A hybrid transmission model for Plasmodium vivax accounting for superinfection, immunity and the hypnozoite reservoir.

Malaria is a vector-borne disease that exacts a grave toll in the Global South. The epidemiology of Plasmodium vivax, the most geographically expansive agent of human malaria, is characterised by the accrual of a reservoir of dormant parasites known as hypnozoites. Relapses, arising from hypnozoite activation events, comprise the majority of the blood-stage infection burden, with implications for the acquisition of immunity and the distribution of superinfection. Here, we construct a novel model for the transmission of P. vivax that concurrently accounts for the accrual of the hypnozoite reservoir, (blood-stage) superinfection and the acquisition of immunity. We begin by using an infinite-server queueing network model to characterise the within-host dynamics as a function of mosquito-to-human transmission intensity, extending our previous model to capture a discretised immunity level. To model transmission-blocking and antidisease immunity, we allow for geometric decay in the respective probabilities of successful human-to-mosquito transmission and symptomatic blood-stage infection as a function of this immunity level. Under a hybrid approximation-whereby probabilistic within-host distributions are cast as expected population-level proportions-we couple host and vector dynamics to recover a deterministic compartmental model in line with Ross-Macdonald theory. We then perform a steady-state analysis for this compartmental model, informed by the (analytic) distributions derived at the within-host level. To characterise transient dynamics, we derive a reduced system of integrodifferential equations, likewise informed by our within-host queueing network, allowing us to recover population-level distributions for various quantities of epidemiological interest. In capturing the interplay between hypnozoite accrual, superinfection and acquired immunity-and providing, to the best of our knowledge, the most complete population-level distributions for a range of epidemiological values-our model provides insights into important, but poorly understood, epidemiological features of P. vivax.

Identification of emergencies in the telephone queue and routing to a fast track (FAST): study protocol for a prospective, two-armed cohort study.

BACKGROUND: In Germany, the telephone patient service 116,117 for callers with non-life-threatening health issues is available 24/7. Based on structured initial assessment, urgency and placement of suitable medical care offer have been offered since 2020. The service has been in increasing demand for several years: Depending on time and residence, this can result in longer waiting times. METHODS: Prospective, two-armed cohort study with two intervention groups and one control group, alternating between blinding and unblinding for employees of 116,117 regarding prioritization status. Two interventions based on automated voice dialogues (1: Simple self-rating tool, 2: Automated brief query of emergency symptoms). In case of high level of urgency, callers are prioritized. Validation of urgency and need for care is carried out routinely based on structured initial assessment. DISCUSSION: By creating and providing a largely reproducible documentation of the implemented solutions for a waiting queue management, the developed approach would be available for comparable projects in the German health care system or in the European context. This potentially leads to a reduction in the use of resources in the development of comparable technical solutions based on automated voice dialogs. TRIAL REGISTRATION: DRKS00031235, registered on 10th November 2023, https://drks.de/search/de/trial/DRKS00031235 .

A Fuzzy-PI Clock Servo with Window Filter for Compensating Queue-Induced Delay Asymmetry in IEEE 1588 Networks.

Clock synchronization is one of the popular research topics in Distributed Measurement and Control Systems (DMCSs). In most industrial fields, such as Smart Grid and Flight Test, the highest requirement for synchronization accuracy is 1 µs. IEEE 1588 Precision Time Protocol-2008 (PTPv2) can theoretically achieve sub-microsecond accuracy, but it relies on the assumption that the forward and backward delays of PTP packets are symmetrical. In practice, PTP packets will experience random queue delays in switches, making the above assumption challenging to satisfy and causing poor synchronization accuracy. Although using switches supporting the Transparent Clock (TC) can improve synchronization accuracy, these dedicated switches are generally expensive. This paper designs a PTP clock servo for compensating Queue-Induced Delay Asymmetry (QIDA), which can be implemented based on ordinary switches. Its main algorithm comprises a minimum window filter with drift compensation and a fuzzy proportional-integral (PI) controller. We construct a low-cost hardware platform (the cost of each node is within USD 10) to test the performance of the clock servo. In a 100 Mbps network with background (BG) traffic of less than 70 Mbps, the maximum absolute time error (max |TE|) does not exceed 0.35 µs, and the convergence time is about half a minute. The accuracy is improved hundreds of times compared with other existing clock servos.

Transient GI/MSP/1/N Queue.

A non-zero correlation between service times can be encountered in many real queueing systems. An attractive model for correlated service times is the Markovian service process, because it offers powerful fitting capabilities combined with analytical tractability. In this paper, a transient study of the queue length in a model with MSP services and a general distribution of interarrival times is performed. In particular, two theorems are proven: one on the queue length distribution at a particular time t, where t can be arbitrarily small or large, and another on the mean queue length at t. In addition to the theorems, multiple numerical examples are provided. They illustrate the development over time of the mean queue length and the standard deviation, along with the complete distribution, depending on the service correlation strength, initial system conditions, and the interarrival time variance.

[Frontozygomatic dermoid cysts]. / Kystes dermoïdes fronto-zygomatiques.

Dermoid cysts are embryological derivatives from soft tissues. They result from an ectodermic inclusion in the mesoderm, during the early embryonic development. These cysts have a slow development and are mostly encountered in the pediatric population. Eighty percent of them are located in the head and neck area, and most of them are on the frontozygomatic suture. They are superficial or deep on clinical examination. The diagnosis is mostly easy, sometimes with the help of radiological examination. The confirmation is histological. Surgical removed by an open approach, without cyst rupture is the gold standard treatment.

[Emergency management of a young patient with ponytail syndrome]. / Prise en charge en urgence d'un patient jeune victime du syndrome de la queue-de-cheval.

A 31-year-old man was brought to the emergency department because, for the past two days, he had been experiencing paresthesia-like sensory disturbances in his lower limbs, with dorsal pain that was not relieved by analgesics, as well as the appearance of sphincter disturbances and increasing difficulty in mobilization due to balance disturbances and pain. Presentation of this clinical case.

On the Influence of AQM on Serialization of Packet Losses.

We study the influence of the active queue management mechanism based on the queue size on the serialization of packet losses, i.e., the occurrences of losses in long, consecutive series. We use a traffic model able to mimic precisely the autocorrelation function of traffic, which is known to be far from zero in packet networks. The main contribution is a theorem on the burst ratio parameter, describing the serialization of losses, proven for an arbitrary function assigning drop probabilities to queue sizes. In numerical examples, we show the impact of the autocorrelation strength, drop probability function, and load of the link, on the serialization of losses.

Optimal Scheduling in General Multi-Queue System by Combining Simulation and Neural Network Techniques.

The problem of optimal scheduling in a system with parallel queues and a single server has been extensively studied in queueing theory. However, such systems have mostly been analysed by assuming homogeneous attributes of arrival and service processes, or Markov queueing models were usually assumed in heterogeneous cases. The calculation of the optimal scheduling policy in such a queueing system with switching costs and arbitrary inter-arrival and service time distributions is not a trivial task. In this paper, we propose to combine simulation and neural network techniques to solve this problem. The scheduling in this system is performed by means of a neural network informing the controller at a service completion epoch on a queue index which has to be serviced next. We adapt the simulated annealing algorithm to optimize the weights and the biases of the multi-layer neural network initially trained on some arbitrary heuristic control policy with the aim to minimize the average cost function which in turn can be calculated only via simulation. To verify the quality of the obtained optimal solutions, the optimal scheduling policy was calculated by solving a Markov decision problem formulated for the corresponding Markovian counterpart. The results of numerical analysis show the effectiveness of this approach to find the optimal deterministic control policy for the routing, scheduling or resource allocation in general queueing systems. Moreover, a comparison of the results obtained for different distributions illustrates statistical insensitivity of the optimal scheduling policy to the shape of inter-arrival and service time distributions for the same first moments.

Non-Stationary Characteristics of AQM Based on the Queue Length.

We performed a non-stationary analysis of a class of buffer management schemes for TCP/IP networks, in which the arriving packets were rejected randomly, with probability depending on the queue length. In particular, we derived formulas for the packet waiting time (queuing delay) and the intensity of packet losses as functions of time. These results allow us to observe how the evolution of the waiting time and losses depend on initial conditions (e.g., the full buffer) and system parameters (e.g., dropping probabilities, load, packet size distribution). As side results, the stationary waiting time and packet loss probability were obtained. Numerical examples demonstrate applicability of the theoretical results.

Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach.

The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time processing at edge servers, existing message queue systems face challenges in adapting to changing system conditions, such as fluctuations in the number of devices, message size, and frequency. This necessitates the development of an approach that can effectively decouple message processing and handle workload variations in the AIoT computing environment. This study presents a distributed message system for AIoT edge computing, specifically designed to address the challenges associated with message ordering in such environments. The system incorporates a novel partition selection algorithm (PSA) to ensure message order, balance the load among broker clusters, and enhance the availability of subscribable messages from AIoT edge devices. Furthermore, this study proposes the distributed message system configuration optimization algorithm (DMSCO), based on DDPG, to optimize the performance of the distributed message system. Experimental evaluations demonstrate that, compared to the genetic algorithm and random searching, the DMSCO algorithm can provide a significant improvement in system throughput to meet the specific demands of high-concurrency AIoT edge computing applications.

Comparative Analysis of Power Consumption between MQTT and HTTP Protocols in an IoT Platform Designed and Implemented for Remote Real-Time Monitoring of Long-Term Cold Chain Transport Operations.

IoT platforms for the transportation industry are portable with limited battery life and need real-time and long-term monitoring operations. Since MQTT and HTTP are widely used as the main communication protocols in the IoT, it is imperative to analyze their power consumption to provide quantitative results that help maximize battery life in IoT transportation systems. Although is well known that MQTT consumes less power than HTTP, a comparative analysis of their power consumption with long-time tests and different conditions has not yet been conducted. In this sense, a design and validation of an electronic cost-efficient platform system for remote real-time monitoring is proposed using a NodeMCU module, in which experimentation is carried out for HTTP and MQTT with different QoS levels to make a comparison and demonstrate the differences in power consumption. Furthermore, we characterize the behavior of the batteries in the systems and compare the theoretical analysis with real long-time test results. The experimentation using the MQTT protocol with QoS 0 and 1 was successful, resulting in power savings of 6.03% and 8.33%, respectively, compared with HTTP, demonstrating many more hours in the duration of the batteries, which could be very useful in technological solutions for the transport industry.

Hypnozoite dynamics for Plasmodium vivax malaria: The epidemiological effects of radical cure.

Malaria is a mosquito-borne disease with a devastating global impact. Plasmodium vivax is a major cause of human malaria beyond sub-Saharan Africa. Relapsing infections, driven by a reservoir of liver-stage parasites known as hypnozoites, present unique challenges for the control of P. vivax malaria. Following indeterminate dormancy periods, hypnozoites may activate to trigger relapses. Clearance of the hypnozoite reservoir through drug treatment (radical cure) has been proposed as a potential tool for the elimination of P. vivax malaria. Here, we introduce a stochastic, within-host model to jointly characterise hypnozoite and infection dynamics for an individual in a general transmission setting, allowing for radical cure. We begin by extending an existing activation-clearance model for a single hypnozoite, adapted to both short- and long-latency strains, to include drug treatment. We then embed this activation-clearance model in an epidemiological framework accounting for repeated mosquito inoculation and the administration of radical cure. By constructing an open network of infinite server queues, we derive analytic expressions for several quantities of epidemiological significance, including the size of the hypnozoite reservoir; the relapse rate; the relative contribution of relapses to the infection burden; the distribution of multiple infections; the cumulative number of recurrences over time, and the time to first recurrence following drug treatment. We derive from first principles the functional dependence between within-host and transmission parameters and patterns of blood- and liver-stage infection, whilst allowing for treatment under a mass drug administration regime. To yield population-level insights, our analytic within-host distributions can be embedded in multiscale models. Our work thus contributes to the epidemiological understanding of the effects of radical cure on P. vivax malaria.

A tail-specific protease is required for Legionella pneumophila intracellular multiplication.

Legionella pneumophila is a Gram-negative bacterium found in natural and man-made water systems where it replicates within amoebas and ciliates. In humans, once inside the lungs, L. pneumophila replicates in alveolar macrophages and causes Legionnaires' disease, a severe pneumonia. The Icm/Dot type IVb secretion system is a major virulence factor required for intracellular multiplication. The Icm/Dot system allows the secretion of effectors into the cytoplasm of the host cell. These effectors modify host cell vesicular trafficking and prevent maturation of the phagosome. The innate immune response is crucial in restricting L. pneumophila proliferation. TNF-α is one of the major cytokines involved in this process as it renders macrophages more resistant to L. pneumophila infection and induces apoptosis of L. pneumophila-infected macrophages. Tail-specific proteases (Tsp) are involved in tolerating thermal stress and in virulence. We have previously characterized the Tsp encoded by L. pneumophila, showing that it is important for surviving thermal stress and for infection of amoeba when a temperature change occurs during infection. Here, we demonstrated that Tsp is required for intracellular multiplication in macrophages. Absence of tsp is associated with higher production of TNF-α by macrophages in response to L. pneumophila infection. This effect is independent of the Icm/Dot secretion system.

Performance evaluation of an EMS system using queuing theory and location analysis: A case study.

In emergency medical services (EMS), response time is a key factor that shows the performance of the system. This factor is composed of two parts including activation time and travel time. The activation time of an emergency call is the time a call center spends on taking an incoming call for EMS and decides whether an ambulance should be dispatched or the emergency can be resolved by giving some medical advices. Having a good number of call center operators including call takers and dispatchers can help to reduce this time and thus the response time. However, this alone may not be enough to have a reasonable cycle time. In fact, having idle ambulances located in right places when emergency calls occur is an influential factor to reduce the travel time and thus have an optimal response time and save people's lives. Although many researchers have studied improving either the activation time or the travel time, to the best of our knowledge, there exists no study focusing on both. Motivated by this gap, in this study, a framework is proposed which uses queuing theory and location analysis to address both activation and travel times. In this regard, first, queuing theory is applied to evaluate the performance of an EMS call center and reduce the average activation time. Then, three mathematical models including mobile stations, MEXCLP and MECRP are applied to locate ambulances such that the average travel time is minimized. To shed light on the merits of using queuing theory and location models, computational results based on the real-world data from Tehran EMS Center are provided. The proposed methodology can reduce the average response time by approximately four minutes and increase the average coverage by 35%. This work is an example of the tremendous positive impact that the application of queuing theory and mathematical modeling can have. The proposed framework can significantly decrease the cycle time and increase the ambulance coverage level. The findings of this study help the policy makers of EMS centers with evaluating the performance of their systems and determining the optimal number of operators and locations of ambulances in a way that enhances the quality of emergency services.

mmS-TCP: Scalable TCP for Improving Throughput and Fairness in 5G mmWave Networks.

The millimeter-wave (mmWave) band, which can provide data rates of multi-gigabits per second, could play a major role in achieving the throughput goals of 5G networks. However, the high-bandwidth mmWave signal is susceptible to blockage by various obstacles, which results in very large and frequent degradation in the quality of the received signals. TCP, the most representative transport layer protocol, suffers from significant performance degradation due to the very dynamic channel conditions of the mmWave signal. Therefore, in this paper, we propose a congestion control algorithm that guarantees sufficient throughput in 5G mmWave networks and that does not significantly worsen TCP fairness. The proposed algorithm, which is a modification of Scalable TCP (S-TCP) that is designed for high-speed networks, provides a more stable performance than the existing TCP congestion control algorithm in mmWave networks through simple modifications. In various simulation experiments that considered the actual mobile user environment, the proposed mmWave Scalable TCP (mmS-TCP) algorithm demonstrated throughput up to 2.4 times higher than CUBIC TCP in single flow evaluation, and the inter-protocol fairness index when competing with CUBIC flow significantly improved from 0.819 of S-TCP to 0.9733. Moreover, the mmS-TCP algorithm reduced the number of duplicated ACKs by 1/4 compared with S-TCP, and it improved the average total throughput and intra-protocol fairness simultaneously.

BEST-Blockchain-Enabled Secure and Trusted Public Emergency Services for Smart Cities Environment.

In the last few years, the Internet of things (IoT) has recently gained attention in developing various smart city applications such as smart healthcare, smart supply chain, smart home, smart grid, etc. The existing literature focuses on the smart healthcare system as a public emergency service (PES) to provide timely treatment to the patient. However, little attention is given to a distributed smart fire brigade system as a PES to protect human life and properties from severe fire damage. The traditional PES are developed on a centralised system, which requires high computation and does not ensure timely service fulfilment. Furthermore, these traditional PESs suffer from a lack of trust, transparency, data integrity, and a single point of failure issue. In this context, this paper proposes a Blockchain-Enabled Secure and Trusted (BEST) framework for PES in the smart city environment. The BEST framework focuses on providing a fire brigade service as a PES to the smart home based on IoT device information to protect it from serious fire damage. Further, we used two edge computing servers, an IoT controller and a service controller. The IoT and service controller are used for local storage and to enhance the data processing speed of PES requests and PES fulfilments, respectively. The IoT controller manages an access control list to keep track of registered IoT gateways and their IoT devices, avoiding misguiding the PES department. The service controller utilised the queue model to handle the PES requests based on the minimum service queue length. Further, various smart contracts are designed on the Hyperledger Fabric platform to automatically call a PES either in the presence or absence of the smart-home owner under uncertain environmental conditions. The performance evaluation of the proposed BEST framework indicates the benefits of utilising the distributed environment and the smart contract logic. The various simulation results are evaluated in terms of service queue length, utilisation, actual arrival time, expected arrival time, number of PES departments, number of PES providers, and end-to-end delay. These simulation results show the effectiveness and feasibility of the BEST framework.

On Transient Queue-Size Distribution in a Model of WSN Node with Threshold-Type Power-Saving Algorithm.

This article proposes a queueing model of the operation of a wireless sensor network node, in which a threshold strategy for starting the node after a period of no transmission is used. In this model, transmission of packets is resumed when the number of packets in the accumulation buffer reaches a predefined level. In the literature, most of the results for models with limited access to the service station are obtained in equilibrium. In this paper, a formula for the Laplace transform of the transient queue-size distribution is obtained and written using the key input parameters of the system. The analytical apparatus uses the concept of the embedded Markov chain, the formula for total probability, renewal theory and some supporting algebraic results. Numerical examples are attached as well.

Dynamic QoS Management for a Flexible 5G/6G Network Core: A Step toward a Higher Programmability.

The academic and professional community has recently started to develop the concept of 6G networks. The scientists have defined key performance indicators and pursued large-scale automation, ambient sensing intelligence, and pervasive artificial intelligence. They put great efforts into implementing new network access and edge computing solutions. However, further progress depends on developing a more flexible core infrastructure according to more complex QoS requirements. Our research aims to provide 5G/6G core flexibility by customizing and optimizing network slices and introducing a higher level of programmability. We bind similar services in a group, manage them as a single slice, and enable a higher level of programmability as a prerequisite for dynamic QoS. The current 5G solutions primarily use predefined queues, so we have developed highly flexible, dynamic queue management software and moved it entirely to the application layer (reducing dependence on the physical network infrastructure). Further, we have emulated a testbed environment as realistically as possible to verify the proposed model capabilities. Obtained results confirm the validity of the proposed dynamic QoS management model for configuring queues' parameters according to the service management requirements. Moreover, the proposed solution can also be applied efficiently to 5G core networks to resolve complex service requirements.

Transient Behavior of a Queueing Model with Hyper-Exponentially Distributed Processing Times and Finite Buffer Capacity.

In the paper, a finite-capacity queueing model is considered in which jobs arrive according to a Poisson process and are being served according to hyper-exponential service times. A system of equations for the time-sensitive queue-size distribution is established by applying the paradigm of embedded Markov chain and total probability law. The solution of the corresponding system written for Laplace transforms is obtained via an algebraic approach in a compact form. Numerical illustration results are attached as well.

Novel Method to Manage Student Questions in the Anatomy Laboratory Using a Virtual Meeting Platform.

Large class sizes and often few instructors in anatomy courses make it challenging for student laboratory groups to have their questions addressed in a timely manner. Instructors are often unaware of the number of requests for assistance, as well as the order in which assistance is requested, and students often spend a long time waiting for an instructor to become available. As a result of brainstorming with some of our students, a call button system of sorts was suggested. Instructors in consultation with the college's IT department came up with the idea of using Zoom Meetings question and answer (Q&A) feature to manage student questions. Zoom allows one to broadcast a Zoom Meeting to up to 50,000 participant attendees, and instructors, logged in as panelists (on a mobile device, e.g., iPad), can interact with the student attendees via the Q&A feature. The students join the webinar using their dissection table number as their ID and request assistance in the Q&A. These requests show up with a time stamp and are automatically queued on the panelist's Q&A window. Instructors employ the type answer feature to acknowledge the question by typing in their respective initials, which can be seen live by the other instructors (panelists). This allows student questions to be queued so that the instructors can address them in a timely, first-in/first-out order. Student feedback regarding the use of this system for the Small Animal Anatomy course was positive.