Control Formulation Research Articles

Smoked Fish Salam: Development and Sensory Analysis

Objective: The aim of this study is to develop smoked salamis (cold and hot) from mechanically separated meat (MSM) of tilapia, and to evaluate their acceptance through sensory analysis. Theoretical Framework: With the increase in fish production, large quantities of fish by-products are also generated, such as carcasses, heads, fillets, among others with high nutritional value that can be used in human and animal nutrition. Method: The methodology adopted for this research includes a control formulation subjected to smoking (cold and hot), and two others with the inclusion of 10 and 20% of CMS in natura, totaling four treatments. In the dehydration process, the salamis were weighed and subjected to pre-drying in a forced ventilation oven for three hours at 55ºC. Then, they were placed in a stainless steel smoker that produced smoke by burning sawdust (4h/55ºC). The cold smoking process was carried out using 20% of liquid smoke/volume of water, where the salamis were immersed for 15 minutes, drained and taken to the oven (4h/55ºC). At the end of the process, the weight loss of the sausages was calculated and sensory analyses were performed, where 50 untrained judges evaluated the products in terms of acceptance and purchase intention. Results and Discussion: The results obtained revealed that total losses ranged from 16.71 to 32.79%. The type of smoking influenced the acceptance of the salamis (p<0.05), where color and aroma were the parameters that presented the highest values for hot-smoked salamis, as observed for purchase intention. Research Implications: Fish salamis enriched with fish protein sources are an excellent alternative for human nutrition, as they represent an excellent nutritional source for people who are concerned about healthy foods. There are several studies using animal protein sources such as fish to prepare healthy and easy-to-prepare foods, since due to people's fast-paced routines today, they need quick and healthy foods. Originality/value: this study contributes to the literature by highlighting the supplementation of food with processed fish by-products and enhanced in the form of fish sausages.

An innovative practical roadmap for optimal control strategies in malware propagation through the integration of RL with MPC

While there has been considerable research into optimal control formulations for mitigating cyber threats, a significant gap persists between the theoretical and numerical insights derived from such research and the practical implementation of these optimal mitigation strategies in real-time scenarios. This paper introduces a multifaceted approach to enhance and optimize optimal control strategies by seamlessly integrating reinforcement learning (RL) algorithms with model predictive control (MPC) techniques for the purpose of malware propagation control. Optimal control is a critical aspect of various domains, ranging from industrial processes and robotics to epidemiological modeling and cybersecurity. The traditional approaches to optimal control, particularly open-loop strategies, have limitations in adapting to dynamic and uncertain environments. This paper addresses these limitations by proposing a novel roadmap that leverages RL algorithms to fine-tune and adapt MPC parameters within the context of malware propagation containment. In sum, this practical roadmap is anticipated to serve as a valuable resource for researchers and practitioners engaged in the development of cybersecurity solutions.

White cabbage waste powder improves gluten-free rice-based breadsticks functional and nutritional characteristics

Fruit and vegetable industrialization generates large amounts of organic residues abundant in bioactive compounds. In the present work, white cabbage powders (WCP) were used to partially replace rice flour (5, 10, 20 and 30% w/w) in the formulation of gluten-free breadsticks. Physicochemical (moisture content, water and oil absorption capacity), pasting, and antioxidant properties (reducing sugars, total phenols and DPPH scavenge ability) were evaluated in flour blends. Breadsticks quality was evaluated by analysing dough rheology, physicochemical (aw, colour, texture) and antioxidant properties. Water and oil absorption capacities improved with WCP addition, whereas pasting properties worsened. Dynamic oscillatory tests revealed that WCP incorporation increased G’ and G’’ values. Colour attributes were also significantly modified with WCP addition, whereas breadsticks hardness reduced compared to control formulation. Nutritional properties of breadsticks improved with WCP addition, as deduced from the better antioxidant characteristics obtained for both blends and breadsticks, when vegetable powders were added. In conclusion, this study reveals that WCP can be suggested as functional food ingredient to increase the nutritional properties of new, rice-based gluten-free breadsticks.

Current Status of Semaglutide Injection andDevelopment Prospects in China

Obesity is a global issue that closely affects public health, and China’s obesity rate is among the highest in the world. Recently, Semaglutide injection was approved for marketing in China as the first weekly formulation for long-term weight control. This review consolidates and analyzes various types of research related to Semaglutide regarding weight loss, to comprehensively describe the different aspects of the drug. As a glucagon-like peptide 1 receptor agonists (GLP-1RA), Semaglutide works by mimicking the action of innate hormone to enhance the cell signaling activity and corresponding outcome. It has been approved to effectively reduce weight and improve weight-related factors in overweight or obese patients with a guaranteed safety profile. Comparing to traditional methods of losing weight, this medication is time and effort-saving, which makes it highly competitive in this field. Although there are still unsolved issues and challenges faced by the drug, such as high price and acceptance among doctors and patients, it is highly likely to become a new and anticipated method of weight management in China

Air quality in different urban hotspots in a metropolitan city in India and the environmental implication.

This research study investigates hourly data on concentrations of five major air pollutants such as particulate matter (PM10, PM2.5) and gaseous pollutants (SO2, NO2, CO) measured during 2022 at four hotspot sites (industrial site, traffic site, commercial site, harbour, and one residential site) in Chennai, India. The analysis encompasses temporal variations spanning annual, seasonal, and diurnal variations in the pollutants. Notably, PM10 and CO emerge as the predominant pollutants, with the highest concentrations at industrial and traffic sites (PM10: 67.64 ± 40.77µg/m3, CO: 1.41 ± 0.84mg/m3; traffic site: PM10: 58.67 ± 20.05µg/m3, CO: 0.99 ± 0.57mg/m3). Seasonal dynamics reveal prominent winter spikes in particulate matter (PM10, PM2.5) and carbon monoxide (CO) concentrations, while nitrogen dioxide (NO2) and sulphur dioxide (SO2) levels peak during the summer season, particularly in the harbour area. The proximity to roadways exerts a discernible influence on diurnal patterns, with traffic sites showcasing broader rush hour peaks compared to sharper spikes observed at other sites. Furthermore, distinct bimodal patterns are evident for PM10 and PM2.5 concentrations in residential and harbour areas. A common lognormal distribution pattern is identified across the studied sites, suggesting consistent air quality trends despite contrasting locations. The conditional probability function (CPF) is used in conjunction with local meteorological conditions for identifying key pollution sources in each location. The implementation of polar plots emphasizes industries as principal local sources of pollution, at industrial sites significantly contributing to PM10, SO2, and NO2 concentrations under specific wind conditions. The main objective of the present study is to facilitate a good understanding of pollutant dynamics, pollution sources, and their intricate interplay with meteorological factors, thereby contributing to the formulation and implementation of effective air pollution control and mitigation strategies.

Artificial Neural Networks for Energy Demand Prediction in an Economic MPC‐Based Energy Management System

ABSTRACTMicrogrids are a development trend and have attracted a lot of attention worldwide. The control system plays a crucial role in implementing these systems and, due to their complexity, artificial intelligence techniques represent some enabling technologies for their future development and success. In this paper, we propose a novel formulation of an economic model predictive control (economic MPC) applied to a microgrid designed for a faculty building with the inclusion of a predictive model to deal with the energy demand disturbance using a recurrent neural network of the long short‐term memory (RNN‐LSTM). First, we develop a framework to identify an RNN‐LSTM using historical data registered by a smart three‐phase power quality analyzer to provide feedforward power demand predictions. Next, we present an economic MPC formulation that includes the prediction model for the disturbance within the optimization problem to be solved by the MPC strategy. We carried out simulations with different scenarios of energy consumption, available resources, and simulation times to highlight the results obtained and analyze the performance of the energy management system. In all cases, we observed the correct operation of the proposed control scheme, complying at all times with the objectives and operational restrictions imposed on the system.

Surfactant-Assisted Wet Granulation-Based Matrix Tablets without Exceptional Additives: Prolonging Systemic Exposure of Model BCS Class II Ketoprofen.

The present studywas aimed to ameliorate the issue of solubility and thereby, bioavailability of ketoprofen, a BCS Class II drug. The sustained release matrix tablets (MT) were prepared using surfactant-assisted wet granulation (SAWG) with 1-5% of different surfactants. The tablet characteristics were within the compendial limits. The selected sustained release-compliant matrix tablet formulation containing granules prepared using 3% Soluplus® (MT2) released the drug by swelling-erosion. In human volunteers, MT2 attained the maximum plasma concentration (Cmax) of 5.72µg /ml ± 0.30 h, time to Cmax (Tmax) of 5.56 ± 0.30 h and maintained the plasma concentration above its minimum effective concentration (MEC), 0.7 µg.ml-1 till 24h. A control formulation, prepared from granules without surfactant (MT16), promptly attained Cmax of 9.62 ± 0.76 µg/ml within 1h but rapidly declined to below MEC in 8h. Area under the curve from initial point to infinity (AUC0-∞) of MT2 (78.65 ± 7.64 µg.h.ml-1) was 2.29 folds higher than 34.39 ± 3.06 µg.h.ml-1 of MT16. With decreased Cmax, increased AUC0-∞, delayed Tmax and retained ketoprofen concentration above MEC for longer time, MT2 corresponded with the in-vitro sustained drug release characteristic. There is a likelihood of administration of once-a-day single dose of MT2 without plasma fluctuations, expected from two doses of MT16. SAWG helped developing a swellable-erodible sustained release matrix tablet formulation of ketoprofen with the desired biopharmaceutical and pharmacokinetics properties, merely by addition of Soluplus® in granules and without incorporation of any special ingredients or the major manipulation of the formulative ingredients in the formulation.

Spread developed with peanuts, baru almonds, and ora-pro-nóbis mucilage: chemical, technological, and bioactive characteristics

The number of people changing their eating habits towards healthier foods is increasing. Among foods, peanut butter is widely consumed all around the world. However, the lipid content of peanut butter is high, which ends up being a reason for restriction for some consumers. One strategy is to replace peanuts with baru almonds, an almond native to the Brazilian Cerrado, using ora-pro-nóbis mucilage to maintain the characteristics. Therefore, the objective of this study was to develop and evaluate the spread with peanuts, baru almonds, and ora-pro-nóbis mucilage. Different baru almond and ora-pro-nóbis mucilage concentrations substituted the peanut concentration on the spread. Chemical, physical, technological, bioactive, and storage characteristics were evaluated. Spread with the highest amount of ora-pro-nóbis mucilage (0.2 g/100 g of butter) showed a 16% increase in protein content. The mineral profile was improved in the formulations developed compared with spreads. The firmness of the spread did not show a significant difference from the peanut-based control formulation. Furthermore, antioxidant activity was higher in a developed spread. During storage, up to 30 days, most formulations maintained their initial pH and acidity, with changes in color parameters. Spread showed great nutritional value, being an interesting food alternative to improve diet quality.

Novel Parallel Formulation for Iterative Reinforcement Learning Control

Novel Parallel Formulation for Iterative Reinforcement Learning Control

Topical Anti-Inflammatory Formulations from Medicinal Plant Extracts: Stability, Efficacy, and Cytokine Modulation in a Carrageenan-Induced Paw Edema Model

Background: Traditional anti-inflammatory drugs, like NSAIDs, often cause side effects, which has fueled interest in plant-based alternatives with fewer adverse effects. Medicinal plants such as turmeric (Curcuma longa), ginger (Zingiber officinale), frankincense (Boswellia serrata), ashwagandha (Withania somnifera), and gotu kola (Centella asiatica) are known for their bioactive compounds with anti-inflammatory properties. This study aimed to evaluate the anti-inflammatory efficacy of these plant extracts in topical formulations. Methods: Ethanol extracts of the selected plants were prepared and formulated into topical gel and cream forms. Stability testing was conducted over a 30-day period to confirm the formulations' consistency, color, and pH. Anti-inflammatory efficacy was assessed using a carrageenan-induced paw edema model in Wistar rats. The animals were divided into six groups, including control, standard drug (indomethacin), and plant-based formulations at two extract concentrations (5% and 10%). Edema reduction was measured using a plethysmometer, and serum cytokine levels (TNF-α and IL-6) were quantified via ELISA. Histopathological analyses of tissue samples further evaluated the anti-inflammatory effects. Results: Both gel and cream formulations demonstrated stability over 30 days. The 10% extract cream formulation achieved the highest reduction in paw edema (70%) and reduced inflammation levels comparable to indomethacin. The 10% extract gel showed similar results (65% reduction). Biochemical analysis revealed significant reductions in TNF-α and IL-6 levels, especially in the 10% cream and gel groups, aligning with histopathological findings that indicated reduced tissue damage and inflammatory cell infiltration in treated groups compared to controls. Conclusion: The findings suggest that these plant extracts possess potent anti-inflammatory effects when formulated into stable, topical products. The 10% extract cream formulation was particularly effective, offering a promising alternative for managing inflammation with fewer side effects.

Analysis of a Simplified Predictive Function Control Formulation Using First Order Transfer Function for Adaptive Cruise Control

This paper presents a formulation and analysis of a low computation Predictive Functional Control (PFC), which is a simplified version of the more advanced Model Predictive Control (MPC) for an Adaptive Cruise Control (ACC) system by using a representation of first order closed-loop transfer function. In this work, a non-linear mathematical model of vehicle longitudinal dynamics is considered as a control plant. Then, a simple Proportional Integral (PI) controller is employed as an inner loop to identify the first-order relationship between its actual and desired trajectory speed according to the reasonable time constant based on the logical response of pedals pressing. To directly control the whole plant, the PFC is formulated as an outer loop to track the desired speed together with the convergence rate based on a user preference while satisfying constraints related to acceleration and safe distancing. Since PFC is formulated based on the first-order transfer function, the prediction and tuning processes are straightforward and specific to this system. The simulation results confirm that the proposed controller managed to track the desired speed while maintaining a comfortable driving response. Besides, the controller also can retain safe distancing during the car following application, even in the presence of unmeasured disturbance. In summary, this framework can avoid the need to formulate an inverse non-linear model that is typically used when deploying a hierarchical control structure to compute the throttle and brake pedals pressing as it has been replaced with an inner loop PI controller. The performance also is comparable yet more conservative due to the simplification. These findings can become a good reference for designing and improving the ACC controller, as the framework can be easily generalized for any type of vehicle for future work.

Incorporation of mixed strawberry and acerola jam into Greek-style goat yogurt with autochthonous adjunct culture of Limosilactobacillus mucosae CNPC007: Impact on technological, nutritional, bioactive, and microbiological properties

This study aimed to assess the impact of adding strawberry and acerola jam, along with Limosilactobacillus mucosae CNPC007, on the technological, nutritional, bioactive, and microbiological properties of Greek-style goat yogurt. Six yogurt formulations were developed: without and with the addition of L. mucosae CNPC007 (CY and PY, respectively), and with 10 % and 15 % jam (CY10, CY15, PY10, and PY15, respectively). The inclusion of jam enriched the yogurt with phenolic compounds and significantly enhanced antioxidant activity, as measured by FRAP and ABTS assays. The highest values were observed after 28 days of storage in the PY15 formulation (0.177 ± 0.01 and 3.43 ± 0.01 µmol TEAC/g, respectively), compared to CY (0.013 ± 0.01 and 0.19 ± 0.01 µmol TEAC/g, respectively) and PY (0.010 ± 0.01 and 0.23 ± 0.01 µmol TEAC/g, respectively). This increase was likely driven by the presence of anthocyanins and flavonoids in the jam, as indicated by heatmap correlation analysis. DPI and EPI were also influenced by the addition of jam and L. mucosae CNPC007, with EPI increasing in the PY10 and PY15 formulations, reaching approximately 40 % after 28 days. The incorporation of jam resulted in a decrease in the L* (<90) and an increase in the b* (>14) color parameters. Additionally, jam-enriched formulations exhibited higher syneresis and lower water retention capacity (WRC) throughout storage compared to control formulations, with average syneresis exceeding 26 % and WRC falling below 75 % after 28 days. In general, all yogurt formulations showed a reduction in lactose, an increase in glucose and galactose, and the production of lactic acid during storage. The lower lactose content observed after 28 days of storage in the PY (0.84 ± 0.01 g/100 g), PY10 (0.82 ± 0.01 g/100 g), and PY15 (0.98 ± 0.01 g/100 g) formulations indicates active sugar metabolism by L. mucosae CNPC007. All formulations met microbiological safety standards, confirming their suitability for consumption. Formulations containing L. mucosae CNPC007 showed viable cell counts exceeding the minimum recommended to produce health benefits (>7 log CFU/g) throughout the 28-day refrigerated storage and after in vitro digestion. These findings underscore the potential of combining tropical fruit jams with probiotics to develop a multifunctional, value-added yogurt product that delivers substantial health benefits to consumers.

Image based Modeling and Control for Batch Processes

This manuscript addresses the problem of leveraging thermal images for modeling and feedback control, specifically tailored for terminal quality control of batch processes. The primary objective, common in many batch processes, is to produce products with quality variables aligning with user specifications, available for measurement only at batch termination, precluding the direct use of classical control strategies. Furthermore, in many instances, traditional online sensors such as thermocouples may not be available, but instead spectral inputs like thermal images or acoustic data may be more readily available for feedback control. The challenge is to not only use the non-traditional sensor data for building a dynamic model but also to use that model for terminal quality control. The proposed approach involves a multi-layered modeling strategy. Initially, a dimensionality reduction technique is employed to condense the high-dimensional image into a set of representative outputs. Subsequently, subspace identification (SSID) is applied to develop a Linear Time-Invariant (LTI) State Space (SS) model between the inputs and the reduced outputs. Finally, a Partial Least Squares (PLS) model is constructed linking the terminal states of a batch (identified using SSID) with the product qualities obtained for that specific batch. This model is then incorporated into a Model Predictive Control (MPC) formulation. The effectiveness of the MPC is illustrated by showcasing its capability to generate products of high quality by deploying the MPC on a bi-axial lab-scale rotational molding setup.

Effect of Nitrite-Embedded Packaging Film on Growth of Listeria monocytogenes in Nitrite-free and Conventionally-cured Bologna Sausage

Listeria monocytogenes is a pathogen frequently associated with ready-to-eat (RTE) meat and poultry products. Nitrite is a key antimicrobial additive that can offer some degree of protection against L. monocytogenes when included in meat product formulations. The objectives of this study were to determine the potential of nitrite-embedded film to affect the growth of L. monocytogenes following postthermal processing of conventionally-cured and nitrite-free bologna. Two bologna treatment formulations, a conventionally-cured control formulation (CON) and a nitrite-free formulation (UCC), were manufactured, packaged in conventional (CF) or nitrite-embedded (NEF) film, inoculated with 3.5 log CFU/cm2 of a cocktail of L. monocytogenes strains, and stored at 10 ± 1 °C. CON-NEF and UCC-NEF treatments had significantly slower (P < 0.05) growth of L. monocytogenes than CON-CF and UCC-CF, with populations in UCC-CF (which contained no nitrite) increasing by 3.4 logs after 10 d of storage in UCC-CF and 3.6 logs after 50 d in CON-CF (which had formulated nitrite only), while in the NEF-packaged samples, with or without formulated nitrite, they did not exceed the inoculum level until after day 40. Initial (day 0) residual nitrite was significantly greater (P < 0.05) in the control formulation. Packaging in NEF, however, resulted in an increase of 27–28 ppm by day 3, regardless of formulation, after which it decreased rapidly. Results suggest NEF can be used as a post-lethality antimicrobial intervention in food safety intervention strategies, in both cured and uncured processed meat products.

Insights into muscle metabolic energetics: Modelling muscle-tendon mechanics and metabolic rates during walking across speeds.

The metabolic energy rate of individual muscles is impossible to measure without invasive procedures. Prior studies have produced models to predict metabolic rates based on experimental observations of isolated muscle contraction from various species. Such models can provide reliable predictions of metabolic rates in humans if muscle properties and control are accurately modeled. This study aimed to examine how muscle-tendon model individualization and metabolic energy models influenced estimation of muscle-tendon states and time-series metabolic rates, to evaluate the agreement with empirical data, and to provide predictions of the metabolic rate of muscle groups and gait phases across walking speeds. Three-dimensional musculoskeletal simulations with prescribed kinematics and dynamics were performed. An optimal control formulation was used to compute muscle-tendon states with four levels of individualization, ranging from a scaled generic model and muscle controls based on minimal activations, inclusion of calibrated muscle passive forces, personalization of Achilles and quadriceps tendon stiffnesses, to finally informing muscle controls with electromyography. We computed metabolic rates based on existing models. Simulations with calibrated passive forces and personalized tendon stiffness most accurately estimate muscle excitations and fiber lengths. Interestingly, the inclusion of electromyography did not improve our estimates. The whole-body average metabolic cost was better estimated with a subset of metabolic energy models. We estimated metabolic rate peaks near early stance, pre-swing, and initial swing at all walking speeds. Plantarflexors accounted for the highest cost among muscle groups at the preferred speed and were similar to the cost of hip adductors and abductors combined. Also, the swing phase accounted for slightly more than one-quarter of the total cost in a gait cycle, and its relative cost decreased with walking speed. Our prediction might inform the design of assistive devices and rehabilitation treatment. The code and experimental data are available online.

EVALUATING THE EFFICACY OF CITRONELLA ESSENTIAL OIL (Cymbopogon nardus) AS A CONTROL AGENT FOR WAREHOUSE RICE WEEVIL (Sitophilus oryzae)

Sitophilus oryzae or rice weevil is a primary pest of rice that is very detrimental. Pest control that is usually carried out is fumigation using phosphine gas and fumigation using methyl bromide. The use of insecticides has several negative impacts on humans and the environment, so it is necessary to control pests naturally, namely using citronella essential oil. Citronella essential oil contains high levels of citronella and geraniol compounds and these compounds are contact toxic and antifeedant against insects. This research aims to determine the effect of citronella essential oil on mortality using the fumigation method and the response of rice lice to citronella essential oil in the flourdisc bioassay test. This research was carried out at the insect pest control and biodetriosation and formulation laboratory, using a completely randomized plan. The results showed that citronella oil was classified as effective in controlling the population of S. oryzae with a mortality of 41% using fumigation method and had anti-feedant properties compared to the control in the flour disk assay test. In the flourdisc bioassay method, the percentage of 2 gr/L influences the low relative growth rate, relative consumption rate and conversion efficiency of consumed food and the food prevention index continues to increase. Citronella essential oil has potential and effectiveness as a control for the warehouse pest rice weevil (Sitophilus oryzae).

Identification of influencing factors and risk assessment of underground space flooding in the mountain city

As a consequence of the process of urbanization, there is an increasing reliance on and exploitation of underground spaces. Moreover, these areas are susceptible to urban waterlogging, which can be difficult to drain, potentially leading to significant risks. At present, there are few simulations in hydrodynamic models that consider underground spaces. The risk of inundation of underground spaces remains an uncertain phenomenon. This study conceptualized underground spaces as storage areas, with the aim of simulating the spatial distribution of flood risk for different return periods. We studied the flooding processes and characteristics of three underground space types. The results indicate that the flood evolution simulated by the simplified modeling method that incorporates underground space is more aligned with the actual situation. To further analyze the risk distribution of urban waterlogging, we choose the XGBoost model and SHapley Additive exPlanations (SHAP) method to assess the influence of specific indicators on the occurrence of urban waterlogging in mountainous regions. Our analysis revealed that key factors include density of road (DR), flow velocity (V), density of pipes (DP), elevation (DEM), and inundation height (H), with contribution rates of 23.13 %, 17.06 %, 14.67 %, 10.12 %, and 9.04 %, respectively. This analysis clarified the risk of underground inundation within the study area, which can serve as a reference point for the formulation of flood control and drainage strategies.

Formulating iron ore pellet induration process in an industrial straight grate system: Real-time experimentation and validation

Understanding the complex process of iron ore pellet induration is crucial in a straight grate system in the steelmaking industry. There is no attempt made so far to predict the behavior of this unit considering the physiochemical processes (drying, carbon combustion and limestone calcination) along with the heat transfer within the pellet, and between the hot gas and pellet. Moreover, the reported models are validated mainly with the pot test data. To address these research gaps, in this contribution, a rigorous model framework is proposed for an industrial induration unit considering all these above-mentioned issues together with some other practical aspects, including the heat transfer from hot gas to grate bar and heat loss due to air leakage into the system. To validate this rigorous formulation, attempt is further made to perform the real-time experimentation with induration system equipped with a thermocar. It is shown first time that the predicted temperature profiles of the pellets, grate bar and exit gas associated with the running bed are consistent with the plant data. The fuel consumption data is further obtained to investigate the performance of the proposed formulation at different operating regimes. It is observed that the mean absolute percentage error (MAPE) between the measured and predicted fuel rates is reasonably low (i.e., 4.2%). With this, it is recommended to use the proposed formulation for online property prediction, process design, optimization, troubleshooting, control and scale-up of the induration unit.

Thruster-Pointing-Constrained Optimal Control for Satellite Servicing Using Indirect Optimization

Future space missions such as in-space assembly of telescopes and on-orbit servicing require rendezvous and proximity operations trajectories that avoid thruster-induced contamination of delicate components onboard the client spacecraft. We present a novel technique to incorporate a hard thruster pointing constraint into the indirect optimal control formulation and solve the problem using a single-shooting method. A thruster pointing constraint is an inequality constraint that imposes a limit on the angular range over which a spacecraft thruster is permitted to operate, thus mitigating plume contamination during rendezvous and proximity operations. Through novel incorporation of the constraint directly into the dynamic model, the problem can be easily solved with no a priori knowledge of the burn sequence or information about when the constraint is active or inactive. Our formulation is capable of handling a constant thruster pointing constraint as well as one that varies as a function of distance from the target spacecraft. Results are presented under Clohessy–Wiltshire dynamics; however, the method can be easily extended to handle nonlinear dynamic systems. As expected, we see an increase in fuel consumption with increasing constraint angle for the solution of problems with the same boundary conditions and time of flight. To validate our method, we compare the performance and results to those of a direct method, sequential convex optimization, utilizing the CVX MATLAB plug-in and the MOSEK solver. We found that our approach converged more easily and required no hand-tuning of parameters. It also converged to solutions that satisfy the pointing constraints to a stricter tolerance. We anticipate that our novel approach to generating thruster-pointing-constrained fuel-optimal trajectories will be enabling to a host of future servicing space missions.

Osteoblastic Cell Sheet Engineering Using P(VCL-HEMA)-Based Thermosensitive Hydrogels Doped with pVCL@Icariin Nanoparticles Obtained with Supercritical CO2-SAS.

New clinical strategies for treating severe bone and cartilage injuries are required, especially for use in combination with implant procedures. For this purpose, p(VCL-co-HEMA) thermosensitive hydrogels have been activated with icariin-loaded nanoparticles to be used as bone-cell-harvesting platforms. Supercritical CO2-SAS technology has been applied to encapsulate icariin, a small molecule that is involved in osteoblastic differentiation. Thus, physical-chemical analysis, including swelling and transmittance, showed the impact of HEMA groups in hydrogel composition. Moreover, icariin (ICA) release from p(VCL-co-HEMA) platforms, including pVCL@ICA nanoparticles, has been studied to evaluate their efficacy in relevant conditions. Finally, the thermosensitive hydrogels' cell compatibility, transplant efficiency, and bone differentiation capacity were tested. This study identifies the optimal formulations for icariin-activated hydrogels for both control and HEMA formulations. Using this technique, osteoblastic sheets that were rich in collagen type I were successfully transplanted and recultivated, maintaining an optimal extracellular matrix (ECM) composition. These findings suggest a new cell-sheet-based therapy for bone regeneration purposes using customized and NP-activated pVCL-based cell platforms.