Copper(I) sulfide (Cu2S) is a low-cost, earth-abundant, and non-toxic thermoelectric material for applications in the middle-high temperature range (>650 K). Although 3D printing these materials can simplify their manufacturing, elevated temperatures observed during sintering impair their crystal structure and energy conversion efficiency. In this study, we demonstrated a novel post-processing methodology to revert the thermoelectric properties of the 3D printed Cu2-xS materials back to the unimpaired state via sulfur infusion. After printing and sintering, sulfur was infused into the specimens under vacuum to optimize their crystal structure and achieve high thermoelectric efficiency. Chemical analysis and X-ray Diffraction (XRD) tests showed that after the sulfur infusion process, the Cu/S ratio was reverted close to the stoichiometric level. 3D printed Cu2-xS showed p-type thermoelectric behavior with electrical conductivity peaking at 143 S-cm-1 at 750 K and Seebeck coefficient of 175 µV-K-1 at 627 K. Figure of merit (ZT) value of 1.0 at 780 K was achieved which is the highest value ever reported for a 3D printed Cu2-xS thermoelectrics at this temperature. Fabrication of environmentally friendly thermoelectric materials with extended dimensional freedom and conversion efficiency has the potential to impact the thermoelectric industry with new energy conversion applications and lowered manufacturing costs.

This research investigated the antihypertensive effects of tamarind products and compared their potentials based on their animal model’s data verified by molecular docking, multitarget interactions in network pharmacology, and dynamic simulation assays. The GC-MS characterized tamarind products were administered to the cholesterol-induced hypertensive Wistar albino rat models. Two-week-intervened animals were dissected to collect serum and organs which were respectively subjected to the analyses of hypertension-linked markers and tissue architectures. Lead biometabolites of tamarinds interacted with eight target receptors in molecular docking and dynamic simulation studies and they were tested for multitarget interactions using network pharmacological analyses. Results showed that serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), C-reactive protein (CRP), Troponin I, and lipid profiles were maximally reinstated by the phenolic-enriched ripened sour over the sweet tamarind flesh extracts, but seed extracts had a smaller influence. Among the tamarind’s biometabolites, Gamma-sitosterol (ϒ-sitosterol) was found to be the best ligand in managing hypertension via the possible ligand-receptor interactions with the guanylate cyclase which displayed the best drug-likeliness through the highest binding energy -9.3 Kcal. Multitargeted interactions-based degree algorithm and phylogenetic tree of pathways showed 14 targeted genes, of which NR3C1, REN, PPARG, and CYP11B1 hub genes, were consistently modulated by the ϒ-sitosterol to reduce hypertension and related risk factors. The dynamic simulation study showed that the P-RMSD values of ϒ-sitosterol-guanylate cyclase were stable between 75.00 to 100.00 ns at the binding pocket. The findings demonstrate that ripened sour tamarind extract may be supplemented to be a more prospective antihypertensive target or nutraceuticals affirming through advanced preclinical and clinical studies.

Manufacturers of photovoltaic modules do not provide all the information necessary to predict their performance under different climatic conditions. This forces the development of mathematical models of behavior and the application of mathematical methods for the calculation of their associated parameters. A toolbox called PVMSim implemented in MATLAB/GUI is proposed in this paper. PVMSIm provides models allowing the simulation of photovoltaic modules. A two-diode model is used to represent the effect of irradiance and temperature on the V-I and V-P characteristic curves. The accuracy of PVMSim has been vaildated by applying the models to two mono-crystalline and multi-crystalline solar modules of different power ratings and manufacturers. The model PVMSim model accuracy was verified against the manufacturer’s datasheet. This paper shows that this tool is useful for designers and professionals who require an intuitive graphical interface for fast and accurate modeling, simulation and sizing of photovoltaic systems.

Soybean is a highly nutritious legume grown globally as a food and feed crop. An examination of a collection of 10 cultivated and 6 wild Korean soybean varieties showed that there is phenotypic variability notable in different soybeans. Therefore, to develop a list of biomarker candidates useful for growing soybeans of better quality and quantity, the genes of 16 Korean soybean varieties were compared with those of the reference Glycine max var. Williams 82. The comparison was made through gene sequencing to facilitate selection of nsSNPs. The objective of the study was to find out the structural and functional variations caused by nsSNPs and discuss whether the collection of Korean soybean varieties qualifies as biomarkers based on their phenotypic traits. Analysis of the data collected was done using four software: SIFT, Polyphen, PANTHER, and I-mutant 2.0, which are designed to detect the rate of functional and structural variations caused by the nsSNPs in cultivated and wild soybean varieties. Genotypic information obtained in the analysis was used to develop a core collection of biomarkers based on whether nsSNP content was found in more than half of the 16 samples. Therefore, the list of biomarker candidates developed from this study showed that Korean soybean could provide valuable information needed in both future crop genetic research and identification of biomarkers.

Dysregulation of the angiotensin-II Type-I receptor (AT1R) and its pathway was reported to associate with poor-prognosis in several malignancies, including colorectal-cancer (CRC). We have explored the therapeutic-potential of targeting AT1R using valsartan, and its pharmacological-interaction with Fluorouracil (5-FU) in CRC. Anti-proliferative function was evaluated in 2-/3-dimensional cells and in vivo models. Anti-proliferative, anti-migratory, apoptotic function and effect on cell-cycle was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), wound-healing test, and Fluorescence-activated cell sorting (FACS), respectively, while gene-expression was determined at mRNA/protein levels. By histogical analysis and measuring of oxidative/antioxidant markers, we evaluated the anti-inflammatory properties of valsartan. Valsartan suppressed cell-growth and impacted the anti-tumor-activities of 5-FU by apoptosis-induction. Valsartan inhibited the cells migration by perturbation of Matrix metalloproteinase (MMP1). Furthermore, valsartan inhibited tumor-growth and metastasis, and this was more notable in valsartan/5-FU combination-treated-group. The mechanism was plausible to be via the induction of Reactive-oxygen-species (ROS) and down-regulation of Superoxide-dismutase (SOD), thiol/catalase (CAT) as well as Vascular endothelial growth factor (VEGF) and Transforming growth factor beta (TGF-β). Valsartan may protect cells against intestinal fibrosis by modulation of pro-fibrotic and pro-inflammatory components include fibronectin, Interleukin) IL-1β (, Tumor necrosis factor alpha) TNF-α (, Interferon gamma) INF-γ (, and Monocyte Chemotactic Protein 1 (MCP-1). Our findings demonstrated that targeting the AT1R receptor may inhibit tumor-growth and ameliorate fibrosis and inflammation associated with CRC via modulation of AT1 and TGF-β pathways.

A series of dinuclear copper(I) N,C,N- and P,C,P-carbodiphosphorane (CDP) complexes using multidentate ligands CDP(Py)2 (1) and (CDP(CH2PPh2)2 (13) have been isolated and characterized. Detailed structural information was gained by single crystal XRD analyses of nine representative examples. The common structural motive is the central double ylidic carbon atom with its characteristic two lone-pairs involved into binding of two geminal L-Cu(I) fragments at Cu-Cu distances in the range 2.55 – 2.67 Å. In order to enhance conformational rigidity within the characteristic Cu-C-Cu triangle, two types of chelating side arms were symmetrically attached to each phosphorus atom: two 2-pyridyl functions in ligand CDP(Py)2 (1) and its dinuclear copper complexes 2-9 and 11, as well as two diphenylphosphinomethylene functions in ligand CDP(CH2PPh2)2 (13) and its di- and mononuclear complexes 14-18. Neutral complexes were typically obtained via reaction of 1 with Cu(I) species CuCl, CuI, and CuSPh or via salt elimination reaction of [(CuCl)2(CDP(Py)2] (2) with sodium carbazolate. Cationic Cu(I) complexes were prepared upon treating 1 with two equivalents of [Cu(NCMe)4]PF6, followed by the addition of either two equivalent of an aryl phosphine (PPh3, P(C6H4OMe)3) or one equivalent of a bisphosphine ligands DPEPhos, XantPhos or dppf. For the first time carbodiphosphorane CDP(CH2PPh2)2 (13) could be isolated upon treating its precursor [CH(dppm)2]Cl (12) with NaNH2 in liquid NH3. A protonated and a deprotonated derivative of ligand 13 were prepared and their coordination was compared to neutral CDP ligand 13. NMR analysis and DFT calculations reveal, that the most stable tautomer of 13 does not show a CDP (or carbone) structure in its uncoordinated base form. For most of the prepared complexes, photoluminescence upon irradiation with UV light at room temperature was observed. Quantum yields (PL) were determined to 36% for dicationic [(CuPPh3)2(CDP(Py)2)](PF6)2 (4) and to 60% for neutral [(CuSPh)2(CDP(CH2PPh2)2] (16).

Natural Gas (NG) processing is a prominent industrial separation process. Among the available techniques, the innovative membrane process shows potential for efficient removal of impurities, including carbon dioxide (CO₂). This study focuses on utilizing breakthroughs in membrane separation to drive sustainable CO₂ extraction from natural gas. Through comprehensive research and analysis, we explore the effectiveness and feasibility of membrane-based systems in removing CO₂ impurities from NG, thus promoting greener and more sustainable industrial practices. Our findings underscore the transformative nature of membrane separation technology, presenting new possibilities for a more environmentally-friendly and sustainable approach to CO₂ extraction from natural gas.Natural Gas (NG) processing utilizes various techniques for impurity removal, with the membrane process emerging as a promising option for efficient carbon dioxide (CO₂) extraction. This research proposes the integration of a simple mathematical model into ASPEN HYSYS to design a membrane system for CO₂/CH₄ separation. The study also investigates parameter sensitivities by altering operating conditions, such as feed composition and pressure, as well as membrane properties, including selectivity. By analyzing these variables, we aim to optimize the performance and efficiency of the membrane system, facilitating the sustainable extraction of CO₂ from NG. The findings contribute to advancing the design and operation of membrane-based processes for CO₂ separation, paving the way for greener and more sustainable industrial practices. In addition, this study explores various configurations for optimizing the design of the membrane system, including single-stage with and without recycling as well as double-stage configurations. The investigation demonstrates that methane recovery can be enhanced through the recycling of the permeate stream and by implementing a double stage membrane system. These findings highlight the potential for improving the efficiency and performance of the membrane system, enabling higher methane recovery rates. By considering different configurations, this research contributes to the development of more effective and sustainable CO₂ extraction processes from natural gas.

Optimal control has emerged as an indispensable tool in the domain of mechanical robotic systems. The dynamic processes under consideration in this paper are characterized by differential equations with an unknown coefficient. The problem addressed is time-optimal and exhibits bilinear characteristics. To investigate this inverse optimal problem, the classical method has been employed alongside Pontryagin’s Maximum Principle (PMP). This article aims to provide an exact piecewise function for controlling trajectories, specifically accounting for viscous friction. The goal is to determine the reachability set and to find the minimal process time. Notably, no simplifying assumptions were made during the analytical transformations.

Discussing quantum theory foundations, von Neumann noted that the measurement process should not be regarded in terms of a temporal evolution. A reason for his claim is insurmountability of the gap between reversible and irreversible processes. The time operator formalism that goes beyond such a gap is adequate framework for elaboration of the measurement problem. It considers signals to be stochastic processes, whether they correspond to variables or distribution densities. Signal processing like that utilizes statistical properties to perform its tasks, which is the definition of statistical signal processing. A hierarchy of the measurement process is indicated by crossing between states and devices, which implies an evolution in the temporal domain. The concept has generalized to an open system by the use of duality in frame theory.

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.

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.

The dynamics of the main photosynthetic structures is studied by mathematical modeling methods in this article. Chlorophyll portion variability in phytoplankton and the formation of energy-intensive substances in the process of photosynthesis underlie the models. These cellular components are considered in terms of their participation in the growth of specific biomass. Computational experiments are presented that simulate various degrees of environmental friendliness. The corresponding functions are built in accordance with seasonal fluctuations throughout the year in the Far East region of Russia. The stability of model solutions in long-term dynamics is also investigated. The models were tested for biological adequacy and their effectiveness was compared. For the model selected as a result of the comparison, the optimal control problem has been formulated and solved. It is shown that in this way it is possible to reduce the space of the initial components of the model system.

How to optimally allocate COVID-19 vaccines and scarce public goods is a crucial and sensitive question to scholars, policy-makers, and practitioners. The ethical dimensions and principles of vaccine allocation between groups are widely agreed upon, whereas the ethical dimensions and principles of vaccine distribution between countries at the peak of the COVID-19 pandemic are highly controversial. This article aims to investigate how vaccines were globally allocated across countries and propose an optimal allocation mechanism for vaccines and scarce public goods. The results show that, to a certain extent, the global allocation of COVID-19 vaccines was fair and effective. Countries with more cases and deaths obtained more vaccines and vaccinations. Wealthier countries might receive more vaccinations but also suffer more severe consequences of COVID-19. Though COVAX could miss its initial vaccine delivery targets, the facility should be considered successful in its core goals and plays a critical role in controlling the pandemic. The study proposes a fair and effective mechanism of vaccine allocation that combines the roles of markets and interventions of international organizations and national governments with three degrees: emergency, priority, and market.

The challenge of achieving ultrafast switching of electric polarization in ferroelectric materials remains unsolved, as there is no experimental evidence of such switching to date. In this study, we have developed an enhanced model that describes switching within a two-dimensional space of generalized coordinates. Our findings indicate that stable switching in barium titanate cannot be achieved through a single linearly polarized pulse. When the intensity of the linearly polarized pulse reaches a certain threshold, the sample experiences depolarization, but not stable switching. Our study also reveals that phonon friction plays a minor role in the switching dynamics and provides an estimate of the optimal parameters of the perturbing pulse with the lowest intensity that results in depolarization of an initially depolarized sample.

: This study investigates the use of various thunderstorm indices in predicting severe thunderstorms events during the monsoon season in four different regions in India. The research evaluates the performance of the prediction model using a model skill score and utilizes the Weather Research and Forecasting (WRF) model with the double moment microphysics scheme to simulate model cases. It also compares fifteen thunderstorm indices derived from the ERA5 dataset to identify the most effective index for predicting severe thunderstorms events. The results of this study show that in-corporating thunderstorm indices with model skill scores improves severe thunderstorms fore-casting in the monsoon season in India. The result revealed that determining the optimal threshold for each index is crucial in achieving accurate predictions. The study also highlights the importance of considering multiple indices rather than relying on a single index to predict severe thunderstorms events. The advance indices such as Energy Helicity Index (EHI), Supercell Composite Parameter (SCP), mainly works well with extreme severe thunderstorms. The simplistic indices can predict the weak or severe thunderstorm easily. The use of multiple thunderstorm indices can also help mete-orologists to make more accurate predictions, which can further enhance public safety. In conclu-sion, this study demonstrates the potential of incorporating thunderstorm indices with model skill scores like HSS and TSS and combinations of different skill scores in severe thunderstorms fore-casting during the monsoon season in India. Future research can build upon the findings of this study to develop more accurate and reliable severe weather forecasting models.

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. The estimate is global in the sense that no a priori knowledge is required on the parameters to be determined. Different neural network algorithms are tested on a series of data sets. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results.

Trajectory Optimization (TO) is the sequence of processes that are considered in order to produce the best path that mends the overall performance or reduces the consumption of the resources where the restriction system remains maintained. In this survey, an inclusive review of the latest advancements in modeling and optimization of trajectory generation in robotic applications will be discussed broadly. In recent times, numerous studies have employed optimal control techniques involving direct and indirect methods in order to convert the authentic Trajectory Optimization problem into a constrained parameter optimization problem. Moreover, a huge variety of optimization algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), Sequential Quadratic Programming (SQP), and Particle Swarm Optimization (PSO) are used aiming to find the optimal solutions for trajectory planning. It is observable that, minimizing the jerk, energy consumption, and execution time among the most widely used design objectives, on the other hand, the robot’s joints configurations and the motor torques are the most used design variables. This paper aims to review the fundamental techniques and their coincident robotic applications in the field of trajectory optimization aiming to afford some steering for related researchers.

Studies have shown that in many practical applications, data interpolation by splines leads to better approximation and higher computational efficiency as compared to data interpolation by a single polynomial. Data interpolation by splines can be significantly improved if knots are allowed to be free rather than at a priori fixed locations such as data points. In practical applications, the smallest possible curvature is often desired. Therefore, optimal splines are determined by minimizing a derivative of continuously differentiable functions comprising the spline of the required order. The problem of obtaining an optimal spline is tantamount to minimizing derivatives of a nonlinear differentiable function over a Banach space on a compact set. While the problem of data interpolation by quadratic splines has been accomplished analytically, interpolation by splines of higher orders or in higher dimensions is challenging. In this paper, to overcome difficulties associated with the complexity of the interpolation problem, the interval over which data points are defined, is discretized and continuous derivatives are substituted by their discrete counterparts. It is shown that as the mesh of the discretization approaches zero, a resulting near-optimal spline approaches an optimal spline. Splines with the desired accuracy can be obtained by choosing an appropriate mesh of the discretization. By using cubic splines as an example, numerical results demonstrate that the linear programming (LP) formulation, resulting from the discretization of the interpolation problem, can be solved by linear solvers with high computational efficiency and resulting splines provide a good approximation to the optimal splines.

Model predictive control (MPC) is a multi-objective control technique that can handle 2 system constraints. However, the performance of an MPC controller highly relies on a proper 3 prioritization weight for each objective, which highlights the need for a precise weight tuning 4 technique. In this paper, we propose an analytical tuning technique by matching the MPC 5 controller performance with the performance of a linear quadratic regulator (LQR) controller. The 6 proposedmethodology derives the transformation of LQRweightingmatrixwith a fixedweighting 7 factor using discrete algebraic Riccati equation (DARE) and designs MPC controller using the 8 idea of discrete time linear quadratic tracking problem (LQT) in the presence of constraints. 9 The proposed methodology ensures the optimal performance between unconstrained MPC and 10 LQR controller and provides a sub-optimal solution while the constraints are active during 11 transient operations. The resultingMPC behaves as the discrete time LQR by selecting appropriate 12 weighting matrix in the MPC control problem and ensures the asymptotic stability of the system. 13 In this paper, the effectiveness of the proposed technique is investigated in the application of 14 a novel vehicle collision avoidance system which is designed in the form of linear inequality 15 constraints within MPC. The simulation results confirm the potency of the proposed MPC control 16 technique in performing a safe, feasible and collision free path while respecting the inputs, states 17 and collision avoidance constraints.

Noise reduction is the major issue in the loudspeaker for the application of the musical instruments and related areas. In this paper, a noise disturbance control of a loudspeaker with optimal and robust controllers has been done successfully. The noise of the loudspeaker has been analyzed by simply track a reference cone displacement with the actual cone displacement. Static output feedback and H infinity optimal loop shaping controllers have been used to compare the actual and reference cone displacements by using a sine wave and random cone displacement signals and a promising results have been analyzed.

With the rapid spread of carbon trading in the global economy, the interactions of prices between carbon (or clean/renewable energy) and traditional fossil energies such as coal and oil have raised growing attention, but little research have discussed their dynamic volatility spillover and time-varying correlation. The purpose of this study is to investigate these issues, for the weekly data of EUA futures, Biofuel and Brent oil prices from 25 October 2009 to 5 July 2020. We employ the VAR-GARCH model with the BEKK specification. Our results are summarized as follows. At first, we identified the sudden changes and the volatility persistence in the three markets, and also confirmed that the volatility of the markets has changed significantly over time. Secondly, we find that there are a weak volatility spillover effect among the three markets, while a strong spillover effect between the EUA and Brent oil markets. Lastly, in financial markets, the EUA can be used as a hedging portfolio for the Biofuel and Brent oil markets. These results can help investors to well compose their portfolios and manage their investment risks, and help potential pollutant emission sources to join in carbon market in a cost-effective way.

The energy efficient problem of parallel-connected pumps in heating, ventilation, and air-conditioning (HVAC) systems has received an increasing attention in recent years. While many pump optimization methods are proposed and show great performance, pumps are not always energy efficient and lack flexibility. In this paper, we propose a distributed control algorithm for parallel pumps in HVAC system in a peer-to-peer setting. Based on a spanning tree of the network of the intelligent nodes and a population of potential solutions randomly sampled, the algorithm makes optimal control decision for pumps to minimize energy consumption and meet the system demand. The theoretical analysis on convergence of the algorithm is established. Unlike traditional control structure, the whole system is fully distributed and each pump is controlled by an intelligent node that runs identical control code and coordinates with other nodes through direct data exchange. Simulation experiments on 6 parallel-connected pumps are provided for different working cases to demonstrate the effectiveness of the proposed algorithm and compare with other four methods. The results show that our method strictly satisfies the demand constraint and presents a good energy saving potential, the convergence guarantee, the flexibility. The maximum energy saving can be up to 29.92%. Besides, the hardware test clearly presents that our method can perform on low-cost Raspberry Pi3 and reduce system cost.

Background: Outbreak of the Covid-19 is now an ongoing global health emergency. At the end of December 2019, the first infection was reported in Wuhan and the world did not pay attention to this extremely contaminated disease and plucked to react rapidly. The World is in an vulnerable state in disease spreading, facing a great loss of lives and socio-economic aspects also. That is why we have proposed a potential mathematical model with data analysis to predict and control the outcome of this pandemic. Methods: The model presented the epidemic dynamics of multiple compartments. We collected available online data of Spain. In primary step, we estimated the parameters using either the data analysis or reference papers. Then we did the data fitting analysis in comparison with the outcome of our mathematical results. The results of the system depended not only the parameters also on social consciousness. Results: It is found that disease progression in this model is determined by the basic reproductive ratio, $R_0$, the actual epidemic of $R_0$ and effective $R(t)$ of each day. If $R_0>1$, the number of latently infected individuals grows exponentially; endemic solution is stable while infection rate decays if $R_0<1$. The optimal control theory stated that vaccination and treatment strategies are highly effective for reducing both susceptible and infected population and to increase the recover rate high. In Spain, after state of alarm (quarantine) on 14 March 2020, reported cases increasing for 13 days only and from the 14th day, daily reported cases started to decline albeit with small fluctuation. Our proposed model approximates that the disease in Spain could be fully under control by after July 2020. Conclusion: Outbreak will be in control of health care system, reduce the death rate and will ensure social-economic stability.

Demand responsive transport (DRT) is operated according to flexible routes, dispatch intervals, and dynamic demand, is attracting a lot of attention. The biggest characteristic of DRT service is that the vehicle routes and schedules are operated optimally based on real-time travel requests of using passengers without fixed operating schedules. Today, the smart-city era has arrived, particularly because of progress in the wireless communications technology and technology related to location information service and real-time passenger demands and requests, and services that change the vehicles’ operating schedules in real-time according to dynamic demand have attracted more attention. In this study, we analyze the effects of the DRT system to solve the first mile/last mile problem based on a proposed DRT routing algorithm considering real-time travel behavior. The algorithm is modified from the dynamic vehicle routing problem (DVRP), in which a DRT-based routing algorithm tends to minimize users’ cost and providers’ operation cost. So far, the DVRP has only been able to serve a single request per vehicle at a time. However, this needs to be extended for the purpose of DRT, wherein several passengers board a vehicle at the same time. The routing algorithm can serve multiple requests at a time and schedule picks ups, drop offs, and rides according to the requests and as calculated by the dispatch algorithm. The basic principle of routing is as follows. The DRT vehicle moves on an attractive path and picks up a passenger if boarding is requested, but it does not simply hang around as a DVRP would. In this step, if another DRT vehicle is present near another passenger, the vehicle that would minimize that passenger’s total travel time picks up the passenger. The optimal routing algorithm developed in this study is applied to the activity-based model; that is, a microscopic traffic demand estimation method is implemented through an activity-based model by using an open-source, activity-based model package called Multi-Agent Transport Simulation (MATSim). MATSim is used for the simulation, because it combines a multi-modal traffic flow simulation with a scoring model for agents, and it provides co-evolutionary algorithms that can alter agents’ daily routines. This process is applied to a type of mode choice and route choice repeatedly over several iterations until some form of user equilibrium has been reached. This study analyzed the feasibility of implementing the DRT service by analyzing the benefits for the users and cost of the operator from the effects of increasing public transportation use and providing personalized mobility service based on DRT implementation by the introduction of DRT will be analyzed according to the scale of DRT supply. Through the simulation, the DRT is expected to provide convenient, fast, and cost-effective mobility services to customers; provide an optimal vehicle scale to providers; and, ultimately, achieve a safe and efficient transportation system.

An SIRS (Susceptible–Infected–Removed-Susceptible) mathematical model for the transmission dynamics of the Transfusion–Transmitted Malaria (TTM) model with optimal control pair u₁(t) and u₂(t) was developed and studied in this research work. The model Transfusion–Transmitted Malaria disease–free equilibrium and endemic equilibriums points were determined. The model exhibited two equilibriums; disease-free and endemic equilibrium. It is shown that the disease–free equilibrium was locally asymptotically stable if the associated basic reproduction numbers R₀ is less than unity while the disease persists if R₀ is greater than unity. The global stability of the Transfusion–Transmitted Malaria model at the disease-free equilibrium was established using the comparison method. The optimality system was derived and an optimal control model of blood screening and drug treatment for the Transfusion–Transmitted Malaria model was investigated. Conditions for the optimal control were considered using Pontryagin’s Maximum Principle and solved numerically using the Forward and Backward Finite Difference Method (FBDM). Numerical results obtained are in perfect agreement with our analytical results.

Human African Trypanosomiasis (HAT) commonly known as sleeping sickness, is a neglected tropical vector borne disease caused by trypanosome protozoa. It is transmitted by bites of infected tsetse fly. In this paper we first present the vector-host model which describes the general transmission dynamics of HAT. In the tsetse fly population, the HAT is modelled by three compartments while in the human population, the HAT is modelled by four compartments. The next generation matrix approach is used to derive the basic reproduction number, R₀, and also it is proved that if R₀ ≤ 1 the disease free equilibrium is globally asymptotically stable, which means the disease dies out. The disease persist in the population if the value of R₀ > 1. Furthermore, the optimal control model is determined by using the Pontryagin’s maximum principle with control measures such as education, treatment and insecticides used to optimize the objective function. The model simulations confirm that the use of the three control measures are very efficient and effective to eliminate HAT in Africa.

The paper deals with the modelization and optimization of an integrated multi-component energy system. On-off operation and presence-absence of components must be described by means of binary decision variables, besides equality and inequality constraints; furthermore, the synthesis and the operation of the energy system should be optimized at the same time. In this paper a hierarchical optimization strategy is used, adopting a genetic algorithm in the higher optimization level, to choose the main binary decision variables, whilst a MILP algorithm is used in the lower level, to choose the optimal operation of the system and to supply the merit function to the genetic algorithm. The method is then applied to a distributed generation system, which has to be designed for a set of users located in the center of a small town in the North-East of Italy. The results show the advantage of distributed cogeneration, when the optimal synthesis and operation of the whole system are adopted, and significant reduction in the computing time by using the proposed two-level optimization procedure.

This article, we study the sufficient conditions for the controllability of second-order impulsive partial neutral evolution differential systems with infinite delay in Banach spaces by using the theory of cosine families of bounded linear operators and fixed point theorem.

Multiobjective optimization plays an increasingly important role in modern applications, where several criteria are often of equal importance. The task in multiobjective optimization and multiobjective optimal control is therefore to compute the set of optimal compromises (the Pareto set) between the conflicting objectives. The advances in algorithms and the increasing interest in Pareto optimal solutions have led to a wide range of new applications related to optimal and feedback control which results in new challenges such as expensive models or real-time applicability. Since the Pareto set generally consists of an infinite number of solutions, the computational effort can quickly become challenging which is particularly problematic when the objectives are costly to evaluate or when a solution has to be presented very quickly. This article gives an overview over recent developments in accelerating multiobjective optimal control for complex problems where either PDE constraints are present or where a feedback behavior has to be achieved. In the first case, surrogate models yield significant speed-ups. Besides classical meta-modeling techniques for multiobjective optimization, a promising alternative for control problems is to introduce a surrogate model for the system dynamics. In the case of real-time requirements, various promising model predictive control approaches have been proposed, using either fast online solvers or offline-online decomposition. We also briefly comment on dimension reduction in many-objective optimization problems as another technique for reducing the numerical effort.

Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.

Milroy's disease (MD), also known as hereditary lymphedema type I, is a rare autosomal dominantly inherited primary lymphedema. It accounts for approximately twenty percent of all primary lymphedemas. MD typically presents clinically with bilateral lower extremity lymphedema. Our case report is about a rare case of MD presenting with unilateral lymphedema in both upper and lower extremities in a patient admitted to our clinic. A 24-year-old woman who had been under observation for lymphedema since she was 8 years old was diagnosed with MD by physical examination, venous Doppler ultrasound, whole body lymphoscintigraphy, and molecular genetic testing in our clinic, and partial improvement was achieved with Complete Decongestive Therapy, the gold standard treatment for lymphedema. Genetic counseling services may be especially useful for the patient and family. Although MD is rarely seen in the literature, many more studies are needed to identify carrier variants in the community.

Obesity and overweight are associated with many metabolic diseases, such as hypertension, diabetes, and dyslipidemia, which are closely related to a sedentary lifestyle and lack of exercise. Aerobic exercise effectively increases the high-density lipoproteins-cholesterol (HDL-C) levels and decreases the triglyceride (TG) levels. The consumption of Cuban policosanol (Raydel®) is also effective in enhancing the HDL-C quantity and HDL functionality to treat dyslipidemia and hypertension. On the other hand, no study has examined the effects of a combination of high-intensity exercise and policosanol consumption in obese subjects to improve metabolic disorders. In the current study, 17 obese subjects (average BMI 30.0±1.1 kg/m2, eight male and nine female) were recruited to participate in a program combining exercise and policosanol (20 mg) consumption for 12 weeks. After completion, their BMI, waist circumference, total fat mass, systolic blood pressure (SBP), and diastolic blood pressure (DBP) decreased by approximately 15% (p=0.022), 12.7% (p=0.008), 33% (p=0.006), 11% (p<0.046), and 13% (p=0.007), respectively. In the serum lipid profile, at week 12, they showed a remarkable decrease in the total cholesterol (TC) and triglyceride (TG) levels, up to 17% (p<0.019) and 54% (p<0.002) from the baseline, respectively. Although the serum HDL-C was increased by approximately +12% from the baseline, the percentage of HDL-C in TC, HDL-C/TC (%), was increased by up to +32% (p=0.007) at week 12. The serum coenzyme Q10 (CoQ10) level was increased 1.2-fold in all participants at week 12 from the baseline. In particular, the male participants showed a 1.4-fold increase (p=0.027) from the baseline. The larger increase in serum CoQ10 was correlated with the larger increase in the serum HDL-C during 12 weeks. The hepatic function parameters were improved; the serum -glutamyl transferase decreased at week 12 by up to 55% (p<0.007), while the aspartate aminotransferase and alanine transaminase levels decreased within the normal range. In the lipoprotein level, the extent of oxidation and glycation were reduced significantly in VLDL and LDL, with a remarkable decrease in the TG content in particles. The antioxidant abilities of HDL2 and HDL3, such as paraoxonase (PON) and ferric ion reduction ability (FRA), were enhanced significantly by up to 1.8-fold (p<0.001) and 1.6-fold (p<0.001) at week 12. The particle size and number of HDL2 were increased up to +10% during the 12 weeks with a remarkable decrease in the TG content, glycation extent, oxidation up to 32% (p=0.032), 18% (p=0.043), and 11% (p=0.023), respectively. The particle number and diameter of HDL3 were increased by up to +9% with a remarkable increase in the PON activity, FRA activity, and TC content of +82% (p<0.001), +56% (p<0.001), and +32% (p=0.009), respectively. Expression of apolipoproteinA-I in HDL2 and HDL3 were significantly elevated more in both gender around 30~48% with more distinct band intensity and less glycation at week 12. These improvements in HDL quality and functionality were linked to the higher survivability of adult zebrafish and their embryos. Under the co-presence of carboxymethyllysine (CML), a microinjection of HDL2 to zebrafish embryo from week 0 resulted in approximately 47% survivability with developmental defects and attenuated speed. On the other hand, the HDL2 microinjection from week 12 resulted in remarkably higher survivability (~ 70%). In conclusion, 12 weeks of Cuban policosanol (Raydel®, 20 mg) consumption with high-intensity exercise showed significant improvement in blood pressure, body fat mass, blood lipid profile without liver damage, CoQ10 metabolism, and renal impairment. At week 12, all participants showed a remarkable decrease in oxidation and glycation extent in the VLDL and LDL with a decrease in the TC and TG content. Significant enhancement of the qualities and functionalities in HDL2 and HDL3 by the policosanol consumption were also detected: increase in apoA-I content, TC content, particle size, and particle numbers along with antioxidant abilities, such as PON and FRA.

The intensive care unit is characterized by the critical care of the infants and children who access it, as well as the high complexity of care. This implies and requires optimal integration among the various professionals working there and their ability to work as a team. The purpose of the study was to describe how nurses perceive clinical risk and how they relate to it and to identify adverse events and related risk factors. Nine nurses, two moderators and one external observer partici-pated in the focus group. In the qualitative analysis, 9 themes describing the perception of clinical risk in PICU were identified, including teamwork, specific training, time management, team communication, management, individual errors, structural criticality, patient fac-tors/characteristics, and standardization. Safety culture can be fostered by hospital management to involve PICU nurses in promoting patient safety, which could improve breaking down barriers that prevent nurses from fulfilling their roles.

Immune surveillance by natural killer (NK) cells and their recruitment to sites of inflammation renders them susceptible to viral infection, potentially modulating their effector function. Here, we analyzed innate RNA receptor signaling in NK cells downstream of direct Influenza A virus (IAV) infection and its impact on NK cell effector function. Infection of NK cells with IAV resulted in the activation of TBK1, NF-κB and subsequent type-I IFN secretion. CRISPR- generated knockouts in primary human NK cells revealed that this effect depended on the antiviral cytosolic RNA receptor RIG-I. Transfection of NK cells with synthetic 3p-dsRNA, a strong RIG-I agonist that mimics viral RNA, resulted in a similar phenotype and rendered NK cells resistant to subsequent IAV infection. Strikingly, both IAV infection and 3p-dsRNA transfection enhanced degranulation and cytokine production by NK cells when exposed to target cells. Thus, RIG-I activation in NK cells both supports their cell intrinsic viral defense and enhances their cytotoxic effector function against target cells.

Apoptosis under severe hypoxia is induced through p53 phosphorylation and HIF-1α-dependent p53 accumulation via ATR activation by DNA damage response (DDR) activation through replication stress. We previously demonstrated that the topoisomerase I catalytic inhibitor, 3EZ, 20Ac-ingenol, specifically induced apoptosis in Jeko-1 and Panc-1 cells, both of which are cell lines that show cyclin D1 overexpression. After progression to the S phase facilitated by nuclear cyclin D1, in the presence of 3EZ, 20Ac-ingenol, an intra S phase checkpoint was induced in ATR activation as part of replication stress-induced DDR. In this study, we examined whether 3EE, 20Ac-ingenol induces a higher degree of p53 phosphorylation and additional HIF-1α and p53 accumulation in response to replication stress-induced DDR activation under the hypoxic condition than under the normoxic condition by controlling ATR activation. 3EE, 20Ac-ingenol induced p53 activation and HIF-1α-dependent p53 accumulation through cooperative ATR activation via induced DDR with the hypoxia in Panc-1 cells. The Jeko-1 cells showed slight HIF-1α accumulation under hypoxia, but this was not decreased by 3EE, 20Ac-ingenol, so that the cells remained resistant to hypoxia. 3EE, 20Ac-ingenol induces an intricate interplay between p53 and HIF-1α accumulation via ATR activations that results in high p53 accumulation, which advanced transient expression and early disappearance of HIF-1?. The strong p53 accumulation and consequent PTEN activation also decreased HIF-1α accumulation and PD-L1 expression, which resulted in intense apoptosis.

Hydraulic fracturing for oil-gas and geothermal reservoir stimulation is closely related to the generation and propagation of Mode I crack. Nonlinear deformation due to rock heterogeneity occurs at such crack tip, which causes the fracture process zone (FPZ) to form before the crack propagates unsteadily. However, the relationship between the FPZ characteristics and rock heterogeneity still remain elusive. We used three rock types common in reservoir for experimental investigation, and each of them includes two subtypes with different heterogeneity due to grain size or microstructural characteristics. Drawing on the experiment results, we calculated the FPZ size in each cracked chevron notched Brazilian disk, and we reproduced the formation process of the FPZ in marble by discrete element method. We showed that strong heterogeneity is favorable to large FPZ size, can enhance the ability of crack generation and complicate crack morphology. Coupling the Weibull distribution with fracture mechanics, the dependence of the FPZ size on heterogeneity degree can be theoretically explained, which suggests that inherent heterogeneity of rocks set physical foundation for formation of FPZ. These findings can improve our recognition to formation mechanism of the Mode I crack and provide useful guidelines for evaluating reservoir fracability.

Electronic structure calculations have been carried out to examine the effect of protonation and water molecules on the heme group of peroxidases in different redox (ferric, ferrous, compounds I and II) and spin states. Shared geometries, spectroscopic properties at Soret region, and thermodynamics of peroxidases are discussed. B3LYP and M06-2X density functionals with different basis sets were employed on a common molecular model of the active site (Fe-centred porphine and proximal imidazole). Computed Gibbs free energies indicate that the corresponding aquo complexes are not thermodynamically stable, supporting the five-coordinate Fe(III) centre in native ferric peroxidases, with a water molecule located at a non-bonding distance. Protonation of the ferryl oxygen of compound II is discussed in terms of thermodynamics, Fe–O bond distances, and redox properties. It is demonstrated that this protonation is necessary to account for the experimental data and computed Gibbs free energies that reveal pKa values of compound II about 8.5 – 9.0. Computation suggests that the origin of the general oxidative properties of peroxidase species, as well as their reactivity towards water and protons and Soret spectral properties, mostly resides on the iron porphyrin and its proximal ligand histidine.

Mesenchymal stem cells (MSCs) are involved in the process of extracellular matrix (ECM) remodeling where collagens play a pivotal role. We recently demonstrated that the remodeling of adsorbed collagen type I might be disordered upon oxidation following its fate in the presence of human adipose-derived MSC (ADMSCs). With the present study, we intended to learn more about the effect of polyphenolic antioxidant Epigallocatechin gallate (EGCG) attempting to mimic the conditions of oxidative stress in vivo and its putative prevention by antioxidants. Collagen Type I was isolated from mouse tail tendon (MTC) and labeled with FITC before oxidizing according to Fe2+/H2O2 protocol. FITC-collagen remodeling by ADMSC was assessed morphologically before and after EGCG pretreatment and confirmed via detailed morphometry analysis measuring the anisotropy index (AI) and fluorescence intensity (FI) in selected regions of interest (ROI), namely: outside the cells; over the cells and central (nuclear perinuclear) region, whereas the pericellular proteolytic activity was measured by de-quenching of fluorescent collagen probes (FRET effect). Here we provide morphological evidence that MTC undergoes significant reorganization by the adhering ADMSC along with the substantial activation of pericellular proteolysis, and further confirm that both processes are suppressed upon collagen oxidation. An important observation was that this abrogated remodeling cannot be prevented by the EGCG pretreatment. Conversely, the detailed morphometry analysis showed that oxidized FITC-collagen rather tends to accumulate beneath the cells and around the cell’s nuclei suggesting the activation of alternative routes for its removal, such as internalization and/or transcytosis. Morphometry analysis also revealed that both processes are supported by EGCG pretreatment.

We obtain exact solutions to the field equations for 5 dimensional LRS Bianchi type-I spacetime in $f(R,T)$ theory of gravity where specifically the following three cases are considered: (i) $f(R,T)=\mu(R+T)$, (ii) $f(R,T)=R \mu + R T \mu^2$ and (iii) $f(R,T)=R+\mu R^2+\mu T$ where $R$ and $T$ respectively the Ricci scalar and trace of the energy-momentum tensor. It is found that the equation of state (EOS) parameter $w$ is governed by the parameter $\mu$ involved in the $f(R,T)$ expressions. We fine-tune the parameter $\mu$ to obtain effect of phantom energy in the model, however we also restrict this parameter to obtain a stable model of the universe. It is noted that the model isotropizes at finite cosmic time.

Mitochondria play key roles in cellular energy metabolism in eukaryotes. Mitochondria of most organisms contain their own genome and specific transcription and translation machineries. The expression of angiosperm mtDNA involves extensive RNA-processing steps, such as RNA trimming, editing, and the splicing of numerous group II-type introns. Pentatricopeptide repeat (PPR) proteins are key players of plant organelle gene expression and RNA metabolism. In the present analysis, we reveal the function of the MITOCHONDRIAL SPLICING FACTOR 2 gene (MISF2, AT3G22670) and show that it encodes a mitochondria-localized PPR protein that is crucial for early embryo-development in Arabidopsis. Molecular characterization of embryo-rescued misf2 plantlets indicates that the splicing of nad2 intron 1 and thus respiratory complex I biogenesis are strongly compromised. Moreover, the molecular function seems conserved between MISF2 protein in Arabidopsis and its orthologous gene (EMP10) in maize, suggesting that the ancestor of MISF2/EMP10 was recruited to function in nad2 processing before the monocot-dicot divergence, ~200 million years ago. These data provide new insights into the function of nuclear-encoded factors in mitochondrial gene expression and respiratory chain biogenesis during plant embryo development.

In the last two decades, variably doped strontium barium niobate (SBN) has attracted a lot of scientific interest mainly due to its specific non-linear optical response. Comparably, the parental compound, i.e., undoped SBN, appears to be less studied so far. Here, two different cuts of single-crystalline nominally pure strontium barium niobate in the composition Sr0.61Ba0.39Nb2O6 (SBN61) are comprehensively studied and analyzed with regard to their photoconductive responses. We present conductivity measurements under systematically varied illumination conditions along either the polar z-axis or perpendicular to it (x-cut). Apart from a pronounced photoconductivity (PC) already under daylight and a large effect upon super-bandgap illumination in general, we observe (i) distinct spectral features when sweeping the excitation wavelength over the sub-bandgap region as then discussed in the context of deep and shallow trap states, (ii) extremely slow long-term relaxation for both light-on and light-off transients in the range of hours and days, (iii) a critical dependence of the photoresponse on the pre-illumination history of the sample, and (iv) a current-voltage hysteresis depending on both the illumination and the electrical-measurement conditions in a complex manner.

A good management of diabetes requires at the same time self-regulation behaviour and a balanced involvement of family components. This study’s aims were: understanding fear of injections and perceptions of family conflicts in preadolescents and adolescents with type 1 diabetes mellitus and their mothers, comparing their perceptions, and identifying the risk factors impacting patients’ quality of life. Participants were one hundred and two patients (Mean age = 14.63, SD = 2.43; age range = 10-19 years; Females = 52) and their mothers (Mean age = 46.94, SD = 6.2, age range = 27-63 years), who filled in self and proxy-report questionnaires. Twenty % of patients and 14.7% of their mothers reported clinical score for fear of self-injection and blood testing. Mothers reported higher fear of injecting and family conflicts compared with the patients. Age, fear of injecting and family conflicts impacted significantly on patients’ quality of life perceptions. Clinical consideration and recommendations are given basing on the empirical results.

Japanese encephalitis (JE) is a vaccine preventable disease caused by the Japanese encephalitis virus (JEV), which is primarily prevalent in Asia. JEV is a Flavivirus, classified into a single serotype with five genetically distinct genotypes (I, II, III, IV, and V). JEV genotype III (GIII) had been the most dominant strain and caused numerous out breaks in the JEV endemic countries until 1990. However, recent data shows the emergence of genotype I (GI) as a dominant genotype and it is gradually displacing GIII. The exact mechanism of this genotype displacement is still unclear. The virus can replicate in mosquito vectors and vertebrate hosts to maintain its zoonotic life cycle; pigs and aquatic wading birds act as an amplifying/reservoir hosts, and humans and equines are the dead end hosts. The important role of pigs as an amplifying host for JEV is well known. However, the influence of other domestic animals especially birds that live in high abundance and close proximity to human is not well studied. Here, we strive to briefly highlight the role of birds in JEV zoonotic transmission, discovery of birds as a natural reservoirs and amplifying host for JEV, species of birds susceptible to JEV infection, and the proposed effect of JEV on poultry industry in future perspective which have been neglected for a long times. We also discussed the recent in vitro and in vivo studies which show that the newly emerged GI viruses replicated more efficiently in bird-derived cells and ducklings/chicks than GIII, and an important role of birds in the JEV genotype shift from GIII to GI.

Indoor dusts are collectively formed from anthropogenic and atmospheric activities. Particle matter 10 (PM10) is inhalable and causes significant inflammation by interaction with the pulmonary epithelial barrier. The mediators involved in bronchial epithelial cells response to dust are remined unknown. The air-liquid interface of our lung on chip model was exposed to indoor dust collected from highly polluted houses in Delhi, India. The media were collected after 4 days and cytokine levels were measured. We found that the concentration of IFN, IFNγ, Interleukin-6 (IL-6), IL1b, TNFa, and Granulocyte monocyte colony stimulating factor (GM-CSF) were significantly increased after exposure to indoor dust. IFN type I pathways were a major response from dust exposure. Further investigation is needed to determine the mechanism of action and targets of dust in bronchial epithelial cells.

The cardioprotective effects of volatile anesthetics versus total intravenous anesthesia (TIVA) are controversial, especially in patients undergoing non-cardiac surgery. Using current generation high-sensitivity cardiac troponin (hs-cTn), we aimed to evaluate the effect of anesthetics on the occurrence of myocardial injury after non-cardiac surgery (MINS). From February 2010 to December 2016, 3555 patients without preoperative hs-cTn elevation underwent non-cardiac surgery under general anesthesia. Patients were grouped according to anesthetic agent; 659 patients were classified into a propofol-remifentanil total intravenous anesthesia (TIVA) group, and 2896 patients were classified into into a volatile group. To balance the use of remifentanil between groups, a balanced group (n=1622) was generated with patients who received remifentanil infusion in the volatile group, and two separate comparisons were performed (TIVA vs. volatile and TIVA vs. balanced). The primary outcome was occurrence of MINS, defined as rise of hs-cTn I ≥ 0.04 ng/mL within postoperative 48 hours. The secondary outcomes were 30-day mortality, postoperative acute kidney injury (AKI), and adverse events during hospital stay (mortality, type I myocardial infarction (MI), and new-onset arrhythmia). In propensity-matched analyses, the occurrence of MINS was lower in the TIVA group compared to the volatile group (OR 0.642; 95% CI 0.450-0.914; p = 0.014). However, after balancing the use of remifentanil, there was no difference between groups in the risk of MINS (OR 0.832; 95% CI 0.554-1.251; p-value = 0.377). There were no significant associations between the two groups in type 1 MI, new-onset atrial fibrillation, in-hospital and 30-day mortality before and after balancing the use of remifentanil. However, the incidence of postoperative AKI was lower in the TIVA group (OR 0.362; 95% CI 0.194-0.675; p-value = 0.001). After balancing the use of remifentanil, volatile anesthesia and TIVA showed comparable effects on MINS in patients undergoing non-cardiac surgery without preoperative myocardial injury. Further studies are needed on the benefit of remifentanil infusion.

Nucleoli are emerging as key sensors of cellular stress and regulators of the downstream consequences on proliferation, metabolism, senescence and apoptosis. NF-kB signalling is activated in response to a similar plethora of stresses, which leads to modulation of cell growth and death programs. Although these pathways are distinct, it is increasingly apparent that they converge at multiple levels. Exposure of cells to certain insults causes a specific type of nucleolar stress that is characterised by degradation of the PolI complex component, TIF-IA, and increased nucleolar size. Recent studies have shown that this atypical nucleolar stress lies upstream of cytosolic IkB degradation and NF-kB nuclear translocation. Under these stress conditions, the RelA component of NF-kB accumulates within functionally altered nucleoli to trigger a nucleophosmin dependent, apoptotic pathway. In this review, we will discuss these points of crosstalk and their relevance to the anti-tumour mechanism of aspirin and small molecule CDK4 inhibitors. We will also briefly discuss how NF-kB-nucleoli crosstalk may be more broadly relevant to the regulation of cellular homeostasis and how it may be exploited for therapeutic purpose.

Looking at different operating climatic conditions, the electrical behavior predicting photovoltaic modules gets very important. For the estimation of output power from photovoltaic (PV) plants this is a very essential and basic aspect. In this paper, the relationship between the I-V curve and the irradiation spectrum is discussed by combining the single diode model. An explicit elementary analytical model with two defined shape parameters is discussed and improved with three approximations and second order Taylor expansion. Then, the explicit elementary analytical model is investigated under varying conditions leveraging the four parameters I_ph, I₀, R_s and R_sh from the single diode model. The relationship between the physical parameters and the condition parameters are discussed and applied to extract the shape parameters at different scenarios. Considering the aging effect, the process of calculation to predict the I-V curve under different splitting spectra is simplified as follow: (1) two shape parameters are gotten from the I-V data at measurement reference conditions (MRC); (2) the short circuit current, open circuit voltage and shape parameters under any splitting spectrum can be calculated based on the relationship provided in article; (3) the performance of PV panel can be predicted with parameters. The validation of this model was experimentally proven leveraging monocrystalline silicon photovoltaic module with different splitting films. Results showed that the model accurately predicts the I-V characteristics for the examined PV modules at different irradiance spectra and cell temperatures. Moreover, the presented model performs superior compared to other investigated models when looking at accuracy and simplicity.

The activity of prioritizing software requirements should be done as efficiently as possible. Selecting the most stable requirements for the most important customers for the development company can be a positive factor when we consider that the available resource does not always encompass the implementation of all requirements. Quantitative methods for reaching software prioritization in releases are many in the field of Search-Based Software Engineering (SBSE). However, we show that it is possible to use qualitative Verbal Decision Analysis (VDA) methods to solve this same type of problem. Moreover, we will use the ZAPROS III-i methods to prioritize requirements considering the opinion of the decision-maker, who will participate in this process. Finally, the results obtained in the VDA structured methods were quite satisfactory when compared to the methods using SBSE. A comparison of results between quantitative and qualitative methods will be made and discussed later.

This work presents an innovative application of optimal control theory to the strategic scheduling of battery storage in the day-ahead electricity market, with a focus on enhancing profitability while factoring in battery degradation. The study incorporates in the optimisation framework the cost of battery capacity degradation, the effects of capacity degradation and internal resistance degradation into dynamics. We employ a continuous-time representation of the dynamics, in contrast with many other studies that use a discrete-time approximation with rather coarse intervals. We adopt an equivalent circuit model coupled with empirical degradation parameters to simulate a battery cell’s behaviour and degradation mechanisms with good support from experimental data. Utilising direct collocation methods with mesh refinement allows for precise numerical solutions to the complex, nonlinear dynamics involved. Through a detailed case study of Belgium’s day-ahead electricity market, we determine the optimal charging and discharging schedules under varying objectives: maximizing net revenues, profits considering capacity degradation, and profits considering both capacity degradation and internal resistance increase due to degradation. The results demonstrate the viability of our approach and underscore the significance of integrating degradation costs into the market strategy for battery operators, alongside its effects on the battery’s dynamic behaviour. Our methodology extends previous work by offering a more comprehensive model that empirically captures the intricacies of battery degradation, including a fine and adaptive time domain representation, focusing on the day-ahead market, and utilising accurate direct methods for optimal control. The paper concludes with insights into the potential of optimal control applications in energy markets and suggestions for future research avenues.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

This study entailed the design and analysis of a 400 m-class underwater glider operated by a bladder-type buoyancy engine. The underwater glider was designed for high-speed movement with a maximum velocity of 2 knots. The shape of the hull was designed to reduce water resistance using the Myring hull profile equation. The reliability was verified by performing simulations using resistance coefficients. The relationship between the control value of the ballast discharged from the buoyancy engine and the glider's speed according to the path angle was analyzed. Further, the relationship between the optimal glide angle and the design control value of the ballast was derived, and the optimal glider speed was estimated accordingly. Based on the analysis results, a bladder-type buoyancy engine was developed, and the maximum speed of the tested underwater glider was measured via sea trials.

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

The present work concerns with presenting an explicit formula for new shifted wavelet (NSW) functions. Wavelet functions have many applications and advantages in both applied and theoretical fields. They are formulated with different orthogonal polynomials to construct new techniques for treating some problems in sciences, and engineering. A new important differentiation property of NSW in terms of NSW themselves is obtained and proved in this paper. Then it is utilized together with the state parameterization technique to find solution of optimal control problem (OCP) approximately. The suggested method converts the OCP into a quadratic programming problem, which can be easily determined on computer. As a result, the approximate solution closes with the exact solution even with a small number of NSW utilized in estimation. The error bound estimation for the proposed method is also discussed. Some test numerical examples are solved to demonstrate the applicability of the suggested method. For comparison, the exact known solutions against the obtained approximate results are listed in Tables.

Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in Network Intrusion Detection System (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which can’t identify unknown attacks. Deep learning can help NIDS to detect novel threats since it has a strong generalization ability. The deep neural network’s architecture has a significant impact on the model’s results. We propose a genetic algorithm based model to find the optimal number of hidden layers and the number of neurons in each layer of the deep neural network (DNN) architecture for the network intrusion detection binary classification problem. Experimental results demonstrate that the proposed DNN architecture shows better performance than classical machine learning algorithms at a lower computational cost.

The main goal of this paper is to show that Bayesian optimization could be regarded as a general framework for the data driven modelling and solution of problems arising in water distribution systems. Hydraulic simulation, both scenario based, and Monte Carlo is a key tool in modelling in water distribution systems. The related optimization problems fall in a simulation/optimization framework in which objectives and constraints are often black-box. Bayesian Optimization (BO) is characterized by a surrogate model, usually a Gaussian process, but also a random forest and increasingly neural networks and an acquisition function which drives the search for new evaluation points. These modelling options make BO nonparametric, robust, flexible and sample efficient particularly suitable for simulation/optimization problems. A defining characteristic of BO is its versatility and flexibility, given for instance by different probabilistic models, in particular different kernels, different acquisition functions. These characteristics of the Bayesian optimization approach are exemplified by the two problems: cost/energy optimization in pump scheduling and optimal sensor placement for early detection on contaminant intrusion. Different surrogate models have been used both in explicit and implicit control schemes. Showing that BO can drive the process of learning control rules directly from operational data. BO can also be extended to multi-objective optimization. Two algorithms have been proposed for multi-objective detection problem using two different acquisition functions.

The incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. To this end, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.

Recently, the mapping industry has been focusing on the possibility of large-scale mapping from unmanned aerial vehicles (UAVs) owing to advantages such as easy operation and cost reduction. In order to produce large-scale maps from UAV images, it is important to obtain precise orientation parameters. For this, various techniques have been developed and are included in most of the commercial UAV image processing software. For mapping, it is equally important to select images that can cover a region of interest (ROI) with the fewest possible images. Otherwise, to map the ROI, one may have to handle too many images, and commercial software does not provide information needed to select images, nor does it explicitly explain how to select images for mapping. For these reasons, stereo mapping of UAV images in particular is time consuming and costly. In order to solve these problems, this study proposes a method to select images intelligently. We can select a minimum number of image pairs to cover the ROI with the fewest possible images. We can also select optimal image pairs to cover the ROI with the most accurate stereo pairs. We group images by strips, and generate the initial image pairs. We then apply an intelligent scheme to iteratively select optimal image pairs from the start to the end of an image strip. According to the results of the experiment, the number of images selected is greatly reduced by applying the proposed optimal image–composition algorithm. The selected image pairs produce a dense 3D point cloud over the ROI without any holes. For stereoscopic plotting, the selected image pairs were map the ROI successfully on a digital photogrammetric workstation (DPW), and a digital map covering the ROI is generated. The proposed method should contribute to time and cost reductions in UAV mapping.

The bending performance of a basalt-polypropylene fiber-reinforced concrete (HBPFRC) was characterized by testing 24 400×100×100 mm3 prismatic specimens in a four-point bending test JSCE-SF4 configuration. The type and content of both fibers was varied in order to guarantee different target levels of post-cracking flexural performance. The results evidenced that mono-micro basalt fiber reinforced concrete (BFRC) allows the increase of the flexural strength (pre-cracking stage), while macro polypropylene fiber reinforced concrete can effectively improve both bearing capacity and ductility of the composite for a wide crack width range. Compared with the plain concrete specimens, flexural toughness and equivalent flexural strength of macro polypropylene fiber-reinforced concrete (PPFRC) and the hybrid fiber-reinforced concrete (HFRC) increased by 3.7~7.1 times and 10%~42.5%, respectively. From both technical and economic points of view, the optimal mass ratio of basalt fiber to polypropylene fiber resulted to be 1:2, with a total content of 6 kg/m3. This HFRC is seen as a suitable material to be used in sewerage pipes where cracking control (crack formation and crack width control) is of paramount importance to guarantee the durability and functionality of the pipeline as well as the ductility of the system in case of local failures.

Hasselmann and coauthors proposed the discrete interaction approximation (DIA) as the best tool replacing the nonlinear evolution term in a numerical wind-wave model. Much later, Polnikov and Farina radically improved the original DIA by means of location all the interacting four wave vectors, used in the DIA configuration, exactly at the nodes of the numerical frequency-angular grid. This provides nearly two-times enhancing the speed of numerical calculation for the nonlinear evolution term in a wind-wave model. For this reason, the proposed version of the DIA was called as the fast DIA (FDIA). In this paper we demonstrate all details of the FDIA concept for several frequency-angular numerical grids of high resolution, with the aim of active implementation the FDIA in modern versions of world-wide used wind-wave models.

In this study, the thermal behavior of a PCM-based heat sink in the presence of horizontal fins was numerically investigated. These types of heat sink can be effective in electronic cooling applications. Independent variables included aspect ratio (AR), number of horizontal fins (n) and their length (LR), while the objective function was defined to maximize the safe operation time (tmax). The incorporation of horizontal fins has a positive effect (thermal conductivity enhancement) as well as a negative effect (latent heat reduction). Based on the results, the optimal number of horizontal fins was five. As the number of fins rises up to five, the incremental effect of thermal conductivity improvement (positive effect) was superior to the decremental effect of the latent heat reduction (negative effect), hence the objective function (tmax) improved. However, with a further increase in the number of fins upon five, the negative effect prevailed over the positive effect and therefore the safe operation time diminished.

The semi-enclosed estuary is very susceptible to changes in the physical and environmental characteristics of the inflow from the land and the coastal sea weather and so the continuous and comprehensive monitoring is necessary for managing the estuary. Nevertheless, the standard procedure or schematic framework has not been proposed appropriately to determine how many instruments are necessary and where they need to be deployed to detect critical changes. Therefore, the present work proposes a systematical strategy for the deployments of the monitoring array by using the combination of the graphical optimization with the objective mapping technique. In order to reflect the spatiotemporal characteristics of the bay, the representative variables and eigenvectors are determined by the Empirical Orthogonal Function (EOF), and the cosine angle among them are calculated for a design index of optimization. At the recommended locations, the sampled representative variables are interpolated to reconstruct their spatiotemporal distribution and compared with the distributions of the true values. Analysis confirms that the selected locations, even with a small number of points, can be used for on-site monitoring. Also, the present framework suggests how to determine installable regions for real-time monitoring stations, which reflect the global and local characteristics of the semi-enclosed estuary.

Solar radiation is closely related to the energy buildings consume for cooling, heating, and lighting purposes. Glazing is the only material of the building envelope that transmits solar radiation and needs to be appropriately designed to reduce energy cㅈonsumption. Currently, smart glass technology is being actively investigated and developed for effective solar radiation control. Among the various types of smart glass, electrochromic glazing is one of the most promising technologies, as it can adjust transmittance on its own, has a wider transmittance range in both the clear and darkened states, and consumes less electricity. Considering the importance of solar radiation adjustment in electrochromic glazing technology, this study attempted to develop an optimal control method for electrochromic glazing. Toward this goal, the solar radiation incident on vertical surfaces and outdoor temperature conditions were controlled in three regions with different climatic characteristics, and the annual cooling, heating, and lighting loads, discomfort glare, and interior illumination were analyzed. This approach enabled the optimal conditions with respect to visual comfort to be determined. Subsequently, the EDPI (Energy and daylight performance index) was used to optimize control conditions for each region, thereby producing integrated evaluations from results with different units and properties. The proposed control method will be utilized to develop a control algorithm and a control system to reduce building energy consumption.

South Korea proposed reducing greenhouse gas emissions by 37% compared to the expected emissions by 2030 as the POST-2020 greenhouse gas reduction target. Electric vehicle distribution in the public sector is essential to achieve the carbon dioxide reduction target for transportation. In particular, when buses with internal combustion engines, which travel long distances and contribute substantially to greenhouse gas emissions, are replaced with electric buses, it is expected that greenhouse gas emissions will be significantly reduced. There are three types of electric buses with different power supply systems: a plug-in type in which power is supplied when a plug is inserted, a battery-swapping type in which a battery mounted on top of the vehicle is swapped at a swapping station, and a wireless type in which the battery is wirelessly charged through self-induction at a charging facility installed on the road. Vehicles of each charging type have different advantages and disadvantages. The performance, charging type, battery capacity, and operating environment of electric buses are mutually related parameters that must be considered when introducing such vehicles. Therefore, the optimal charging type must be selected according to the operating environment to enable the widespread use of electric buses. As such, this report proposes the optimal charging type according to the operating environment of public-sector electric vehicles.

The fine structure of Apricot pectin polysaccharides is discussed from both literature and recent work we have performed. Structural characterization utilized 1D and 2D homo- and hetero-nuclear NMR spectroscopy including results from High Performance Size Exclusion Chromatography (HP-SEC), HP Anion-Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD) and FTIR spectroscopy. The purified pectin fraction (F1AP) was found to be composed of D-galacturonic acid, L-rhamnose, D-arabinose and D-galactose in a 1.0 : 0.1 : 0.36 : 0.12 molar ratio, respectively, which is consistent with a pectin RG-1 branched with arabinogalactan side chain polysaccharides, and has a weight-average molecular weight of approximately 1588.2 kDa. The slope of the hydrodynamic radius versus the molar mass was 0.57, indicating the presence of coil conformations. The results from HPAEC-PAD, HPSEC and NMR spectroscopy (1H, 13C, zTOCSY, HSQC, HSQCTOXY and HMBC) demonstrated that F1AP fine fraction F1AP1, derived from original F1AP, has a backbone of (1→4)-linked -D-galacturonic acid and -L-rhamnopyranosyl residues branched with arabinogalactan of multiply glycosidic linkages of T- α-Araf, 3-α-Araf, 5-α-Araf, T- α -Arap, 2- α-Arap side chains, having methyl and acetylated groups, and has high molecular weights (1945 kDa). While the other F1A6 fraction consists predominately of an HG region of pectin polysaccharides with low molecular weights (117.5 kDa), less aggregated. The F1AP1 polysaccharide was highly viscous and its hydrodynamic radius was 64,3 nm. The exponent b of Rh-Mw (conformation plot) was determined to be 0.48, indicating a compact flexible coil conformation of the macromolecule in solution. However, the F1AP6 fraction of apricot fruits belong to backbone of repeats units of [-(1→4)-α-D-GalpA-1]n – both HG and partly contents RG-II polysaccharides, bearing heterosugar sidechains, including α-Ara, α -Rha and β-Gal residues and adopt more stiffness rod like conformation.

Numerous studies were published suggesting that troponin level is related to adverse outcomes in chronic cardiac and non-cardiac conditions. Our study investigated whether troponin levels gathered from an unselected blood sample taken during outpatient care are associated with adverse outcomes in a population with stable coronary artery disease. In a cohort of 949 patients with stable coronary artery disease, average age of 67.5 ± 9.5 years, 69.5% male, 52.1% diabetics, 51.6% with previous myocardial infarction, 57.9% with triple-vessel disease, 21.7% of patients encountered new events during an average period of monitoring of 2.07 ± 0.81 years. Troponin I/99th percentile categorized into tertiles emerged as an independent predictor of death and combined events risk (hazard ratio: 2.02 (1.13-3.60), p=0.017; 2.30 (1.37-3.88, p=0.002, respectively). A troponin ratio > 0.24 was able to identify 53.3% of patients at risk of death and heart failure hospitalization. In patients with stable coronary artery disease and adherent to treatment, troponin level is independently associated with death and heart failure hospitalization in a medium-term follow up.

The growth of plant and process of yield formation in crops are moderated by surrounding conditions as well as interaction of genetic background of plants and environment. In the last two decades significant changes in climate can be observed generating unfavorable and harmful impact on plant development. Drought stress can be considered as one of the most dangerous environmental factor influencing plant life cycle and decreasing production of biomass and finally the yield. Plants can react to water deficit in a wide degree what is dependent on the species, the genetic variability within the species, the phase of the plant ontogenesis, the intensity of stress, and other potential stress factors. In plants there can be observed hybrids between distinct taxa which exhibit certain traits adopted to tolerate stress conditions better than parental plants. Oat × maize addition (OMA) plants are good example of fertile hybrids with retained maize chromosomes as addition to complete oat genome. Hybrids generated via wide crossing can exhibit morphological, physiological and biochemical variations implemented by the occurrence of extra chromosomes of maize, as well as interaction of maize and oat chromatin. The molecular analysis indicated 12.5% OMA lines among all tested descendants of wide oat-maize crossing. On the fourteenth day of the drought, a significant effect of stress on the content of soluble sugars and phenolic compounds was observed, soil drought significantly reduced plant biomass above ground and several yield components. Less water lost revealed by results of the excised leaf water loss test was correlated with high yield of OMA lines. Phenolic compounds content might be used as biochemical indicator of plant drought tolerance since there were significant correlation with high kernel yields of plants subjected to drought stress.

RNA editing involves the insertion, deletion or substitution of single nucleotides within a RNA molecule, without altering the DNA sequence. Adenosine to inosine (A-to-I) editing consists of an RNA modification where single adenosines along the RNA sequence are converted into inosines. Such a biochemical transformation is catalyzed by enzymes belonging to the family of adenosine deaminases acting on RNA (ADARs) and occurs either co- or post-transcriptionally. Initially, the A-to-I RNA editing phenomenon was discovered and studied in messenger RNAs (mRNAs), where it can influence RNA splicing and cause the recoding of codon sequences. The employment of more powerful, high-throughput detection methods has recently revealed that A-to-I editing widely occurs in non-coding RNAs, including microRNAs (miRNAs). MiRNAs are a class of small regulatory non-coding RNAs (ncRNAs) acting as translation inhibitors, known to exert relevant roles in controlling cell cycle, proliferation, and cancer development. Indeed, a growing number of recent researches have evidenced the importance of miRNA editing in cancer biology by exploiting various detection and validation methods. Herein, we briefly overview early and currently available A-to-I miRNA editing detection and validation methods and discuss the significance of A-to-I miRNA editing in human cancer.

Systemic lupus erythematosus (SLE) is a heterogenous autoimmune disease. While its etiology remains elusive, current understanding suggests a multifactorial process with contributions by genetic, immunologic, hormonal, and environmental factors. A hypothesis that combines several of these factors proposes that genomic elements, the L1 retrotransposons, are instrumental in SLE pathogenesis. L1 retroelements are transcriptionally activated in SLE and produce two proteins, ORF1p and ORF2p, which are immunogenic and can drive type I interferon (IFN) production by producing DNA species that activate cytosolic DNA sensors. In addition, these two proteins reside in RNA-rich macromolecular assemblies that also contain well-known SLE autoantigens like Ro60. We surmise that cells expressing L1 will exhibit all the hallmarks of cells infected by a virus, resulting in a cellular and humoral immune response similar to those in chronic viral infections. However, unlike exogenous viruses, L1 retroelements cannot be eliminated from the host genome. Hence, dysregulated L1 will cause a chronic, but perhaps episodic, challenge for the immune system. The clinical and immunological features of SLE can be largely explained by this model. Here we review the support for, and the gaps in, this hypothesis of SLE and its potential for new diagnostic, prognostic, and therapeutic options in SLE.

Streptococcus mutans is well known for having virulence factors associated with its cariogenic role, such as glucosyltransferases, which have been used as targets for the virtual screening of molecules with inhibitory capacity. The Antigen I/II of S. mutans is involved in the adhesion to the surface of the tooth and the bacterial co-aggregation in the biofilm formation, despite that, this protein has not been used as a target in a virtual strategy search for inhibitors. In this study we identified in silico and evaluated in vitro molecules with adhesion inhibitory potential on S. mutans Ag I/II. A virtual screening of 883,551 molecules was conducted, cytotoxicity analysis on fibroblast cells, S. mutans adhesion studies, scanning electron microscopy analysis for bacterial integrity, and molecular dynamics simulation were also performed. We have found three molecules (ZI-187, ZI-939, ZI-906) that were not cytotoxic and inhibited the adhesion of S. mutans to polystyrene microplates. Molecular dynamic simulation by 300 nanoseconds showed stability of the interaction between ZI-187 and Ag I/II (PDB: 3IPK). This work provides three new molecules that targets Ag I/II and have the capacity to inhibit in vitro the S. mutans adhesion on polystyrene microplates and provides a new computational line for the search and selection of safe inhibitory molecules against different pathogens.

Gastrointestinal tumors including pancreatic and colorectal cancers represent one of the greatest public health issues worldwide, leading to million global deaths. Recent research demonstrated that the human heavy chain ferritin (HFt) can encapsulate different type of drugs in its cavity and can bind to its receptor, CD71, in several solid and hematological tumors, thus highlighting the potential use of ferritin for tumor-targeting therapies. Here, we describe the development and characterization of a novel nanomedicine based on the HFt that is named The-0504. In particular, this novel system is a nano-assembly comprising an engineered version of HFt that entraps about 80 molecules of a potent, wide-spectrum, non-camptothecin topoisomerase I inhibitor (Genz-644282). The-0504 can be produced by a standardized pre-industrial process as a pure and homogeneously formulated product with favourable lyophilization properties. The preliminary anticancer activity was evaluated in cultured cancer cells and in a mouse model of pancreatic cancer. Overall results reported here make The-0504 a candidate for further preclinical development against CD-71 expressing deadly tumors

Aberrant neutrophil extracellular trap (NET) formation and the loss of barrier integrity in inflamed intestinal tissues have long been associated with inflammatory bowel disease (IBD). However, whether NETs alter intestinal epithelium permeability during colitis remains elusive. Here, we demonstrated that NETs promote the breakdown in intestinal barrier function for the pathogenesis of intestinal inflammation in mouse models of colitis. NETs were abundant in the colon of mice with colitis experimentally induced by dextran sulfate sodium (DSS) or 2,4,6-trinitrobenzene sulfonic acid (TNBS). Analysis of the intestinal barrier integrity revealed that NETs impaired gut permeability, enabling the initiation of luminal bacterial translocation and inflammation. Furthermore, NETs induced the apoptosis of epithelial cells and disrupted the integrity of tight junctions and adherens junctions. Intravenous administration of DNase I, an enzyme that dissolves the web-like DNA filaments of NETs, during colitis restored the mucosal barrier integrity which reduced the dissemination of luminal bacteria, and attenuated intestinal inflammation in both DSS and TNBS models. We conclude that NETs serve a detrimental factor in the gut epithelial barrier function leading to the pathogenesis of mucosal inflammation during acute colitis.

Curcumin, a natural polyphenolic compound isolated from the plant Curcuma longa, is known to induce autophagy in various cancer cells, including lung cancer. In the present study, we also confirmed by LC3 immunofluorescence and immunoblotting analyses that curcumin triggers autophagy in human lung adenocarcinoma A549 cell line. In parallel with autophagy induction, gene expression of human GD3 synthase (hST8Sia I) responsible for ganglioside GD3 synthesis was markedly elevated in response to curcumin in A549 cells. To investigate transcriptional activation of hST8Sia I associated with autophagy formation in curcumin-treated A549 cells, functional characterization of the 5’-flanking region of the hST8Sia I gene was carried out using luciferase reporter assay system. Deletion analysis demonstrated that the -1146 to -646 region, which includes putative c-Ets-1, CREB, AP-1 and NF-κB binding sites, functions as the curcumin-responsive promoter of hST8Sia I in A549 cells. Site-directed mutagenesis and chromatin immunoprecipitation assay demonstrated that the NF-κB binding site at -731 to -722 was indispensable for the curcumin-induced hST8Sia I gene expression in A549 cells. Moreover, the transcriptional activation of hST8Sia I by curcumin A549 cells was strongly inhibited by compound C, an inhibitor of AMP-activated protein kinase (AMPK). These results suggest that curcumin controls hST8Sia I gene expression via AMPK signal pathway in A549 cells.

Artificial intelligence (AI) has found extensive applications in the sustainability domain. The municipal solid waste incineration (MSWI) process can achieve waste-to-energy (WTE) goals through the assistance of automation and information technologies. In theory, AI can facilitate the intelligent operation of the MSWI process, simultaneously achieving low pollution emissions and high production efficiency. This study provides an overview of AI applications in the MSWI process. Addressing fundamental challenges, the optimal control of the MSWI process is categorized into four aspects: modeling, control, optimization, and maintenance. Subsequently, this study conducts a detailed analysis and discussion of AI applications in each of these technological domains. In conclusion, this paper outlines the future research directions and provides an outlook on the fundamental issues pertaining to AI applications in the optimal control of the MSWI process.

Certain configurations of liquefied natural gas refueling stations exhibit a deficiency in managing boil-off gas. Furthermore, the ill-conceived linkage between the submersible pump and the gas storage tank pipeline leads to impeded natural gas transmission. This study employs Computational Fluid Dynamics (CFD) methodology to scrutinize the hydrodynamic attributes of T-type tee and dovetail tee configurations implemented in the pipeline design connecting the submersible pump and storage tank in an LNG filling station across diverse operational scenarios. The T-type tee induces detachment of the primary flow from the inner wall due to inertial forces, resulting in vortex formation and heightened resistance, accompanied by increased energy dissipation. Conversely, the dovetail tee, with its circular wall transition, mitigates vortex generation, reducing the separation zone and consequently minimizing resistance and energy loss. The maximum static differential pressure between the inlet and outlet of the dovetail tee is diminished by 52.52% when compared to that of the T-type tee. In the most noteworthy scenarios, the local resistance coefficient of the dovetail tee is even less than 1/10 of that of the T-type tee. In practical engineering applications, the incorporation of dovetail tees leads to a 17.58% reduction in the required elevation difference. This results in a more uniform flow field and enhanced stability in both flow rate and pressure. Such improvements contribute to heightened engineering efficiency and environmental sustainability, particularly evident in the design of LNG filling stations.

Inverse optimal control is a method for recovering the cost function used in an optimal control problem in expert demonstrations. Most studies on inverse optimal control have focused on building the unknown cost function through the linear combination of given features with unknown cost weights, which are generally considered to be constant. However, in many real-world applications, the cost weights may vary over time. In this study, we propose an adaptive online inverse optimal control approach based on a neural-network approximation to address the challenge of recovering time-varying cost weights. We conduct a well-posedness analysis of the problem and suggest a condition for the adaptive goal, under which the weights of the neural network generated to achieve this adaptive goal are unique to the corresponding inverse optimal control problem. Furthermore, we propose an updating law for the weights of the neural network to ensure the stability of the convergence of the solutions. Finally, simulation results for an example linear system are presented to demonstrate the effectiveness of the proposed strategy. The proposed method is applicable to a wide range of problems requiring real-time inverse optimal control calculations

Third-generation biomass production utilizing microalgae exhibits sustainable and environmentally friendly attributes, along with significant potential as a source of physiologically active compounds. However, the process of screening and localizing strains that are capable of producing high-value-added substances necessitates a significant amount of effort. In the present study, we have successfully isolated the indigenous marine diatom Odontella aurita OAOSH22 from the East coast of Korea. Subsequently, we conducted a comprehensive analysis of its morphological, molecular, and biochemical characteristics. Afterwards, comprehensive analysis was conducted on the morphological, molecular, and biochemical characteristics, along with testing for optimal growth conditions. The morphological characteristics of the isolate were observed using optical and electron microscopes, and it exhibited typical features of O. aurita. Additionally, the molecular phylogenetic inference derived from the sequence of the small-subunit 18S rDNA confirmed the classification of the microalgal strain as O. aurita. This isolate has been confirmed to contain 7.1 mg g-1 dry cell weight (DCW) of fucoxanthin, a powerful antioxidant substance, in terms of dry cell weight (DCW). In addition, this isolate contains 11.1 mg g-1 DCW of eicosapentaenoic acid (EPA), which is one of the nutritionally essential polyunsaturated fatty acids. Therefore, this indigenous isolate exhibits a significant potential as a valuable source of bioactive substances for various bio-industrial applications.

In response to the issue of vehicle escape guidance, this manuscript proposes a unified intelligent control strategy synthesizing optimal guidance and Meta Deep Reinforcement Learning (DRL). Optimal control with minor energy consumption is introduced to meet terminal latitude, longitude and altitude. Maneuvering escape is realized by adding longitudinal and lateral direction maneuver overloads. Maneuver command decision model is calculated based on Soft-Actor-Critic (SAC) networks. Meta learning is introduced to enhance autonomous escape capability, which improves generalization performance to time-varying scenarios not encountered in the training process. In order to obtain training samples at a faster speed, this manuscript uses the prediction method to solve reward values, which avoiding a large number of numerical integration. The simulation results manifest that the proposed intelligent strategy can achieve high precise guidance and effective escape.

This paper presents an analysis of the sensitivity of controlling an autonomous surface object among a group of encountered objects to the inaccuracy of state control process data. For this purpose, a safe and optimal model of the control process was defined. An algorithm for determining the optimal and safe trajectory of an object, based on the multi-object game model, was developed; for comparative analysis, an algorithm for calculating only the optimal trajectory, not taking into account the maneuverability of other objects, was additionally developed. First, simulation-based studies of the algorithms enabled a comparative analysis of a number of different acceptable strategies for optimally shifting the trajectory of maneuvering objects from a single initial direction. Thereafter, the main goal of this paper was implemented: an analysis of the sensitivity characteristics of safe control, assessed with the risk of collision, both on the inaccuracy of navigation data and on the number of possible control strategies. Finally, final conclusions and a plan for further research on the subject of the paper were formulated.

Intersections within urban centers do not allow all citizens to move in a fluid manner. In this sense, this paper proposes a queuing network model based on Kendall's notation for the intersection of two urban streets (East 53rd Street and East 56th Street) in Panama City. A set of traffic lights operating under a fixed time scheme controls the vehicular flow at the intersection. The objective is to optimize the vehicular flow at the intersection by minimizing the waiting time of the vehicles using mathematical models, Linear Regressor Model, and simulations performed in MATLAB evaluating the waiting time experienced by the vehicles. Based on the results obtained, the optimal signal timing of the traffic lights is determined to minimize the waiting time for both streets.

The local reactive power control in distribution grids with a high penetration of distributed energy resources (DERs) is essential in future power system operation. Appropriate control characteristic curves for DERs support stable and efficient distribution grid operation. However, the current practice is to configure local controllers collectively with constant characteristic curves that may not be efficient for volatile grid conditions or the desired targets of grid operators. To address this issue, this paper proposes a time series optimization-based method to calculate control parameters, which enables each DER to be independently controlled by an exclusive characteristic curve for optimizing its reactive power provision. To realize time series optimizations, the open-source tools pandapower and PowerModels are interconnected functionally. Based on the optimization results, Q(V)- and Q(P)-characteristic curves can be individually calculated using the linear decision tree regression to support voltage stability and provide reactive power flexibility and potentially reduce grid losses and component loadings. In this paper, the newly calculated characteristic curves are applied in two representative case studies, and the results demonstrate that the proposed method outperforms the reference ones suggested by grid codes.

Based on some geometrical properties of the Rabinovich system the closed-form solutions of the equations has been established. Moreover the Rabinovich system is reduced to a nonlinear differential equation depending on an auxiliary unknown function. The approximate analytical solutions are built using the Optimal Auxiliary Functions Method (OAFM). A good agreement between the analytical and corresponding numerical results has been performed. The accuracy of the obtained results emphasizes that this procedure could be successfully applied for more dynamical systems with these geometrical properties.

Reasonable trajectory planning is the precondition for the parafoil airdrop system to achieve autonomous accurate homing and safe landing. In order to successfully realize the self-homing of the parafoil airdrop system, a new trajectory optimization design scheme is proposed in this paper. The scheme is based on the parafoil's unique flight and control characteristics and adopts a segmented homing design. Compared with the current common trajectory design method, its core feature is to avoid the problem that the straight-line flight distance before landing is limited by the radius of the height-reducing area and ensure landing accuracy and safety. Firstly, the different starting states of the parafoil airdrop system and the landing requirements were comprehensively considered, and the homing trajectory is reasonably segmented. Based on the requirements of energy control, stable flight, and landing accuracy, the optimal objective function of the trajectory was established, and the trajectory parameters, calculation methods, and constraints were given. Secondly, the cuckoo search algorithm was applied to optimize the objective function to obtain the final home trajectory. Finally, the trajectory planning under different airdrop conditions was simulated and verified. The results showed that the planned trajectories could reach the target point accurately and meet the flight direction requirements, proving the proposed scheme's correctness and feasibility.

In the new period, the state has made every effort to promote the new urbanization of public sports service. Entropy method, coupled coordination model, cold hot spot analysis is used to explore the dynamic relationship between public sports services and the development of new urbanization in China from 2008 to 2017. The results show that: (1) The development of the internal subsystem of public sports service is not balanced, the sports financial investment system grows rapidly, but the development of professional sports talent team is slow. (2) The imbalance of regional development cannot be ignored, and the public sports service level shows a decreasing gradient from east to west. (3) The regional development features are different. The eastern region is dominated by the coordinated development of sports public service and urbanization, while the central region is mainly in the type of public sports service lag, while the western region has multiple complex characteristics of low-level coordination and public sports service lag. Therefore, it is proposed that the construction of modern public sports service system should be investigated in the context of the development of new urbanization. It should be promoted from the following aspects: promoting the extension of public sports service to rural areas, engendering the "citizen's right" of sports health to the migrant population, conforming to the trend of mass sports intelligence, developing green sports and revitalizing idle sports assets in cities.

Parts produced by laser or electron-beam powder bed fusion (PBF) additive manufacturing are prone to residual stresses, deformations, and other defects linked to non-uniform temperature distribution during the manufacturing process. Several researchers have highlighted the important role scan sequence plays in achieving uniform temperature distribution in PBF. However, scan sequence continues to be determined offline based on trial-and-error or heuristics, which are neither optimal nor generalizable. To address these weaknesses, we have articulated a vision for an intelligent online scan sequence optimization approach to achieve uniform temperature distribution, hence reduced residual stresses and deformations, in PBF using physics-based and data-driven thermal models. This paper proposes SmartScan, our first attempt towards achieving our vision using a simplified physics-based thermal model. The conduction and convection dynamics of a single layer of the PBF process are modeled using the finite difference method and radial basis functions. Using the model, the next best feature (e.g., stripe or island) that minimizes a thermal uniformity metric is found using control theory. Simulations and experiments involving laser marking of a stainless steel plate are used to demonstrate the effectiveness of SmartScan in comparison to existing heuristic scan sequences for stripe and island scan patterns. In experiments, SmartScan yields up to 43% improvement in average thermal uniformity and 47% reduction in deformations (i.e., warpage) compared to existing heuristic approaches. It is also shown to be robust, and computationally efficient enough for online implementation.

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow (OPF) problem and is called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution (DE) operator in a single algorithmic framework. Additionally, an adaptive method (AM) is proposed to update the number of solutions evolved by each DE operator based on both the diversity of population and quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering the intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results and thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%.

The paper is concerned with a class of stochastic differential equations in infinite dimensional Hilbert space with random coefficients driven by Teugel's martingales which are more general processes. and its optimal control problem. Here Teugels martingales are a family of pairwise strongly orthonormal martingales associated with L\'{e}vy processes (see Nualart and Schoutens). There are three major ingredients. The first is to prove the existence and uniqueness of the solutions by continuous dependence theorem of solutions combining with the parameter extension method. The second is to establish the stochastic maximum principle and verification theorem for our optimal control problem by the classicconvex variation method and dual technique.The third is to represent an example of a Cauchy problem for a controlled stochastic partial differential equation driven by Teugels martingales which our theoretical results can solve.

This study proposes a novel flexible bus dispatching system where a fleet of fully automated modular bus units, together with conventional buses, serves the passenger demand. These modular bus units can either operate individually or combined (forming larger modular buses with a higher passenger capacity). This provides enormous flexibility to manage the service frequencies and vehicle allocation, reducing thereby the operating cost and improving passenger mobility. We develop an optimization model used to determine the optimal composition of bus units and the optimal service frequency at which the buses (both conventional and modular) are dispatched across each bus line. We explicitly account for the dynamics of traffic congestion and complex interactions between the modes at the network level based on the recently proposed three-dimensional macroscopic fundamental diagram (3D-MFD). To the best of our knowledge, this is the first application of the 3D-MFD and modular bus units for the frequency setting problem in the domain of bus operations. Numerical results show the improvements in the total system cost made by adapting the number of combined modular bus units and their dispatched frequencies to the evolution of both, the car and the passenger demand. A comparison with the commonly used approach that considers only the bus system (neglecting the complex multimodal interactions and congestion propagation) reveals the value of the proposed modeling framework.

This paper introduces a closed-loop control strategy for maintaining consistency of liquid temperature in commercial Drop on Demand (DoD) inkjet printing. No additional sensors or additional actuators are installed in the printhead while achieving the consistency in liquid temperature. To this end, this paper presents a novel in situ sensing-actuation policy at every individual liquid-nozzle, where the jetting mechanism has three distinct roles. It is used for jetting liquid droplet onto the print media based on the print-job. It is used as a soft sensor to estimate the real-time liquid temperature of the jetting nozzle. While not jetting liquid, it is used as a heating actuator to minimize the gradient of liquid temperature among nozzles. The soft sensing based in situ controller is implemented in an experimentally validated digital twin that models the thermo-fluidic processes of the printhead. The digital twin is scalable and flexible to incorporate an arbitrary number of liquid-nozzles, making the control strategy applicable for future designs of the printhead.

Fish schooling implies an awareness of the swimmers for their companions. In flow mediated environments, in addition to visual cues, pressure and shear sensors on the fish body are critical for providing quantitative information that assists the quantification of proximity to other swimmers. Here we examine the distribution of sensors on the surface of an artificial swimmer so that it can optimally identify a leading group of swimmers. We employ Bayesian experimental design coupled with two-dimensional Navier Stokes equations for multiple self-propelled swimmers. The follower tracks the school using information from its own surface pressure and shear stress. We demonstrate that the optimal sensor distribution of the follower is qualitatively similar to the distribution of neuromasts on fish. Our results show that it is possible to identify accurately the center of mass and even the number of the leading swimmers using surface only information.

The growth of demand for metallic minerals has faced with the need for new techniques and improving technologies for all mine life cycle operations. Nowadays, the exploitation of old tailings and mine wastes facilities could represent a solution to this demand, with economic and environmental advantages. W-Sn Panasqueira Mine has been operating for more than 100 years. Its first processing plant “Rio” was located near Zêrere river being the mineral processing residues deposited on the top hillside on the margin of this river in Cabeço do Pião tailings dam. The lack of maintenance and monitoring of this enormous structure in the last twenty years represents high risks to the environment and population of the surrounding region. The re-mining of the tailings by hydrometallurgical methods was considered, in order to satisfy these two enounced conditions - metals demand and environmental risk, aiming for the sale of the metal to pay the environmental intervention. Field samples campaign allowed collecting data and results from laboratory tests driving to use regression optimization. The re-mining solution was studied, taking into account the technical, economic, social, and environmental aspects.

Modern gas turbines firing temperatures (1500-2000K) are well beyond the maximum allowable blade material temperatures. Continuous safe operation is made possible by cooling the HP turbine first stages -nozzle vanes and rotor blades- with a portion of the compressor discharge air, a practice that induces a penalty on the cycle thermal efficiency. Therefore, a current issue is to investigate the real advantage, technical and economical, of raising maximum temperatures much further beyond current values. In this paper, process simulations of a gas turbine are performed to assess HP turbine first-stage cooling effects on cycle performance. A new simplified and properly streamlined model is proposed for the non-adiabatic expansion of the hot gas mixed with the cooling air within the blade passage, which allows for a comparison of several cycle configurations at different TIT (turbine inlet temperature) and max (total turbine expansion ratio) with a realistically acceptable degree of approximation.. The calculations suggest that, at a given max, the TIT can be increased in order to reach higher cycle efficiency up to a limit imposed by the required amount and temperature of the cooling air. Beyond this limit, no significant gains in thermal efficiency are obtained by adopting higher max and/or increasing the TIT, so that it is convenient in terms of cycle performance to design at lower rather than higher max. The small penalty on cycle efficiency is compensated by lower plant cost. The results of our model agree with those of some previous much more complex and computationally expensive studies, so that the novelty of this paper lies in the original method adopted on which the proposed model is based, and in the fast, accurate and low resource intensity of the corresponding numerical procedure: all advantages that can be crucial for industry needs. The presented analysis is purely thermodynamic, with no investigation on the effects of the different configurations on plant costs, so that future work addressing a thermo-economic analysis of the air-cooled gas turbine power plant is the next logical step.

Hippophae is a tree species with ecological, economic and social benefits. In this study, we assembled and annotated chloroplast genomes of sympatric Hippophae gyantsensis and H. rhamnoides subsp. yunnanensis. Their full-length are 155260 and 156415 bp, respectively. Each of them has 131 genes, comprising 85 protein-coding genes, 8 ribosomal RNA genes and 38 transfer RNA genes. After comparing the chloroplast genomes, we found 1302 base difference loci, and 63.29% are located in the intergenic region or intron sequences and 36.71% are located in the coding sequences. The SSC region has the highest mutation rate, followed by the LSC region; the IR regions have the lowest mutation rate. Among the protein-coding genes, three had a ratio of nonsynonymous to synonymous substitutions (Ka/Ks) >1 (but P values were non-significant) and 66 had Ka/Ks <1 (46 were significant). In general, the chloroplast protein-coding genes may be subject to purification selection. Among H. gyantsensis and H. rhamnoides subsp. yunnanensis chloroplast protein-coding genes, there are 20 and 16 optimal codons, respectively. Most of the optimal codons were ending with A or U, which indicates significant AT preference. It is an important reference for studies on the general characteristics and evolution of the Hippophae chloroplast genome.

This paper addresses the problem of assessing and optimizing acoustic positioning system for underwater target localization with range measurements only. We present a new three-dimensional assessment model to assess the optimal geometric beacon formation whether meet user needs. For the sake of mathematical tractability, it is assumed that the measurements of the range between the target and beacons are corrupted with white Gaussian noise with variance is distance-dependent. Then by adopting dilution of precision (DOP) parameters in the assessment model, the relationship between DOP parameters and positioning accuracy is derived. In addition, the optimal geometric beacon formation that will yield the best performance is achieved by minimizing the values of geometric dilution of precision (GDOP) on condition that the position of target is known and fixed. Next, in order to make sure whether the estimate positioning accuracy over interesting region satisfy the precision needed by the users, geometric positioning accuracy (GPA), horizonal positioning accuracy (HPA) and vertical positioning accuracy (VPA) are utilized to assess the optimal geometric beacon formation. Simulation examples are designed to illustrate the exactness of the conclusion. Unlike other work which only use GDOP to optimize the formation and cannot assess the performance of the specified dimensions, this new three-dimensional assessment model can assess the optimal geometric beacon formation in each dimension for any point in three-dimensional space, which can provide users with guidance advices to optimize performance of every specified dimension.

A microstructure-based model is developed to study the effective anisotropic properties (magnetic, dielectric or thermal) of two phase particle-filled composites. The Green’s function technique and the effective field method are used to derive theoretically the homogenized (averaged) properties for a representative volume element containing isolated inclusion and an infinite, chain-structured particles. Those results are compared with the FE approximations conducted for the assumed representative volume element. In addition, as a special case, the Maxwell–Garnett model is retrieved when particle interactions are not taken into consideration. We shall also give some information on the optimal design of the effective anisotropic properties taking into account the shape of magnetic particles.

This paper proposes a method based on genetic algorithm (GA) for the security-constrained optimal dispatch of integrated natural gas and electricity networks, considering operating scenarios in both energy systems. The mathematical formulation of the optimization problem consists of a multi-objective function which aims to minimize both cost of thermal generation (diesel and natural gas) as well as the production and transportation of natural gas. The joint gas-electricity system is modeled by two separate groups of nonlinear equation, which are solved by the combination of Newton's method with the GA. The applicability of the proposed method is tested in the Belgian gas network integrated with the IEEE 14-bus test system and a 15-node natural gas network integrated with the IEEE 118-bus test system. The results demonstrate that the proposed method provides efficient and secure solutions for different operating scenarios in both energy systems.

The main objective of this paper is to find a close link between the adaptive level of significance, presented here, and the sample size. We, statisticians, know of the inconsistency, or paradox, in the current classical tests of significance that are based on p-value statistics that is compared to the canonical significance levels (10%, 5% and 1%): "Raise the sample to reject the null hypothesis" is the recommendation of some ill-advised scientists! This paper will show that it is possible to eliminate this problem of significance tests. The Bayesian Lindley's paradox – "increase the sample to accept the hypothesis" – also disappears. Obviously, we present here only the beginning of a possible prominent research. The intention is to extend its use to more complex applications such as survival analysis, reliability tests and other areas. The main tools used here are the Bayes Factor and the extended Neyman-Pearson Lemma.

This paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed multi-objective optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF) model for the optimal operation. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant savings in electricity cost with network operational constraints satisfied.

Abstract. The remarks by the Supreme Leader of the Islamic Revolution on the toll of the famines that afflicted occupied Iran in World War I and World War II indicate a desire to incorporate these calamities in Iran’s national narrative and collective memory. His criticism of famine historiography and stated toll numbers, and the unfolding catastrophic famine in Gaza, justify and necessitate a fresh look at each famine’s historiography and toll. This article re-estimates the toll of each famine by including many overlooked and neglected primary sources and in ways not previously done. It builds a trajectory of Iran’s demographic development from 1810 to 1944, and derives the toll of each famine. The World War II famine and typhus epidemics had claimed 5.5 million victims and Ayatollah Khamenei’s criticisms concerning its stated duration and toll valid. World War I famine was also more deadly, though the 1869-73 famine was not far behind. At least 15.5 million Iranians died in the two world wars, a fact nowhere reflected in the history of the conflicts. Iran’s 1944 population of 12 million was unchanged from that of 1850 and a century of population growth obliterated

Introduction: maxillary hypoplasia and mandibular asymmetry may be corrected with orthognathic surgery at the completion of growth. Many patients require segmental Le Fort I osteotomies to obtain the most stable results. Unfortunately, if Invisalign is chosen for pre-surgical preparation, ClinCheck © software does not allow for prediction when these complex surgeries are planned. The objective of this paper was to show the potential of aligners beyond its software in most complex cases like multiple-piece maxillary osteotomies in cleft and non-cleft patients. Method: Thirteen patients who underwent pre-surgical treatment with clear aligners-Invisalign (study group) were matched in terms of diagnosis, surgical procedure, and orthodontic complexity with thirteen patients treated using fixed appliances (control group). A technique based on simple superimposition was devised to enhance the software for creating a suitable occlusion for segmental pre-surgical treatments. Virtual curves following the lower arch were employed to guide the correct pre-surgical positions of the upper teeth. The amount of impressions required in both groups to achieve satisfactory pre-surgical alignment of the segmented arches was compared. Results: one or no refinement phase were needed in the Invisalign group to reach an acceptable pre-surgical occlusion while the amount of pre-surgical impressions taken in order to reach adequate coordination with fixed appliance treatment was slightly higher. The average overall treatment duration did not show a statistically significant variation between the groups. Conclusions: it appears that clear aligner could serve as an effective treatment for individuals with skeletal discrepancies, including cleft and craniofacial anomalies, necessitating segmental Le Fort I osteotomies when aided by the suggested superimposition approach during digital pre-surgical movement simulations. More sophisticated softwares will certainly be implemented in the future.

High incidence of epithelial malignancies in HIV-1 infection is associated with co-infection with oncogenic viruses, such as high-risk human papillomaviruses (HR HPVs), most often HPV16. A collaboration between HIV-1 and HR HPVs in the malignant transformation of epithelial cells exposed to both viruses have long been anticipated. Here, we delineated the effects on in vitro and in vivo properties of HPV16-infected cervical cancer cells of HIV-1 reverse transcriptase. Epidermoid carcinoma Ca Ski cells were made to express RT of HIV-1 clade A (RT_A) or Green Fluorescence Protein (GFP) by lentiviral transduction, subclones with one or six copies of RT_A and six copies of GFP DNA were generated. Expression by subclones of GFP was assessed by flow cytometry, and of RT_A, by Western blotting. Cells were assessed for the levels of mRNA of the RT_A, E6 and its isoforms, and cellular factors characterizing oxidative stress, and EMT by the real-time PCR. Parameters of glycolysis and mitochondrial respiration were assessed by Seahorse technology. Subclones were surveyed for the changes in cell cycle, doubling time, migration capacity, clonogenic activity and for the capacity to form tumors in nude mice. Ca Ski RT_A produced 20-55 fg of RT_A per cell. Expression of RT_A caused a proportional increase in the expression of E6*I isoform. In Ca Ski, RT_A suppressed mitochondrial respiration and oxygen consumption, and increased glycolysis. Compared to parental cells and GFP control, transcription in Ca Ski RT_A of epithelial (E-CADHERIN) state marker was increased, and of mesenchymal (VIMENTIN) decreased, indicating acquisition by cells of the hybrid epithelial/mesenchymal (E/M) phenotype. While Ca Ski GFP and Ca Ski RT_A with one gene insert had reduced migration rate, decreased clonogenic activity in vitro, and diminished capacity to form tumors in nude mice, increase in RT_A copicity/expression mitigated these effects. Altogether, expression of HIV-1 RT_A gave Ca Ski cells the plasticity required to overcome negative effects of lentiviral transduction and potentially increased their tumorigenicity.