Transmission Control Research Articles

Dynamic modeling, clutch parameter adaptation, and control of automatic transmission for tracked vehicles

In this study, a novel TCU control structure and algorithms including also dynamic model of the transmission will perform the gear shifting of automatic transmissions used in tracked military vehicles are designed. In case of inherent wear of the clutches, the clutch parameters are estimated by means of an adaptation algorithm that uses only the information from the transmission input and output speed sensors. These estimated clutch parameters are used in clutch torque calculation is utilized by control algorithms. For the clutch speed control in the inertia phase, a PID control structure with a negative feedforward term that cancels the nonlinearities of the system is proposed. The feedforward term utilizes the estimated wear clutch coefficients in the calculation of friction coefficients. The parameters of the PID controller are optimized by a genetic algorithm. The designed all structure are firstly tested on a MATLAB/Simulink power train simulation model, and then tested using a unique transmission on a transmission dynamometer test bench to examine its suitability for real transmission scenarios. The performances of proposed PID control and a backstepping nonlinear controller that we constructed for the tracked vehicles are compared with and without clutch wear. Maximum tracking error is decreased by 98% with proposed adaptive PID control structure with nonlinear feedforward term compare to backstepping controller. In the case of clutch wear, the back-stepping control exists in the literature has been found to result in oscillation. By updating the estimated friction coefficient from adaptation algorithm, in the backstepping controller, it is concluded that these oscillations can be eliminated. Additionally, on-off solenoid valves, are widely used, are known to cause torque interruptions and jerks during gear shifting. It has been observed the control structure presented in this study reduced the jerks by one quarter.

TCP BBR-n interplay with modern AQM in Wireless-N/AC networks: Quest for the golden pair.

Effective congestion control on the internet has been a problem since its inception. Transmission Control Protocol (TCP), being the most widely used transport layer protocol tries to mitigate it using a variety of congestion control algorithms. Cubic, Reno, and Bottleneck Bandwidth and Round-trip propagation time (BBR) are the most deployed congestion controls. BBR v2 is leading the congestion control race with its superior performance in terms of better throughput and lower latency. Furthermore, Active Queue Management (AQM) algorithms try to mitigate the congestion control at the network layer through active buffer control to avoid bufferbloat. The most efficient congestion control occurs when TCP and AQM work together. Indeed, it is the TCP-AQM algorithm "Golden pair" that can result in the most efficient performance. This paper proposes such a novel pair based on our previously tested and published BBR-n (BBR new) with the most effective of the modern AQMs, that completely gels together to provide lower latency in wireless networks based on Wireless N/AC. Real-time experiments were performed using Flent on our physical testbed with BBR-n and modern AQMs such as Fair Queuing (FQ), Constrained Delay (CoDel), Proportional Integral controller Enhanced (PIE), Common Applications Kept Enhanced (Cake) and Flow Queuing Controlled Delay (FQ_CoDel). Various tests done on our physical testbed helped us identify CAKE as the most optimum AQM that fits with our proposed BBR-n while providing optimum throughput and lower latency in 802.11N/AC-based wireless networks.

Congenital transmission of Chagas disease: The role of newborn therapy on the disease’s dynamics

Chagas disease, also known as American trypanosomiasis, is caused by a protozoan blood-borne pathogen called Trypanosoma cruzi. The World Health Organization (WHO) has classified Chagas as one of 21 neglected tropical diseases present in the world and estimates that 6-7 million people are currently infected with Chagas. Congenital transmission of Chagas disease contributes to a significant amount of new infections, especially in endemic areas where 22.5% of new infections are due to congenital transmission. In this paper, we investigate congenital transmission’s impact on Chagas disease dynamics through a mathematical model. Specifically, we examine how treating a proportion of infants born to infected individuals impacts the progression and spread of Chagas disease. The influence of newborn therapy on the dynamics of the model is thoroughly investigated, both theoretically and numerically. The results illustrate the importance of treating a high proportion of newborns to reduce the number of infected cases of the disease. The findings show that the therapy given to newborns is necessary but not sufficient to curb the transmission of Chagas disease, and a comprehensive approach that includes vector and vertical transmission control strategies is essential for eradicating Chagas disease. We also observed that if vector transmission can be controlled, then at least 55% of the newborns need to be treated to eliminate the disease.

Geneticand phenotypic characterization of a novel ST45-K43 carbapenem-resistant Klebsiella pneumoniae strain causing bloodstream infection: a potential clinical threat.

Klebsiella pneumoniae is a common pathogen of nosocomial infection, which can cause pneumonia, urinary tract infection, cystitis, and bloodstream infections (BSIs). Here, we genetically characterize a novel carbapenem-resistant K. pneumoniae (CRKP) strain recovered from the blood of a 44-year-old male patient with severe acute necrotizing pancreatitis and septic shock in China. The strain is a ST45 K. pneumoniae with a novel serotype of K43, named 18SHX166. The susceptibility testing results showed that 18SHX166 was resistant to cephalosporin and carbapenems but still susceptible to ceftazidime-avibactam, quinolones, colistin, and amikacin. Genomic sequencing revealed that 18SHX166 contains three plasmids, namely pSHX166-Hv, pSHX166-KPC, and pSHX166-3. pSHX166-Hv harbored the iucABCD operon, encoding the siderophore of aerobactin. pSHX166-KPC harbored blaKPC-2 gene and possessed complete conjugative regions. The conjugation experiment verified pSHX166-KPC as a self-transmissible plasmid mediating the dissemination of antibiotic resistance, with a conjugation rate of 2.21 × 10-5. Additionally, the growth curve showed that 18SHX166 demonstrates a higher growth rate than the control strains. The characteristics of 18SHX166 indicate a potential high risk of clinical transmission.IMPORTANCEST45-K43 carbapenem-resistant Klebsiella pneumoniae isolate, 18SHX166, carries a carbapenem resistance plasmid and virulence plasmid. It has the characteristics of multidrug resistance, high transmissibility, and a fast growth rate, which could pose a threat to the control of antimicrobial resistance and clinical transmission, causing a severe challenge to public health.

Infections caused by Haemophilus ducreyi: one organism, two stories.

SUMMARYChancroid, a sexually transmitted infection caused by Haemophilus ducreyi, is characterized by painful genital ulcers (GU) and inguinal lymphadenitis. H. ducreyi was recently described as a major cause of non-sexually transmitted cutaneous ulcers (CU) on the lower legs in children in yaws-endemic regions. This review explores the relationship between CU and GU strains of H. ducreyi; their clinical presentation, diagnosis, epidemiology, and treatment; and how findings from a human challenge model relate to GU and CU. We contrast the decline of GU with the persistence of CU caused by H. ducreyi. Factors such as transmission dynamics, control, and elimination efforts are discussed. Syndromic management and targeted treatment of sex workers can eradicate chancroid, while skin colonization by CU strains and environmental factors may necessitate topical treatments or vaccination for CU eradication. Efforts should focus on identifying additional reservoirs of CU strains, improving hygiene, and eliminating asymptomatic colonization to eradicate this painful infection in children.

Heterogating Gel Iontronics: A Revolution in Biointerfaces and Ion Signal Transmission.

Currently, existing iontronic systems are limited and struggle to process electronic-to-multi-ionic transport, resulting in interchange inefficiencies and incompatibilities between artificial ion devices and biological tissue interfaces. The development of heterogating gel iontronics offers a significant advancement in bridging this gap, drawing inspiration from the complex ionic transmission mechanisms found in biological synapses within neural networks. These heterogating gels utilize a biphasic architecture, where the heterointerface effect constructs ionic transfer energy barriers, enabling distinct signal transmission among different ions. In systems with multiple ion species, heterogating gel iontronics allow for precise control of ion transmission, realizing hierarchical and selective cross-stage signal transmission as a neuromorphic function. This perspective highlights the vast potential of heterogating iontronics in applications such as biosensing, neuroprosthetics, and ion separation technologies. Meanwhile, it also addresses the current challenges, including scaling production, ensuring biocompatibility, and integrating with existing technologies, which are crucial for future development. The advancement of heterogating gels is expected to promote the integration between abiotic and biotic systems, with broad implications for smart sensors, bioneural devices, and beyond.

Bidirectional Vectorial Holography Using Bi-Layer Metasurfaces and Its Application to Optical Encryption.

The field of optical systems with asymmetric responses has grown significantly due to their various potential applications. Janus metasurfaces are noteworthy for their ability to control light asymmetrically at the pixel level within thin films. However, previous demonstrations are restricted to the partial control of asymmetric transmission for a limited set of input polarizations, focusing primarily on scalar functionalities. Here, optical bi-layer metasurfaces that achieve a fully generalized form of asymmetric transmission for any input polarization are presented. The designs owe much to the theoretical model of asymmetric transmission in reciprocal systems, which elucidates the relationship between front- and back-side Jones matrices in general cases. This model reveals a fundamental correlation between the polarization-direction channels of opposing sides. To circumvent this constraint, partitioning the transmission space is utilizedto realize four distinct vector functionalities within the target volume. As a proof of concept, polarization-direction-multiplexed Janus vectorial holograms generating four vectorial holographic images are experimentally demonstrated. When integrated with computational vector polarizer arrays, this approach enables optical encryption with a high level of obscurity. The proposedmathematical framework and novel material systems for generalized asymmetric transmission may pave the way for applications such as optical computation, sensing, and imaging.

A trans-synaptic IgLON adhesion molecular complex directly contacts and clusters a nicotinic receptor.

The localization and clustering of neurotransmitter receptors at appropriate postsynaptic sites is a key step in the control of synaptic transmission. Here, we identify a novel paradigm for the synaptic localization of an ionotropic acetylcholine receptor (AChR) based on the direct interaction of its extracellular domain with a cell adhesion molecule of the IgLON family. Our results show that RIG-5 and ZIG-8, which encode the sole IgLONs in C. elegans, are tethered in the pre- and postsynaptic membranes, respectively, and interact in vivo through their first immunoglobulin-like (Ig) domains. In addition, ZIG-8 traps ACR-16 via a direct cis- interaction between the ZIG-8 Ig2 domain and the base of the large extracellular AChR domain. Such mechanism has never been reported, but all these molecules are conserved during evolution. Similar interactions may directly couple Ig superfamily adhesion molecules and members of the large family of Cys-loop ionotropic receptors, including AChRs, in the mammalian nervous system, and may be relevant in the context of IgLON-associated brain diseases.

Pylore Krishnaier Rajagopalan: Pioneer in Kyasanur Forest Disease Research and His Contributions to Zoonotic Disease Studies.

Pylore Krishnaier Rajagopalan was a distinguished public health expert who made significant breakthroughs in the research of Kyasanur forest disease (KFD), a prevalent tick-borne viral ailment in South India. His extensive research on KFD provided vital insights into the impact of the disease on public health and considerably advanced our knowledge of it. Rajagopalan's work also encompasses the study of zoonotic diseases, where he made substantial contributions to our understanding of their epidemiology and control. His research on KFD was instrumental in comprehending the disease transmission dynamics, clinical manifestations, and control strategies, resulting in improved management practices in regions where the disease is endemic. Rajagopalan's contributions have had a long-lasting impact on public health practices, as his work has influenced both scientific research and public health policies. The enduring effects of his work can be observed in the enhanced disease surveillance, outbreak response, and comprehension of zoonotic disease dynamics, which will continue to inform contemporary public health practices.

Are electric vehicles riskier? A comparative study of driving behaviour and insurance claims for internal combustion engine, hybrid and electric vehicles

Electric vehicles (EVs) differ significantly from their internal combustion engine (ICE) counterparts, with reduced mechanical parts, Lithium-ion batteries and differences in pedal and transmission control. These differences in vehicle operation, coupled with the proliferation of EVs on our roads, warrant an in-depth investigation into the divergent risk profiles and driving behaviour of EVs, Hybrids (HYB) and ICEs. In this unique study, we analyze a novel telematics dataset of 14,642 vehicles in the Netherlands accompanied by accident claims data. We train a Logistic Regression model to predict the occurrence of driver at-fault claims, where an at-fault claim refers to First and Third Party damages where the driver was at fault. Our results reveal that EV drivers are more exposed to incurring at-fault claims than ICE drivers despite their lower average mileage. Additionally, we investigate the financial implications of these increased at-fault claims likelihoods and have found that EVs experience a 6.7% increase in significant first-party damage costs compared to ICE. When analyzing driver behaviour, we found that EVs and HYBs record fewer harsh acceleration, braking, cornering and speeding events than ICE. However, these reduced harsh events do not translate to reducing claims frequency for EVs. This research finds evidence of a higher frequency of accidents caused by Electric Vehicles. This burden should be considered explicitly by regulators, manufacturers, businesses and the general public when evaluating the cost of transitioning to alternative fuel vehicles.

A methodology for predicting and optimizing the lubrication of an off-road machine transmission

This article presents an analysis method based on lumped-parameters (LP) and computational fluid dynamics (CFD) to evaluate the behavior and calibrate the lubrication (LUB) circuit in an agricultural dual-clutch transmission. Gearbox LUB is crucial because it affects reliability, life, and transmission efficiency. The transmission’s hydraulic circuit consists of the higher pressure power transmission control and actuation circuit and the low pressure LUB circuit. The former was analyzed with LP approach, instead the latter was modeled with CFD approach due to its geometric complexity. The results will be contextualized by commenting on the advantages and limitations of LP and CFD analysis, finally outlining a mixed analysis methodology. The simulations are solved for different engine speed. The results are used to calibrate a comprehensive LP model (model) and to optimize the LUB circuit by adjusting some critical design parameters. As an experimental approach, simplified tests are usually performed ignoring the action of the centrifugal force, which has a great impact on the flow regime inside the LUB ducts. This work aims to develop a methodology for analyzing LUB in all parts of the gearbox, which can help designers test various combinations within industrial timeframes and obtain reliable and the most efficient configuration.

Performance Control of the 2-Speed Transmission Equipped to Electric Motor Driven Track Vehicle with Cross-Drive

Performance Control of the 2-Speed Transmission Equipped to Electric Motor Driven Track Vehicle with Cross-Drive

A Comprehensive IoT edge based smart irrigation system for tomato cultivation

Agriculture industry is the primary engine for a country's economic development. Growing crops using minimum irrigation water is a major challenge for farmers. In conventional farming, crops may be affected by various diseases due to inadequate irrigation scheduling. Recent proposals have suggested using Edge-IoT, AI, and distributed computing to accelerate the inference procedure utilized in smart irrigation applications. The use of resource-constrained edge servers and edge devices used to deliver smart agriculture applications can cause latency-sensitive workloads to interfere with one another. To address this issue, we design a long-range (LoRa) edge IoT computing-based sustainable and customized smart irrigation framework to capture the real-time data of tomato plants. This helps in automatic underground drip irrigation scheduling. This also predicts total water demand and usage, and measure plant growth status. The edge-IoT cloud data transmission control and optimization has been enforced using Smart irrigation data optimization and robust transmission (SIDORT) Message Queuing Telemetry Transport (MQTT) system. We develop a hybrid algorithm named Linked least traversal (LLT) for machine-to-machine communication (M2M). Also, a Reinforcement learning (RL) based Optimal Soil Wetness Closeness Policy (OSWCP) for irrigation scheduling has been proposed. The performance of the proposed smart irrigation models has been validated through extensive experiments using real-time data in which OSWCP performance has been measured at a 97.88 % accuracy rate. Additionally, a comparison of our proposed architecture has been accomplished by resolving the existing smart irrigation system challenges.

ABBR: An augmented BBR for collaborative intelligent transmission over heterogeneous networks in IIoT

In the era of Industry 5.0, with the deep convergence of Industrial Internet of Things (IIoT) and 5G technology, stable transmission of massive data in heterogeneous networks becomes crucial. This is not only the key to improving the efficiency of human–machine collaboration, but also the basis for ensuring system continuity and reliability. The arrival of 5G has brought new challenges to the communication of IIoT in heterogeneous environments. Due to the inherent characteristics of wireless networks, such as random packet loss and network jitter, traditional transmission control schemes often fail to achieve optimal performance. In this paper we propose a novel transmission control algorithm, aBBR. It is an augmented algorithm based on BBRv3. aBBR dynamically adjusts the sending window size through real-time analysis to enhance the transmission performance in heterogeneous networks. Simulation results show that, compared to traditional algorithms, aBBR demonstrates the best comprehensive performance in terms of throughput, latency, and retransmission. When random packet loss exists in the link, aBBR improves the throughput by an average of 29.3% and decreases the retransmission rate by 18.5% while keeping the transmission delay at the same level as BBRv3.

Impact of initial outbreak locations on transmission risk of infectious diseases in an intra-urban area

Infectious diseases usually originate from a specific location within a city. Due to the heterogenous distribution of population and public facilities, and the structural heterogeneity of human mobility network embedded in space, infectious diseases break out at different locations would cause different transmission risk and control difficulty. This study aims to investigate the impact of initial outbreak locations on the risk of spatiotemporal transmission and reveal the driving force behind high-risk outbreak locations. First, we built a SLIR (susceptible-latent-infectious-removed)-based age-stratified meta-population model, integrating mobile phone location data, to simulate the spreading process of an infectious disease across fine-grained intra-urban regions (i.e., 649 communities of Shenzhen City, China). Based on the simulation model, we evaluated the transmission risk caused by different initial outbreak locations by proposing three indexes including the number of infected cases (CaseNum), the number of affected regions (RegionNum), and the spatial diffusion range (SpatialRange). Finally, we investigated the contribution of different influential factors to the transmission risk via machine learning models. Results indicate that different initial outbreak locations would cause similar CaseNum but different RegionNum and SpatialRange. To avoid the epidemic spread quickly to more regions, it is necessary to prevent epidemic breaking out in locations with high population-mobility flow density. While to avoid epidemic spread to larger spatial range, remote regions with long daily trip distance of residents need attention. Those findings can help understand the transmission risk and driving force of initial outbreak locations within cities and make precise prevention and control strategies in advance.

Adaptive Transmission Interval-Based Self-Triggered Model Predictive Control for Autonomous Underwater Vehicles with Additional Disturbances

Most existing model predictive control (MPC) methods overlook the network resource limitations of autonomous underwater vehicles (AUVs), limiting their applicability in real systems. This article addresses this gap by introducing an adaptive transmission, interval-based, and self-triggered model predictive control for AUVs operating under ocean disturbances. This approach enhances system stability while reducing resource consumption by optimizing MPC update frequencies and communication resource usage. Firstly, the method evaluates the discrepancy between system states at sampling instants and their optimal predictions. This significantly reduces the conservatism in the state-tracking errors caused by ocean disturbances compared to traditional approaches. Secondly, a self-triggering mechanism was employed, limiting information exchange to specified triggering instants to conserve communication resources more effectively. Lastly, by designing a robust terminal region and optimizing parameters, the recursive feasibility of the optimization problem is ensured, thereby maintaining the stability of the closed-loop system. The simulation results illustrate the efficacy of the controller.

Comparative Study Between the OSI Model and the TCP/IP Model: Architecture and Protocols in Computer Networking Systems

In the world of computing and networking, it is critical to understand the theoretical framework that underlies data communication to ensure the best performance and compatibility between various systems. Both the Open Systems Interconnection (OSI) and Transmission Control Protocol/Internet Protocol (TCP/IP) models offer a comprehensive perspective on how the entire communication operation is separated into various layers, with each layer assigned particular roles and functions. This paper compares the OSI and TCP/IP models in terms of the functionalities and responsibilities of the various layers in each model, with an emphasis on how these layers work together to ensure effective and robust network communications. The paper covers encapsulating and decapsulating processes, managing sessions, and ensuring reliable data transmission. The TCP/IP model focuses on practical application with four main layers, while the OSI model has seven detailed layers that provide a theoretical and structured approach. The goal of both models is reliable and standardized communication, which in turn promotes interoperability in a variety of network environments.

Epidemiologic Assessment of Scabies: Actuality of Airborne Transmission and Additional Standards to Reduce Spread of Contagion and Reinfestation

Scabies are caused by parasites that live their entire life within the outer layers of the epidermis. When dislodged either by gravity, friction, motion, wind, or static electricity, they assume great risks to survival. Innate abilities to sense human smell and heat, to move over short distances, and to penetrate the skin quickly allow them a fighting chance to find a new host if they land within 4 inches of a human. Females store sperm, allowing one mite to begin a colony. Transmission is by person-to-person, fomite, and airborne. They are aerodynamic, light, and balloon-shaped, all making airborne transmission easier than previously understood, as well as explaining the dissemination of mites beyond the normal zones of activity of the index case. Presently, the bulk of the medical literature suggests that transmission from inanimate objects poses little concern in common scabies. However, as mites can navigate through cloth gowns, one might consider protection with more protective garb. Mites cannot penetrate through waterproof clothing, and thus, this attire should be recommended to avoid reinfestation and infesting others. Sofas, chairs, office furniture, and car seats on which an index case might sit need to be covered with plastic sheeting. Given that the half-life of ivermectin is 18 hours and that mites dehydrate within 96 hours, strict transmission controls are only needed for 3 days to avoid reinfestation as well as infesting others. Key Points Scabies is an intensely itchy skin rash caused by a burrowing mite that infects the outer layers of the skin. Scabies is contagious and usually spread by direct, prolonged skin-to-skin contact with an infected person; however, fomite and airborne transmission are also operative. Precautions should be in place to avoid direct skin-to-skin contact between a patient with scabies and visitors. Water-proof clothing would be advisable, especially in cases involving Norwegian scabies. Success rates with oral ivermectin would more closely approach 100% if all transmission factors, including fomite and airborne, were addressed.

Marginal improvement procedures for top-[formula omitted] selection

Given a fixed simulation budget, the problem of selecting the best and top-m alternatives among a finite set of alternatives have been studied separately in simulation optimization literature, because the existing sampling procedures are often dedicated to one problem. Under a Bayesian framework, we formulate the top-m selection into a stochastic dynamic program, and characterize the optimal sampling policy via Bellman equations. To determine sequential sampling decisions, we measure the expected marginal improvement from obtaining one additional simulation observation based on predictive distributions, and then develop two cheaply computational approximations to the improvement, thereby yielding two generic sampling procedures that are efficient in selecting top-m alternative(s). The two procedures are proved to be consistent, in a sense that the best and top-m alternatives can be correctly identified as the simulation budget goes to infinity. Numerical experiments on synthetic problems and a coronavirus transmission control application are conducted to demonstrate the efficiency and generality of our procedures.

Bunyamwera Virus Infection of Wolbachia-Carrying Aedes aegypti Mosquitoes Reduces Wolbachia Density.

Wolbachia symbionts introduced into Aedes mosquitoes provide a highly effective dengue virus transmission control strategy, increasingly utilised in many countries in an attempt to reduce disease burden. Whilst highly effective against dengue and other positive-sense RNA viruses, it remains unclear how effective Wolbachia is against negative-sense RNA viruses. Therefore, the effect of Wolbachia on Bunyamwera virus (BUNV) infection in Aedes aegypti was investigated using wMel and wAlbB, two strains currently used in Wolbachia releases for dengue control, as well as wAu, a strain that typically persists at a high density and is an extremely efficient blocker of positive-sense viruses. Wolbachia was found to reduce BUNV infection in vitro but not in vivo. Instead, BUNV caused significant impacts on density of all three Wolbachia strains following infection of Ae. aegypti mosquitoes. The ability of Wolbachia to successfully persist within the mosquito and block virus transmission is partially dependent on its intracellular density. However, reduction in Wolbachia density was not observed in offspring of infected mothers. This could be due in part to a lack of transovarial transmission of BUNV observed. The results highlight the importance of understanding the complex interactions between multiple arboviruses, mosquitoes and Wolbachia in natural environments, the impact this can have on maintaining protection against diseases, and the necessity for monitoring Wolbachia prevalence at release sites.