding the ecological roles and evolutionary history of their extinct counterparts.

On Transducing Properties of Kombucha-Proteinoid Complexes.

We investigate the information processing capacities of kombucha-proteinoid proto-brains, focusing on the transducing properties through accommodation spiking, tonic bursting spiking, and optical and acoustic stimulation. We explore self-organization, adaptability, and emergent phenomena in this unconventional proto-architecture. By constructing kombucha-proteinoid networks exposed to diverse audio stimuli, we analyze nonlinear dynamics using time series analysis. Assessing information representation in the presence of extreme noise, we examine the system's resilience. Our results illustrate intricate pathways resulting from the interplay between the synthetic biological substrate and bio-inspired stimulation. The kombucha-proteinoid proto-brains consistently map complex stimuli to distinct activation levels, showcasing their adaptability and potential for information processing without the need for external shaping circuits.

Constrained Maximization of the Economic Production Model of Lithium Ore Exploration in Nasarawa

Over 20,000 years ago, mining was discovered as one of the oldest production industries generating over US$700 billions’ of revenue in the world by a few mining companies. For some time, mining work has resulted in a very demanding affair as a result of greater depth, low-grade, limited resources, and complex geo-mining conditions. Therefore, optimization of the mining system plays a vital role in profit maximization with the satisfaction of many constraints. However, today’s mining industry uses complex and sophisticated systems whose reliability has become a critical issue. This work adopted the financial market theory of development to propose a maximized constrained optimization economic production model for lithium ore exploration in Nasarawa, Nigeria using three methods such as: the break-even principle method of cut-off grade between revenue earned and cost incurred; the mortimer’s method principle to determine ore based in two cut-off criteria (original and average good) and the lane method for net profit value thereby maximizing processing capacity. Data obtained from the field and the Ministry of Mines and Solid Minerals were analyzed using energy dispersive x-ray fluorescence (EDXRF) showing the presence of lithium. The froth flotation technique used showed the beneficiation thereby achieving improved lithium concentrates and the inductively coupled atomic emission revealed a high presence of lithium of over 1859 parts per million (ppm) and other minerals.

SHA-256 Hardware Proposal for IoT Devices in the Blockchain Context.

This work proposes an implementation of the SHA-256, the most common blockchain hash algorithm, on a field-programmable gate array (FPGA) to improve processing capacity and power saving in Internet of Things (IoT) devices to solve security and privacy issues. This implementation presents a different approach than other papers in the literature, using clustered cores executing the SHA-256 algorithm in parallel. Details about the proposed architecture and an analysis of the resources used by the FPGA are presented. The implementation achieved a throughput of approximately 1.4 Gbps for 16 cores on a single FPGA. Furthermore, it saved dynamic power, using almost 1000 times less compared to previous works in the literature, making this proposal suitable for practical problems for IoT devices in blockchain environments. The target FPGA used was the Xilinx Virtex 6 xc6vlx240t-1ff1156.

SPECIFIC ENERGY CAPACITY OF PROCESSING AND ENERGY EFFICIENCY FOR PROCESS OF GRINDING WITH WHEELS FROM SUPERHARD MATERIALS

The analysis of modern research shows that when evaluating the specific energy intensity of the abrasive processing process, one should pay attention not only to the indicators of grinding power and material removal rate, but also to the indicator of the wear of the abrasive tool, which we will show below for the grinding tool made of superhard materials. It is shown that the traditional method of estimating the specific energy capacity based on the ratio of the grinding power to the processing productivity does not provide an adequate solution, since with it the specific heat capacity of processing exceeds the specific heat capacity of melting of the processing material by almost an order of magnitude. Therefore, it is the application of a new approach to the assessment of the specific energy intensity of diamond grinding, taking into account the wear of the working layer of the diamond wheel, and makes it possible to estimate the indicators of the specific energy intensity of grinding and the energy efficiency coefficient. It has been proven that when estimating the specific energy capacity of grinding metal-ceramic composite materials consisting of a low-melting and refractory component, the latent heat capacity of melting of the low-melting component should be taken as the basis. It is shown that the plastic mode of grinding occurs precisely when the specific energy capacity of grinding, taking into account the wear of the wheel, becomes close to the specific heat capacity of melting of a brittle material.

A Novel Secure and Energy-efficient Routing Method for the Agricultural Internet of Things Using Whale Optimization Algorithm

The Internet of Things (IoT) is an all-encompassing system that tracks and monitors real-world activities by gathering, handling, and interpreting data from IoT equipment. It has successfully been applied in several fields, particularly smart agriculture since there is a high demand for high-quality foodstuffs worldwide. It is essential to develop new agricultural production schemes to meet these demands. The heterogeneity of IoT devices makes security essential for IoT communication. Also, IoT devices are restricted in terms of processing, memory, and power capacities. Therefore, energy is a key factor in extending the life of an agricultural IoT network. This study presented a novel energy-aware and secure routing scheme using the Whale Optimization Algorithm (WOA) for IoT, referred to as SRWOA. The simulation results indicate that SRWOA uniformly distributes energy consumption in IoT and maximizes the packet delivery ratio.

Assessment of the Influence of Headwind Speed and Direction on the Specific Resistance when Rolling a Wagon from a Shipment Hump

The quality of the sorting process, the processing capacity of the station, and the safety of the rolling stock and transported goods depend on the design and current condition of the hump. Studying and assessing the influence of various factors on the specific resistance to the movement of cars from the air and wind will simplify the solution of individual problems in this area. The paper shows a calculation taking into account weather conditions to estimate the speed of railway cars. The presented values ​​can be used as reference material when determining the design meteorological conditions for the design of hump humps.