Overload Situations Research Articles

A Novel Adaptive Model Predictive Control Strategy of Solid Oxide Fuel Cell in DC Microgrids

Solid oxide fuel cell (SOFC) becomes increasingly popular in dc microgrid applications. Controlling SOFC is challenging because the dynamics of SOFC are difficult to maintain under complex internal reactions and changing operating conditions. To solve these problems, this article proposes a novel adaptive model predictive control (AMPC) algorithm, which adopts a parameter estimator to update the system parameters online. The robustness of the proposed AMPC is investigated under different microgrid scenarios, including the overload, underload, short-circuit, and significant dc bus voltage drop situations. The proposed AMPC algorithm produces superior SOFC control performance over the conventional model predictive control (MPC), Wiener MPC, and PI and fuzzy PI controllers. Furthermore, it significantly reduces the system model dependence that is shared by nearly all the model-based SOFC control methods. The convergence of parameter estimation in the proposed AMPC is rigorously proved. The effectiveness of the proposed algorithm is validated through hardware-in-the-loop experiments under various operating conditions and system parameter variations.

HARNESS: High Availability Supportive Self Reliant Network Slicing in 5G Networks

Mobile Network Operator (MNO)s avail the benefit of providing an isolated service with the network slice in a variety of forms like enhanced Mobile Broadband (eMBB), ultra Reliable Low Latency Communications (uRLLC), and massive Machine Type Communications (mMTC). However, they face challenges in handling situations of overload, congestion, and scaling with the arrival of unexpected control plane User Service Requests (USRs) leading to the dropping of USRs, and hence disturbing the slice’s High Availability (HA). This paper presents a novel High Availability supportive self Reliant NEtwork Slicing System (HARNESS) for 5G Core, powered by intelligent and autonomous Self Organizing Network (SON) paradigm. In HARNESS, we propose algorithms to intelligently schedule and serve the significant portion of control plane USRs for both delay tolerant and delay sensitive slices, to ensure their uninterrupted HA service provision. Along with efficient resource utilization, the HARNESS shows improvements over the traditional HA provisioning methods, in preventing the occluding of crucial control plane USRs by 60% and reducing the average response time for these USRs by 50%. We developed the HARNESS framework in a 5G test-bed system using eXpress Data Path (XDP) and extended Berkeley Packet Filter (eBPF) mechanism for coherent and optimized end-to-end working of it. With this additional gear, HARNESS productively contributes to achieving 3.2% better slice service HA in the minimal two nodes active/active cluster configuration.

Conversational recommendation: Theoretical model and complexity analysis

Recommender systems help users find items of interest in situations of information overload in a personalized way, using needs and preferences of individual users. In conversational recommendation approaches, the system acquires needs and preferences in an interactive, multi-turn dialog. This is usually driven by incrementally asking users about their preferences about item features or individual items. A central research goal in this context is efficiency, evaluated concerning the number of required interactions until a satisfying item is found. Today, research on dialog efficiency is almost entirely empirical, aiming to demonstrate, for example, that one strategy for selecting questions to ask the user is better than another one in a given application. This work complements empirical research with a theoretical, domain-independent model of conversational recommendation. This model, designed to cover a range of application scenarios, allows us to investigate the efficiency of conversational approaches in a formal way, particularly concerning the computational complexity of devising optimal interaction strategies. An experimental evaluation empirically confirms our findings.

Scaling beyond Bandwidth Limitations: Wireless Control with Stability Guarantees under Overload

An important class of cyber-physical systems relies on multiple agents that jointly perform a task by coordinating their actions over a wireless network. Examples include self-driving cars in intelligent transportation and production robots in smart manufacturing. However, the scalability of existing control-over-wireless solutions is limited as they cannot resolve overload situations in which the communication demand exceeds the available bandwidth. This article presents a novel co-design of distributed control and wireless communication that overcomes this limitation by dynamically allocating the available bandwidth to agents with the greatest need to communicate. Experiments on a real cyber-physical testbed with 20 agents, each consisting of a low-power wireless embedded device and a cart-pole system, demonstrate that our solution achieves significantly better control performance under overload than the state of the art. We further prove that our co-design guarantees closed-loop stability for physical systems with stochastic linear time-invariant dynamics.

Iron Metabolism Markers in Patients with Tuberculosis Combined with HIV Infection

Background. Changes of iron metabolism in patients with tuberculosis combined with HIV infection is an important task of phthisiology, since, on the one hand, iron deficiency can have a negative effect on the course of the tuberculous process. On the other hand, compensation for iron deficiency may be creating an iron overload situation, promoting replication of M. tuberculosis. Aims to study in a comparative aspect, changes in iron metabolism markers in patients with tuberculosis combined with HIV infection and without it. Methods. The study included 284 tuberculosis patients who were divided into 2 groups. The first group included 141 patients with tuberculosis combined with HIV (TB/HIV group). The comparison group consisted of 143 tuberculosis patients without HIV (TB group). The assessment of the bodys iron supply was carried out in terms of the concentration of serum iron, transferrin (TF), and ferritin (FT). The study was conducted separately in men and women, since the indicators of iron metabolism in healthy men and women differ significantly. Results. It was found that in men with TB/HIV patients, the decrease in serum iron less than the lower limit of the norm took place in 47.6%, and in the TB group in 27.3% of cases (p 0.01). The concentration of TF in the blood serum in the group of TB/HIV patients in men decreased in 69.9%, and in the group of TB patients in 31.2% of cases (p 0.01). The level of FT in the TB/HIV group increased in 19.4%, and in the TB group in 8.3% of cases (p 0.05). In women, a decrease in iron levels in the group of TB/HIV patients was observed in 39.5%, and in the TB group only in 2.2% of cases (p 0.01), a decrease in the level of TF was observed in 55.2% and 24.3% (p 0.01). A decrease in ferritin levels below 15 ng/ml was observed in 15.7% of women with TB/HIV and in 10.6% of TB patients. A negative relationship was found between iron content and CRP levels. Conclusion. The results of studied made it possible to conclude that in all cases the decrease in iron was caused not by a true deficiency of iron, but by its redistribution in the body. At the same time, a small number of women with tuberculosis combined with HIV infection and tuberculosis without HIV infection showed a significant decrease in ferritin levels, which indicated that they had a true iron deficiency.

Spring Festival Holiday Tourism Data Mining Based on the Deep Learning Model

With the advent of the era of big data, people have entered a situation of information overload, how do users filter out the information they need from a large amount of information. When users browse the website, they will record their search or click behavior, and the recommendation system will mine the data based on these data, and recommend the information they need for each user. With the birth of the recommender system, it has indeed changed the way people obtain information. Instead of relying solely on search engines to obtain information, it can obtain the information they want without people’s “consciousness.” This shift has made it easier for people to access information. This paper conducts research on travel recommendation during the Spring Festival holiday. The paper introduces deep learning model and data mining technology, proposes that the recommendation system has three important modules, and obtains the corresponding flowchart. The recommendation system was optimized, and a comparison chart of coverage before and after optimization was obtained. Before optimization, the coverage rate of cities and scenic spots was 45.52% and 21.25%, respectively, and reached 55.65% and 49.81% after optimization.

Beyond microplastics - investigation on health impacts of submicron and nanoplastic particles after oral uptake in vitro

The continuously increasing use of plastics is supposed to result in a rising exposure of MNPs to humans. Available data on human health risks of microplastics after oral uptake increased immensely in the past years and indicates very likely only low risks after oral consumption. Concerning nanoplastics, uptake, transport and potential adverse effects after oral uptake are less well understood. This study aims to investigate differences between microplastic particles and particles in the submicron- and nanoscaled size derived from food-relevant polymers with a particle size range consistent with higher potential for cellular uptake, fate, and effects when applied to human intestinal and liver cells. This work includes the development of cellular and subcellular detection methods for synthetic polymeric particles in the micro- and nanometer-range, using Scanning Electron Microscopy, Small-Angle X-ray and Dynamic Light Scattering methods, Asymmetric Flow Field Flow Fractionation, octanol-water fractionation, fluorescence microscopy and flow cytometry. Polylactic acid (250 nm and 2 μm (polydisperse)), melamine formaldehyde (366 nm) and polymethylmethacrylate (25 nm) were thoroughly characterized. The submicro- and nanoplastic test particles showed an increased uptake and transport quantity through intestinal cells. Both types of particles resulted in observed differences of uptake behavior, most likely influenced by different lipophilicity, which varied between the polymeric test materials. Toxic effects were detected after 24 h only in overload situations for the particles in the submicrometer range. This study provides further evidence for gastrointestinal uptake of submicro- and nanoplastics and points towards differences regarding bioavailability between microplastics and smaller plastic particles that may result following the ingestion of contaminated food and beverages. Furthermore, the results reinforce the importance for studying nanoplastics of different materials of varying size, surface properties, polymer composition and hydrophobicity.

Mixed-model sequencing versus car sequencing: comparison of feasible solution spaces

ABSTRACT In the automotive industry, a great challenge of production scheduling is to sequence cars on assembly lines. Among a wide variety of scheduling approaches, academics and manufacturers pay close attention to two specific models: Mixed-Model Sequencing (MMS) and Car Sequencing (CS). Whereas MMS explicitly considers the assembly line balance, CS operates with sequencing rules to find the best car sequence fulfilling the assembly plant requirements, like minimising work overload for assembly workers. Meanwhile, automakers including Renault Group are increasingly willing to consider other requirements, like end-to-end supply chain matters, in production planning and scheduling. In this context, this study compares MMS- and CS-feasible solution spaces to determine which workload-oriented sequencing model would be the most appropriate to later integrate new optimisation. We introduce two exact methods based on Dynamic Programming to assess the gap between both models. Numerical experiments are carried out on real-life manufacturing features from a Renault Group assembly plant. They show that MMS generates more feasible sequences than CS regardless of the sequencing rule calculation method. Only the sequencing rules used by real-life production schedulers result in a higher number of distinct feasible sequences for CS, highlighting that the plant might select a sequence with work overload situations.

Transportation in the Sharing Economy

Traditionally, individuals and firms have bought and owned resources. For instance, owning a car was a status symbol for people. In recent years, this focus has changed. Young people just want to have some convenient means of transportation available. Sharing cars, bikes, or rides is also acceptable and has the advantage of increased sustainability compared with everyone owning such a device. A similar development can also be observed in industry. Already for decades, smaller farmers in rural areas have shared some expensive harvesting machines, via cooperatives. In recent years, cost pressures have incentivized all firms to use their equipment more efficiently and to avoid idle capacities. This has led, among other things, to the exchange of transportation requests between smaller carriers, when one of them faces an overload situation and another has idle resources. Similarly, some production firms share storage space and logistics service providers operate this storage jointly with greater efficiency than each firm could do separately. All these tendencies have led to the development of a new paradigm, the “Sharing Economy.” In transportation, these resources are the vehicles used to deliver goods or move passengers. Given an increasing pressure to act economically and ecologically sustainable, efficient mechanisms that help to benefit from idle capacities are on the rise. They are typically organized through digital platforms that facilitate the efficient exchange of goods or services and help cope with data privacy issues. Both transportation companies and heavy users of transportation services need to learn how to play in a world of shared idle capacities. “Transportation in the Sharing Economy” was the theme of the 2019 Transportation Science and Logistics Workshop held in Vienna, and it is therefore also the focus of this associated special issue. The papers included cover several forms of shared resources in transportation, where the first part deals with freight, whereas in the second part, the focus lies on passenger transportation. Each study highlights the benefits of sharing resources. We received 40 submissions, of which 10 papers were accepted for this special issue after the reviewing process.

Single-stage MBBR as post-treatment step for upgrading large WWTPs – Experiences of one-year pilot plant operation

In growing urban areas, increasing nitrogen loads to large WWTPs can be problematic for the existing nitrification/denitrification stage and necessitate the enlargement of the entire wastewater treatment system. Nitrogen removal is usually the most critical process in overload situations, often limited by the hydraulic capacities for recirculation. A simple and cost-effective way to meet low nitrogen effluent requirements is the proposed single-stage MBBR. This system can be implemented additionally as a bypass in the effluent. To investigate the practicability of the proposed concept, a pilot plant was operated to polish treated wastewater with an MBBR. The process is designed for post-treatment denitrification to eliminate the remaining nitrate‑nitrogen in the already treated wastewater. The paper extends the current knowledge of low concentration gradients, since no information is available on the post-treatment of nitrate‑nitrogen to 2.5 mg/L or below. In addition, the tested hydraulic retention time (HRT) of only 60 min is exceptional, allowing future single-stage MBBRs to be sized smaller. The first results of one year of operation showed a stable nitrate‑nitrogen reduction from 10.0 mgNO3-N/L to ≪5.0 mgNO3-N/L to comply with required effluent concentrations for total nitrogen. A maximum removal rate of 2.07 gNOx-N/(m2·d) at T = 20 °C was reached. Average NOx-N removal of 71% could be achieved at a minimal HRT of only 1 h. Following a two-month start-up phase, the process proved to be robust: after carbon dosage interruptions, full performance was regained after only three days in summer.

Research of Juice-Containing Products with Collagen Additive

One of the most important tasks for food enterprises is the development of food rations and products with high biological value, enriched with essential substances. To expand the range of such products, non-traditional plant and animal raw materials are widely used. Protein raw materials are of particular interest, since they have structural and physiological significance for the human body. Collagen is one of the most popular and multifunctional bioactive supplements. Collagen is a major protein in human connective tissue: cartilage, cornea, arteries and skin. It affects their strength and energy, structure and elasticity, strengthens not only muscle fibers, but also smooth muscles, such as the heart. Collagen is constantly reproduced in the human body on its own, but after a person reaches 25 years of age, this process slows down and progressively weakens in old age. Collagen storage disorders can also be the body at levels over 90%, which is unattainable when collagen is taken in pill triggered in situations of constant overload (for example, in strength sports or in cases of intense physical activity). The liquid form of collagen for drinking is absorbed by or capsule form. We have developed recipes for a new range of juice products based on fruit and vegetable raw materials, enriched with vegetable and animal collagen, tomato, beef, pork and fish. The optimal amount of this biological additive in beverages has been determined, while ensuring the required quality of products, the preservation of its active properties has been studied. Also, studies have been carried out on juice products with a collagen supplement "in vivo".

Predictor-Based Current Limitation Method for a DC Motor-Actuated Upper-Limb Rehabilitation Exoskeleton

Current limitation is crucial to protect DC motors from overheating in overload situations. This consideration is more critical in applications that involve the movement of variable loads, such as exoskeleton applications, where there exists dynamic human-robot interaction. This work presents a software current limitation method based on a continuous DC motor model predictor. By predicting, according to the motor model, the voltages that would make the current match a threshold, the proposed method dynamically saturates the maximum voltages applicable to the motor to maintain the current under the predefined threshold. Using this method, a full-time current limitation can be obtained, but if desired, it also allows current peaks of configurable duration. Only motor parameters need to be known for the application of this algorithm, and it is easily adjustable to different DC motor models. Stand-alone motor tests show an effective limitation of current, achieving up to a 98.04% of maximum current when limited. The method has also been successfully validated in a rehabilitation exoskeleton application with four participants, obtaining an average current of 92.34% of current threshold when limited.

Management of Severe Acute Kidney Injury

Acute kidney injury (AKI) is encountered in approximately one-fourth of children admitted to the intensive care units (ICUs). As AKI is known to prolong ICU stay as well as increase the overall morbidity and mortality, it is important to identify it timely and take appropriate measures to curtail further injury. Infections continue to be the most common cause in developing countries. While pneumonia, diarrhea, and tropical infections such as dengue, malaria, scrub typhus, and leptospirosis are major causes of AKI in children; glomerular diseases, systemic disorders, envenomations, and drugs also account for a major proportion of AKI in low and low-middle income countries. Fluid overload is associated with adverse outcomes in multiple studies; hence proper assessment of volume status is vital. Novel prognostic markers such as renal angina index and furosemide stress test are increasingly being applied in routine clinical care. The current guidelines recommend against the usage of furosemide for the prevention and management of AKI, except in a situation of fluid overload. Kidney replacement therapy (KRT) should be initiated promptly in AKI when indicated. The timing of initiation of KRT in AKI continues to be debatable and has attracted considerable research. While peritoneal dialysis continues to be the modality most often used in infants and young children, continuous KRT and sustained low-efficiency dialysis are used in hemodynamically unstable patients. Timely identification and management of the various complications reduce mortality. Cutting-edge multinational trials over the past decade have significantly impacted our understanding in managing this complex disorder.

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.

The Beauty of the Fragment Reconstituted in the Great Wall

Max Hattler’s short abstract animations demonstrate an awareness of the form’s historic 1920’s European Abstract Animation precedents, is informed by the structurally focused minimalism of the 60’s and re-tools pre-cinema toys. Yet his work speaks to the contemporary technological environment he occupies and experiences directly. His move to Hong Kong and his recent Serial Parallels is also a predictive probe into future media environments. Hattler’s digital architectures are designed to make sense of the technological situation of speed and information overload which Vilem Flusser marks as amnesic and Marshall McLuhan identifies as an acoustic space readable through pattern recognition. His practice makes productive use of the flexible and modular qualities of contemporary digital image-making technologies for both production and publication purposes.

Design and Analysis of Zigzag Classifier in Food Industry Applications

In a zigzag classifier the material is being entertained utilizing varied channel velocities and mass load of the air. Specialty of zigzag classifier is it is being used in separation of particles having about the same size, but differing specific gravity, Separation of bulk materials which cause challenges and expensive costs if sieved. In this Zigzag classifier, sugar, salt, flour and grain, starch, milk products; spices; tea, gelatin, and vegetables are included in a typical application for the food sector. Zigzag classifiers are usually maintenance free, wear-resistant, overload-resistant and not sensitive to changes in the composition of the feed material. Due to these properties, the classification system can be operated without any oversight for lengthy durations. Even under overload situations, the goal output is clean particles or lightweight material.

The role of leptin in monitoring training loads during rowing: a systematic review

Objective: In competitive sports, too small or too large loads lead to poor sports results. Situation of overload are particularly dangerous to the body, which may lead to overtraining. In this work, the literature on the possibility of assessing training loads with the use of leptin concentration measurement in men and women practicing rowing was analysed. Materials and methods: A systematic review was performed using the Scopus, Pubmed and Google Scholar databases between 1995-2020. After an initial analysis of 56 articles and taking the analysed topics into account, 25 articles were included in this review. As part of the review, data for 75 rowers were analysed. The usefulness of leptin - a hormone produced by adipose tissue - as a marker of training loads in several sports disciplines, with particular emphasis on rowing, was evaluated. Within this context, the role of leptin may be to control these loads due to its relatively high sensitivity in response to increases in training intensity or volume. The presented general characteristics of rowing and the physiological basis of exercise are the background for considerations on the possibility of using leptin as a burden marker in this discipline. Results: Due to the fact that the concentration of leptin correlates with the content of adipose tissue and BMI (Body Mass Index), its changes may inform about training loads directly related to the amount of energy expenditure. A review of the literature from the last 25 years, i.e. from the moment when this hormone was discovered, allowed to formulate the thesis that leptin may be a marker of training loads, however, determining its concentration makes sense when the same factors that may affect its secretion are taken into account each time. Conclusions: Training in rowing, that involves high training loads, causes significant changes in blood leptin levels. Training periods with high exercise load, associated with a significant increase in energy expenditure, lead to a decrease in resting leptin concentration, while periods with less load increase it. The main factor determining changes in leptin concentration during training is the amount of energy expenditure, which in the case of rowing involving very large muscle groups, is very high. Although the amount of energy expenditure in training, leading to a decrease in leptin concentration is difficult to determine, the energy expenditure cannot be less than 800 kcal in a single training unit.

Stochastic mixed model sequencing with multiple stations using reinforcement learning and probability quantiles

In this study, we propose a reinforcement learning (RL) approach for minimizing the number of work overload situations in the mixed model sequencing (MMS) problem with stochastic processing times. The learning environment simulates stochastic processing times and penalizes work overloads with negative rewards. To account for the stochastic component of the problem, we implement a state representation that specifies whether work overloads will occur if the processing times are equal to their respective 25%, 50%, and 75% probability quantiles. Thereby, the RL agent is guided toward minimizing the number of overload situations while being provided with statistical information about how fluctuations in processing times affect the solution quality. To the best of our knowledge, this study is the first to consider the stochastic problem variation with a minimization of overload situations.

Solving the mixed model sequencing problem with reinforcement learning and metaheuristics

This study presents a reinforcement learning (RL) approach for the mixed model sequencing (MMS) problem with a minimization of work overload situations. The proposed approach generates the sequence in a constructive way, so that an action denotes the model to be sequenced next. The trained policy quickly creates an initial sequence, which allows us to use the cutoff time to further improve the solution quality with a metaheuristic. Our numerical evaluation based on an existing benchmark dataset shows that our approach is superior to established methods if the demand plan follows its expected distribution from the learning process.

Specific amino acid supplementation rescues the heart from lipid overload-induced insulin resistance and contractile dysfunction by targeting the endosomal mTOR–v-ATPase axis

ObjectiveThe diabetic heart is characterized by extensive lipid accumulation which often leads to cardiac contractile dysfunction. The underlying mechanism involves a pivotal role for vacuolar-type H+-ATPase (v-ATPase, functioning as endosomal/lysosomal proton pump). Specifically, lipid oversupply to the heart causes disassembly of v-ATPase and endosomal deacidification. Endosomes are storage compartments for lipid transporter CD36. However, upon endosomal deacidification, CD36 is expelled to translocate to the sarcolemma, thereby inducing myocardial lipid accumulation, insulin resistance, and contractile dysfunction. Hence, the v-ATPase assembly may be a suitable target for ameliorating diabetic cardiomyopathy. Another function of v-ATPase involves the binding of anabolic master-regulator mTORC1 to endosomes, a prerequisite for the activation of mTORC1 by amino acids (AAs). We examined whether the relationship between v-ATPase and mTORC1 also operates reciprocally; specifically, whether AA induces v-ATPase reassembly in a mTORC1-dependent manner to prevent excess lipids from entering and damaging the heart. MethodsLipid overexposed rodent/human cardiomyocytes and high-fat diet-fed rats were treated with a specific cocktail of AAs (lysine/leucine/arginine). Then, v-ATPase assembly status/activity, cell surface CD36 content, myocellular lipid uptake/accumulation, insulin sensitivity, and contractile function were measured. To elucidate underlying mechanisms, specific gene knockdown was employed, followed by subcellular fractionation, and coimmunoprecipitation. ResultsIn lipid-overexposed cardiomyocytes, lysine/leucine/arginine reinternalized CD36 to the endosomes, prevented/reversed lipid accumulation, preserved/restored insulin sensitivity, and contractile function. These beneficial AA actions required the mTORC1–v-ATPase axis, adaptor protein Ragulator, and endosomal/lysosomal AA transporter SLC38A9, indicating an endosome-centric inside-out AA sensing mechanism. In high-fat diet-fed rats, lysine/leucine/arginine had similar beneficial actions at the myocellular level as in vitro in lipid-overexposed cardiomyocytes and partially reversed cardiac hypertrophy. ConclusionSpecific AAs acting through v-ATPase reassembly reduce cardiac lipid uptake raising the possibility for treatment in situations of lipid overload and associated insulin resistance.