The prevention, mitigation and treatment of movement impairments, ideally, requires early diagnosis or identification. As the human movement system has physiological and functional redundancy, movement limitations do not promptly arise at the onset of physical decline. A such, prediction of movement limitations is complex: it is unclear how much decline can be tolerated before movement limitations start. Currently, the term ‘homeostatic reserve’ or ‘physiological reserve’ is used to refer to the redundancy of the human biological system, but these terms do not describe the redundancy in the muscle architecture of the human body. The result of functional redundancy is compensation. Although compensation is an early predictor of movement limitations, clear definitions are lacking and the topic is underexposed in literature. The aim of this article is to provide a definition of compensation and emphasize its importance. Compensation is defined as an alteration in the movement trajectory and/or altering muscle recruitment to complete a movement task. Compensation for capacity is the result of a lack in neuromusculoskeletal reserve, where reserve is defined as the difference between the capacity (physiological abilities of the neuromusculoskeletal system) and the task demand. Compensation for movement objectives is a result of a shift in weighting of movement objectives, reflecting changing priorities. Studying compensation in biomechanics requires altered protocols in experimental set-ups, musculoskeletal models that are not reliant on prescribed movement, and inclusion of alternative movement objectives in optimal control theory.

The electric vehicle (EV) industry is experiencing rapid growth, accompanied by continuous advancements in charging infrastructure to satisfy the rising need for fast and reliable charging. Particularly, the focus has shifted towards EV fast charging (EVFC) and its impact on the power grid. This paper presents a comprehensive analysis and survey of scholarly literature and projects conducted in this field over the past decade. The findings highlight the rising demand for EVFC and the need to address its potential adverse effects on the power grid. However, there is a noticeable lack of clear research guidance regarding charging time. To tackle these challenges and pave the way for future solutions, extensive research on DC fast charging, ultra-fast charging, and the integration of vehicle-to-grid (V2G) systems is required. This review paper thoroughly investigates the development of fast charging technology for electric vehicles (EVs), including its advantages and comparative analyses from various perspectives. Furthermore, it delves into the advancements in DC fast charging infrastructure, emphasizing charging standards and control modes. The study also investigates different categories of battery chargers for both on-board and off-board charging. Additionally, it explores the classification of DC-DC converters in the context of DC fast charging stations, discusses control strategies for EV systems, identifies existing challenges, and outlines future trends in EV fast charging.

Flooding during the rainy season poses a significant threat to the city of Hargeisa, impacting the well-being of both its residents and the local ecosystems. This research focuses on urban flood control, with a specific emphasis on finding sustainable solutions for managing large stream in Hargeisa. The study identifies five key dimensions, including infrastructure, transportation, environmental soil, life, and property, as critical factors in addressing the issue. By employing a comparative method and collecting data through closed-ended questions, the research aims to analyze and weigh eleven potential solutions, seeking to identify the most effective approaches. The findings of the study indicate that constructing a dam emerges as a promising and sustainable solution, with a weightage of 70 percent. This highlights the potential of a dam in mitigating the impact of floods in the region. Additionally, considering the government's economic capacity, the implementation of check dams is identified as another viable option, with a weightage of 95 percent for reducing the flood power of the stream. These solutions offer practical and effective measures to address the recurring problem of flooding in Hargeisa. To support future decision-making and planning, the research underscores the need for establishing a comprehensive rainfall data database. This database would store relevant information on rainfall patterns, enabling better understanding and prediction of flood events. The study emphasizes the importance of collaboration between local government authorities, environmental organizations, and stakeholders to develop and implement effective flood control strategies. This research provides a systematic approach that can inform and benefit regional and global researchers, policymakers, and municipal governments in their efforts to address urban flood control challenges, not only in Hargeisa but also in similar contexts worldwide.

In this paper, a capacitor microphone system is presented to improve the conversion of mechanical energy to electrical energy using a nonlinear auto regressive moving average-L2 (NARMA-L2) and model predictive control (MPC) controllers for the analysis of the open loop and closed loop system. The open loop system response shows that the output voltage signal need to be improved. The comparison of the closed loop system with the proposed controllers have been analyzed and a promising result have been obtained using Matlab/Simulink.

The ubiquitous diffusion of Power Electronic Converters (PECs) in many fields of application including traction and energy conversion is suggesting the possibility of new and better integration of advanced power conversion and ICT services. This work investigates the possible advancements in the use of optical fibers for control of PECs, using Plastic Optical Fiber. The optical communication link connects the switching control to the converter control, following the line of separation between the expertises of the power electronic engineer and the control engineer. Control wise, the PEC becomes a black box compatible with any off-board controller, now immune from the Electromagnetic Interference (EMI) produced by the power switches. The redundant optical link is ready for the high switching (and sampling) frequencies possible with the use of SiC power semiconductor devices (100 kHz+). Distributed control of multiple PEC units and advanced telemetry for diagnostics and prognostics are targeted. A proof-of-concept demonstrator is presented and tested. Moreover, the possible evolution towards a power electronic cloud with remote management and orchestration is described.

The current work shows the optimization in the preparation of nanosized titanium carbide (TiC) in-situ through mechanical alloying (MA). Metallic titanium (Ti) powders, along with two carbon sources, carbon nanotubes (CNTs), and stearic acid (SA), were used to reduce the particle size using a high-energy Spex800 mill. The combined use of 2 wt % of these carbon sources and n-heptane as a liquid process control agent (PCA) proved crucial in generating nanoscale powder composites through a simple and scalable synthesis process within a 4-hour timeframe. The use of 20 wt % of both carbon sources was compared to determine the ability of CNTs to form carbides and the decomposition of PCAs during mechanical milling. The result reveals structures like nanoblocks and nanolumps with and important size reduction. The structure and morphology of the composites and starting materials were evaluated through x-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM).

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.

In addition to provide an extremely clean environment for primary loop of high-temperature gas-cooled reactor (HTR), the primary helium circulator (PHC) using electromagnetic levitation technology also provides an effective means for vibration control. Besides synchronous vibration produced by mass imbalance and sensor runout, double-frequency vibration produced by unbalanced magnetic pull (UMP) is serious in PHC engineering prototype (PHC-EP). In this paper, we firstly analyzed the mechanism of UMP and the multi-frequency vibration characteristics in combination with the PHC-EP. Then we put forward a distributed iterative learning control (ILC) algorithm and a parallel control scheme to suppress the periodic vibrations. Finally, we verified the methods by carrying out experimental researches on the active magnetic bearing (AMB) bench of PHC-EP. The results show that the methods put forward in this paper have significant control effect on the double-frequency vibration generated by UMP of the PHC-EP, and provide theoretical and practical references for the PHC safe operation in HTR.

This study identified and mapped worldwide surveillance actions and initiatives of drinking water quality implemented by government agencies or public health services. The scoping review was conducted between July 2021 and August 2022 based on the Joanna Briggs Institute. The search was performed in relevant databases and grey literature; 49 studies were obtained. Quantitative variables were presented as absolute and relative frequencies, while qualitative variables were analyzed using the IRaMuTeQ software. The actions developed worldwide and their impacts and results provided four thematic classes: (1) assessment of coverage, accessibility, quantity, and drinking water quality in routine and emergency situations; (2) analysis of physical-chemical and microbiological parameters in public supply networks or alternative water supply solutions; (3) identification of household water contamination, communication, and education with the community; (4) and investigation of water-borne disease outbreaks. Preliminary results were shared with stakeholders to favor early knowledge dissemination.

The suspended test masses of gravitational-wave (GW) detectors require precise alignment to be able to operate the detector stably and with high sensitivity. This includes the continuous counter-acting of seismic disturbances, which, below a few Hertz, are not sufficiently reduced by the seismic isolation system. The residual angular motion of suspended test masses is further suppressed by the Angular Sensing and Control (ASC) system. However, in doing so, the angular motion can be enhanced by the ASC at higher frequencies where the seismic isolation system is very effective. This has led to sensitivity limitations between about 10 Hz and 25 Hz of the LIGO detectors in past observation runs. The observed ASC noise was larger than simple models predict, which means that more accurate detector models and new simulation tools are required. We present Lightsaber, a new time-domain simulator of the ASC in LIGO. The simulation is a nonlinear simulation of the optomechanical system consisting of the high-power cavity laser beam and the last two stages of suspension in LIGO including the ASC. The main noise inputs are power fluctuations of the laser beam at the input of the arm cavities, read-out noise of sensors used for the ASC, displacement noise from the suspension platforms, and noise introduced by the suspension damping loops. While the plant simulation uses local degrees of freedom of individual suspension systems, the control is applied on a global angular basis, which requires a conversion between the local and global bases for sensing and actuation. Some of the studies that can be done with this simulation concern mis-centering of the beam-spot (BS) position on the test masses, the role of laser power fluctuations for angular dynamics, and the role of the various nonlinear dynamics.

Background and Objectives: Non-cognitive skills (NCS) are vital components of a socially and financially successful life. They are developed through childhood education, family and school environments, and social settings. The aim of this study was to examine the associations between NCS and the parent–child relationship, mental health, and lifestyle at school and at home for adolescents. Materials and Methods: An internet-based survey was conducted with 1,566 mothers and their children (aged 14) in Japan. Survey items for the children included background (i.e., sociodemographic items, school achievements, and lifestyle), NCS (i.e., grit and self-control scales), and mental health, while their mothers provided social, financial, and educational information, and information on parent–child relationships, including descriptions of the fathers and the father–child relationship. Results: Parent–child relationships were mostly good (i.e., 90.9% for mothers and 75.6% for fathers), with bad relationships being less common (1.6% for mothers and 6.7% for fathers). Adolescent lifestyle parameters and mental health were significantly associated with grit and self-control. Adolescents with good parent–child relationships had significantly higher NCS scores regardless of the gender of the parent. Higher NCS scores were significantly associated with better parent–child relationships, more favorable lifestyles, and better mental health among adolescents. Conclusions: These findings imply that good parent–child relationships may aid in the development of adolescents’ NCS, thereby facilitating positive lifestyles at school and home.

Objectives: The aim of the present study was to evaluate the association between psoriasis and osteoporosis using two different studies. Methods: Data from the Korean National Health Insurance Service-Health Screening Cohort of participants who were ≥ 40 years old were collected from 2002 to 2013. Psoriasis and osteoporosis were included using ICD-10 codes. In study I (a follow-up study), a total of 25,306 psoriasis participants were matched to 101,224 controls with respect to age group, sex, income group, and region of residence, and the occurrence of osteoporosis was analyzed. Crude (simple) and adjusted hazard ratios (HRs) were analyzed using a stratified Cox proportional hazard model. In study II (a nested case–control study), a total of 79,212 osteoporosis patients were matched to 79,212 controls, and a previous history of psoriasis was analyzed. Crude and adjusted odds ratios (ORs) were analyzed using a conditional logistic regression analysis. Subgroup analyses were conducted according to age group and sex. Results: The adjusted HR of osteoporosis was 1.11 (95% confidence interval [CI] = 1.07-1.15, P < 0.001) in study I. In the subgroup analysis according to age and sex, the results were consistent except for the ≥ 60-year-old women. The adjusted OR of psoriasis was 1.22 (95% CI = 1.16-1.28, P < 0.001) in study II. All subgroups demonstrated high adjusted ORs of osteoporosis for psoriasis. Conclusions: Psoriasis increased the risk of osteoporosis in the population of participants aged ≥ 40 years in Korea.

This paper discusses two major applications of SU(3) theory, the first being the question of quantum brachistochrones and problems in time optimal control theory, the second being the use of spherical tensor decompositions of the special functions which are associated to SU(3) via the isotropic oscillator. We discuss the derivation of the quantum brachistochrone problem more generally from the perspective of von Neumann equations and matrix mechanics, arriving at an equivalent formulation to the Lagrangian method. Discussion is given to the application of such advanced methods in quantum computation, and some future directions that may be amenable to a similar sort of an

Health locus of control is the set of beliefs a person has about his or her personal influence on health. The current study aimed at identifying types of locus of control in parents of leukemia children and possible association with depressive symptomatology and current life perception. 104 parents were recruited at the Haematology-Oncologic Clinic of Padua post 1 month from the leukemia diagnosis. Participants were Caucasian with a mean age of 37.28 years (SD=5.89), mostly mothers (87.5%) and with a mean of 12.16 years of education (SD=3.82). After signing the informed consent, they filled in the Ladder of Life questionnaire, the BSI-18 and the Parents Health Locus Of Control (PHLOC). Paired-samples t-test (t= -14.42; df=103; p=0.0001) showed that parents of leukemia children were more inclined to have an external locus of control than an internal one. Hierarchical regression analysis model (R2=0.34; F=4.32; p=0.0001) identified health professional influence (ß= -0.28; p=0.004), current life perception (ß= -0.3; p=0.013) and future life perception (ß= -0.26; p=0.012) as significantly predictors on Parental depression. Improving trust in the medical staff care and parental life perceptions could be a preventive program to cope with parental depression symptomatology.

The bacterial genus and species of Bacillus thuringiensis var israelensis (Bti), is entomotoxic, used in the biological control of mosquito vectors of human diseases, such as malaria and dengue. Following the studies carried out in Mexico and Guatemala with ovillantas, in which the presence of larvae of both species of Anopheles albimanus W and Aedes aegypti L were observed, and with the intention of continuing to develop an ecologically friendly mosquito control, Bti was added to the ovillantas, to improve and already efficient method on the elimination of both types of mosquitoes. The objectives of this work were: to analyze the effectiveness of two commercial formulations of Bti, serovar H-14 (Bactimos) wettable powder, 3,500 ITU, from Biochem prods., and Vectobac, 2,000 ITU wettable powder, (Abbot Lab.) on second and third instars larvae of A. albimanus and Ae. aegypti (Diptera Culicidae). The two formulations were effective against A. albimanus W(higher concentrations), while Ae. aegypti L was very susceptible to Bti, therefore it is proposed for the best control of these genus and vector species of malaria and dengue at adequate concentrations.

This paper studies the pilot control strategy and workload of tilt-rotor aircraft dynamic conversion procedure between helicopter mode and fixed-wing mode. A nonlinear flight dynamics model of tilt-rotor aircraft with full flight modes is established. On this basis, a nonlinear optimal control model of dynamic conversion is constructed, considering factors such as conversion corridor limitations, pilot control, flight attitude, engine rated power, and wing stall effects. To assess pilot workload, an analytical method based on wavelet transform is proposed, which examines the mapping relationship between pilot control input's amplitude, constituent frequencies, and control tasks. By integrating the nonlinear optimal control model and the pilot workload evaluation method, the analysis of pilot control strategy and workload during the conversion procedure is conducted, leading to the identification of strategies to reduce pilot workload. The results indicate that incorporating the item of pilot workload in the performance index results in a notable reduction in the magnitude of collective stick inputs and longitudinal stick inputs. Moreover, it facilitates smoother adjustments in altitude and pitch attitude. Additionally, the conversion of the engine nacelle can be achieved at a lower and constant angular velocity. In summary, the conversion and reconversion procedures are estimated to have a low workload (Level 1 ~ Level 2), with relatively simple and easy manipulation for the pilot.

This paper is concerned with the optimal linear quadratic Gaussian (LQG) control problem for discrete time-varying system with multiple input delays and multiplicative noises. The main contributions are two-fold. Firstly, when the state variables can be observed exactly, we obtain a necessary and suffcient condition for the multiple-delays system in terms of the non-homogeneous relationship between the state and costate, which is the solution to the coupled forward and backward stochastic difference equations. Secondly, when the state variables are partially observed, we derive a suboptimal linear output feedback controller for the discrete-time system based on the obtained results of the optimal LQG control. Numerical examples are shown to illustrate the proposed algorithm.

In this review we summarize existing trends of flow control used to improve the aerodynamic efficiency of wings. We first discuss active methods to control turbulence, starting with flat-plate geometries and building towards the more complicated flow around wings. Then, we discuss active approaches to control separation, a crucial aspect towards achieving high aerodynamic efficiency. Furthermore, we highlight methods relying on turbulence simulation, and discuss various levels of modelling. Finally, we thoroughly revise data-driven methods, their application to flow control, and focus on deep reinforcement learning (DRL). We conclude that this methodology has the potential to discover novel control strategies in complex turbulent flows of aerodynamic relevance.

This article addresses the trajectory tracking between two non-identical systems with chaotic properties. We employ the Rossler chaotic and RCL-shunted Josephson junctions model in similar phase space to study trajectory tracking. In order to achieve the goal tracking, we afford two stages to approximate the target tracking. The first stage utilizes the active control technique to transfer the output signal from the RCLs-J system into the quasi-Rossler system. Then next, the RCLs-J system employs the proposed the iterative learning control scheme and the control signal from the drive system to trace the trajectory of Rossler system. The numerical results demonstrate the proposed method and the tracking system is asymptotically stable.

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower-quality datasets be made available for analysis and comparison alongside those of higher-quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies, community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA’s GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

There are many problems based on solving non-autonomous differential equations of the form x¨(t)+ω2(t)x(t)=0, where x(t) represents the coordinate of a material point and ω is the angular frequency. The inverse problem involves finding the bounded coefficient ω. Continuity of the function ω(t) is not required. The trajectory x(t) is unknown, but the initial and final values of the phase variables are given. The variation principle of minimum time for the entire dynamic process allows for the determination of the optimal solution {x(t),ω(t)}. Thus, the inverse problem is an optimal control problem. No simplifying assumptions were made.

Active flow control is a promising technology for reducing noise, emissions, and power consumption in various applications. To better understand the performance of synthetic jet actuators, a computational model that couples structural mechanics with electrostatics, pressure acoustics, and fluid dynamics has been needed. The model presented here has been validated against experimental data and then used to investigate the fluid behavior inside and outside the synthetic jet actuator cavity, impacts of thermoviscous losses on capturing the acoustic response of the actuator, and viability of different modeling methods of diaphragms in computational simulations. The results capture the feedback from the fluid onto the diaphragm and highlight the need for careful acoustic modeling.

Sustained-release drug delivery systems have evolved significantly over the years, playing a pivotal role in pharmaceutical research and enhancing patient care [1]. This abstract synthesizes key insights from various references to highlight the noteworthy advancements in this field. Recent research has emphasized the importance of understanding drug properties and their impact on sustained-release system design [2] [9]. These advancements enable tailoring drug delivery to optimize therapeutic outcomes [2] [9]. Incorporating innovative technologies such as nanotechnology [1], biodegradable polymers [3], and matrix systems [4] has led to the development of more efficient and patient-friendly sustained-release systems [1] [3] [4] Moreover, the concept of personalized medicine is gaining prominence [5], opening doors to individualized drug delivery strategies [5]. These strategies promise to enhance treatment efficacy while minimizing adverse effects [5]. Theoretical analyses, as exemplified by Higuchi’s work [6], continue to shape the understanding of sustained-release mechanisms [6]. Furthermore, studies on enteric-coated timed-release tablets [10]. highlight advancements in specific drug formulations to meet patient needs [10]. In conclusion, advancements in sustained-release drug delivery systems reflect a dynamic landscape where drug properties, innovative technologies, and personalized approaches converge to improve patient outcomes and drug therapy [7] [8] [10].

Plant-based insecticides are considered among the most economical and eco-friendly chemicals for the protection of field plants and even stored grains. The sweet melon (Cucumis melo L.) insect pest causes more than 90% damage to most melon leaves, vines, and balls at its growth stage. The study looked at how effective the plant extract from Africa Basil and the synthetic insecticide Cymbush were at killing insects on sweet melon (Cucumis melo L.). The study explored four different concentrations (2.5, 50, 75, and 100%) and a synthetic insecticide, Cymbush, against insect pests of sweet melon and compared the effects of distilled water, which is used as a control in a Randomized Complete Block Design (RCBD). The toxicity percentage levels of the African basil extracts against field pests of sweet melon were 25, 50, 75, and 100%. Maximum plant protection of the crop was achieved by the synthetic insecticide Cymbush (3.0 pest point), followed by Africa basil extract B100 (3.3 pest point), whereas weak and minimum insect pest protection were observed in the control (5.53 pest point). In conclusion, these results indicate the utility of African basil plant extracts against field insect pests of sweet melon as potential botanicals to control field insect pests and mitigate the hazardous use of synthetic insecticides on humans, animals, and the environment

The collector and brushless electronic commutation machines based on the working principle of the direct current machines have been widely used in industrial applications through the help of the developments in power electronics, microelectronics, permanent magnets, microprocessors&control, digital signal processing technologies, etc. Internal permanent magnet synchronous motors (IPMSMs) are used in increasing numbers due to their advantages such as high torque/current and torque/inertia, robust construction, high efficiency, reliability, etc. The problems brought by position sensors, especially in terms of application, performance, mass production, and cost, have made sensorless control a necessity in drive systems and applications.This paper presents a backstepping control method for speed sensorless IPMSM based on an extended Kalman filter (EKF). First, a comprehensive nonlinear dynamical model of the IPMSM in the direct and quadrature ( ) rotor frame is derived and its state-space representation is obtained. Then, the rotor speed and current tracking backstepping controllers are designed to achieve precise tracking and anti-disturbance performance. The designed controllers are embedded into the field-oriented control (FOC) scheme. The asymptotic stability condition for the backstepping controller is guaranteed through the Lyapunov stability theorem. Finally, An EKF is designed for estimating the immeasurable mechanical parameters of IPMSM and tracking the system states in a finite time with high steady-state precision. The effectiveness of the proposed methodology is proved by conducting simulations having various dynamic operating conditions such as sudden torque load change, command speed change, and parameter variation.

This research presents a maximum power point tracking of traditional single-ended primary converter (SEPIC) with the aid of fuzzy logic controller (FLC) for regulating the voltage and perturbation and observation(P&O) algorithms for regulating the reference voltage and reaching the maximum power point tracking. This is a promising technique for the conventional SEPIC converter to achieve maximum power point tracking with much less error. Moreover, the method is simple, reliable, and understandable for photovoltaic systems.

A therapy’s outcome is determined by a tumor’s response to treatment which, in turn, depends on multiple factors such as the severity of the disease and the strength of patient’s immune response. Gold standard cancer therapies are in most cases fragile when sought to break the ties to either tumor kill ratio or patient toxicity. Lately, research has shown that cancer therapy can be at most robust when handling adaptive drug resistance and immune escape patterns developed by evolving tumors. This is due to the stochastic and volatile nature of the interactions, at the tumor environment level, tissue vasculature, and immune landscape, induced by drugs. Herein, we explore the path towards antifragile therapy control, that generates treatment schemes that are not fragile but go beyond robustness. More precisely, we describe a first instantiation of a control-theoretic method to make therapy schemes cope with the systemic variability in the tumor–immune–drug interactions and gain more tumor kill with less patient toxicity. Considering the anti-symmetric interactions within a model of the tumor–immune–drug network, we introduce the antifragile control framework that demonstrates promising results in simulation. We evaluate our control strategy against state-of-the-art therapy schemes on various experiments and discuss the insights we gained on the potential that antifragile control could have in treatment design in clinical settings.

This article presents a decentralized phase-shedding technique for multiphase converters. The usual central digital controller is replaced by identical local controllers forming a daisy-chain structure. Phase-shedding decisions are taken locally based on a local inductor current monitoring and threshold crossing management. This control strategy allows to implement as many phases as desired in a modular manner. In order to handle specific events such as load current inrush or a start-up sequence and to guarantee optimal transient responses, additional functions are included into each local controllers. The inter-cell communication protocol is described, along with necessary design considerations of threshold and timing values. Finally, functional simulations are carried out on a 5-leg 12V/1.2V 60W multiphase converter, which validate the proposed decentralized phase-shedding strategy for a microcontroller power supply implementation.

Salivarian trypanosomes are extracellular parasites affecting humans, livestock and game animals. Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense are human infective sub-species of T. brucei causing Human African Trypanosomosis (HAT - sleeping sickness). The related T. b. brucei parasite lacks the resistance to survive in human serum, and only inflicts animal infections. Animal Trypanosomosis (AT) is not restricted to Africa, but is present on all continents. T. congolense and T. vivax are the most widespread pathogenic trypanosomes in sub-Sahara Africa. Trough mechanical transmission, T. vivax has however been introduced into South America. T. evansi is a unique animal trypanosome that is found in vast territories around the world and can cause atypical Human Trypanosomosis (aHT). All salivarian trypanosomes are well adapted to survival inside the host’s immune system. This is not a hostile environment for these parasite, but this is the place where they thrive. Here we provide an overview of the latest insights into the host-parasite interaction and the unique survival strategies allowing trypanosomes to outsmart the immune system. In addition, we review new developments in treatment and diagnosis as well the issues that have hampered the development of field-applicable anti-trypanosome vaccines for the implementation of sustainable disease control.

Reliability assessment is an important component and tool used for process plants since the facility consists of many loops and instruments attached and operates based on each other availability, thus it requires a statistical method to visualize the reliability. The paper focuses on reliability assessment and prediction based on available statistical models such as normal, log-normal, exponential, and Weibull distribution. This paper also visualizes, which model fits best for assessment and prediction and also considers failure modes caused during a simulation mode process control operation. A simulation model is designed in this paper to observe the failure of the control valve causing stiction to visualize the failure modes and predict the best-fit model for reliability assessment.

A nuclear reactor leak is undesirable and unpredictable occurrence in the plant of nuclear energy generation. For this reason, an accurate equipment is needed to inspect and supervise reactors. There are two kind of reactors for research and industry reactors, both of them are needed to inspect. Concern to inspection, regularly check is needed to ensure reactor conditions are always safe to operate. For that reason, an application of advanced technology for detecting leaks is priority. In this research, we are using underwater robot to be implemented. Using the robot is able to detect periodically, continuously with accurate reports to the operator or reactor supervisor. Furthermore, Underwater Robot namely Robaru, with 4 propellers equipped at the robot, Robaru can move on 3 axes x, y and z and rotate. The use of cameras, as well as temperature measurements to obtain data when conducting inspections of the reactor. The survey method used is direct observation to detect leaks. The robot is at a certain distance by following a predetermined connection or path. The robot has successfully performed a good check with an accurate level of positioning accuracy.

We consider a control problem for a diffusive PDE model of heterogeneous population of thermostatically controlled loads (TCLs) aiming to balance the aggregate power consumption within a given amount of time. Using the Green’s function approach, the problem is formulated as an approximate controllability problem for a residue depending on control parameters nonlinearly. A sufficient condition for approximate controllability is derived in terms of initial temperature distribution, operation time of TCLs and threshold value of the aggregate power consumption. Case studies allow to reveal the advantages of the proposed solution from numerical calculations point of view.

Most systems that are the subject of control engineering studies have some non-linearity. An example of this is the horizontal cylindrical tank, commonly used in process industries. To deal with cases like this, several control theories have been developed over time, each one presenting better results in certain systems. This work presents an alternative for the control of nonlinear systems, without necessary modeling or previous information about the system, based on a new optimization law for the artificial neural network training in real time.

This paper discusses wind tunnel test results aimed at advancing active flow control technology to increase the aerodynamic efficiency of an aircraft during take-off. A model of the outer section of a representative civil airliner wing was equipped with two-stage fluidic actuators between the slat edge and wing tip, where mechanical high-lift devices fail to integrate. The experiments were conducted at a nominal take-off Mach number of M = 0.2. At this incidence velocity, separation on the wing section, accompanied by increased drag, is triggered by the strong slat edge vortex at high angles of attack. On the basis of global force measurements and local static pressure data, the effect of pulsed blowing on the complex flow is evaluated, considering various momentum coefficients and spanwise distributions of the actuation effort. It is shown that through local intensification of forcing, a momentum coefficient of less than c_μ = 0.6% suffices to offset the stall by 2.4°, increase the maximum lift by more than 10%, and reduce the drag by 37% compared to the uncontrolled flow.

Waste biogenic materials from seafood exploitation are valuable resources of new compounds exploitation within the blue bioeconomy concept. Here, we describe the effectiveness of Raman technology implementation as an in-line tool for demineralization process control of crustaceans or gastropods. We produced transparent chitin polymer foils from three waste crustacean shells (C. sapidus, S. mantis and M. squinado) using a slow, green chemical approach employing acetic acid, and showed the progressive process of biogenic carbonate dissolution and increasing the Raman characteristic signal of chitin, in a time dependence manner. It turned that chitin foils obtaining is species-specific, and the demineralization bath of waste shell mixture can be effectively tracked by Raman spectroscopy, for solvent control and the recovery of the calcium acetate as valuable by-product. Comparatively, calcium acetate drug, a compound widely used in kidney failure diseases, or as additive in nutraceuticals and food industry, has been obtained here, following a green demineralization path of the sea snail Rapana venosa intact shell, assisted by Raman tech-nology, using 9% acetic acid (vinegar) solution for 14 days. To validate the final products identity and quality, The process of waste shells demineralization and the final products of the treatment were investigated using various Raman techniques and technologies, cross-validating the results with FT-IR, XRD and SEM-EDX techniques. NIR Raman spectroscopy revealed chitin bands in a time-dependent manner, while Resonance Raman spectroscopy showed the preservation of ca-rotenoids after two weeks of acetic acid treatment. A hand-held flexible TacticID Raman system with a 1064 nm excitation demonstrated its effectiveness as a rapid, in-line decision making tool during process control and revealed excellent reproducibility of the lab-based instrument signal, suitable for in situ evaluation of the demineralization status and solvent saturation control. The calcium acetate recovered from residual treatment solutions was assessed regarding its hydration status, purity, and suitability as recrystallized material for further use as pharmaceutical product or ingredient in complex formulations.

Background: Uncontrolled hemorrhage is a major preventable cause of death in patients with trauma. However, the majority of large animal models of hemorrhage have utilized controlled hemorrhage rather than uncontrolled hemorrhage to investigate the impact of immunopathy and coagulopathy on multi-organ failure (MOF) and mortality. This study evaluates these alterations in a severe porcine-controlled and uncontrolled hemorrhagic shock (HS) model. Methods: Anesthetized female swine underwent controlled hemorrhage (22 ml/kg) and uncontrolled hemorrhage by partial splenic resection followed with or without lactated Ringer solution (LR) or Voluven® resuscitation. Blood chemistry, physiologic variables, systemic and tissue levels of complement proteins and cytokines, coagulation parameters, organ function, and damage were recorded and assessed. Results: HS resulted in systemic and local complement activation, cytokine release, metabolic acidosis, hyperkalemia, MOF, and no animal survival. Resuscitation with LR and Voluven® after HS improved hemodynamic parameters (MAP and SI), metabolic acidosis, hyperkalemia, and survival but resulted in increased complement activation and worse coagulopathy. Compared with the LR group, the HS animal treated with Voluven® had worse dilutional anemia, coagulopathy, renal and hepatic dysfunction, increased myocardial complement activation and renal damage, and decreased survival rate. Conclusions: Hemorrhagic shock triggers early immunopathy and coagulopathy that appear associated with MOF and death. This study indicates that immunopathy and coagulopathy are therapeutic targets that may be addressed with a high-impact adjunctive treatment to conventional resuscitation.

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electricity power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electricity power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

Sustainable agriculture has become increasingly important in Tunisia due to the drought that has been affecting the country's climate in recent years. This has become a major threat to the economy, making it necessary to explore alternative methods of agriculture that are more sustainable. Moreover, smart hydroponic cultivation based on renewable energies has become increasingly widespread, promoting the quality and efficiency of agricultural production despite weather parameters variations and global warming. This work aims to create a sustainable agriculture system in Tunisia through the design and implementation of a smart photovoltaic (PV) hydroponic greenhouse. The greenhouse will utilize advanced technology to optimize plant growth and reduce water usage, while also incorporating solar panels to generate renewable energy. The end goal is to create a self-sufficient and eco-friendly agricultural system that can provide fresh produce to local communities year-round. In this work, we are interested to the automation of the hydroponic greenhouse (HG)’s thermal conditioning system based on an asynchronous motor pump and powered by a PV generator. In the first stage, we analyzed the mathematical modeling of a stand-alone PV-HG system that consists of a PV generator, a three-phase inverter, an asynchronous motor pump, and a hydroponic system. After that, we developed a Field Oriented Control based on proportional integral (PI) regulators to adjust the rotation speed of the asynchronous motor pump, which aimed to provide the cooling and heating needs of the plant. The simulation results demonstrated the effectiveness of the proposed system . Additionally, we designed and implemented a smart system based on the internet of things (IoT) to enable remote control of internal and external parameters of the HG. This intelligent solution utilizes sensors, microcontrollers, and other devices and ensures the monitoring and the maintaining of the ideal growing conditions for our plants, guaranteeing that they receive the proper amount of temperature, humidity, and lighting. This type of system can be an invaluable tool for maximizing yields and achieving optimal results. With the right approach and attention to detail, we can create a sustainable and efficient growing environment that will help our plants flourish year-round.

Reconfigurable chiral metasurfaces with dynamic polarization manipulation capability are highly required in optical integrated systems. In this paper, we simultaneously realized giant and large-range switchable asymmetric transmission (AT) and circular conversion dichroism (CCD) in a vanadium dioxide (VO2) based metasurface. The AT and CCD of the insulator VO2 based metasurface reach 0.95 and 0.92, respectively. Utilizing the insulator-to-metallic phase transition of VO2, the AT and CCD could be continuously switched to near zero. Furthermore, the physics mechanism of the giant and switchable AT and CCD are analyzed. The proposed metasurface with large-range switchable AT and CCD is promising in the applications of biochemistry detection, chiral imaging and biosensing.

In this article authors shows chosen problems of technical state diagnosis with the use of identification and technical diagnostics methods such as experimental modal analysis. Relations between methods of dynamic state evaluation and methods of technical state evaluation were indicated. Example modal analysis results illustrate the complexity of projecting dynamic state researches into diagnostic researches of state evaluation.

Several studies have already demonstrated the relationship between the loss of natural habitats and the incidence of diseases caused by vectors, such as dengue, which is an acute fever disease, considered a serious public health problem. The aim of the present study was to analyze the relationship between land use changes between 2009 and 2019 and the occurrence of dengue fever in 2015 and 2019 by municipality, using the state of Minas Gerais as a case study. For this, secondary data obtained from openly available sources were used. Natural vegetation cover data were obtained from the MAPBiomas platform and dengue occurrence data from the Ministry of Health, in addition to socioeconomic indicators from the Brazilian Institute for Geography and Statistics. Between 2015 and 2019, 1,255,731 cases of dengue were recorded throughout the state of Minas Gerais, ranging from 0 to 227 per thousand inhabitants between municipalities. The occurrence of dengue was distributed throughout all regions of Minas Gerais, affected by climatic and socioeconomic aspects. In general, municipalities with net loss of natural vegetation, predominantly located in the Cerrado biome, had the highest number of dengue cases in the studied period. Despite the significant positive relationship between these two variables, three of the eight socioeconomic parameters analyzed also affected the occurrence of dengue: population density, human development index (both positively) and Gini inequality index (negatively). These results indicate that, contrary to expectations, municipalities with better social conditions had more dengue cases. Our study indicates that natural vegetation is, directly or indirectly, involved in the ecosystem service of dengue control, despite the occurrence of this disease being affected by multiple factors that interact in a complex way. Thus, policies towards reducing deforestation must be complemented by a continuous investment in public health policies and reduction of social inequalities to efficiently control dengue fever.

This paper gives solutions to puzzles of double Wheeler’s delayed choice experiments, a photon’s passing two paths simultaneously and wave collapse velocity measure, and shows new quantum control, new quantum oscillation and new controlling photon oscillator (that can be arranged in quantum computer and quantum network as their classical correspondences) in experiments. Furthermore, this paper obtains the measured attractive state and the new useful key technology of altering state’s evolving paths for quantum systems. We discover the reason and the technological way for the present changes the past, further show their feasible experiments of new quantum control, new quantum oscillation and new quantum oscillator. Finally, this paper achieves the collapse response time t of wave, further concretely deduces the measured collapse velocity of quantum system. In the past, the collapse velocity cannot be objectively deduced and experimentally measured.

Discretization is the process of converting a continuous function or model or equation into discrete steps. In this work, adaptive and learning methods are implemented to control DC motors that are used for actuating control surfaces of unmanned underwater vehicles. Adaptive control is a method in which the controller is designed to adapt the system with parameters which vary or are uncertain. Parameter estimation is the process of computing the parameters of a system using a model &amp; measured data. Adaptive methods have been used in conjunction with different parameter estimation techniques. Deterministic artificial intelligence, a learning-based approach that uses the process dynamics defined by physics, is also applied to control the output of the DC motor to track a specified trajectory. This work goes further to evaluate the performance of the adaptive &amp; learning techniques based on different discretization methods. The results are evaluated based on the absolute error mean between the output &amp; the reference trajectory and the standard deviation of the error. The first order-hold method of discretization and surprisingly large sample time of seven tenths of a second yields over sixty percent improvement over the results presented in the prequel literature.

Direct yaw moment control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer andfaster on a race track. The state-of-the-art literature covers the comparison of various controllers (PID, LPV, LQR, SMC, etc.) using ISO manoeuvres. However, more advanced comparison on important characteristics of the controllers performance is missed, such as the robustness of the controllers under changes in the vehicle model, steering behaviour, use of the friction circle and, ultimately, lap time on a track. In this study, we have compared the controllers according to some of the aforementioned parameters on a modelled race car. Interestingly, best lap times are not provided by perfect neutral or close-to-neutral behaviour of the vehicle, but rather by allowing certain deviations from the target yaw rate. In addition, a modified PID controller showed that its performance is comparable to other more complex control techniques such as MPC.

An iterative outlier elimination procedure based on hypothesis testing, commonly known as Iterative Data Snooping (IDS) among geodesists, is often used for the quality control of the modern measurement systems in geodesy and surveying. The test statistic associated with IDS is the extreme normalised least-squares residual. It is well-known in the literature that critical values (quantile values) of such a test statistic cannot be derived from well-known test distributions, but must be computed numerically by means of Monte Carlo. This paper provides the first results about Monte Carlo-based critical value inserted to different scenarios of correlation between the outlier statistics. From the Monte Carlo evaluation, we compute the probabilities of correct identification, missed detection, wrong exclusion, overidentifications and statistical overlap associated with IDS in the presence of a single outlier. Based on such probability levels we obtain the Minimal Detectable Bias (MDB) and Minimal Identifiable Bias (MIB) for the case where IDS is in play. MDB and MIB are sensitivity indicators for outlier detection and identification, respectively. The results show that there are circumstances that the larger the Type I decision error (smaller critical value), the higher the rates of outlier detection, but the lower the rates of outlier identification. For that case, the larger the Type I Error, the larger the ratio between MIB and MDB. We also highlight that an outlier becomes identifiable when the contribution of the measures to the wrong exclusion rate decline simultaneously. In that case, we verify that the effect of the correlation between the outlier statistics on the wrong exclusion rates becomes insignificant from a certain outlier magnitude, which increases the probability of identification.

This study investigates the impact of rotor spacing on the aerodynamic performance of a coaxialcopter. It has been observed that a small distance between two rotors can result in significant interaction between the propellers, consequently affecting the rotor's aerodynamic efficiency. Exploiting this characteristic, the present research introduces a coaxialcopter with variable rotor spacing. Employing finite element numerical simulations, we assess the aerodynamic behavior of this novel configuration. Through comprehensive measurements and analysis of its aerodynamic performance across varying rotor spacings from 0.1R to 1R, we validate the effectiveness of a rotor spacing control strategy for enhancing takeoff maneuvers. Our numerical simulation results reveal that the performance characteristics of both upper and lower rotor converges toward that of a single rotor as pitch ratio increases, along with the reduce of their thrust fluctuations and aerodynamic performance periodicity. Considering stable power consumption patterns and endurance performance, we analysis the interrelations binding of pitch distance of the rotors, rotational speed, and pitch angle, vis-à-vis the thrust coefficient and power coefficient. Through parameter optimization method, we demonstrate that adjusting rotor spacing offers a practical means to enhance payload capacity without increasing power input, thereby improving the efficiency, which validates the practicality and efficacy of the parameter optimization approach. Furthermore, optimizing rotor spacing for specific operational scenarios enhances overall aerodynamic performance, suggesting a viable flight control strategy for takeoff and landing conditions.

This paper presents a novel dynamic camera parameter control method for position and posture estimation of highly miniaturized AR markers (micro AR markers) using a low cost general camera. The proposed method performs iterative calculation of the marker’s position and posture to converge them to specified accuracy with dynamically updating the camera’s zoom, focus and other parameter values based on the detected marker’s depth distances. For a 10 mm square micro AR marker, the proposed system demonstrated recognition accuracy of better than ±1.0% for depth distance and 2.5∘ for posture angle with a maximum recognition range of 1.0 m. In addition, the iterative calculation time was at most 0.7 seconds in an initial detection of the marker. These experimental results suggest that the proposed method and system can be applied to a robotic precise handling of small objects with low cost.

Achieving synchronization between the central and peripheral body clocks is essential for ensuring optimal metabolic function. Meal timing is an emerging field of research that investigates the influence of eating patterns on our circadian rhythm, metabolism, and overall health. This narrative review examines the relationship between meal timing, circadian rhythm, clock genes, circadian hormones, and metabolic function. It analyzes existing literature and experimental data to explore the connection between mealtime, circadian rhythms, and metabolic processes. The available evidence highlights the importance of aligning mealtime with the body’s natural rhythms to promote metabolic health and prevent metabolic disorders. Specifically, studies show that consuming meals later in the day is associated with a elevated prevalence of metabolic disorders, while early time-restricted eating, such as having an early breakfast and an earlier dinner, improves levels of glucose in the blood and substrate oxidation. Circadian hormones, including cortisol and melatonin, interact with mealtimes and play vital roles in regulating metabolic processes. Cortisol, aligned with dawn in diurnal mammals, activates energy reserves, stimulates appetite, influences clock gene expression, and synchronizes peripheral clocks. Consuming meals during periods of elevated melatonin levels, specifically during the circadian night, has been correlated with potential implications for glucose tolerance. Understanding the mechanisms of central and peripheral clock synchronization, including genetics, interactions with chronotype, sleep duration, and hormonal changes, provides valuable insights for optimizing dietary strategies and timing. This knowledge contributes to improved overall health and well-being by aligning mealtime with the body’s natural circadian rhythm.

Cyber Physical Systems (CPS) is the integration of computation and physical process that makes a complete system such as the physical components, networked systems, embedded computers and software and linking together of devices and sensors for information sharing. Cyber Physical Systems are Smart Systems that comprises of the merging and integration of Industry Control Systems, Critical Infrastructures, Internet of Things (IoT) and Embedded Systems. Major industries such as the Chemical and Industrial Plants, Aviation Systems, National Grid, the Stock Exchange, Military Systems, and others depends heavily on these Cyber Physical Systems for financial and economic growth. The benefits of CPS nationally and globally are in the areas of Manufacturing, Energy, Transport, Healthcare and Communication. Cyber Physical Systems incorporates Physical systems, Digital systems and Human elements on network infrastructures to provide interactive systems. However, these three key components the Physical systems, Digital systems and Human elements may have inherent threats and vulnerabilities on them that may run the risk of being compromise, exploited, attacked or hacked. Cybercriminals in their quest to bring down these systems and may cause disruption of services either for fame, revenge, political motive, economic war, cyber terrorism and cyber war. The study seeks to review the risks that are associated with these three key components Physical systems, Digital systems and Human elements. The study considered four main risk mitigation goals for this purpose, and these are Business Value, Organizational Requirements, Threat Agent and Impact based on the review results. We used Analytical Hierarchical Process (AHP) to determine the relative importance of these goals that contributes to developing cybercrime and rich in CPS. For the results, the prioritized goals are then used to assess the risks using a semi-quantitative approach to determine the net threat level.

Incremental control strategies provide undeniable advantages for controlling Uncrewed Aerial Vehicles (UAVs) due to their reduced model dependency and accurate tracking capacities. This is of particular relevance for hybrid UAVs, specially for tail-sitters, which perform complex manoeuvres when transitioning to and from aerodynamic flight. This paper summarizes the research undertaken in the application of the Incremental Nonlinear Dynamics Inversion (INDI) and Incremental Backstepping (IBKS) to a small tail-sitter UAV. After the application of these control strategies in a simulated scenario, the implementation in a Micro-Controller Unit was validated in a Hardware-in-the-Loop scenario. Following such validation, indoor experimental trials were undertaken in order to evaluate the capacity of these controllers to stabilize and control the real aircraft. The stabilization in the flight trials was successfully implemented and allow to conclude that both INDI and IBKS are control strategies suited to control a tail-sitter in vertical flight, providing accurate tracking capabilities under smooth actuation. Furthermore, it was found that the IBKS is significantly more computationally demanding than the INDI, although having a global proof of stability that is of interest in aircraft control.

In the production of grafted vines, losses are caused by fungal pathogens during callus forming or after planting in the soil. To control or reduce natural fungal infections in nurseries, certain applications were conducted in sapling cultivation stage to analyse the efficacy of cyprodinil + fludioxonil, floupyram + tebuconazole active substances and Trichoderma harzianum biological preparation. 1103 Paulsen rootstock and Vitis viniferea L. Sultana cultivars were stored in fungicide suspensions for 60 minutes before and after grafting in the study. After grafting, the seedlings were divided into i) cutting + sawdust ii) cutting + sawdust + soil application groups and transferred to the callus room. Fungicides were applied 1 to 7 days after the callus development to wet the seedling roots 1 to 7 days after they were planted. After nine months in the nursery, the plants were uprooted, classified as diseased or healthy, and analysed for morphological and molecular diagnosis of fungal species, isolation incidence, and seedling quality and yield. After callus development, Fusarium solani was most frequently isolated pathogen in the roots (21.5%), cyprodinil + fludioxonil reduced the Ilyonectria sp. isolation rate in both shoots and roots. Botryosphaeria obtusa and I. liriodendri pathogens were not detected in sick and healthy cyprodinil + fludioxonil-treated saplings. The highest seedling yield was observed with fludioxonil + cyprodinil, cutting + sawdust + soil (78.75%) and cutting + sawdust (70.68%) applications. According to the results of this study, it was found that fungicide applications before and after grafting prevented soil-borne pathogen infections and improved sapling quality.

Disease control programs need to identify breeding sites of mosquitoes which transmit malaria and other diseases to target interventions and identify environmental risk factors. Increasing availability of very high resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, we identified land cover types associated with malaria vector breeding sites in West Africa. Drone images from two malaria endemic regions in Burkina Faso and Côte d’Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region of interest-based and deep learning methods to classify these habitat types from very high resolution natural color imagery. Analysis methods achieved a dice coefficient ranging between 0.68 and 0.88 for different vector habitat types; however, this classifier consistently identified the presence of specific habitat types of interest. This establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.

In an effort to upgrade and provide a unified and improved instrument control and data acquisition system for the ORNL SANS instrument suite (Bio-SANS, EQ-SANS, GP-SANS), beamline scientists and developers teamed up and worked closely together to design and develop a new system. We began with an in-depth analysis of user needs and requirements, covering all perspectives of control and data acquisition based on previous usage data and user feedback. Our design and implementation were guided by the principles from the latest user experience and design research and based on effective practices from our previous projects. In this article, we share details of our design process as well as prominent features of the new instrument control and data acquisition system. The new system provides a sophisticated Q-Range Planner to help scientists and users plan and execute instrument configurations easily and efficiently. The system also provides different user operation interfaces, such as wizard-type tool Panel Scan, a Scripting Tool based on Python Language, and Table Scan, all of which are tailored to different user needs. The new system further captures all the metadata to enable post-experiment data reduction and possibly automatic reduction and provides users with enhanced live displays and additional feedback at the run time. We hope our results will serve as a good example for developing a user-friendly instrument control and data acquisition system at large user facilities.

Asphalt binder requires more investigation to be accurately and precisely extracted since it is a significant procedure for quality control quality assurance (QC/QA) and subsequent binder characterization. In this research, the authors provided a hands-on experience with binder extraction to deliver recommendations concerning the sensitive steps that may affect the outcomes (extracted binder content, P_be%). Based on the extraction by the centrifuge method, two mineral matter determination methods (ashing and centrifuge) were addressed. Field cores were investigated with comparing the P_be% to the actual binder content, P_ba%. Analysis of variance (ANOVA) and Tukey Post-Hoc statistical analyses, in addition to linear least square regression analysis, were used to show the significance of difference according to 38 variant cores randomly obtained from the field segments (in-service roads) via the first two weeks from the construction date. Such cores involved reclaimed asphalt pavement (RAP), reclaimed asphalt shingles (RAS), and a wide range of additives. The two extraction methods were compared with concluding that the centrifuge method was highly recommended based on a quantitative evaluation, which delivered the same average P_ba% based on the 38 cores. Furthermore, the centrifuge method provided much saving in the experimental time (almost half the time required for the ashing method). It was found that the ashing outcomes were equal to the centrifuge outcomes with disregarding the ammonium carbonate addition. Thus, it could be recommended to reassess the ammonium carbonate addition as it might excessively compensate for fake minerals that have not been lost by the ignition oven.

In this paper we evaluate the effects of hard and soft constraints on the Iterative Data Snooping (IDS), an iterative outlier elimination procedure. Here, the measurements of a levelling geodetic network were classified according to the local redundancy and maximum absolute correlation between the outlier test statistics, referred to as clusters. We highlight that the larger the relaxation of the constraints, the higher the sensitivity indicators MDB (Minimal Detectable Bias) and MIB (Minimal Identifiable Bias) for both the clustering of measurements and the clustering of constraints. There are circumstances that increase the family-wise error rate (FWE) of the test statistics, increase the performance of the IDS. Under a scenario of soft constraints, one should set out at least three soft constraints in order to identify an outlier in the constraints. In general, hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. In that process, one should opt to set out the redundant hard constraints. After identifying and removing possible outliers, the soft constraints should be employed to propagate their uncertainties to the model parameters during the process of least-squares estimation.

The authors of the paper have made an attempt to detect the fibre content and fibre spacing in a steel fibre reinforced concrete (SFRC) industrial floor. Two non-destructive testing (NDT) methods: an electromagnetic induction technique and a radar-based technique were applied. The first method allowed to detect the spacing in subsequent layers located in the thickness of the slab. The result of the second method was a 3D visualization of the detected fibre in the volume of concrete slab. The conducted tests showed aptitude and limitations of the applied methods in estimating fibre volume and spacing. The two techniques also allowed to locate the areas with relatively low fibre concentration which are very likely to be characterized by low mechanical properties.

The protection of grapevine from the diseases is now particularly focused on the development of environmentally friendly strategies. Although sulphur is not in itself a toxic substance, a large use towards powdery mildew, in organic vineyards especially, may cause problems to environment, health and safety of viticultural workers and plant phytotoxicity. The activity on powdery mildew of sulphur applied at doses reduced up to 50% in tank mixtures with silicates and Equisetum arvense based products, never tested on grapevine, was assessed. Two-year trials were carried out applying the products every 7-9 days in the period of greatest risk for spring ascosporic infections, in two organic vineyards in the Abruzzo region, Italy. The effectiveness towards the disease of the mixtures was demonstrated, often to a greater extent than that of full-dose sulphur, normally used in the vineyards. Furthermore, in vines treated with the mixtures, increases in yield quantity and quality, such as higher contents of soluble solids and lower levels of total acidity, have been shown. Due to the strong efficacy demonstrated on the leaves, silicon-based products + sulphur mixtures can also be recommended in eradicative applications, aimed at reducing the inoculum of the disease. The great activity of the mixtures demonstrated in this study suggests confirmation through further investigations on different cultivars and vine-growing areas at different levels of infection, also testing the effectiveness of individual silicon products against the disease.

Environment pollution is the major problem for all the sectors. In environment pollution there are different types of pollution is included such as air pollution, water pollution, soil pollution etc. In these types of pollution most of it is air pollution. There are many reasons for pollution of air. Human advance in science but one of the major draw backs of science is the pollution of air rapidly. Air pollution is injurious to health. Every year a large number of people died for the effects of air pollution. It can be improved in many ways among these ways technology upgradation plays a major role here. There are various method that prevent air pollution. Many researchers tried and is trying to prevent the air pollution in many ways. In this review paper I summarise the existing research on different ways for preventing air pollution in addition I will discuss the gaps and future aspect on this topic.

Plant growth promoting rhizobacteria (PGPR) are a diverse group of microorganisms including genera such as Pseudomonas, Bacillus, Serratia, Enterobacter and Klebsiella. These bacteria have the ability to colonize roots externally and internally, and to directly enhance plant growth employing various mechanisms like phytohormone production and nutrient mineralization. These microbes can also promote plant growth indirectly by secreting antimicrobial compounds (e.g., siderophores, hydrogen cyanide) to antagonize root pathogens or by inducing defensive responses in the plant. Interestingly, there are also cases where production of antibiotic compounds such as 2,4-Diacetylphloroglucinol have the direct effect of enhancing plant growth and yield, irrespective of their biocontrol effects. The objective of this paper is to review publications showcasing PGPRs that have the capacity to both control root pathogens and stimulate plant growth, and to discuss what mechanisms might be involved.

Typhoid fever is an infectious disease that affects humanity worldwide particularly in the lower socio-economic communities where many individuals are exposed to a dirty environment and unclean food. A mathematical model is formulated to analyze the impact of control measures such as vaccination of susceptible humans, treatment of infected humans and sanitation in the different socio-economic communities. The model assumed that the population comprises of two socio-economic classes. The essential dynamical system analysis of our model was appropriately carried out. The impact of the control measures was analyzed, and the optimal control theory was applied on the control model to explore the impact of the different control measures. Numerical simulation of the models and the optimal controls were carried out and results obtained indicates that the overall combination of the control measures eradicates Typhoid fever in the population but the controls are more optimal in the higher socio-economic communities.

The dairy industry relies heavily on milk pasteurization to ensure the safety and quality of milk products. Pasteurization is a process that involves heating milk to a specific temperature for a set period of time to kill harmful bacteria and other pathogens while preserving its nutritional value. recent years, newer techniques such as High Temperature Short Time (HTST) pasteurization have gained popularity due to their efficiency and effectiveness. HTST pasteurization involves rapidly heating milk to a high temperature for a short duration of time, followed by rapid cooling. This process helps to minimize the loss of flavor and nutrients in milk while ensuring its safety. However, there is still a need in the market for a compact and remotely controlled process plant for milk pasteurization. The proposed work aims to address this need by designing a process plant that is not only compact but also remotely controlled, allowing for efficient and convenient operation. can control the process plant remotely, allowing for flexibility and convenience in monitoring and managing the pasteurization process from anywhere with an internet connection

With the introduction of HTTP/3, whose transport is no longer the traditional TCP protocol but the novel QUIC protocol, research for solutions to the unfairness of Adaptive Streaming over HTTP (HAS) has become more challenging. That is, because of different transport layers, the HTTP/3 may not be available for some networks and the clients have to use HTTP/2 for their HAS applications instead. Therefore, the scenario that HAS over HTTP/3 (HAS/3) compete against HTTP/2 (HAS/2) must be considered seriously. However, there have been a shortage of investigations on the performance and the origin of the unfairness in such a cross-protocol scenario in order to produce proper solutions. Therefore, this paper provides a performance evaluation and root-cause analysis of the cross-protocol unfairness between HAS/3 and HAS/2. It is concluded that, due to differences in the congestion control mechanisms of QUIC and TCP, HAS/3 clients obtain larger congestion windows, thus requesting higher video bitrates than HAS/2. As the problem lies in the transport layer, existing client-side ABR-based solutions for the unfairness from the application layer may perform suboptimally for the cross-protocol case.

In this article, the research team has systematically developed a method to model the kinematics and dynamics of a 3-wheeled robot subjected to external disturbances and sideways wheel sliding. These models will be used to design control laws that compensate for wheel slippage, model uncertainties, and external disturbances. These are control algorithms developed based on Dynamic Surface Control (DSC). Adaptive trajectory tracking DSC algorithm using fuzzy logic system (AFDSC) and radial neural network (RBFNN) with fuzzy logic system to overcome the disadvantages of DSC and expand the application domain for wheeled Mobile Robots (WMR). However, this Adaptive Fuzzy Neural Network Dynamic Surface Control (AFNNDSC) adaptive controller ensures the closed system is stable and follows the preset trajectory in the presence of wheel slippage model uncertainty and is affected by significant amplitude disturbances. The stability and convergence of the closed-loop system are guaranteed based on the Lyapunov analysis. The AFNNDSC adaptive controller is evaluated by simulation on MATLAB/Simulink software and in a steady state. The maximum position error on the right wheel and left wheel is 0.000572 (m) and 0.000523 (m), and the angular velocity tracking error in the right and left wheels of the control method is 0.000394 (rad/s). The experimental results show the correctness of the theoretical analysis, the effectiveness of the proposed controller, and the possibility of practical application.

Bacteriophages can provide alternative measures for the control of E. coli O157:H7 that is currently an emerging food-borne pathogen of severe public health concern. This study was aimed at characterising E. coli O157:H7 specific phages as potential biocontrol agents for these pathogens. Fifteen phages were isolated and screened against 69 environmental E. coli O157:H7. Only 3 phages displayed broad lytic spectra against environmental shiga toxin-producing E. coli O157:H7 strains. These 3 lytic phages were designated V3, V7 and V8. Subsequent characterization indicated that they displayed very high degree of similarities despite isolation from different locations. Transmission Electron microscopy (TEM) of the phages revealed that they all had isometric heads of about 73 – 77 nm in diameter and short tails ranging from 20 - 25 nm in diameter. Phages V3, V7 and V8 were assigned to the family Podoviridae based on their morphology. Pulsed field gel electrophoresis (PFGE) genome estimation of the 3 phages demonstrated identical genome sizes of ~ 69 nm. The latent periods of these phages were 20 min, 15 min, and 20 min for V3, V7 and V8 respectively while the burst sizes were 374, 349 and 419 PFU/ infected cell respectively. While all the phages were relatively stable over a wide range of salinity, temperatures and pH values, their range of infectivity or lytic profile was rather narrow on environmental E. coli O157:H7 strains isolated from cattle faeces. This study showed that the Podoviridae bacteriophages are the dominant E. coli O57:H7-infecting phages harboured in cattle faeces in the North-West Province of South Africa and due to their favourable characteristics can be exploited in the formulation of phage cocktails for the bio-control of E. coli O157:H7 in meat and other meat products.

The importance of oxygen in the winemaking process is widely known, as it affects the chemical aspects and therefore the organoleptic characteristics of the final product. Hence, it is evident the usefulness of a continuous and real-time measurements of the levels of oxygen in the various stages of the winemaking process, both for monitoring and for control. The WOW project has focused on the design and the development an innovative device for monitoring the oxygen levels in wine. This system is based on the use of an optical fiber to measure the luminescent lifetime variation of a reference metal/porphyrin complex, which decays in presence of oxygen. The developed technology results in a high sensitivity and low cost sensor head that can be employed for measuring the dissolved oxygen levels at several points inside a wine fermentation or aging tank. This system can be complemented with dynamic modeling techniques to provide predictive behavior of the nutrient evolution in space and time given few sampled measuring points for both process monitoring and control purposes. The experimental validation of the technology has been first performed in a controlled laboratory setup to attain calibration and study sensitivity with respect to different photo-luminescent compounds and alcoholic or non-alcoholic solutions, and then in an actual case study during a measurement campaign at a renown Italian winery.

Researchers are always looking to find ways to use energy more efficiently while keeping people comfortable at home. They've tried different methods like fuzzy logic and genetic algorithms to do this. In this paper, we introduce a novel model that combines different techniques like data smoothing, optimization, machine learning, and control algorithms to reach this goal in smart homes. The proposed model is made up of three main parts: smoothing, optimization, and control. The smoothing part uses the Kalman filter to get rid of any unnecessary noise and make sure the data used to predict energy use is clean and smooth. The optimization part uses both genetic with firefly algorithms and artificial neural networks to minimize the gap between the actual environmental conditions and the conditions users find comfortable. It adjusts the comfort settings in real-time using machine learning. The control part uses Mamdani fuzzy logic to make sure energy is delivered in the best way possible to the systems that control temperature, lighting, etc., making the home comfortable and saving energy at the same time. Comparative analyses demonstrate the superiority of the proposed model over existing algorithms, including the Particle Swarm Optimization (PSO) algorithm. Additionally, the paper discusses the importance of adaptive controllers in addressing issues associated with incorrect PID controller selection and highlights the benefits of using the FA-GA in energy optimization and comfort improvement. Overall, the proposed model offers an effective solution for efficient energy consumption optimization and enhanced user comfort in diverse settings through the integration of advanced algorithms and optimization modules.

This paper proposes a new kind of airship actuator configuration for surveillance and environmental monitoring missions. We present the design and application of a 6-propeller electrical airship (Noamini) with independent tilting propellers, allowing improved and flexible maneuverability. The vehicle has different combinations of differential propulsion and can be used in 2, 4 or 6 motors configuration. We developed a high-fidelity airship simulator for the Noamini airship, which was used to test and validate a control-guidance approach. Incremental Nonlinear Dynamic Inversion (INDI) is used for the velocity/attitude control to follow a high-level L1 guidance reference in a simulated waypoint tracking mission with wind and turbulence. The proposed framework will be soon implemented in the onboard control system of the Noamini, an autonomous airship for environmental monitoring and surveillance applications.

Climate change and development have increased urban flooding, requiring modernization of stormwater infrastructure. Retrofitting standard passive systems with controllable valves/pumps is promising, but requires real-time control (RTC). One method of automating RTC is reinforcement learning (RL), a general technique for sequential optimization and control in uncertain environments. The notion is that an RL algorithm can use inputs of real-time flood data and rainfall forecasts to learn a policy for controlling the stormwater infrastructure to minimize measures of flooding. In real-world conditions, rainfall forecasts and other state information, are subject to noise and uncertainty. To account for these characteristics of the problem data, we implemented Deep Deterministic Policy Gradient (DDPG), an RL algorithm that is distinguished by its capability to handle noise in the input data. DDPG implementations were trained and tested against a passive flood control policy. Three primary cases were studied: (i) perfect data, (ii) imperfect rainfall forecasts, and (iii) imperfect water level and forecast data. Rainfall episodes (100) that caused flooding in the passive system were selected from 10 years of observations in Norfolk, Virginia, USA; 85 randomly selected episodes were used for training and the remaining 15 unseen episodes served as test cases. Compared to the passive system, all RL implementations reduced flooding volume by 70.5% on average, and performed within a range of 5%. This suggests that DDPG is robust to noisy input data, which is essential knowledge to advance the real-world applicability of RL for stormwater RTC.

Recently, doubts were raised about the existence of the bilingual advantage in cognitive control. The aim of the present review was to investigate the bilingual advantage and its modulating factors. We searched the Medline, ScienceDirect, Scopus, and ERIC databases for all original data and reviewed studies on bilingualism and cognitive control, with a cut-off date of October 31, 2018, thereby following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocol. The results of the 46 original studies show that, indeed, the majority, 54.3%, reported beneficial effects of bilingualism on cognitive control tasks; however, 28.3% found mixed results, and 17.4% found evidence against its existence. Methodological differences seem to explain these mixed results: particularly, the varying selection of the bilingual participants, the use of non-standardized tests, and the fact that individual differences were often neglected, and that longitudinal designs were rare. Therefore, a serious risk for bias exists in both directions (i.e., in favor of and against the bilingual advantage). To conclude, we found some evidence for a bilingual advantage in cognitive control; however, if significant progress is to be made, better study designs, bigger data, and more longitudinal studies are needed.

The rhizosphere is a rich source of actinomycetes which can produce several potential biologically-active secondary metabolites. The principal goals for this research are to extract, purify and characterize the bioactive secondary metabolites produced by three different strains of actinomycetes isolated from the rhizosphere of rosemary, black locust and olive. The plant growth-promoting effect (PGPE) of the studied strains of actinomycetes on Ocimum basilicum L. (basil) and disease-control effect on necrotic stem lesions of “black leg” caused by Fusarium tabacinum on basil, were in silico evaluated. The cell-free culture filtrates from the studied actinomycetes isolates were evaluated in vitro for their antimicrobial activity against some common phytopathogens. The secondary metabolites obtained from the cell-free culture filtrates have been chemically characterized using high‐resolution electrospray ionization of liquid-chromatography/mass-spectrometric detection (ESI-(HR)Orbitrap-MS). Results of in silico trial showed that all studied isolates demonstrated PGPE on basil seedlings improving some Eco-physiological characteristics and reduced the disease incidence of F. tabacinum. The extracted metabolites from the studied actinomycetes demonstrated antimicrobial activity in Petri-plates assay. The chemical analysis revealed the presence of totally 20 different components. This research emphasizes how valuable the examined isolates are for producing bioactive compounds, indicating their putative antimicrobial activity and their potential employment as fungal-biocontrol agents. In particular, the obtained results revealed the possibility of green-synthesis of some important secondary metabolites such as N-Acetyl-L-histidinol, Rhizocticin A and Eponemycin from actinomycetes. The bioactive metabolites may be successively used to develop novel bio-formulations for both crop protection and/or PGPE.

In healthy ageing, capacity declines in the neural, muscular, and skeletal systems, and each system decline has its effect on the execution of complex motor tasks. This decline in capacity can result in the inability to stand up (sit-to-stand, sit-to-walk), which is a key movement for independence. The mechanisms leading to mobility limitations or inabilities are complex, overlapping, and interdependent and the complementary fields of biomechanics, motor control, and physiology need to be combined to understand these mechanisms. The aim of this review is to provide an overview of the current knowledge of age-related compensation in standing up and to consider the limitations of these results when analysing standing up in daily life using the Capacity, Reserve, Movement Objectives, and Compensation (CaReMoOC) framework that combines biomechanics, motor control, and physiology. A literature search was performed in the search engine Scopus, using the keywords and their synonyms: strateg*(approach, technique, way) AND, sit-to-walk OR sit-to-stand OR rise (raise, arise, stand, stand-up) AND chair (seat). Inclusion criteria were: biomechanics or motor control on sit-to-stand or sit-to-walk in healthy and/or frail adults (<60y) and elderly (>60y), and/or osteoarthritis patients as a specific case of ageing related decline. The review shows that movement compensations in standing up manifest as changes in planned trajectory (Compensation by Selection) and in muscle recruitment (Compensation by Reorganisation). However, as most studies in the literature typically use standardized experimental protocols where movement compensation is restricted, these studies cannot be directly translated to functional tasks, such as the mobility of the elderly in their homes, communities, and clinic. Compensation must be included in future studies in order to facilitate clinical translation. Specifically, future studies in the standing up task should 1) determine the effect of varying arm use strategies (e.g., armrests, knees, chair, cane) on trunk and both lower limb and upper limb joint loading, 2) analyse control strategies in elderly people, 3) determine the biomechanical implications of asymmetry, and 4) incorporate assessments of age-related physical and neural decline as well as changes in psychological priorities.

Abstract— Flight Control System is an integrated avionics system equipped with the minimum required components for an autonomous flight. This paper focuses on the Hardware Design of the Flight Control System and presents specific details of the components and its interface. The system architecture is based on Field Programmable Gate Array and Digital Signal Processor. Employing these two processors in the flight control system would improve the Flight Control System performance in terms of fast sequential processing of high-level control algorithms. In addition to Field Programmable Gate Array and Digital Signal Processor, the flight control computer system will also make use of Global Positioning System and Micro Electro Mechanical System sensors. The project will be implemented using Altera’s System On Programmable Chip builder, currently known as Qsys – Platform Designer implemented in Quartus-II. The system employs Nios-II processor which is 32-bit soft-core embedded-processor architecture designed especially for the Altera’s family of Field Programmable Gate Array. From conceptualization to final design, this paper presents the functionality of the different modulus and complex interfaces employed in this Flight Control System.

This paper aims to demonstrate how the detection of communities for epidemiological networks can be used to reduce the dimensionality of optimal control problems. A range of planted partition stochastic blockmodels are generated, where the underlying communities in the model vary in detectability. A high-performance computing workflow is then used to simulate and estimate reduced model dynamics for the networks, which in turn is used to find optimal control solutions.

Rising fuel costs, significant air pollution, and the need to mitigate the negative consequences of oil consumption have diminished the relevance of traditional vehicles. This shift encourages the adoption of safer, more efficient, and eco-friendly transportation alternatives, such as fuel cell, electric, and hybrid vehicles. Brushless direct current motors are gaining popularity due to their high efficiency, power factor, torque, and controllability. By 2030, Brushless Direct Current motors are expected to replace conventional motors as the standard for power transfer, especially in dynamic applications like automobiles, more electric aircraft. This study explores a control technique to improve real-time control of brushless direct current motors in electric vehicles It presents speed control of these system for electric vehicle applications and an overview of electric vehicle technologies. A model for the 120-degree mode was developed using electrical and mechanical equations in MATLAB/Simulink. Three scenarios were examined to assess the potential of controlling brushless direct current motors using constant and dynamic speed and torque. The actual value reached the reference value in the first two scenarios.

The paper deals with one new property of the linear time-optimal control problems with real eigenvalues of the system, no matter of the number of eigenvalue multiplicity. This property unveils a prospective of synthesizing the time-optimal control without the need of describing the switching hyper-surfaces. The already chrestomathy example of the time-optimal control of a double integrator is resolved by the new technique and compared with the classical synthesis.

In modern inverter applications, multilevel converters are used thanks to their capability of reducing the passive fi lter volumes, improving the overall THD, sharing the power sources across the several converter cells, and providing a reconfi guration ability in case of failure. However, increasing the number of cells makes more complex the control of the converter. This article proposes a decentralized control technique based on the use of elementary modular controllers, associated with each converter cell and communicating with their close neighbors to obtain the balancing of the powers they supplied. Each modular controller can be dynamically removed or added to allow reconfi guration of the converter for functional safety purpose. This method is applied to a 240V/3A 5-cells Cascaded Full-Bridge Multilevel Converter. The response of the system to load transients and cell voltage disturbances demonstrates the robustness of the proposed decentralized control method. Thanks to the use of modular controllers, the number of levels of the converter can be extended to the order N without adding complexity to its control.

In the past few decades, probabilistic interpretations of brain functions have become widespread in cognitive science and neuroscience. In particular, the free energy principle and active inference are increasingly popular theories of cognitive functions that claim to offer a unified understanding of life and cognition within a general mathematical framework derived from information and control theory, and statistical mechanics. However, we argue that if the active inference proposal is to be taken as a general process theory for biological systems, it is necessary to understand how it relates to existing control theoretical approaches routinely used to study and explain biological systems. For example, recently, PID control has been shown to be implemented in simple molecular systems and is becoming a popular mechanistic explanation of behaviours such as chemotaxis in bacteria and amoebae, and robust adaptation in biochemical networks. In this work, we will show how PID controllers can fit a more general theory of life and cognition under the principle of (variational) free energy minimisation when using approximate linear generative models of the world. This more general interpretation provides also a new perspective on traditional problems of PID controllers such as parameter tuning as well as the need to balance performances and robustness conditions of a controller. Specifically, we then show how these problems can be understood in terms of the optimisation of the precisions (inverse variances) modulating different prediction errors in the free energy functional.

While the Internet of Things (IoT) technology has been widely recognized as the essential part of Smart Cities, it also brings new challenges in terms of privacy and security. Access control (AC) is among the top security concerns, which is critical in resource and information protection over IoT devices. Traditional access control approaches, like Access Control Lists (ACL), Role-based Access Control (RBAC) and Attribute-based Access Control (ABAC), are not able to provide a scalable, manageable and efficient mechanism to meet the requirements of IoT systems. Another weakness in today's AC is the centralized authorization server, which can be the performance bottleneck or the single point of failure. Inspired by the smart contract on top of a blockchain protocol, this paper proposes BlendCAC, which is a decentralized, federated capability-based AC mechanism to enable an effective protection for devices, services and information in large scale IoT systems. A federated capability-based delegation model (FCDM) is introduced to support hierarchical and multi-hop delegation. The mechanism for delegate authorization and revocation is explored. A robust identity-based capability token management strategy is proposed, which takes advantage of the smart contract for registering, propagating and revocating of the access authorization. A proof-of-concept prototype has been implemented on both resources-constrained devices (i.e., Raspberry PI node) and more powerful computing devices (i.e., laptops), and tested on a local private blockchain network. The experimental results demonstrate the feasibility of the BlendCAC to offer a decentralized, scalable, lightweight and fine-grained AC solution for IoT systems.

A real-time flight simulation tool is proposed using a Virtual Reality Head-Mounted Display (VR-HMD) for airships operating in beyond the line-of-sight (BLOS) conditions. Particularly, the VR-HMD is developed for stratospheric airships flying at low/high altitudes. The proposed flight simulation tool uses the corresponding aerodynamics characteristics of the airship, the buoyancy effect, mass balance, added mass, propulsion contributions and ground reactions in the FlightGear Fight Simulator (FGFS). The VR headset has been connected to the FGFS along with the radio controller containing the real-time orientation/state of each button that is also simulated to provide better situational awareness and a Head-Up Display (HUD) that has been developed to provide the required flight data. In this work, a system was developed to connect the FGFS and the VR-capable graphics engine, Unity, to a PC and a wireless VR-HMD in real-time with minimal lag between data transmission. A balance was found for FGFS to write to a CSV file at a period of 0.01s. For Unity, the file was read every frame which translates to around 0.0167s (60 Hz). A test procedure was also conducted with a similar rating technique based on the NASA TLX questionnaire that identifies the pilot’s spare mental capacity when completing an assigned task to assure the comfortability of the proposed VR-HMD. Accordingly, a comparison has been made for the aircraft control using the desktop simulator and the VR-HMD tool. Results, showed that the current iteration of the system is ideal to train pilots on using similar systems in a safe and immersive environment. Furthermore, such an advanced portable system may even increase the situational awareness of pilots and allow them to complete a sizeable portion of actual flight tests with the same data transmission procedures in simulation. The resulting VR-HMD flight simulator is also conceived to express the ground control station (GCS) concept and transmit flight information as well as the point of view (POV) visuals in real-time using the real environment broadcasted using an onboard camera.

It has been more than three decades since the discovery of multifunctional factors, Non-POU Domain-Containing Octamer-Binding Protein, NonO and Splicing Factor, Proline-and Glutamine-Rich, SFPQ. Some of their functions, including their participations in transcriptional and posttranscriptional regulation as well as their contribution to paraspeckle subnuclear body organization have been well-documented. In this review, we focus on the roles of NonO and SFPQ in cell cycle with particular attention to their participation in nonhomologous end joining (NHEJ) and homologous recombination (HR) of DNA damage responses induced by irradiation. In these contexts, absence or malfunction of either or both lead to genome instability and ultimately to apoptosis, cellular senescence, and tumor development. This review also will shed light on NonO and SFPQ function in DNA/RNA/protein binding and their association with Ku heterodimer of the NHEJ pathway required for repair of DNA double-strand breaks (DSBs).

Among the array of structurally and toxicologically diverse mycotoxins, aflatoxins have attracted the most interest of scientific research due to their high toxicity and incidence in foods and feeds. Despite the undeniable progress made in various aspects related to aflatoxins, the ultimate goal consisting of reducing the associated public health risks worldwide is far from being reached due to multiplicity of social, political, economic, geographic, climatic, and development factors. However, a reasonable degree of health protection is attained in industrialized countries owing to their scientific, administrative, and financial capacities allowing them to use high-tech agricultural management systems. Less fortunate situation exists in equatorial and sub-equatorial developing countries mainly practicing traditional agriculture managed by smallholders for subsistence, and where the climate is suitable for mould growth and aflatoxin production. A situation that worsens by the climatic change being increasingly suitable for aflatoxigenic mold growth and toxin production. Accordingly, it is difficult to harmonize the regulatory standards of aflatoxins worldwide, which prevents agri-foods of developing countries from access to the market of industrialized countries. To tackle the multi-facetted aflatoxin problems, actions should be taken collectively by the international community involving scientific research, technological and social development, environment protection, awareness promotion, etc. International cooperation should foster technology transfer and exchange of pertinent technical information. This review presents the main historical discoveries leading to our present knowledge on aflatoxins and the challenges that should be addressed presently and in the future at various levels to ensure higher health protection for everybody. In short, it aims to elucidate where we come from and where we should go in terms of aflatoxin research/development.

This research work explains the practical realization of hybrid solar wind based standalone power system with maximum power point tracker (MPPT) to produce electrical power in rural places (residential applications). The solar inspired Ant Colony Optimization (ACO) based MPPT algorithm is employed for the purpose of fast and accurate tracking power from solar and wind system. Fuzzy Logic Control (FLC) inverter controlling strategy is adopted in this presented work compared to classical PI control. Moreover, single Cuk converter is operated as impedance power adapter to execute MPPT functioning. Satisfactory practical results have been realized using dSPACE (DS1104) platform that justify the superiority of proposed algorithms designed under various operating situations.

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles (UAVs) is considered. Adaptive backstepping technology is used to design flight control schemes for quadrotor UAVs. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor UAVs and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during UAV flight under uncertain disturbances. Compared with the existing results, the novelty of this paper is that the proposed formation control scheme does not require the use of the quadrotor model parameters. Finally, a quadrotor UAV swarm system is used to verify the effectiveness of the proposed control scheme.

This work targets the development of a mobility control system for high-speed series hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of the research encompasses the modeling of the series hybrid powertrain specific to military tracked vehicles, as well as an in-depth analysis of their dynamic behavior. Subsequently, the study conducts a critical review of the mobility control approaches sourced from literature, identifying key techniques relevant to high-inertia vehicular applications. Building on the foundational models, the study puts forward a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system's resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are carried out in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system's capacity to improve vehicular response and highlight its potential impact on the future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

Let G be a connected Lie group with Lie algebra g. This review is devoted to studying the fundamental dynamic properties of elements in the normalizer NG of G. Through an algebraic characterization of NG we analyze the different dynamics inside the normalizer. NG contains the well-known left-invariant vector fields and the linear and affine vector fields on G. In any case, we show the shape of the solutions of these ordinary differential equations on G. We give examples in low-dimensional Lie groups. It is worth saying that these dynamics generate the linear and bilinear control systems on Euclidean spaces and the invariant and linear control systems on Lie groups. Moreover, the Jouan Equivalence Theorem shows how to extend this theory to control systems on manifolds.

Due to legal regulations, the rise of globalised (online) commerce and the need for public health protection, the analysis of spirits (alcoholic beverages &gt; 15 % vol) is a task with growing importance for governmental and commercial laboratories. In this article a newly developed method using nuclear magnetic resonance (NMR) spectroscopy for the simultaneous determination of 15 substances relevant for the quality and authenticity assessment of spirits is described. The new method starts with a simple and rapid sample preparation and does not need an internal standard. For each sample a group of 1H-NMR spectra is recorded, among them a 2D spectrum for analyte identification and 1D spectra with suppression of solvent signals for quantification. Using the Pulse Length Based Concentration Determination (PULCON) method, concentrations are calculated from curve fits of the characteristic signals for each analyte. The optimisation of the spectra, their evaluation and the transfer of the results are done fully automatically. Glucose, fructose, sucrose, acetic acid, citric acid, formic acid, ethyl acetate, ethyl lactate, acetaldehyde, ethanol, methanol, n-propanol, isobutanol, isopentanol, 2-phenylethanol and 5-(hydroxymethyl)furfural (HMF) can be quantified with an overall accuracy better than 8 %. This new NMR-based targeted quantification method enables the simultaneous and efficient quantification of relevant spirits ingredients in their typical concentration ranges in one process with good accuracy. It has proven to be a reliable method for all kinds of spirits in routine food control.

In order to follow the Preventive Chemotherapy for the transmission control as recommended by WHO, Gabon initiated in 2014 the mapping of Schistosomiasis and Soil Transmitted Helminthiasis (STH). Here we report the results of the Northern and Eastern health regions, representing a third of the land area and 12% of its total population. All the 9 departments of the two regions were surveyed and from each, 5 schools were examined with 50 schoolchildren per school. The parasitological examinations were realized using the filtration method for urine and the Kato-Katz technique for stool samples. Overall 2245 schoolchildren (1116 girls and 1129 boys), mean aged 11.28 ± 0.04 years, were examined. Combined schistosomiasis and STH affected 1270 (56.6%) with variation between regions, departments and schools. For schistosomiasis, prevalence were 1.7% across the two regions, with no significant difference (p>0.05) between the Northern (1.5%) and the Eastern (1.9%). Schistosomiasis is mainly caused by Schistosoma haematobium with a prevalence of 1.5%, 1.9% and 1.7%, respectively in the North, East and globally. STH are more common than schistosomiasis, with an overall prevalence of 56.1% significantly different between the Northern (58.1%) and Eastern (53.6%) regions (p = 0.034). Trichuris trichiura is the most abundant infection with a prevalence of 43.7% followed by Ascaris lumbricoides 35.6% and hookworms 1.4%. According to these results, an appropriate mass drug administration strategy is given for the control of each neglected tropical disease group surveyed.

Background: Scabies is an unfortunately neglected tropical skin disease. Scabies occurs in Australia, however it is drastically more common amongst select socioeconomically disadvantaged groups. Amongst these, Aboriginal and Torres Strait Islander communities are affected particularly severely, likely secondary to rampant overcrowding. Methods: This literature review has comprehensively explored the relevant evidence available since the year 2000. Objectives: The objective of this article is to provide updates on the identification, management, and control of scabies in Aboriginal and Torres Strait Islander communities. The article also aims to reveal issues with these factors that may be contributing to the inflated prevalence of scabies amongst these groups. Conclusions: Diagnosis currently depends upon clinical examination, dermatoscopy, and skin scraping microscopy; all of which are prone to error. In Australia, topical permethrin remains first-line treatment, however resistance is developing. Other management aspects to consider are environmental measures and treating secondary infections. Scabies prevention is far more cost-effective than managing advanced individual cases, typically ensured through mass drug administration of permethrin or ivermectin. Sustained prevention can prove troublesome for some communities. In order to address the status of scabies as a neglected tropical disease, these issues must be managed first.

Actually wide excision is recommended after the primary excision of any cutaneous melanomas. The definition of the margins of wide excision indicated by the guidelines has remained unchanged over the years, although the reported indications derived from fairly dated studies, in which melanomas tend to be thicker or in advanced stages at diagnosis. These indications may no longer be current; especially in those patients affected by in situ or thin melanoma, exposing patients to a possible overtreatment. A retrospective observational study was conducted in patients who had undergone surgery for melanoma in a single institution. In a univariate model a melanoma-positive wide excision resulted related with a worst progression free survival (PFS); but this association was not confirmed in the multivariable model. Moreover, logistic model were applied to estimate the probability to find a metastasis after wide local excision (WLE) in relation to demographic data of patients and histologic information of the melanoma. Results testified that the Breslow thickness was the only factor associated with the increase of the risk to found metastases in the WLE area. The ROC curve testified that the optimum cut-off value to differentiate patients with respect those without a tumor-positive wide excision, was a Breslow thickness of 2.31mm in women, and 2.4mm in men.

Global temperature rise due to hydrocarbon gases emission that are produced by generating the electrical power has a great attention by the researchers to reduce it till zero emission is successfully achieved. Sustainable energy source such as solar energy, wind, hydro-energy and sea wave energy are focal areas to replace the fossil fuel by clean energy. In this article, daylight is used to minimize the power consumption that required for indoor lighting using electric roller blind. Smart controller is designed to adjust the position of the roller blind stepper motor, and hence, adjust the roller blind opening, based on the preset light intensity, to achieve precise utilization of daylight inside the room. If the desired Lux is not achieved for any reason, the smart controller adjusts the LED circuit current to boost the light intensity to achieve precisely the desired Lux. Comprehensive test cases using MATLAB-Simulink is carried out to verify the performance of the proposed smart controller. Techno-economic analysis is introduced to evaluate the benefits of installing the controller. Summary and recommendation are given at the end.

In this paper, by using the variational method, a sufficient condition for the unique existence of the stationary solution of the reaction-diffusion ecosystem is obtained, which directly leads to the global asymptotic stability of the unique equilibrium point. Moreover, delayed feedback ecosystem with reaction-diffusion item is considered, and utilizing impulse control results in the globally exponential stability criterion of the delayed ecosystem. It is worth mentioning that the Neumann zero-boundary value that the infected and the susceptible people or animals should be controlled in the epidemic prevention area and not allowed to cross the border, which is a good simulation of the actual situation of epidemic prevention. And numerical examples illuminate the effectiveness of impulse control, which has a certain enlightening effect on the actual epidemic prevention work . That is, in the face of the epidemic situation, taking a certain frequency of positive and effective epidemic prevention measures is conducive to the stability and control of the epidemic situation. Particularly, the newly-obtained theorems quantifies this feasible step. Besides, utilizing Laplacian semigroup derives the $p$th moment stability criterion for the impulsive ecosystem.

Central nervous system (CNS) uses vision, vestibular, and somatosensory information to maintain body stability. Research has shown that there is more lumbar proprioception error among low back pain (LBP) individuals as compared to healthy people. In this study, two groups of 20 healthy people and 20 non-specific low back pain participants (LBP) took part in this investigation. This investigation focused on somatosensory sensors and in order to alter proprioception, a vibrator (frequency of 70Hz, amplitude of 0.5 mm) was placed on the soleus muscle area of each leg and two vibrators were placed bilaterally across the lower back muscles. Individuals, whose vision was occluded, were placed on two surfaces (foam and rigid) on force plate, and trunk angles were recorded simultaneously. Tests were performed in 8 separate trials; the independent variables were vibration (4 levels) and surface (2 levels) for within subjects and 2 groups (healthy and LBP) for between subjects (4×2×2). MANOVA and multi-factor ANOVA tests were done. Linear parameters for center of pressure (COP) (deviation of amplitude, deviation of velocity, phase plane portrait (PPP), and overall mean velocity) and nonlinear parameters for COP and trunk angle ((recurrence quantification analysis) RQA and Lyapunov exponents) were chosen as dependent variables. Results indicated that NSLBP individuals relied more on ankle proprioception for postural stability. Similarly, RQA parameters for the COP on both sides and for the trunk sagittal angle indicated more repeated patterns of movement among the LBP cohort. Analysis of short and long Lyapunov exponents showed that people with LBP caused no use of all joints in their bodies (non-flexible), are less stable than healthy subjects.

Soft robotic manipulators consisting of serially-stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for applications such as minimally invasive surgery and for inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with a closed-loop control to compensate the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with 6 inputs and 4 outputs.

Anaerobic digestion of waste material to biogas, with the remaining digestate slurry used as agricultural biofertilizer, is already a route of sustainable fuel production and its uptake will grow further. However, the foam layer that forms on top of the reacting mixture impedes the process and leads to liquid and solid material contaminating the gas product. Ideally, any effective foam repression should be low-cost, and react fast. Therefore, methods of optimizing anaerobic digestion need foam repression as one of the parameters in increasing gas yield. Foam can be repressed by pre-treating substrate which destroys filamentous bacteria and adding trace elements. The drawback to this method is the high cost of pre-treatment, the trace elements not being biodegradable and being toxic at high concentration; this method does not completely repress foam and is only effective under moderate organic loading

Background and Objectives: Place the question addressed in a broad context and highlight the purpose of the study. Materials and Methods: Describe briefly the main methods or treatments applied, including the study population description. Results: Summarize the article’s main findings. Conclusions: Indicate the main conclusions or interpretations. The abstract should be an objective representation of the article, it must not) results. Meanwhile, exclusion criterion is incomplete data in medical record. For the analysis of continuous variables, a General Linear Model (univariate) was employed, with the predictors included specific Personality Disorder. The outcome being the PB, and covariates encompassed age, sex, education, clinical diagnosis, and depression score. Results: Six personality disorders, namely Paranoid, Schizoid, Histrionic, Avoidant, Dependent, and Obsessive-Compulsive Personality Disorder, did not exhibit significant pathogenic beliefs. In contrast, the remaining four personality disorders demonstrated significant associations with specific pathogenic beliefs. Conclusions: While some personality disorders have specific beliefs, it's also common to have pathogenic beliefs that are not specific to their psychodynamic. It's essential to recognize specific pathogenic beliefs for each individual to be targeted for their psychotherapy.

Background: To assess effectiveness, safety of computed tomography (CT)-guided cryoablation for treating adrenal metastases (AMs). Materials and Methods: This study involved 12 patients treated with 13 CT-guided cryoablation procedures for AMs between 2016 and 2020. Patients’ ineligible for surgery, with tumors ≤5 cm, and no significant health risks were included. The procedures, conducted by expert radiologists, included initial non-contrast CT scans to determine lesion morphology, followed by cryoablation with monitoring for complications. Post-treatment, patients underwent regular physical and laboratory checks, including hormonal analysis, and CT scans at specified intervals to assess the treatment's effectiveness and detect disease recurrence or progression. Results: In this study, 12 patients with AMs successfully underwent cryoablation, achieving a primary technical success rate of 91.7% and a secondary rate of 100% after a repeat procedure for one patient. All cryoablation sessions were completed without major complications, with ice ball formations extending 1 cm beyond tumor margins to ensure safety. Over an 8–24-month follow-up (average 16.3 months), six patients required further systemic therapy, with three developing extra-adrenal tumors. Local progression was noted in two patients (16.7%), one of whom underwent a repeat cryoablation. Systemic progression was observed in five patients, involving renal and NSCLC cancer recurrences and bone metastasis. The study reported five deaths due to tumor progression and heart failure, with an average overall survival duration of 32.4 ± 7.6 months.

This article describes the study and digital implementation of a system onboard a TMS 3208F28335 ® DSP for vector control of the bearing motor speed with 4 poles split winding with 250W of power. Smart techniques: ANFIS and Neural Networks were investigated and computationally implemented to evaluate the bearing motor performance under the following conditions: operating as an estimator of uncertain parameters and as a speed controller. Therefore, the MATLAB program and its toolbox were used for the simulations and the parameter adjustments involving the structure ANFIS (Adaptive-Network-Based Fuzzy Inference System) and simulations with the Neural Network. The simulated results showed a good performance for the two techniques applied differently: the estimator and a speed controller using both a model of the induction motor operating as a bearing motor. The experimental part for velocity vector control uses three control loops: current, radial position, and speed, where the configurations of the peripherals, that is, the interfaces or drivers for driving the bearing motor.

Using metaheuristics, such as the Evolutionary Algorithm (EA), within control structures is a realistic approach for certain optimal control problems. Their role is often predicting the optimal control values over a prediction horizon using a process model (PM). The big computational effort sometimes causes problems. Our work addresses a new issue: whether a machine learning (ML) algorithm could “learn” the optimal behaviour of the couple (EA, PM). A positive answer is given by proposing datasets apprehending this couple's optimal behaviour and appropriate ML models. Following a design procedure, a number of closed-loop simulations will provide the sequences of optimal control and state values, which are collected and aggregated in a data structure. For each sampling period, datasets are extracted from the aggregated data. The ML algorithm experiencing these datasets will produce a set of regression functions. Replacing the EA predictor with the ML model, new simulations are carried out, proving that the state evolution is almost identical. The execution time decreases drastically because the PM’s numerical integrations are totally avoided. The performance index equals the best-known value. In different case studies, the ML models succeeded in capturing the optimal behaviour of the couple (EA, PM) and yielded efficient controllers.

In regenerated oak forests, weeds are present throughout the year, the ones appearing in early spring representing a major problem. Hence, the aim of this study was to examine herbicides for early spring broadleaved weed control in the regenerated oak forests while the seedlings are in a dormant stage. During 2019 and 2020 two experiments were set up in regenerated pedunculate oak forests with 2-yar and 3-year-old seedlings and two herbicides were applied in two doses: fluroxypyr at dose 360 g a.i. ha-1 and 540 g a.i. ha-1 and clopyralid at dose 100 g a.i. ha-1 and 120 g a.i. ha-1. The results from the two-year investigations showed that fluroxypyr and clopyralid significantly reduced early spring broadleaved weeds in the regenerated pedunculate oak forests but both doses of fluroxypyr provided greater control of presented weeds than the applied doses of clopyralid. The manual weeding reduced broadleaved weeds in experiments, but that method did not have a long-term effect on the reduction of weeds. Applied doses of herbicides fluroxypyr and clopyralid did not cause phytotoxicity symptoms in dormant oak seedlings. All investigated treatments significantly reduced fresh broadleaved weed biomass compared to the control. Generally, it can be concluded that fluroxypyr and clopyralid can be successfully used for control of many early spring broadleaved weeds in the regenerated pedunculate oak forests, but oak seedlings must be in the dormant stage.

Efforts towards an effective HIV-1 vaccine have remained mainly unsuccessful. There is increasing evidence for a potential role of HLA-C-restricted CD8+ T cell responses in HIV-1 control, including our recent report of HLA-C*03:02 among African children. However, there are no documented optimal HIV-1 CD8+ T cell epitopes restricted by HLA-C*03:02; additionally, the structural influence of HLA-C*03:02 on epitope binding is undetermined. Immunoinformatics approaches provide a fast and inexpensive method to discover HLA-restricted epitopes. Here, we employed immunopeptidomics to identify HLA-C*03:02-restricted CD8+ T cell epitopes. We identified a clade-specific Gag-derived GY9 (GTEELRSLY) HIV-1 p17 matrix epitope exclusively restricted to HLA-C*03:02. Residues E62, T142, and E151 in the HLA-C*03:02 binding groove and positions p3, p6, and p9 on the GY9 epitope are crucial in shaping and stabilizing the epitope binding. Our findings support the growing evidence of the contribution of HLA-C molecules to HIV-1 control and provide a prospect for vaccine strategies.