High throughput hemogram of T cells using digital holographic microscopy and deep learning

T cells of the adaptive immune system provide effective protection to the human body against numerous pathogenic challenges. Current labelling methods of detecting these cells, such as flow cytometry or magnetic bead labelling, are time consuming and expensive. To overcome these limitations, the label-free method of digital holographic microscopy (DHM) combined with deep learning has recently been introduced which is both time and cost effective. In this study, we demonstrate the application of digital holographic microscopy with deep learning to classify the key CD4+ and CD8+ T cell subsets. We show that combining DHM of varying fields of view, with deep learning, can potentially achieve a classification throughput rate of 78,000 cells per second with an accuracy of 76.2% for these morphologically similar cells. This throughput rate is 100 times faster than the previous studies and proves to be an effective replacement for labelling methods.

Whole Scenario of 5G Communication Access in the Digital Transformation of Medium and Large Enterprises

With the evolution and upgrading of the fifth-generation mobile communication technology, the mobile network will support a larger mobile user group and more diverse business scenarios, greatly enhance the Internet service experience, and fully support IoT-aware applications. As the forefront of the Internet of Everything, the wireless access network plays an important role in the evolution of the network. The continuous innovation of a new generation of information technology, especially the application of technologies such as big data, cloud computing, artificial intelligence, and the Internet of Things, has triggered an upsurge in the digital transformation of enterprises. Digital transformation has had a profound impact on the production and operation activities of enterprises and has also changed the organization and management of enterprise innovation activities. From the perspective of the innovation ecosystem, the digital transformation of a single enterprise leads to changes in innovation activities, which will converge and emerge new characteristics at the system level. The purpose of this article is to study the full scenarios of 5G communication access in the digital transformation of medium and large enterprises. This article starts with the development trend of wireless access networks, analyzes network slicing technologies in detail, and points out that wireless access networks are moving towards 5G. Important challenges are faced in the development of the times. Based on the adaptive random access model proposed in this paper, a feedback adaptive optimization method is proposed. This method estimates the real access load through feedback and calculates the access threshold through the access load. Then, broadcast the threshold value to each user equipment through downlink broadcast. The results show that the normalized throughput rate of random access methods using AC-RACH and FC-RACH is higher than that of RA-RACH. Especially, when the arrival rate of user requests is getting higher and higher, the throughput rate of RA-RACH access will continue to decrease with the collision until it approaches zero. By comparing the key data of normalized throughput rate and access success rate, it is concluded that the feedback adaptive method has a significant performance improvement under heavy load conditions compared with the previous method.

Evaluation of Fuel Quality, Throughput Rate and Energy Consumption During Non-Industrial Wood Chip Production with Three PTO Driven Chippers

Physical wood chip quality is essential for failure-free and low emission combustion in small-scale boilers ≤100 kW. In Bavaria, these furnaces are often operated by farmers or private forest owners that produce their own fuels using small to medium sized PTO-driven chippers. As secondary fuel processing steps such as industrial screening are usually too expensive for private forest owners, the selection of suitable raw materials and process parameters to directly produce high quality fuels during chipping are deemed especially relevant for this user group. In the present study, three commonly used small-scale chippers ≤150 kW, i. e. a drum, a spiral and a disc chipper where evaluated in terms of fuel quality, throughput rate and energy consumption during wood chip production. Chipping was done using stem wood of European beech and Norway spruce. Machine settings were the ones recommended by the chipper manufactures for the production of high quality fuels. Additional chipping variants included the use of different raw materials such as crown residues of European willow and varying machine settings including blunt knives, increasing spiral cut length, large screen mesh sizes or increased PTO speeds. Representive wood chip samples were taken after each trial and analysed in their physical fuel properties according to international standards for solid biofuels but also using a continuously measuring image analysis device to determine particle length and particle shape. For all three mobile chippers, wood chips with the particle size class »P31s« according to the revised ISO 17225-4:2021 could be produced when stem wood was used as assortment. Fine content of chips, i. e. particles ≤3.15 mm, was lowest for the spiral chipper and increased for the drum and disc chipper, especially when blunt knives or narrow screen meshes were used for chipping. At the same time, blunt knives increased the particle shape factor (PSF) of the bulk materials indicating a rather broken particle surface structure compared to clean cut particles. Throughput rate decreased and energy consumption increased when fuels with small particle size were produced, e. g. when narrow screen meshes or narrow chipping spirals were applied. This trend was particularly pronounced when blunt knives were used for chipping due to grinding of the material. All three chippers could be recommended for the production of high quality fuels for small-scale boilers when suitable machine settings and raw materials are applied for chipping.

Impact of Hello Intervals in AODV in FANET

Business and classified activity of UAV is changing various bionetwork. To perceive risky issue and investigate research zones, our precise content assessment suggests the critical issue like protection, reception and sanctuary are progressively supplanted by operational contemplations incorporating connection by and blow on other airspace clients. Ongoing episodes show that unlimited robot use can incur issues on other airspace clients like air terminals and crisis administrations. Our audit of current administrative methodologies shows a requirement for additional approach and oversight answer to both run quick and efficient ova utilization development, and work with advancement (for example intraurban bundle conveyance), with execution of the planned engineering is approved utilizing three boundaries, to be specific throughput, parcel conveyance proportion (PDR in various UAVs. The outcomes are contrasted and existing conventions show the adequacy of the work regarding throughput rate.

A Multichannel Allocation Strategy Based on Preemption Threshold and Preemption Probability in Cognitive Radio Networks

In traditional multichannel cognitive radio networks (CRNs), users are split into two different priorities. Because of the low priority of secondary users (SUs), SU packets’ transmissions are easily interrupted by primary users (PUs). In this paper, two control parameters, called preemption threshold H and preemption probability q, are used to regulate the preemption behavior of PU packets to improve the transmission performance of SU packets. When all channels in the system are occupied, the preemption behavior of PU packets will be adjusted according to the amount of SU packets that are transmitting in the system. If the amount is larger than H, the recently arrived PU packet either preempts a channel with probability q or leaves the system with probability 1 − q . The central controller manages the system’s channel usage right and determines a series of access behaviors of user packets. Considering the possible imperfect sensing, a discrete-time queueing model is developed with the proposed preemption control mechanism. Then we obtain some performance index expressions of PU and SU packets founded on the system’s state transition matrix and make the corresponding performance figures through numerical experiment. Finally, we construct a system utility function and determine the optimal preemption threshold and preemption probability through the seagull optimization algorithm (SOA). Experimental data show that the proposed mechanism by setting preemption threshold and preemption probability can significantly reduce SU packets’ outage rate and improve SU packets’ throughput rate.

Construction of Video Courses of Physical Education and Health Education in Colleges and Universities under the MOOC Platform

In the traditional construction process of educational video courses for physical and health education in universities, numerous problems are encountered, such as small storage capacity, significant delay error, and decreased information throughput rate. Therefore, an educational video course for physical and health education in universities based on the Massive Open Online Course (MOOC) platform is constructed. The course is built by constructing a creative environment for video courses, establishing a video course model under the MOOC platform, and the caching code design for video courses. Upon numerous modifications and test runs, with the campus network’s help, the construction of a network teaching video for physical and health theory courses is realized. Our proposed approach’s experimental result shows that the designed course’s frame rate is 10% higher than that of the traditional course designing. The node’s storage capacity is up to 130%, the delay error is significantly reduced, and the information throughput rate is not affected by the increase of network load.

Secure-Aware Multipath Routing Using Atom Search Rider Optimization Algorithm in Wireless Sensor Networks

WSN is comprised of sensor nodes that sense the data for various applications. The nodes are employed for transmitting sensed data to BS through intermediate nodes or the cluster heads in multi-hop environment. Erroneous selection of CHs may lead to large energy consumption and thereby degrades system performance. Hence, an effective technique was developed by proposing Rider-ASO for secure-aware multipath routing in the WSN. The proposed routing protocol offers security to the network concerning various trust factors. Initially, cluster head selection is done using RCSO. Then, the trust values of the cluster heads that are selected is computed to ensure security while routing. For the multipath routing, proposed Rider-ASO is developed by combining ASO and ROA. Thus, the proposed algorithm finds multiple secured paths from the source into destination based on selected CHs. The developed Rider-ASO outperformed other methods with minimal delay of 0.009 sec, maximal average residual energy 0.5494 J, maximal PDR of 97.82%, maximal throughput rate of 96.07%, respectively.

Low Cost Solution to Increase the C2 & C3 Product Recovery from LNG Feed

An operating methane/ethane recovery plant from Liquefied Natural Gas (LNG) feed was facing limitations to process design throughput due to a variation in operating parameter of LNG feed. About 92% of design capacity of LNG feed is only being processed as flooding is observed inside the Demethanizer column, eventually leading to tripping of the plant. The limitations in the throughput has direct implication on the revenue as lesser throughput reduces the product generation. Various field trials were attempted within the existing setup to increase the throughput to the plant, however the throughout could not be increased. Operating an LNG plant is comparatively complex due to its unique characteristics, as even one degree change in the temperature has effect on the liquid vaporization. To achieve the design feed throughput rate, as a permanent solution, the temperature of the feed before entering the demethanizer column has to be increased. Various locations for increasing the temperature in the plant were studied in this paper. The identification of location for preheating plays an important role in the costing. For every one degree Celsius increase in the feed temperature, the duty of the exchanger increases three folds. This paper explains the low cost solutions to increase the throughput to the plant, thereby increasing the product generation of C2, C3 products from LNG feed prior to regasification.

Simulation-Based Performance Analysis for a Novel AVS/RS Technology with Movable Lifts

This paper studies a novel autonomous vehicle-based storage and retrieval system (AVS/RS) design with movable lifts (AVS/RS/ML). In the proposed system, there are aisle-captive lifts that are able to travel along the warehouse aisle to position themselves at the target column location. Those lifts can lift up/down the autonomous vehicles to/from the target storage compartment when they are in standstill. This novel design is proposed as an alternative to existing AVS/RSs to balance the resource utilizations as well as to provide an inexpensive solution with highly utilized autonomous vehicles (i.e., AGVs). As an initial work, for this novel system, two alternative operating designs under different racking configurations are experimented. We compare those two designs by their throughput rate performance metrics under the arrival rate scenarios with highly utilized AGVs (i.e., 95%). Besides, we experiment with two warehouse capacity scenarios: 900 and 1800 storage compartments. The results show that designs with two separate I/O point locations provide a better throughput rate than designs with single I/O point location. Besides, a decreased number of columns in the system improves the system’s performance.

Retail store customer flow and COVID-19 transmission

We examine how operational changes in customer flows in retail stores affect the rate of COVID-19 transmission. We combine a model of customer movement with two models of disease transmission: direct exposure when two customers are in close proximity and wake exposure when one customer is in the airflow behind another customer. We find that the effectiveness of some operational interventions is sensitive to the primary mode of transmission. Restricting customer flow to one-way movement is highly effective if direct exposure is the dominant mode of transmission. In particular, the rate of direct transmission under full compliance with one-way movement is less than one-third the rate under two-way movement. Directing customers to follow one-way flow, however, is not effective if wake exposure dominates. We find that two other interventions—reducing the speed variance of customers and throughput control—can be effective whether direct or wake transmission is dominant. We also examine the trade-off between customer throughput and the risk of infection to customers, and we show how the optimal throughput rate drops rapidly as the population prevalence rises.