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OBJECTIVES: The control chart is a classic statistical technique in epidemiology for identifying trends, patterns, or alerts. One meaningful use is monitoring and tracking Infant Mortality Rates, which is a priority both domestically and for the World Health Organization, as it reflects the effectiveness of public policies and the progress of nations. This study aims to evaluate the applicability and performance of this technique in Brazilian cities with different population sizes using infant mortality data. RESULTS: In this article, we evaluate the effectiveness of the statistical process control chart in the context of Brazilian cities. We present three categories of city groups, divided based on population size and classified according to the quality of the analyses when subjected to the control method: consistent, interpretable, and inconsistent. In cities with a large population, the data in these contexts show a lower noise level and reliable results. However, in intermediate and small-sized cities, the technique becomes limited in detecting deviations from expected behaviors, resulting in reduced reliability of the generated patterns and alerts.

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This research proposes advanced model-based control strategies for a countercurrent flow plate heat exchanger in a virtual environment. A virtual environment with visual and auditory effects is designed, which requires a mathematical model describing the real dynamics of the process; this allows parallel fluid movement in different directions with hot and cold temperatures at the outlet, incorporating control monitoring interfaces as communication links between the virtual heat exchanger and control applications. A multivariable and non-linear process like the plate and countercurrent flow heat exchanger requires analysis in the controller design; therefore, this work proposes and compares two control strategies to identify the best-performing one. The first controller is based on the inverse model of the plant, with linear algebra techniques and numerical methods; the second controller is a model predictive control (MPC), which presents optimal control actions that minimize the steady-state errors and aggressive variations in the actuators, respecting the temperature constraints and the operating limits, incorporating a predictive model of the plant. The controllers are tested for different setpoint changes and disturbances, determining that they are not overshot and that the MPC controller has the shortest settling time and lowest steady-state error.

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Conveyor belts serve as the primary mode of ore transportation in mineral processing plants. Feeders, comprised of shorter conveyors, regulate the material flow from silos to longer conveyor belts by adjusting their velocity. This velocity manipulation is facilitated by automatic controllers that gauge the material weight on the conveyor using scales. However, due to positioning constraints of these scales, a notable delay ensues between measurement and the adjustment of the feeder speed. This dead time poses a significant challenge in control design, aiming to prevent oscillations in material levels on the conveyor belt. This paper contributes in two key areas: firstly, through a simulation-based comparison of various control techniques addressing this issue across diverse scenarios; secondly, by implementing the Smith predictor solution in an operational plant and contrasting its performance with that of a single PID controller. Evaluation spans both the transient flow rate during step change setpoints and a month-long assessment. The experimental results reveal a notable increase in production by 355 t/h and a substantial reduction in flow rate oscillations on the conveyor belt, evidenced by a 55% decrease in the standard deviation.

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A process control agent is an organic additive used to regulate the balance between fracturing and mechanical kneading, which control the size of the as-milled particles. Tributyl phosphate (TBP) is evaluated to act as surface modifier of PbTe, and it is compared with the results obtained using formaldehyde (CH2O). In order to elucidate the nature of the interaction between TBP and the PbTe surface, global and local descriptors were calculated via the density functional theory. First, TBP and CH2O molecules are structurally optimized. Then, vertical ionization energies as well as vertical electron affinities are calculated to elucidate how both molecules behave energetically against removal and electron gain, respectively. The results were compared with those obtained from the electrostatic potential mapped on the van der Waals isosurface. It is inferred that the theoretical insights are useful to propose adsorption modes of TBP and CH2O on the PbTe surface, which are usable to rationalize the facets exposed by PbTe after the surface treatment. The optimized structures of the compound systems showed a close correlation between the surface energy shift (Δγ) and the PbTe facets exhibited. Finally, a Wulff construction was built to compare the usage of TBP and CH2O molecules in PbTe morphology.

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Harvesting is one of the most important stages of the agricultural production process. However, the lack of monitoring during this operation and the absence of efficient methodologies to quantify losses have contributed to the decline in the quality of the operation. The objective of this study was to monitor mechanized soybean harvest by quantifying losses through two methodologies using statistical process control. The study was conducted in March 2016 in an agricultural area in the municipality of Ribeirão Preto, SP, using a John Deere harvester model 1470 with a tangential-type track system and separation by a straw-blower. The experimental design followed the standards established by statistical process control, and every 8 min of harvest, the total losses by the circular framework and rectangular framework methodologies were simultaneously quantified, totaling 40 points. Data were analyzed using descriptive statistics and statistical process control. The averages of the circular methodology framework were values above those found in the rectangular methodology framework, presenting greater representativeness of losses. The process was considered unable to maintain losses of soybeans at acceptable levels during mechanical harvest throughout the operation of the two frameworks. The circular framework for collecting samples at different locations resulted in higher reliability of data.

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Illusion of control (IOC) is a bias in the judgment of personal success with implications to learning theories and health policies; some important questions in the investigation of IOC may be related to traditional measures in the field, namely self-assessment using Likert scales about the sense of control. Statistical process control (SPC) and Shewhart charts are methods developed to monitor and control industrial processes, never applied in psychological studies before. The present two studies investigated the use of the technique of Shewhart charts in the analysis of IOC. The purpose was to explore the use of SPC and Shewhart charts in the analysis of data sequences from psychological experiments; the objective was to analyze the results of reaction time (RT) data sequences plotted in SPC charts, in comparison with self-assessment judgments from an IOC task. Participants were 63 undergraduate students (Study 1) and 103 mine workers (Study 2) instructed to try to control a traffic light on a computer by pressing or not the keyboard. Higher probabilities of the successful outcome generated judgments of illusion and shifts (due to cognitive activity) in the charts of RT; lower probabilities resulted in null illusion and RT presented a random and stable profile. Patterns for different groups emerged in Shewhart charts. SPC can contribute to the analysis of the behavior of sequences of data in psychological studies, so that the charts indicate changes and patterns not detected by traditional ANOVA and other linear models.

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This paper addresses the observability analysis and observer design for a nonlinear interacting three-tank system. The plant configuration is first described using the process and instrumentation diagram (P&ID) and a state-space realization is derived; some insights about the behavior of the nonlinear system, considering equilibrium points and the phase portrait are provided. Then, observability in the Hermann-Krener sense is analyzed. A high-gain observer (HGO) is then designed, using the equivalence of the original state-space realization with its observability canonical form, in order to guarantee convergence of the state estimation. The performance was validated through simulation and experiments in a multipurpose plant equipped with real sensors; the HGO response was compared to a Luenberger observer (for a linear approximation of the plant) and the Extended Kalman Filter (for which convergence is not guaranteed), considering nonlinearities, interaction, disturbances and noise. Theoretical and experimental results show that the HGO can provide robust estimation and disturbance rejection, despite the sensitivity of HGOs to noisy variables in processes such as level of liquids.

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2-methyl-5,6,7,8-tetrahydro-2H-chromen-4(3H)-one (called 6-oxo) is presented as a new AI-1 quorum sensing inhibitor for Vibrio harveyi. The development of a chemical process to afford traceable materials for new biological assays demands the development of analytical methods to ensure their purity and quality. This work describes the use of quantitative 1 H nuclear magnetic resonance (NMR) spectroscopy (qNMR) to assess the purity of a sample of 6-oxo (99.88%) and a sample of its major process impurity (E)-1-(2-hydroxycyclohex-2-en-1-yl)but-2-en-1-one (called HCB; 98.28%). To explore the scope of the use of qNMR to quantify the amount of low-content components in samples related to the chemical process for 6-oxo synthesis, this work also determined the amount of 6-oxo in two HCB samples: (a) the high-purity HCB sample described above and (b) a crude HCB sample collected during the chemical process. Despite the complexity of the crude sample, the amount of 6-oxo was readily assessed and could help to estimate the extent to which 6-oxo was already formed during the HCB synthesis. This information can help the understanding of how the process parameters can be modified to improve the performance of the whole process, by controlling the reaction mechanisms working at each step of this chemical process. In this context, our results reinforce qNMR as a complementary analytical tool for the quantification of the main component found in a sample, contributing to the standardization of reference materials and thus allowing the development of analytical methods for process control and traceability of the samples used for biological assays.

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RESUMEN En el presente trabajo se expone la evolución del proceso de irradiación en Cuba, los principales resultados científico-técnicos e impactos alcanzados hasta la actualidad y las perspectivas de estas aplicaciones, así como la recuperación de las capacidades de irradiación existentes en el país, el control del proceso de irradiación, gestión de la calidad del proceso y los aspectos normativos establecidos.

ABSTRACTS The present paper deals with the evolution of radiation processing in Cuba, its main scientific results and impact up to now and the perspectives of these applications, as well as the recovery of the irradiation capacities existing in the country, the radiation process control, quality management in the mentioned radiation process and the established regulatory aspects.

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This paper proposes the use of the Statistical Process Control (SPC), more specifically, the Exponentially Weighted Moving Average method, for the monitoring of drivers using approaches based on the vehicle and the driver's behavior. Based on the SPC, we propose a method for the lane departure detection; a method for detecting sudden driver movements; and a method combined with computer vision to detect driver fatigue. All methods consider information from sensors scattered by the vehicle. The results showed the efficiency of the methods in the identification and detection of unwanted driver actions, such as sudden movements, lane departure, and driver fatigue. Lane departure detection obtained results of up to 76.92% (without constant speed) and 84.16% (speed maintained at ≈60). Furthermore, sudden movements detection obtained results of up to 91.66% (steering wheel) and 94.44% (brake). The driver fatigue has been detected in up to 94.46% situations.

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Tanneries are industries that may cause high environmental impact. Consequently, they are responsible for generating a large amount of wastewater with high concentrations of contaminants that require significant investment and operating costs in their treatment in order to accomplish the emission standards required by environmental legislation. This work has as main objective to minimize the environmental impact of the water used by tanneries through the study of reuse possibilities of wastewater tanning floats. The major concern is related to the pollutant chromium in the environment, since it is the tanning product that gives the best characteristics to leather and consequently the most used product. The reuse tests were performed on pilot and industrial scales. During the experiments, the following process control parameters were evaluated: pH, density, acid-base indicators for hide and shrinkage temperature. To validate the water reuse in tanneries, samples of wet-blue leather and residual floats were collected from pilot and industrial processes to perform chemical analyses to prove the validity of the process with reuse. Research has shown that reuse techniques, when properly evaluated, can be used in industries. In addition to reducing water demand, the reuse of wastewater in tanning processes minimizes the disposal of the wastewater with chromium and uses the residual chromium float.

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O controle microbiológico durante a produção de preparações farmacêuticas é de grande importância para garantir a qualidade do produto final, quanto às propriedades terapêuticas e de segurança ao paciente. O monitoramento ambiental é uma valiosa ferramenta como forma de mensurar a efetividade das medidas que integram a estratégia de controle de contaminação microbiana. Neste contexto, pouco destaque tem sido dado à manufatura de produtos farmacêuticos não-estéreis, por representarem as classes cujos riscos de contaminação microbiana são menores, quando comparados aos produtos parenterais. Dessa maneira, este estudo teve como objetivo caracterizar os isolados microbianos de amostras de ar ativo e passivo e de superfícies de áreas produtivas não-estéreis. Ainda, visou-se avaliar estatisticamente os dados de monitoramento ambiental, como base para o desenvolvimento de uma abordagem para determinação de limites de alerta e ação. Os resultados obtidos revelaram que a maioria dos microrganismos encontrados são de origem humana, seguidos por bactérias e fungos provenientes do solo. As diferenças sazonais foram observadas, principalmente, para a ocorrência de fungos, mais prevalentes no período seco. Foi desenvolvida uma abordagem estatística baseada em (1) determinação de subgrupos racionais, (2) avaliação da distribuição estatística e (3) determinação de limites, utilizando, como critério, o índice de capacidade do processo (Cpk). Um melhor entendimento do perfil microbiano das áreas produtivas e a determinação de limites de acordo com a distribuição real dos dados levará à destinação dos recursos necessários a ações que visem a qualidade do produto e a segurança do paciente

The microbiological control during the production of pharmaceutical preparations is of great importance for quality assurance of the final product regarding to therapeutic properties and patient safety. Environmental monitoring is a valuable tool to measure the effectiveness of the actions that integrate the microbial contamination control strategy. In this context, little attention has been given to the manufacture of non-sterile pharmaceutical products, because they represent classes whose microbial contamination risks are lower when compared to parenteral products. Considering this scenario, this study aimed to characterize microbial isolates from surfaces, active and passive air sampling of non-sterile manufacturing areas. Furthermore, it was expected to statistically evaluate the environmental monitoring data, as a basis for the development of an approach for determining alert and action limits. The results showed that most of the microorganisms found are from human source, followed by bacteria and fungi typically found in the soil. The seasonal differences were mainly observed for fungi recovery, which were more prevalent in the dry period. A statistical approach was developed based on (1) the determination of rational subgroups, (2) evaluation of the statistical distribution and (3) limit determination, using the process capacity index (Cpk) as criteria. A better understanding of the typical manufacturing areas microbial profile and the determination of limits according to the actual data distribution will lead to the allocation of the necessary resources to actions focusing on product quality and patient safety

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Tissue engineering and the manufacturing of regenerative medicine products demand strict control over the production process and product quality monitoring. In this chapter, the application of process systems engineering (PSE) approaches in the production of cell-based products has been discussed. Mechanistic, empirical, continuum and discrete models are compared and their use in describing cellular phenomena is reviewed. In addition, model-based optimization strategies employed in the field of tissue engineering and regenerative medicine are discussed. An introduction to process control theory is given and the main applications of classical and advanced methods in cellular production processes are described. Finally, new nondestructive and noninvasive monitoring techniques have been reviewed, focusing on large-scale manufacturing systems for cell-based constructs and therapeutic products. The application of the PSE methodologies presented here offers a promising alternative to overcome the main challenges in manufacturing engineered tissue and regeneration products.

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Health Level Seven (HL7) is one of the standards most used to centralize data from different vital sign monitoring systems. This solution significantly limits the data available for historical analysis, because it typically uses databases that are not effective in storing large volumes of data. In industry, a specific Big Data Historian, known as a Process Information Management System (PIMS), solves this problem. This work proposes the same solution to overcome the restriction on storing vital sign data. The PIMS needs a compatible communication standard to allow storing, and the one most commonly used is the OLE for Process Control (OPC). This paper presents a HL7-OPC Server that permits communication between vital sign monitoring systems with PIMS, thus allowing the storage of long historical series of vital signs. In addition, it carries out a review about local and cloud-based Big Medical Data researches, followed by an analysis of the PIMS in a Health IT Environment. Then it shows the architecture of HL7 and OPC Standards. Finally, it shows the HL7-OPC Server and a sequence of tests that proved its full operation and performance.

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This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time.

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ABSTRACT For the release of pharmaceutical products into the drug market; most of the pharmaceutical companies depend on acceptance criteria - that are set internally, regulatory and/or pharmacopeially. However, statistical process control monitoring is underestimated in most quality control in cases; although it is important not only for process stability and efficiency assessment but also for compliance with all appropriate pharmaceutical practices such as good manufacturing practice and good laboratory practice, known collectively as GXP. The current work aims to investigate two tablet inspection characteristics monitored during in-process control viz. tablet average weight and hardness. Both properties were assessed during the compression phase of the tablet and before the coating stage. Data gathering was performed by the Quality Assurance Team and processed by Commercial Statistical Software packages. Screening of collected results of 31 batches of an antibacterial tablet - based on Fluoroquinolone -showed that all the tested lots met the release specifications, although the process mean has been unstable which could be strongly evident in the variable control chart. Accordingly, the two inspected processes were not in the state of control and require strong actions to correct for the non-compliance to GXP. What is not controlled cannot be predicted in the future and thus the capability analysis would be of no value except to show the process capability retrospectively only. Setting the rules for the application of Statistical Process Control (SPC) should be mandated by Regulatory Agencies.

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A distillation device that acquires continuous and synchronized measurements of temperature, percentage of distilled fraction and NIR spectra has been designed for real-time monitoring of distillation processes. As a process model, synthetic commercial gasoline batches produced in Brazil, which contain mixtures of pure gasoline blended with ethanol have been analyzed. The information provided by this device, i.e., distillation curves and NIR spectra, has served as initial information for the proposal of new strategies of process modeling and multivariate statistical process control (MSPC). Process modeling based on PCA batch analysis provided global distillation trajectories, whereas multiset MCR-ALS analysis is proposed to obtain a component-wise characterization of the distillation evolution and distilled fractions. Distillation curves, NIR spectra or compressed NIR information under the form of PCA scores and MCR-ALS concentration profiles were tested as the seed information to build MSPC models. New on-line PCA-based MSPC approaches, some inspired on local rank exploratory methods for process analysis, are proposed and work as follows: a) MSPC based on individual process observation models, where multiple local PCA models are built considering the sole information in each observation point; b) Fixed Size Moving Window - MSPC, in which local PCA models are built considering a moving window of the current and few past observation points; and c) Evolving MSPC, where local PCA models are built with an increasing window of observations covering all points since the beginning of the process until the current observation. Performance of different approaches has been assessed in terms of sensitivity to fault detection and number of false alarms. The outcome of this work will be of general use to define strategies for on-line process monitoring and control and, in a more specific way, to improve quality control of petroleum derived fuels and other substances submitted to automatic distillation processes monitored by NIRS.

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In recent years, interest for petrochemical processes has been increasing, especially in refinement area. However, the high variability in the dynamic characteristics present in the atmospheric distillation column poses a challenge to obtain quality products. To improve distillates quality in spite of the changes in the input crude oil composition, this paper details a new design of a control strategy in a conventional crude oil distillation plant defined using formal interaction analysis tools. The process dynamic and its control are simulated on Aspen HYSYS® dynamic environment under real operating conditions. The simulation results are compared against a typical control strategy commonly used in crude oil atmospheric distillation columns.

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Enteric viruses are pathogens associated with food- and waterborne outbreaks. The recovery of viruses from food or water samples is affected by the procedures applied to detect and concentrate them. The incorporation of an internal process control virus to the analyses allows monitoring the performance of the methodology. The aim of this study was to produce a recombinant adenovirus (rAdV) and apply it together with bacteriophage PP7 as process controls. The rAdV carries a DNA construction in its genome to differentiate it from wild-type adenovirus by qPCR. The stability of both control viruses was evaluated at different pH conditions. The rAdV was stable at pH 3, 7, and 10 for 18 h. PP7 infectious particles were stable at pH 7 and showed a 2.14 log reduction at pH 10 and total decay at pH 3 after 18 h. Three virus concentration methods were evaluated: hollow-fiber tap water ultrafiltration, wastewater ultracentrifugation, and elution-PEG precipitation from lettuce. Total and infectious viruses were quantified and their recoveries were calculated. Virus recovery for rAdV and PP7 by ultrafiltration showed a wide range (2.10-84.42 and 13.54-84.62%, respectively), whereas that by ultracentrifugation was 5.05-13.71 and 6.98-13.27%, respectively. The performance of ultracentrifugation to concentrate norovirus and enteroviruses present in sewage was not significantly different to the recovery of control viruses. For detection of viruses from lettuce, genomic copies of PP7 were significantly more highly recovered than adenovirus (14.74-18.82 and 0.00-3.44%, respectively). The recovery of infectious virus particles was significantly affected during sewage ultracentrifugation and concentration from lettuce. The simultaneous use of virus controls with dissimilar characteristics and behaviors might resemble different enteric viruses.

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Background: The effect of diverse oxygen transfer coefficient on the L-erythrulose production from meso-erythritol by a newly isolated strain, Gluconobacter kondonii CGMCC8391 was investigated. In order to elucidate the effects of volumetric mass transfer coefficient (K La) on the fermentations, baffled and unbaffled flask cultures, and fed-batch cultures were developed in present work. Results: With the increase of the K La value in the fed-batch culture, L-erythrulose concentration, productivity and yield were significantly improved, while cell growth was not the best in the high K La. Thus, a two-stage oxygen supply control strategy was proposed, aimed at achieving high concentration and high productivity of L-erythrulose. During the first 12 h, Klawas controlled at 40.28 h-1 to obtain high value for cell growth, subsequently K La was controlled at 86.31 h-1 to allow for high L-erythrulose accumulation. Conclusions: Under optimal conditions, the L-erythrulose concentration, productivity, yield and DCW reached 207.9 ± 7.78 g/L, 6.50 g/L/h, 0.94 g/g, 2.68 ± 0.17 g/L, respectively. At the end of fermentation, the L-erythrulose concentration and productivity were higher than those in the previous similar reports.

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