Limited Processing Capacity Research Articles

Drying ripe mangoes using a step-down industrial microwave-hot air belt dryer

A microwave-hot air belt dryer (MHABD) showed high specific energy consumption (SEC) due to its limited material processing capacity and extended drying time. Thus, this research presents the development and performance evaluation of an industrial microwave-hot air belt dryer (IMHABD) for drying Namdokmai Sithong mango slices. The IMHABD system, optimized using the COMSOL Multiphysics program, features a 0.9 m × 4.08 m × 0.5 m chamber with 36 magnetrons having a maximum microwave power of 28,800 W (each magnetron produces 800 W) at a frequency of 2,450 MHz. Two drying methods were studied, step-down microwave power drying (IMHABD-S) and constant microwave power drying (IMHABD-C). IMHABD-S, with a power range of 150–350 W combined with hot air at 65 °C, outperformed IMHABD-C, delivering enhanced drying rates, improved color attributes, and reduced shrinkage, along with decreased hardness and toughness values. All dried slices had a water activity lower than 0.6. An IMHABD-S operated at 350 W for 1.5 h showed the lowest SEC. Economic analysis revealed strong support for the IMHABD process, with a net present value (NPV) of 13,647 USD, an internal rate of return (IRR) of 15%, and a 4.95-year payback with a 10-year service life, highlighting its technical efficacy and economic viability for mango drying applications.

The emotion filmmaker: Temporal memory, time-emotion integration, and affective style.

Emotional experiences are temporally dynamic, but prior work suggests that temporal features are usually neglected in remembered emotion. For instance, retrospective emotion evaluations are often biased by discrete salient timepoints, such as the peak and end moments, at the expense of objective event duration (i.e., peak-end effects and duration neglect). However, how these retrospective emotion biases originate, as well as their significance for emotional functioning, remain unclear. Here, we test the hypothesis that retrospective emotion biases are related to fundamental limits of temporal processing and memory capacity. Further, we examine whether these limits have implications for emotional functioning. Participants (n = 60) underwent a novel paradigm comprising affectively-rich movie sequences while providing emotion ratings continuously (moment-by-moment) and retrospectively. Temporal memory for previously watched emotional movie sequences and dispositional negativity were measured. Our findings revealed a greater "end" bias as the duration of emotional-movie sequences increased, suggesting that limitations in temporal processing capacity may contribute to retrospective emotion biases. Critically, temporal-memory errors were associated with larger retrospective emotion biases and with individual differences in dispositional negativity. Collectively, these results indicate that retrospective emotion biases may stem partly from mnemonic temporal errors that are emotionally maladaptive. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Production forecast, comprehensive utilization, management measures and visualization analysis of construction waste

To achieve the national policy objectives of carbon peak and carbon neutrality, as outlined in the 14th Five-Year Plan, it is essential to enhance resource utilization efficiency, establish a resource recycling system, promote a green economy, and develop a green development policy framework. This thesis utilizes statistical data from the Chongqing municipality yearbook and employs the Time Series Forecasting Model (TSFM) and Gray Prediction Model (GM) to predict the generation of construction waste (CW) in Chongqing Municipality from 2021 to 2030.By 2030, engineering waste, demolition waste, renovation waste, and total CW generation are predicted to increase by 40.93%/34.30%, 37.3%/57.78%, 6.00%/9.55%, and 38.71%/57.85%, respectively, compared to 2020. This indicates significant pressure on the city's CW disposal system. The current situation of CW disposal and transfer in Chongqing City shows that the main methods are simple landfills, engineering backfills, and even private dumping. The actual resource utilization rate is still relatively low. Current CW disposal enterprises have some disposal and recycling capacity, but most are private, with insufficient distribution points and limited processing capacity. This results in a low overall comprehensive utilization rate of CW in central Chongqing. Since 2003, Chongqing Municipality has issued CW disposal-related policy documents. Although relevant policies have been introduced, they need further improvement. Recycled products are mainly bricks and aggregates, and there is a lack of local standards, which hinders effective resource utilization of CW in Chongqing. Finally, using the Citespace tool, a visual analysis of global CW research hotspots and trends over the past 14 years was conducted to accelerate CW resource utilization in Chongqing Municipality.

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.

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.

Evolution of blockchain accounting literature from the perspective of CiteSpace (2013–2023)

Against the backdrop of the Industrial Revolution 4.0, the advantages of blockchain technology in traceability, transparency, safety improvement, and efficiency improvement have made it possible to reduce the work of accounting personnel by 50 %, thus saving billions of dollars for global companies by combining this technology with accounting. However, the blockchain technology associated with accounting is in the experimental stage and has several problems to be solved including limited data processing capacity, information confidentiality, and regulatory difficulties. This innovation and progress in science and technology has provided more abundant, efficient, and professional technical support for the research of blockchain accounting documents. Among these advances, CiteSpace software has promoted the development of blockchain and accounting in the direction of visualization, comprehensiveness, security, and relevance. In this study, we used the knowledge map drawn by CiteSpace to search the core Blockchain Accounting database from 2013 to 2023 on the Web of Science (WoS). We obtained 1414 documents measured according to co-citation analysis, log-likelihood ratio (LLR) network clustering, co-occurrence keywords, and emergent time zone diagram method. We analyzed and summarized the important documents, research keywords, key research fields, and knowledge evolution related to "blockchain accounting" by network, literature integration, and popular research topics. We found that adopting blockchain technology in accounting information systems is expected to improve recordkeeping and reporting. Blockchain, as an innovative technology, provides a tamper-proof, traceable, and shareable platform for accounting information by using a distributed ledger system. By implementing blockchain, artificial intelligence can improve safety, transparency, and accuracy, and also may completely change the way we manage financial records. With its ability to improve overall efficiency and reduce errors, blockchain technology may change our familiar accounting methods. In addition, blockchain technology, intelligent contract, artificial intelligence, the Internet, information systems, and supply chain are the most important keywords, while blockchain technology, intelligent contract, and artificial intelligence are important components of blockchain accounting knowledge system. This research provided an important opportunity to advance the understanding of the crucial contribution of blockchain to the accounting field.

Pedestrian Abnormal Behavior Detection System Using Edge–Server Architecture for Large–Scale CCTVEnvironments

As the deployment of CCTV cameras for safety continues to increase, the monitoring workload has significantly exceeded the capacity of the current workforce. To overcome this problem, intelligent CCTV technologies and server-efficient deep learning analysis models are being developed. However, real-world applications exhibit performance degradation due to environmental changes and limited server processing capacity for multiple CCTVs. This study proposes a real-time pedestrian anomaly detection system with an edge–server structure that ensures efficiency and scalability. In the proposed system, the pedestrian abnormal behavior detection model analyzed by the edge uses a rule-based mechanism that can detect anomalies frequently, albeit less accurately, with high recall. The server uses a deep learning-based model with high precision because it analyzes only the sections detected by the edge. The proposed system was applied to an experimental environment using 20 video streams, 18 edge devices, and 3 servers equipped with 2 GPUs as a substitute for real CCTV. Pedestrian abnormal behavior was included in each video stream to conduct experiments in real-time processing and compare the abnormal behavior detection performance between the case with the edge and server alone and that with the edge and server in combination. Through these experiments, we verified that 20 video streams can be processed with 18 edges and 3 GPU servers, which confirms the scalability of the proposed system according to the number of events per hour and the event duration. We also demonstrate that the pedestrian anomaly detection model with the edge and server is more efficient and scalable than the models with these components alone. The linkage of the edge and server can reduce the false detection rate and provide a more accurate analysis. This research contributes to the development of control systems in urban safety and public security by proposing an efficient and scalable analysis system for large-scale CCTV environments.

An adaptable scheduling model for mixed flexible flow line with production continuity and processing capacity

In industrial production, in order to maximize demand fulfillment with limited processing capacity, manufacturers introduce a mixed-model flexible flow line (MFFL), which allows concurrent processing of multiple SKUs and produces more products in both quantity and category. In this study, we develop an adaptive mixed-integer linear programming (MILP) scheduling model for the MFFL problem. The model captures two key constraints in industrial production: production continuity and process capability. For the MFFL problem, we also propose a five-level scheduling strategy that integrates on-time and in-full (OTIF), early production, late delivery, using safety stock, and finally cutting demand. The scheduling strategy and model are demonstrated by real cases with high efficiency. Interestingly, the proposed scheduling strategy and model also achieve machine load balancing in production. Furthermore, we explore the impact of production continuity and introduce alternative objective functions to reduce overproduction with acceptable increases in solving time. This study is helpful for manufacturers to satisfy the demand as much as possible under the constraint of processing capacity and the requirement of production continuity.

A trust based secure access control using authentication mechanism for interoperability in internet of things

The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.

Access authentication via blockchain in space information network.

Space Information Network (SIN) has significant benefits of providing communication anywhere at any time. This feature offers an innovative way for conventional wireless customers to access enhanced internet services by using SIN. However, SIN's characteristics, such as naked links and maximum signal latency, make it difficult to design efficient security and routing protocols, etc. Similarly, existing SIN authentication techniques can't satisfy all of the essentials for secure communication, such as privacy leaks or rising authentication latency. The article aims to develop a novel blockchain-based access authentication mechanism for SIN. The proposed scheme uses a blockchain application, which has offered anonymity to mobile users while considering the satellites' limited processing capacity. The proposed scheme uses a blockchain application, which offers anonymity to mobile users while considering the satellites' limited processing capacity. The SIN gains the likelihood of far greater computational capacity devices as technology evolves. Since authenticating in SIN, the technique comprises three entities: low Earth orbit, mobile user, and network control centre. The proposed mutual authentication mechanism avoids the requirement of a ground station, resulting in less latency and overhead during mobile user authentication. Finally, the new blockchain-based authentication approach is being evaluated with AVISPA, a formal security tool. The simulation and performance study results illustrate that the proposed technique delivers efficient security characteristics such as low authentication latency, minimal signal overhead and less computational cost with group authentication.

Unlocking the potential of Tanzania's cashew processing industry: A comparative analysis with Côte d’Ivoire and Mozambique

Cashew processing is a vital contributor to economic growth in Tanzania, renowned for its cashew nut production. However, despite the country’s historical prominence in cashew production, only 5% of raw cashews undergo local processing, resulting in substantial economic losses. This paper explores the challenges and opportunities within Tanzania’s cashew processing industry, focusing on limited local processing capacity, inefficient tools, raw material availability, market access, and government support. Comparative insights from Côte d’Ivoire and Mozambique further enrich our understanding of the cashew sector. It recommends increasing local processing capacity, enhancing technical expertise through training, ensuring a reliable supply of high-quality raw materials, improving market access via information systems, and strengthening government support with tailored policy frameworks. Notably, the paper emphasizes regional collaboration among African cashew-producing nations as a crucial strategy for collective growth and knowledge exchange. By drawing upon their experiences, this study aims to provide guidance for policymakers, industry stakeholders, and investors to revitalize and sustain Tanzania’s cashew processing sector.

PENERAPAN METODE REGRESI LINEAR SEDERHANA DALAM MEMPREDIKSI TANDAN BUAH SEGAR MASUK DI PKS DOLOK ILIR

Oil palm is a very important crop in the agricultural sector today. This is because oil palm is the country's largest foreign exchange earner as well as a driver of the people's economy and plays a role in employment. Dolok Ilir Palm Oil Mill is one of the business units of PT Perkebunan Nusantara 4 which is engaged in the palm oil sector. As a plantation that has a palm oil processing plant, PKS Dolok Ilir also processes palm oil from other PTPN IV plantation units. Fresh fruit bunches entering the Dolok Ilir PKS are still difficult to predict. The high number of incoming Fresh Fruit Bunches and limited processing capacity causes some fruits cannot be processed on the same day, this will have an impact on reducing the quality of Fresh Fruit Bunches (FFB) and the quality of Crude Palm Oil (CPO). From these problems, an algorithm is needed to predict incoming Fresh Fruit Bunches (FFB) at the Dolok Ilir PKS.

Severe processing capacity limits for sub-lexical features of letter strings

When reading, the visual system is confronted with many words simultaneously. How much of that information can a reader process at once? Previous studies demonstrated that low-level visual features of multiple words are processed in parallel, but lexical attributes are processed serially, for one word at a time. This implies that an internal bottleneck lies somewhere between early visual and lexical analysis. We used a dual-task behavioral paradigm to investigate whether this bottleneck lies at the stage of letter recognition or phonological decoding. On each trial, two letter strings were flashed briefly, one above and one below fixation, and then masked. In the letter identification experiment, participants indicated whether a vowel was present in a particular letter string. In the phonological decoding experiment, participants indicated whether the letter string was pronounceable. We compared accuracy in a focused attention condition, in which participants judged only one of the two strings, with accuracy in a divided attention condition, in which participants judged both strings independently. In both experiments, the cost of dividing attention was so large that it supported a serial model: participants were able to process only one letter string per trial. Furthermore, we found a stimulus processing trade-off that is characteristic of serial processing: When participants judged one string correctly, they were less likely to judge the other string correctly. Therefore, the bottleneck that constrains word recognition under these conditions arises at a sub-lexical level, perhaps due to a limit on the efficiency of letter recognition.

Blockhain and Biometrics Challenges and Solutions

Blockchain technology has garnered significant attention in recent years due to its ability to revolutionize conventional processes by providing faster, more secure, and cost-effective solutions. This study explores the symbiotic relationship between blockchain and biometrics, investigating how these technologies can mutually reinforce each other. The research makes a dual contribution: firstly, it comprehensively analyses blockchain and biometrics, highlighting their convergence's potential advantages and obstacles. Secondly, it delves deeper into utilising blockchain for safeguarding biometric templates. Although the potential benefits outlined earlier are promising, integrating blockchain and biometric technologies faces challenges due to constraints within current blockchain technology. These constraints include a limited transaction processing capacity, the need to store all system transactions leading to increased storage demands, and insufficiently explored resilience against diverse attacks. Historically, biometric systems have been vulnerable to both physical and software-based attacks. While techniques like presentation attack detection can somewhat mitigate physical sensor vulnerabilities, safeguarding against software attacks necessitates adopting biometric template protection measures. Despite advancements in this area, there remains scope for enhancing these methods. Integrating blockchain and biometrics promises to enhance security and efficiency across various sectors. By combining blockchain's immutability and transparency with biometric data's uniqueness and reliability, organizations can establish robust systems that protect sensitive information while streamlining processes. This research underscores the importance of understanding the intricacies of merging these technologies to leverage their full potential effectively. Overall, this study sheds light on the transformative power of integrating blockchain and biometrics, offering insights into how this synergy can drive innovation, improve security measures, and optimize operations in a rapidly evolving digital landscape.

Design and Characterization of an Upscaled Dielectric Barrier Discharge-Based Ten-Layer Plasma Source for High-Flow-Rate Gas Treatment

Dielectric barrier discharge (DBD)-based technology is considered a promising alternative for controlling indoor air pollutants. However, its limited processing capacity and lack of design techniques have restricted its use in practical applications. This paper introduces a methodology for designing upscaled DBD reactors with a processing capacity of up to 1000 L/min for treating high-flow-rate gases to mitigate indoor air pollution. A ten-layer high-flow-rate DBD reactor was constructed, with fundamental characterizations, including electrical and spectroscopic measurements, conducted to verify the feasibility of the proposed methodology. In particular, the flow paths of the ten-layer DBD reactor were optimized by incorporating an air diffuser and perforated metal plates, all without significant modifications. Computational fluid dynamics simulations showed a remarkably improved velocity uniformity (0.35 m/s to 0.04 m/s, as evidenced by the velocity standard deviation) in the 10 flow channels. These simulation results were consistent with the experimental results, wherein the velocity standard deviation reduced from 1.38 m/s to 0.13 m/s. Moreover, multi-gas plasma ignition for up to six gas species and high-flow-rate plasma generation of up to 1000 L/min were achieved. These results provide the foundation for developing DBD technologies for practical applications in high-flow-rate gas treatment, particularly for controlling indoor air pollution.

DEVELOPMENT OF A LOGISTICS SCHEME FOR CROSSING THE BORDER WITH THE EU BY TRAILER TRAINS WHEN TRANSPORTING GRAIN GROUP LOADS

Purpose. One of the problems that arises when crossing the land border with the EU countries by rail or road, when transporting grain cargo, is the need for phytosanitary control. It involves taking samples of cargo and performing laboratory analyzes. Customs clearance of cargo without this procedure is impossible in Ukraine. The need for phytosanitary inspection of grain cargo after crossing the border is a requirement of EU legislation for import or transit through the territory of these countries. The organization of combined transportation of grain cargo in interstate traffic in transit through Eastern European countries towards seaports is certainly an urgent task. This is confirmed by the redistribution of grain exports with an increasing share of these cargoes moving through western crossings. The organization of combined containerized transportation is conditioned by the limited processing capacity of transshipment points and railcar change points at border stations. The purpose of this article is to build a logistics chain for crossing the border by container trains running from Khyriv station of the regional branch of Lviv Railway to Przemysl-Bakonczyce station of Polish State Railways, subject to preliminary phytosanitary control directly at Khyriv station under the control of the Polish side. The article also solves the problem of building a train schedule with the coordination of the duration and schedule of working hours of the locomotive crews of the freight locomotives of the Polish State Railways at Medyka or Przemyśl stations. Methods. Methods of production process control and methods of schedule theory were used. Findings. The sequence and duration of technological operations performed at the Khyriv station, which are 1.2 hours, provided that cars are ready for departure in an amount sufficient to fill all train platforms, have been developed. The consumption of locomotive hours for running a counter-railer train between the initial and final stations is calculated, which is 4.7 hours. It is established that during a 12-hour work shift of the locomotive crew of Polish State Railways, two trains can be serviced with a departure interval between them in the range of 5...7 hours. Practical value. The results of this work can be used in the development and construction of schedules for the movement of container trains in cross-border traffic.

Sensory processing in humans and mice fluctuates between external and internal modes.

Perception is known to cycle through periods of enhanced and reduced sensitivity to external information. Here, we asked whether such slow fluctuations arise as a noise-related epiphenomenon of limited processing capacity or, alternatively, represent a structured mechanism of perceptual inference. Using 2 large-scale datasets, we found that humans and mice alternate between externally and internally oriented modes of sensory analysis. During external mode, perception aligns more closely with the external sensory information, whereas internal mode is characterized by enhanced biases toward perceptual history. Computational modeling indicated that dynamic changes in mode are enabled by 2 interlinked factors: (i) the integration of subsequent inputs over time and (ii) slow antiphase oscillations in the impact of external sensory information versus internal predictions that are provided by perceptual history. We propose that between-mode fluctuations generate unambiguous error signals that enable optimal inference in volatile environments.

A review and analysis of impression management with photographs in sustainability reporting

PurposeAlthough photographs in sustainability reports are useful in conveying complex messages, they may also be used to manipulate the presentation of disclosures to exploit the limited cognitive processing capacity of humans. Therefore, this paper aims to examine the features of photographs aimed at capturing individuals’ attention through visual structures and evoking specific emotions through carefully chosen content. Furthermore, it examines whether such framing practice is explained by incentives for legitimizing behaviours and influencing reputation.Design/methodology/approachThe authors conduct a content analysis of photographs in 154 sustainability reports published by US companies. The authors captured the nature of photographs, the context in which they are being used, their themes and emotional content and layout and interaction features to understand how photographs are used for attribute framing to influence information processing. Furthermore, the authors statistically examine the framing practice between companies with different characteristics to identify any patterns for the impression management use of photographs in sustainability reports.FindingsPhotographs are often large with a horizontal orientation to capture attention and show content viewed at eye level and in either medium or close-up shots to engage viewers. Furthermore, photographs are emotionally loaded with different themes such as depictions of people, technology and nature. These themes are used to predominately evoke positive emotions of awe, nurturance, pride, amusement and attachment. This practice is often used by companies in environmentally sensitive areas that have close consumer relationships or are covered controversially in the media.Originality/valueThe authors reveal reporting practices and identify photographic features that attract attention and convey emotions that go beyond aesthetic qualities. This is important because emotions conveyed through photographs can be potentially misleading and influence judgements subconsciously.

A reconceptualization of sentence production in post-stroke agrammatic aphasia: the synergistic processing bottleneck model.

The language production deficit in post-stroke agrammatic aphasia (PSA-G) tends to result from lesions to the left inferior frontal gyrus (LIFG) and is characterized by a triad of symptoms: fragmented sentences, errors in functional morphology, and a dearth of verbs. Despite decades of research, the mechanisms underlying production patterns in PSA-G have been difficult to characterize. Two major impediments to progress may have been the view that it is a purely morphosyntactic disorder and the (sometimes overzealous) application of linguistic theory without interceding psycholinguistic evidence. In this paper, empirical evidence is examined to present an integrated portrait of language production in PSA-G and to evaluate the assumption of a syntax-specific syndrome. In light of extant evidence, it is proposed that agrammatic language production results from a combination of morphosyntactic, phonomotor, and processing capacity limitations that cause a cumulative processing bottleneck at the point of articulatory planning. This proposed Synergistic Processing Bottleneck model of PSA-G presents a testable framework for future research. The paper ends with recommendations for future research on PSA-G.

Asymptotic collective behaviors of a delayed multi‐particle system with multiple processes

It is a significant issue to explore the collective behaviors of the delayed complex systems. This paper studies asymptotic collective behaviors of a delayed multi‐particle system with multiple processes while particles interact directionally and locally. Up to now, the studies on dynamic behaviors of multi‐particle systems do not involve limited processing capacity, that is, the information queuing phenomenon is ignored. To this aim, we introduce multiple processes to formulate the evolution of a delayed multi‐particle system. To optimize the delay parameters, we choose the greedy principle to set the processing order. The main idea is to decompose the velocity into each process and use functional differential equation theory and matrix theory to constrain the velocity variation rate while the processing order is fixed. As the new results, in the non‐critical and general situation, when the time delay is less than or equal to the threshold value and the eigenvalue 1 of the average matrix is semi‐simple, we achieve the criterion of flocking and multi‐cluster with exponential convergence rate involving multiple processes. Furthermore, we get the lower bound estimate of the processing capacity.