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Supplementary Material for an article submission to Processes (MDPI):Figure S1:Response surface plots for the recovery of xylosaccharides depending on the different variables studied: (a) Moisture content and time, (b) Moisture content and temperature, and (c) Time and temperature.Figure S2:Surfaces Plot for hydrolysis efficiency and glucan conversion depending on the different variables studied: (a) moisture content and time, (b) moisture content and temperature, and (c) time and temperature for hydrolysis efficiency, (d) moisture content and time, (e) moisture content and temperature, and (f) time and temperature for glucan conversion.Figure S3: Variation of hydrolyzed glucose produced from 100 g sawdust with respect to xylan removal after steam explosion. Figure S4:(a) Solids recovery, (b) final glucose concentration, (c) hydrolysis efficiency and (d) glucan conversion efficiency vs. pretreatment severity (S0).Table S1: Standardized models obtained for solid recovered, final glucose concentration, hydrolysis efficiency and glucan conversion efficiency. Figure S5:Pareto chart of standardized effects for (a) xylosaccharides recovery, (b) hydrolysis efficiency, and (c) and glucan conversion efficiency.;Figure S6:Experimental glucan efficiency conversion of exploded solids vs. model predicted values (Equation 2).

Research predominantly focuses on problematic behaviors in children with symptoms of attention-deficit/hyperactivity disorder (ADHD) to explain why they are disliked by their classroom peers. By contrast, the current study explores characteristics of peers that are associated with them disliking classmates with ADHD symptoms. To do so, we undertook a novel methodological approach using hierarchical linear modeling to examine the strength of the association between child characteristics, their sociometric ratings given to classmates, and the recipients’ ADHD symptom levels. Participants were 194 children (Grades K–4) in 12 classrooms. Using the sociometric method, children rated their liking versus disliking of each classmate. Children’s ADHD symptoms were reported by the teacher. Children’s self-reported stigma about ADHD, their own sociometric ratings received, and teacher ratings of children’s academic competence were collected. Results suggested that children who reported more stigma about ADHD, and who were more socially and academically competent, had a stronger negative association between the sociometric ratings they gave and the recipients’ ADHD symptoms (i.e., were more likely to dislike classmates with ADHD symptoms). These effects were strongest at the end of the academic year relative to the beginning of the year. Implications for interventions targeting the peer group are discussed.

Advances in cashless technologies create a dilemma for gambling regulators. Research indicates that cash purchases entail a ‘pain of paying’ that is attenuated with more abstract forms of payment, yet limited research has directly tested the impact of mode of payment on gambling behavior. Across two experiments, community-recruited gamblers were randomized to use an authentic slot machine in the laboratory, under different conditions of monetary endowment. In Experiment 1 (n = 61), participants were endowed with funds to play the slot machine, in either a cash or voucher format. In Experiment 2 (n = 48), participants acquired the cash endowment as a windfall or from an earning task. In session-level analyses, bet size and bet volume did not vary as a function of monetary condition. In more sensitive trial-level analyses, no interactions involving the monetary manipulations were consistent across the two experiments. Data from both experiments indicated faster spin initiation latencies as a function of losing streak length, and slower spin initiation latencies and larger bet size as a function of the prior win magnitude. These trial-level analyses show systematic influences on gambling behavior in the laboratory environment, supporting the basic sensitivity of our design. Overall, our data provide weak evidence for the hypothesis that monetary factors influence gambling tendencies. Acknowledging the possibility of the null hypothesis, these data also highlight the methodological challenges with manipulating monetary value in gambling research, including the use of endowed funds, and controlling for sources of variability when using authentic slot machines.

The development and sustainability of second-generation biorefineries are essential for the production of high added value compounds and biofuels and their application at the industrial level. Pretreatment is one of the most critical stages in biomass processing. In this specific case, hydrothermal pretreatments (liquid hot water [LHW] and steam explosion [SE]) are considered the most promising process for the fractionation, hydrolysis and structural modifications of biomass. This review focuses on architecture of the plant cell wall and composition, fundamentals of hydrothermal pretreatment, process design integration, the techno-economic parameters of the solubilization of lignocellulosic biomass (LCB) focused on the operational costs for large-scale process implementation and the global manufacturing cost. In addition, profitability indicators are evaluated between the value-added products generated during hydrothermal pretreatment, advocating a biorefinery implementation in a circular economy framework. In addition, this review includes an analysis of environmental aspects of sustainability involved in hydrothermal pretreatments.

Life cycle assessments of fuel bioethanol produced in Uruguay from liquid hot water pretreated switchgrass were performed for two scenarios: the production of ethanol and electricity and a biorefinery producing ethanol, electricity, furfural, acetic, and formic acid. Experimental data and material and energy balances derived from the simulations were used to analyze the global warming potential of fuel bioethanol. Greenhouse gas (GHG) emissions in both scenarios were lower than the reference emissions for fossil fuel. The biorefinery scenario had a better performance in terms of environmental impacts, and the biofuel produced met GHG reduction requirements. Switchgrass composition, enzyme dosage, fermentation and hydrolysis efficiency, and solids content had a significant effect on environmental performance, with enzyme use being the most significant factor. A multi-objective optimization was used to find the values of solid content and enzyme dose that minimize GHG emissions and the minimum ethanol selling price (MESP). An enzyme dosage of 37 mgprotein/gglucan and solids content of 21% w/w were the optimal conditions for bioethanol production with an associated GHG value of 2 ± 5 g CO2 eq./MJethanol and a MESP of $0.84/L.

Modern kraft pulp mills generate solid waste of 1–2% of incoming debarked wood. Given the size of these plants, with an annual production capacity of at least 1000,000 tons, each plant generates 20,000–30,000 dry tons of waste per year. The largest current use of these residues is for combustion in biomass boilers for steam and power generation. However, the conversion of biomass into biofuels and chemicals is gaining interest due to increasing demands for energy, limited sources of fossil fuels, and growing concerns about the environmental impact of greenhouse gas emissions. This chapter shows the laboratory-scale results of the use of eucalyptus wood wastes to obtain cellulose pulp by alkali pulping reinforced with hydrogen peroxide to obtain alkaline peroxide mechanical pulp or cellulosic bioethanol. Based on the results, an industrial-scale techno-economic analysis of the processes is presented and compared with current alternatives for energy generation.

SOFC-GT hybrid systems can be a good solution for small-medium size applications of distributed generation thanks to their high efficiency and their high fuel flexibility. Fueling these systems with raw biogas coming from biomass gasification makes them also completely renewable, but it introduces a high variability of performance due to the syngas composition fluctuations. For this reason, this work pursues the aim of realizing a robust system optimization, necessary to obtain the best design and ensure high efficiency combined with low variability. To do this, a co-flow, planar, anode supported SOFC Simulink model was used. Moreover, a related surrogate model was created to decrease the computational time and increase exponentially the number of simulations. To calculate the robust optimum design, the Monte Carlo method was used, simulating the syngas composition distribution with 2000 points and to the operating envelope with 5000 input combinations. Mean value and standard deviation in system efficiency were used to select a Pareto front. The robust points turned out to be those with low electric load, small-medium pressure, and high temperature, while maximum efficiency points were characterized by higher pressure levels. The smaller standard deviation at lower pressure was shown to be linked to the bottoming cycle operation and in particular to the gas turbine off-design condition. This difference between the two design conditions (robust optimum and efficiency optimum) confirmed the importance of this optimization process and the influence of fuel composition on system performance.

Eucalyptus sawdust is a residue from the pulp industry, currently used for energy production. Organosolv and autohydrolysis pretreatments for integrated valorization of this residue within a biorefinery approach was investigated. Organosolv pretreatment was used for selectively extract lignin, and autohydrolysis pretreatment was effective for hemicellulose solubilization. Glucose production of 33.7 g/100 geucalyptus was achieved after organosolv pretreatment, while dissolving 6.4 g/100 geucalyptus of xylan-derived sugars and recovering 10.3 g/100 geucalyptus of lignin after precipitation. After autohydrolysis pretreatment, glucose production of 32.3 g/100 geucalyptus was reached, while 7.5 g/100 geucalyptus of xylan-derived sugars and 2.7 g/100 geucalyptus of acetyl groups were effectively dissolved in a separate liquid stream. Non-ionic surfactant (PEG 6000) was used to enhance cellulose hydrolysis. Integration of a suitable pretreatment and enzymatic hydrolysis steps was shown to be a feasible strategy for the co-production of different value-added products (lignin, xylose, xylo-oligomers, acetic acid), towards a cost-effective eucalyptus biorefinery.

Butanol is an important bulk chemical and considered an advanced biofuel with better properties than ethanol. It can be produced by acetone–butanol–ethanol (ABE) or isopropanol-butanol-ethanol (IBE...

The cost-effectiveness of turbomachinery is a key aspect within the small-size compressor market. For this reason, Tesla turbomachinery, invented by Nikola Tesla in 1913, could be a good solution, particularly for low volumetric flow applications, where volumetric compressors are usually used. It consists of a bladeless rotor which stands out for its ease of construction and its ability to maintain almost the same performance as size decreases. One of its advantages is that it can run either as a turbine or as a compressor with minor modifications at the stator. The objective of this paper is to investigate a 3kW Tesla compressor, which design was derived from an analogous Tesla expander prototype (59% isentropic efficiency from the numerical study), by conducting a computational fluid dynamic analysis for different disk gaps and diffuser configurations. The potential of the Tesla compressor is shown to be quite promising, with a peak isentropic efficiency estimated at 53%. Although bladeless compressor is a simple turbomachinery device, different parts i.e., diffuser, tip clearance, and volute need to be optimized. Utilizing computational fluid dynamics algorithms, different disk gaps and different diffusers are simulated in order to increase the overall performance of the compressor and understand the flow dynamic behavior behind this technology. The dimensionless Ekman number is used to express the optimum disk space of the compressor rotor. Thus, the overall performance of the Tesla compressor is improved by 5–10% points compared to the initial model. Simultaneously, diffuser optimization strategies are applied and proved that there is a direct impact on the optimum design conditions, improving the pressure ratio at high mass flow rates.

Dynamic compressors operating region is mainly constrained by fluid-dynamic instabilities occurring at low mass flow rate conditions, such as surge and rotating stall. This work presents a vibro-acoustic experimental investigation on a centrifugal compressor of an automotive turbocharger aimed to identify and confirm some surge precursor values in correspondence of its inception conditions. The experimental campaign was carried out at the University of Genoa and developed on a vaneless diffuser turbocharger exploited for the pressurization of an innovative solid oxide fuel cell (SOFC) emulator. The investigated turbocharger is coupled with a pressure vessel for a former emulation activity on a pressurized SOFC. In this kind of plants, the joint effect of large volume size downstream of the compressor makes more complex the dynamic behavior of the whole system during transients, thus significantly increasing surge onset risk. The activity The main goal is to obtain a suitable quantitative indicator capable to detect in advance surge inception by relying only on vibrational and acoustic system response. Several transient operations starting from a compressor stable condition to surge instability onset were performed at different initial rotating speeds by progressively closing specific valves in the air line. When moving close to the surge line, vibro acoustic signals were acquired at a high sampling rate to detect variations in compressor blade passage phenomena due to possible interactions with rotating stall inception. Meanwhile, the trend of pressures, temperatures and mass flow rates measured in specific plant sections were acquired at a lower sampling rate to obtain a link between the compressor vibro-acoustic and performance behavior. Cyclostationary analysis and Several post-processing methods in time, angle and frequency domains were performed on microphone and accelerometer acquired signals to provide innovative diagnostic and predictive solutions (precursors) able to warn the incoming of surge compressor instability with cheap and not intrusive sensors like microphones and accelerometers.

Background and aims Immersion during slot machine gambling has been linked to disordered gambling. Current conceptualizations of immersion (namely dissociation, flow and the machine zone) make contrasting predictions as to whether gamblers are captivated by the game per se ('zoned in') or motivated by the escape that immersion provides ('zoned out'). We examined whether selected eye-movement metrics can distinguish between these predictions. Design and setting Pre-registered, correlational analysis in a laboratory setting. Participants gambled on a genuine slot machine for 20 minutes while wearing eye-tracking glasses. Participants Fifty-three adult slot machine gamblers who were not high-risk problem gamblers. Measurements We examined self-reported immersion during the gambling session and eye movements at different areas of the slot machine screen (the reels, the credit window, etc.). We further explored these variables' relationships with saccade count and amplitude. Findings The ratio of dwell time on the game's credit window relative to the game's reels was positively associated with immersion (t(51) = 1.68, P = 0.049 one-tailed, R2 = 0.05). Follow-up analyses described event-related changes in these patterns following different spin outcomes. Conclusions Immersion while gambling on a slot machine appears to be associated with active scanning of the game and a focus on the game's credit window. These results are more consistent with a 'zoned in' account of immersion aligned with flow theory than a 'zoned out' account based on escape.

Introduction: The post-laryngectomy state is characterized by several alterations in lung function. A reliable estimation of lung function can be very useful in laryngectomees to prevent postoperative complications and to evaluate the results of the treatment. Objective: Characterize the presence of respiratory functional disorders and the functional pattern of laryngectomees through the use of an extratracheal device. Methods: This transversal study included 50 patients submitted to total laryngectomy at least 6 months prior to this investigation, as the treatment of choice for laryngeal cancer. Results: 56% percent of the participants had altered breathing pattern, distributed as follows: 14 with obstructive pattern with no air trapping, 11 with obstructive pattern with air trapping and only 3 with restrictive pattern. On average, the diffusion decreased (74.3%) and airway resistance increased (121.7%) when compared to the expected average values for the Brazilian individuals. Conclusion: Most patients submitted to total laryngectomy present altered lung function, usually the obstructive type, frequently associated to a history of smoking. Resumo: Introdução: A condição pós-laringectomia é caracterizada por várias alterações na função pulmonar. Uma estimativa confiável da função pulmonar pode ser muito útil em pacientes laringectomizados para prevenir complicações após as intervenções cirúrgicas e avaliar os resultados do tratamento. Objetivo: Caracterizar a presença de distúrbios funcionais respiratórios e o padrão funcional de pacientes laringectomizados através do uso de um dispositivo extratraqueal. Método: Estudo transversal que incluiu 50 pacientes submetidos à laringectomia total pelo menos seis meses antes desta investigação, como tratamento de escolha para o câncer de laringe. Resultados: Dos participantes, 56% apresentavam padrão respiratório alterado, assim distribuídos: 14 com padrão obstrutivo sem aprisionamento aéreo, 11 com padrão obstrutivo e aprisionamento aéreo e apenas três com padrão restritivo. Em média, verificou-se que a difusão encontrava-se diminuída (74,3%) e a resistência das vias aéreas aumentada (121,7%) em relação aos resultados esperados em brasileiros. Conclusão: A maioria dos pacientes submetidos à laringectomia total apresenta função pulmonar alterada, do tipo obstrutiva, quase sempre associada a história de tabagismo. Keywords: Respiratory function tests, Spirometry, Plethysmography, Laryngectomy, Squamous cell, Palavras-chave: Testes de função respiratória, Espirometria, Pletismografia, Laringectomia, Célula escamosa

Butanol has shown to have superior fuel properties when compared to ethanol and has many applications in chemicals industries. It can be produced by isopropanol-butanol-ethanol (IBE) fermentation by some natural Clostridium beijerinckii strains that can produce isopropanol instead of acetone, along with butanol and ethanol, producing an alcohol biofuel mixture. In this work, biobutanol production from eucalyptus sawdust by cellulose hydrolysis and fermentation was evaluated. Eucalyptus sawdust was first subjected to autohydrolysis pretreatment at mild severe conditions (180 °C, 45 min) to enhance the hemicellulose recovery and preserve the xylan fractions (xylose and xylo-oligomers) for further processing. The pretreated solids obtained were subjected to enzymatic hydrolysis and fermentation under different process configurations: separate hydrolysis and fermentation (SHF), simultaneous hydrolysis and fermentation (SSF), and pre-saccharification and simultaneous saccharification and fermentation (PSSF). Butanol and IBE concentrations of 4.2 g/L and 8.7 g/L were achieved in SHF at 48 h, which resulted 35% and 45% higher than in SSF, respectively. Under this condition, the butanol yield reached 0.15 gbutanol/gsugars, which allowed to achieve a process efficiency of butanol production from eucalyptus sawdust of 12%.

This paper reports a review of an environmentally clean and efficient source of energy such as solid oxide fuel cell hybrid systems. Due to climate concerns, most nations are seeking alternative means of generating energy from a clean, efficient and environmental-friendly method. However, this has proven a big hurdle for both academic and industry researchers over many years. Currently, practical and technically feasible solution can be obtained via an integration of a microturbine and a fuel cell (hybrid systems). Combining the two distinct systems in a hybrid arrangement the efficiency of the microturbine increases from 25 to 30% to the 60–65% range. Hence, this paper outlines an engineering power generation solution towards the acute global population growth, the growing need, environmental concerns, intelligent use of energy with attendant environmental and hybrid system layouts concerning arising problems and tentative proposed solutions. Furthermore, advantages of a solid oxide fuel cell hybrid systems with respect to the other technologies are identified and discussed rationally. Special attention is devoted to modelling with software and emulator rigs and system prototypes. The paper also reviews the limitations and the benefits of these hybrid systems in relationship with energy, environment and sustainable development. Few potential applications, as long-term potential actions for sustainable development, and the future of such devices are further discussed.

During the last decades there has been a rise of awareness regarding the necessity to increase energy systems efficiency and reduce carbon emissions. These goals could be partially achieved through a greater use of gas turbine - solid oxide fuel cell hybrid systems to generate both electric power and heat. However, this kind of systems are known to be delicate, especially due to the fragility of the cell, which could be permanently damaged if its temperature and pressure levels exceed their operative limits. This could be caused by degradation of a component in the system (e.g. the turbomachinery), but also by some sensor fault which leads to a wrong control action. To be considered commercially competitive, these systems must guarantee high reliability and their maintenance costs must be minimized. Thus, it is necessary to integrate these plants with an automated diagnosis system capable to detect degradation levels of the many components (e.g. turbomachinery and fuel cell stack) in order to plan properly the maintenance operations, and also to recognize a sensor fault. This task can be very challenging due to the high complexity of the system and the interactions between its components. Another difficulty is related to the lack of sensors, which is common on commercial power plants, and makes harder the identification of faults in the system. This paper aims to develop and test Bayesian belief network based diagnosis methods, which can be used to predict the most likely degradation levels of turbine, compressor and fuel cell in a hybrid system on the basis of different sensors measurements. The capability of the diagnosis systems to understand if an abnormal measurement is caused by a component degradation or by a sensor fault is also investigated. The data used both to train and to test the networks is generated from a deterministic model and later modified to consider noise or bias in the sensors. The application of Bayesian belief networks to fuel cell - gas turbine hybrid systems is novel, thus the results obtained from this analysis could be a significant starting point to understand their potential. The diagnosis systems developed for this work provide essential information regarding levels of degradation and presence of faults in gas turbine, fuel cell and sensors in a fuel cell – gas turbine hybrid system. The Bayesian belief networks proved to have a good level of accuracy for all the scenarios considered, regarding both steady state and transient operations. This analysis also suggests that in the future a Bayesian belief network could be integrated with the control system to achieve safer and more efficient operations of these plants.

This paper aims to develop and test Bayesian belief network-based diagnosis methods, which can be used to predict the most likely degradation levels of turbine, compressor, and fuel cell (FC) in a hybrid system based on different sensors measurements. The capability of the diagnosis systems to understand if an abnormal measurement is caused by a component degradation or by a sensor fault is also investigated. The data used both to train and to test the networks are generated from a deterministic model and later modified to consider noise or bias in the sensors. The application of Bayesian belief networks (BBNs) to fuel cell—gas turbine hybrid systems is novel, thus the results obtained from this analysis could be a significant starting point to understand their potential. The diagnosis systems developed for this work provide essential information regarding levels of degradation and presence of faults in a gas turbine, fuel cell and sensors in a fuel cell—gas turbine hybrid system. The Bayesian belief networks proved to have a good level of accuracy for all the scenarios considered, regarding both steady-state and transient operations. This analysis also suggests that in the future a Bayesian belief network could be integrated with the control system to achieve safer and more efficient operations of these plants.

Compressor response investigation in nearly unstable operating conditions, like rotating stall and incipient surge, is a challenging topic nowadays in the turbomachinery research field. Indeed, turbines connected with large-size volumes are affected by critical issues related to surge prevention, particularly during transient operations. Advanced signal-processing operations conducted on vibrational responses provide an insight into possible diagnostic and predictive solutions which can be derived from accelerometer measurements. Indeed, vibrational investigation is largely employed in rotating-machine diagnostics together with time-frequency analysis such as smoothed pseudo-Wigner Ville (SPWVD) time-frequency distribution (TFD) considered in this paper. It is characterized by excellent time and frequency resolutions and thus it is effectively employed in numerous applications in the condition monitoring of machinery. The aim and the innovation of this work regards SPWVD utilization to study turbomachinery behavior in detail in order to identify incipient surge conditions in the centrifugal compressor starting from operational vibrational responses measured at significant plant locations. The so developed investigation allows us to assess the reliability of this innovative technique with respect to conventional ones in this field of research, highlighting at the same time its qualities and drawbacks in detecting fluid machinery unstable behavior. To this aim, an experimental campaign has been conducted on a T100 microturbine connected with several volume sizes and this has allowed to assess diagnostic technique reliability in plant configurations with different dynamic properties. The results show that SPWVD is able to successfully identify system evolution toward an unstable condition, by recognizing different levels and features of the particular kind of instability that is going to take place within the plant. Instability phenomena regarding rolling bearings have also been identified and their interaction with surge onset has been investigated for diagnostic purposes.