Production Components Research Articles

Environmental implications and levelized cost analysis of E-fuel production under photovoltaic energy, direct air capture, and hydrogen

The ecological transition in the transport sector is a major challenge to tackle environmental pollution, and European legislation will mandate zero-emission new cars from 2035. To reduce the impact of petrol and diesel vehicles, much emphasis is being placed on the potential use of synthetic fuels, including electrofuels (e-fuels). This research aims to examine a levelised cost (LCO) analysis of e-fuel production where the energy source is renewable. The energy used in the process is expected to come from a photovoltaic plant and the other steps required to produce e-fuel: direct air capture, electrolysis and Fischer-Tropsch process. The results showed that the LCOe-fuel in the baseline scenario is around 3.1 €/l, and this value is mainly influenced by the energy production component followed by the hydrogen one. Sensitivity, scenario and risk analyses are also conducted to evaluate alternative scenarios, and it emerges that in 84% of the cases, LCOe-fuel ranges between 2.8 €/l and 3.4 €/l. The findings show that the current cost is not competitive with fossil fuels, yet the development of e-fuels supports environmental protection. The concept of pragmatic sustainability, incentive policies, technology development, industrial symbiosis, economies of scale and learning economies can reduce this cost by supporting the decarbonization of the transport sector.

Revisiting social responsibility as a characteristic feature of social interactions in various fields

The relevance of the research topic is determined by the fact that social responsibility seems to be an important condition for the stability of social order and development. During the periods of crisis, the problem of leveling social responsibility among individuals and communities arises. The purpose of the research is to identify the most significant areas of social life of a modern man in the 21st century, where social responsibility is considered as a significant category that requires particularly close scientific analysis. When working with empirical material, methods applied in Sociology of culture and Sociology of management have been used - axiological, typological, structural-functional ones. Based on the results of the research, it has been revealed that research into the implementation of social responsibility in the sphere of economic relations - business and corporate interactions - is most in demand. Scientists are also interested in the need to demonstrate social responsibility in the field of Biotechnology and activities of engineers, who should focus not only on the scientific and technical, but also on the humanitarian component of production. In the current information society, the social responsibility of the media is of particular importance. The key conclusions include theses that social responsibility as a way of positively responding to the requests of those in need (individuals, groups, society) is being formed very slowly due to various historical, socio-economic, general cultural and psychological reasons; social responsibility is difficult to manage, it cannot be formed under compulsion; it is necessary to find a balance of economic benefits and ethical altruistic values that are embedded in the religious and traditional systems of ethnic cultures.

Sustainable production of 2,3,5,6-Tetramethylpyrazine at high titer in engineered Corynebacterium glutamicum.

Corynebacterium glutamicum was metabolically engineered to produce 2,3,5,6-tetramethylpyrazine followed by a design of experiments approach to optimize medium components for high-titer production.

Performance of novel Ca-biocomposites produced from banana peel and eggshell for highly efficient removal and recovery of phosphate from domestic wastewater

Using biowaste-based adsorbents to remove phosphorus (P) from wastewater offers significant benefits concerning eutrophication mitigation and addressing waste management challenges. In this work, Ca-biocomposites were prepared by pyrolysis (700 °C) of a mixture of banana peel (BP) and eggshell (ES). The mass ratio of BP to ES was varied in 2:1, 1:1, and 1:2 ratios. Among the tested mixtures, the BPES-1:2 sample exhibited excellent P removal performance, reaching a maximum P adsorption capacity (Qmax) of 214 ± 5 mg P/g. The adsorption process fitted well with the Avrami order kinetic model (R2 > 0.996) and the Liu isotherms model (R2 > 0.997). The excellent fit of the experimental data to the Avrami model suggests that chemisorption is the dominant interaction mechanism, leading to precipitation through the formation of calcium phosphates. Additionally, the Liu model anticipates that the energetic characteristics of the adsorbent's active sites cannot be identical. This is in agreement with the presence of Ca(OH)2 and CaCO3 in the adsorbent material, where the Ca(OH)2 active sites are preferred by the adsorbate molecules (PO43−) for occupation. Furthermore, thermodynamic analysis revealed that P adsorption is a spontaneous process of exothermic nature (ΔH° < 0). The calculated activation energy for the process (72.81 kJ/mol) suggests the P adsorption mechanism involves strong chemical bonding between the adsorbent and P species. In addition, precipitation of apatite (Ca5(PO4)3OH), a vital component in fertilizer production, was observed during the adsorption process. In tertiary treated wastewater applications, the BPES-1:2 biocomposite demonstrated a P removal efficiency of 90%. The solubility of P in a 2% formic acid solution was 100%, while the water-soluble P content was measured at 5.6%. These findings highlight the product's sustainable and environmentally beneficial nature by demonstrating its potential as a slow-release fertilizer, contributing to the application of the 3R slogan: Reduce, Reuse, Recycle. This value-added product is promising in supplying nutrients to plants over an extended period while minimizing the risk of nutrients leaching into the environment.

Articles, software, data: An Open Science ethological study

Background. Open Science seeks to render research outputs visible, accessible, reusable. The Open Science framework is currently evolving vigorously due, among others reasons, to the UNESCO Open Science Recommendation adopted in November 2021. In this context, it is relevant to better visualize and describe the relationships that hold among the direct protagonists of this changing landscape: research teams and their research outputs, namely: articles, software and data, as their comprehension will certainly contribute to foster better Open Science practices.Method. In this work we review and describe, through the information collected in a large number of bibliographic references, the current changing trends involving some essential, defining, characteristics and behaviors of the main components of the scientific production, namely, research teams and three kinds of research outputs they produce in many scientific areas. This comparative study is based, among others, in our recent work on the evolving concepts of research software, research data in the context of Open Science.Results. In this work we observe and document some key features in this evolving landscape such as the changing and extended roles of research team members; the need to develop a new citing and referencing culture for articles, but specially for research software and data; the rising relevance of open access (to publications, software, data) policies all over the world; the existence of some barriers and difficulties like the regulations concerning academic research close to industry, or other technological applications; the need to develop standards for the “right to be forgotten”; the need to consider the impact of Open Science costs for less favored communities, countries, institutions...Conclusions. This calls for the urgent need to observe and depict further this changing Open Science ecosystem, and to propose –as we have partially attempted in this work– new concepts to analyze this context as well as to contribute to ongoing research-on-research and to improve the implementation of Open Science practices, in order to foster better ways towards a sound, inclusive and fairer Open Science landscape.

Artificially reared ewes cannot be distinguished from natural reared ewes based on observed maternal behavior or lamb weaning weights.

Artificially rearing lambs is an important component of United States sheep production as some flocks select for increasing litter size to boost productivity. However, there is a conception among shepherds that artificially reared ewe lambs will ultimately result in poor mothers since they were not naturally raised. The objective of this study was to determine if differences in maternal behavior could be detected between ewes raised artificially and those raised naturally and if dam rearing type had an impact on lamb growth performance. Forty-eight ewes were enrolled comprised of 4 equal sized groups: artificially reared primiparous, naturally reared primiparous, artificially reared multi-parous, and naturally reared multi-parous. Ewes were observed using remote cameras to record maternal behaviors toward the lambs during and shortly after parturition. Behavior of 29 ewes during the first hour after parturition was analyzed. Independent multivariable regression models were evaluated for: proportion of time spent grooming, proportion of time spent helping the lambs nurse, number of helpful bouts, and the number of negative bouts. No statistically significant difference (P < 0.05) was detected between artificially reared and naturally reared ewes for the proportion of time spent grooming and the proportion of time spent helping the lambs nurse. Historical flock data were utilized to evaluate lamb growth between artificially and naturally reared ewes. No detrimental associations between artificially reared ewes and lamb weaning weights were observed. This study shows that artificially reared ewes are no different in terms of mothering behaviors and may be used as potential replacement candidates.

Eco-friendly diet: nutrient digestibility, nitrogen and energy balances and growth performance of growing pigs.

The traditional approach to formulating pig diets is based only on minimizing cost while meeting nutritional requirements and thus does not consider the environmental impacts associated with producing feed ingredients. To reduce the overall environmental impact of pork production, feed ingredients can be considered to formulate environmentally friendly diets. However, their potential effects on pig performance could decrease environmental benefits at the farm gate. The objective of this study was to quantify the effects of such eco-friendly pig diets on nitrogen (N) and energy (E) balances, the components of heat production (HP), and the performance of growing pigs. Digestibility coefficients of dry matter (84.5% vs. 88.2%, P < 0.01) and N (80.4% vs. 86.3%, P < 0.01) were significantly lower for the eco-friendly diet than the Control-diet (a commercial diet used in France). N excretion in feces was significantly higher for the group of pigs fed the eco-friendly diet than for the group fed the Control-diet (9.8 vs. 6.9g/d, respectively, P = 0.01), while the N retention tended to be lower (27.8 vs. 30.3g/d, respectively; P = 0.06). The metabolizable E:digestible E ratio did not differ between diets, but total HP was significantly lower for the eco-friendly diet group than for the Control-diet group (1,340 vs. 1,388 kJ/kg body weight0.60/d, respectively, P = 0.03). Using feed ingredients with lower environmental impacts, such as locally produced protein or co-products from wheat processing, is an effective way to decrease the environmental impacts of pig production. However, the nutritional composition of these eco-friendly ingredients could be overestimated, in particular the true digestibility of amino acids. This indicates the need to better estimate and consider the true digestibility of eco-friendly diets to decrease environmental impacts of livestock production without decreasing animal performance.

Review of the Planning and Distribution Methodologies to Locate Hydrogen Infrastructure in the Territory

The member countries of the European Union (EU) have prioritized the incorporation of hydrogen as a key component of their energy objectives. As the world moves towards reducing its dependence on fossil fuels, alternative sources of energy have gained prominence. With the growing development of Fuel Cell Electric Vehicles (FCEVs), the establishment of an infrastructure for hydrogen production and the creation of a network of service stations have become essential. This article’s purpose is to conduct a methodical review of literature regarding the use of green hydrogen for transportation and the planning of imperative infrastructure in the territory of the EU, specifically Hydrogen Refueling Stations (HRS). In order to increase the acceptance of fuel cell vehicles, a comprehensive network of hydrogen refueling stations (HRS) must be built that enable drivers to refuel their vehicles quickly and easily, similar to gasoline or diesel vehicles. The literature review on this topic was conducted using the Web of Science database (WOS), with a variety of search terms proposed to cover all the key components of green hydrogen production and refueling infrastructure. The implementation of HRS powered by renewable energy sources is an important step in the adoption of fuel cell vehicles, and overcoming the obstacles that come with their implementation will require cooperation and innovation from governments, private businesses, and other stakeholders.

Optimization Solutions of a Multistage Balanced Transport Problem with using of the Potential Method

Route optimization is an important issue because it allows improving the economic component in production. Its generalization to optimization problems on networks is shown. The transport task is formulated in the network setting: to make a plan of cargo trans-portation on the transport network so that the cargo stocks were taken out of the points of depar-ture, the needs of consumers at the destinations were met, and the total cost of transportation was minimal. The algorithm of its solution is given, revealed on a concrete example of delivery of products to customers who sell these products on a daily basis. Tables of the basic and optimal plan, a transport network of the optimal plan of transportations are made. The process of solving such a problem by modeling in the environment is proposed. The simulation model of this process was created with using the FlexSim software. The process of creating the simulation model is demonstrated

Neurofeedback in the treatment of cognitive impairment in patients with early cerebral small vessel disease

To compare the effectiveness of neurofeedback (NFB) at infra-low and alpha frequencies in the treatment of cognitive impairment in patients with early cerebral small vessel disease (cSVD). The study included 71 patients (average age 52.8±6.3 years, men 15%, women 85%) with early cSVD and 21 healthy volunteers (average age 53.2±4.8 years, men 29%, women 71%). All participants were assessed for clinical manifestations and cognitive functions, brain MRI, and EEG. cSVD patients were randomized by an envelope method with double-blind placebo control. Three groups of neurofeedback were formed: infra-low waves (n=25), alpha waves (n=22), simulated neurofeedback using EEG (placebo) (n=24). Fifteen sessions of 30 minutes were conducted 2-5 times a week. The cognitive profile and EEG were assessed immediately and 6-8 weeks after completion of the neurofeedback course. Patients with early cSVD had subjective (65%) and moderate (35%) cognitive impairment with predominant deviations in the components of executive brain functions (EBF). Neurofeedback using infra-low waves significantly improved EBF in the components of productivity, switching and inhibition, non-verbal delayed memory immediately after the course, maintaining the effect for at least 6-8 weeks, which was accompanied by an increase in the power (μB2) of the alpha rhythm in the occipital regions. Neurofeedback using alpha waves showed improvement in the Stroop test (interference index) in the delayed period. In patients with early cSVD and deterioration of EBF, it is preferable to conduct biofeedback neurotraining at infra-low frequencies to treat cognitive impairment and create a cognitive reserve. An increase in the power of the alpha rhythm in the occipital regions during the course can be considered a prognostic marker of its effectiveness.

Resource-efficient condition determination through discrete production system monitoring

Machine data plays a significant role in a production environment, as operators strive to constantly optimize their processes and increase efficiency while maintaining the required quality parameters. Recorded machine data provides comprehensive insights into the condition of the monitored machines and their components. This data can be used, for example, in operations for condition monitoring, predictive maintenance, quality control and automation. However, the collection, transfer and storage of machine data is still a key challenge due to various causes. Current condition monitoring approaches are often used alongside other data-intensive methods such as machine learning and deep learning algorithms. However, there is a pressing need to develop new concepts for discrete data analysis that enable accurate fault diagnosis and effective maintenance planning without relying on extensive datasets. This paper presents a discrete concept for resource efficient production system condition monitoring. This concept consists of a data processing pipeline where many data reduction steps are done. Using the collected data of a drive, a principal component in production, we showed that the reduction of the parameters to be collected and the aggregation of data does not necessarily change the informative value and consequently condition/state determination is still possible. The data reduction steps along a data process pipeline showed the potential to save resources. This should relieve the network and reduce storage and computing capacity.

Enabling industrial energy efficiency and flexibility with dynamic simulation-based optimization of manufacturing operations

In the face of substantial environmental impact, energy-intensive industries are compelled to deal with a spectrum of future energy scenarios, including the adoption of electrification and hydrogen use. In addition, these sectors are under pressure to enhance energy efficiency and adaptability to reduce costs. The integrated planning and control of production and energy system components is challenging due to the complexity and lack of available methods, though. This paper addresses this gap, by introducing a simulation-based method that optimizes production and energy system components. The planning method is based on a multicriteria meta-heuristic with an integrated simulation of production and energy system behavior. It evauates different future energy scenarios with electrification and hydrogen use including variable energy markets and storage systems. The method is applied and validated in a case study in an energy-intensive steel production. The results show the significant benefits of the dynamic planning and optimization for various variables in two different heat-treatment process technologies.

PRODUCTIVE BEHAVIOR OF DIFFERENT SOYBEAN GENOTYPES IN THE WESTERN REGION OF PARANÁ

The agribusiness sector is responsible for the largest percentage of the Brazilian GDP; nevertheless, agricultural activities have a low return rate and a high cost risk. To meet the financial needs of producers and agribusiness sectors, the choice of the genotype to be planted in commercial areas is one of the first decisions to be made. This study aimed to evaluate the production components of five different soybean genotypes in the western region of Paraná in the 2022/2023 season under standardized planting conditions. The experimental design used was a randomized complete block (RCB) with 5 treatments and 4 replications, totaling 20 experimental plots. The treatments consisted of planting different soybean genotypes (M 6100 XTD, AS 3615 I2X, P 96R10 IPRO, DM 60IX64 RSF I2X, and M 6110 I2X), all of indeterminate growth and early maturity. The genotypes AS 3615 I2X, DM 60IX64 RSF I2X, and M 6110 I2X have the Intacta2 Xtend technology, while M 6100 XTD has the Xtend Biotec technology, and P 96R10 has the Intacta RR2 PRO technology. Furthermore, all materials belong to the relative maturity group (GMR) 6.1, except for DM 60IX64 RSF I2X, which is in the GMR 6.0 group. The following parameters were evaluated: plant height (AP), number of racemes (NR), number of pods per plant (NVP), number of grains per pod (NGV), thousand-grain weight (MMG), productivity (PROD), and vegetative index (IV). After measuring the mentioned parameters, the results were subjected to the Tukey statistical test to compare the means, where significant differences (p&lt;0.05) were observed among the genotypes (M 6100 XTD, AS 3615 I2X, P 96R10 IPRO, DM 60IX64 RSF I2X, and M 6110 I2X) for the morphological and productive variables NGV, MMG, and IV. For the productive component NGV, the genotype P 96R10 IPRO had the lowest mean (2.32 grains per pod) compared to the others. However, the same genotype had a higher mean MMG (153.59 g) when compared to AS 3615 I2X and DM 60IX64 RSF I2X. The variables that showed significant differences among the genotypes did not affect the final PROD of the experiment's genotypes because the evaluated genotypes have a high production capacity but different technologies. As there was no chemical management disruption, significant pest and disease attacks, or adverse weather conditions, all genotypes were able to develop their maximum production capacity.

Account of additional factors for damping torsional oscillations

Some parameters are influenced by the turbine unit's torsional oscillations. The fundamental comes from damping these oscillations, which are brought on by a departure in the turbine blades' speed from the device's prediction of the steam volume, and attenuation of fluctuations due to the distribution of energy in the turbine's productive components. The usual single-machine infinite bus system is used for the analysis. For various turbine-generator shafts and various generator operating situations, rotating mass mechanical system evaluations for small-signal stability and large disturbance are conducted. It is demonstrated that the shaft's “structural' damping (H) and “steam' damping (Kn) coefficients have a considerable impact on the damping of torsional modes. The goal of this work is to determine the effect of changing the damping factors in the mathematical model of the steam turbine shaft on the system's static stability, as well as the extent to which these variables' limits on damping rotational oscillations on the maximum torsional torques generated in the shaft masses. The mathematical model of the steam turbine shaft with a single machine and transmission line to an infinite bus system was simulated using Dymola software, and the static and dynamic effects of damping factors (H) and (Kn) on system stability were demonstrated. By evaluating the best case for parameters with the least influence on the system's stability, the results were obtained by changing the factors (Kn) from 0.005 to 0.5 and (H) from 0.005 to 0.2 and the extent of its effect on the maximum torque of the steam turbine masses and reducing it by 8.4 %, as well as by reducing the settling time of the system after disturbances occur and reaching to Steady state by about 90 %.

Natural deep eutectics: expanding green solvents for thermally-/photo-induced polymerization of N-isopropylacrylamide toward key components for sustainable production of semi-natural polymers

Natural deep eutectic solvents (NADESs), which consist of natural components, have attracted attention as environmentally friendly solvents. We describe the design and synthesis of natural deep eutectic monomers (NADEMs) and NADEM-based polymers.

Case of topological optimisation of a part produced by the FDM process

The article is devoted to the topological optimisation of an ABS part, which will be manufactured by the FDM (Fused Deposition Modelling) process. Firstly, the maximum deformation and stress are noted by simulating the part (under loads) before optimisation. Secondly, and with optimisation along two privileged directions, we check the distribution of the deformation and the stress on the volume of the part.The methodology is based on topological optimisation under ANSYS (SIMP method). The study support piece is a garage release handle.The numerical results prove the usefulness of choosing a manufacturing direction to have an optimised part that is light and of better resistance than the initial part (made by the conventional process).Several parameters influence the right solution choice in this study. For future research, we can opt for an optimal solution in line with a minimum cost.The presented procedure can be generalised and applied to components of similar characterisation and other additive production methods.This article shows the usefulness of topological optimisation to guide the designer and an effective tool to design resistant parts by additive manufacturing. Thus, 3D printing can compete with conventional processes.

Development of a suction gripper network based on the biological role model of an octopus

The handling of fragile, sensitive or flexible components in assembly technology and production requires grippers that are designed for gentle handling of the objects to be gripped. Suction grippers are still a widespread standard solution for this purpose. However, rising energy prices are making pneumatic grippers, which work with a central upstream compressed air supply, increasingly unattractive. The generation of the compressed air itself, the mostly leaky transmission and the relatively inefficient vacuum generation are cost drivers that many users would like to avoid. Consequently, vacuum-based gripper means are required for industrial production, which work without externally generated compressed air. At the Fraunhofer IWU, a compressed-air-free suction pad composite has been developed that enables gripping of components with a wide variety of shapes. The underlying concept is inspired by the function of the suction arms (tentacles) of an octopus. By evacuating several small volume areas, which can be individually mechanically actuated, safe and sensitive gripping of objects is possible. For the generation of the vacuum, a piston system and a principle of an artificial muscle were developed, which is controlled based on shape memory alloys.

Vermicompost (Traditional Methods) is an Important Component of Agricultural Productivity and an Efficient Tool for Environmental and Economic Sustainability

Vermicompost (Traditional Methods) is an Important Component of Agricultural Productivity and an Efficient Tool for Environmental and Economic Sustainability

Machine learning tools for peptide bioactivity evaluation – Implications for cell culture media optimization and the broader cultivated meat industry

Although bioactive peptides have traditionally been studied for their health-promoting qualities in the context of nutrition and medicine, the past twenty years have seen a steady increase in their application to cell culture media optimization. Complex natural sources of bioactive peptides, such as hydrolysates, offer a sustainable and cost-effective means of promoting cellular growth, making them an essential component of scaling-up cultivated meat production. However, the sheer diversity of hydrolysates makes product selection difficult, highlighting the need for functional characterization. Traditional wet-lab techniques for isolating and estimating peptide bioactivity cannot keep pace with peptide identification using high-throughput tools such as mass spectrometry, requiring the development and use of machine learning-based classifiers.This review provides a comprehensive list of available software tools to evaluate peptide bioactivity, classified and compared based on the algorithm, training set, functionality, and limitations of the underlying models. We curated independent test sets to compare the predictive performance of different models based on specific bioactivity classification relevant to promoting cell culture growth: antioxidant and anti-inflammatory. A comprehensive screening of all bioactivity classifiers revealed that while there are approximately fifty tools to elucidate antimicrobial activity and sixteen that predict anti-inflammatory activity, fewer tools are available for other functionalities related to cell growth — five that predict antioxidant activity and two for growth factor and/or cell signaling prediction. A thorough evaluation of the available tools revealed significant issues with sensitivity, specificity, and overall accuracy. Despite the overall interest in estimating peptide bioactivity, our work highlights key gaps in the broader adoption of existing software for the specific application of cell culture media optimization in the context of cultivated meat and beyond.

Mentoring practices that predict doctoral student outcomes in a biological sciences cohort.

Despite the importance of a diversity of backgrounds and perspectives in biological research, women, racial and ethnic minorities, and students from non-traditional academic backgrounds remain underrepresented in the composition of university faculty. Through a study on doctoral students at a research-intensive university, we pinpoint advising from faculty as a critical component of graduate student experiences and productivity. Graduate students from minority backgrounds reported lower levels of support from their advisors and research groups. However, working with an advisor from a similar demographic background substantially improved productivity and well-being of these students. Several other aspects of mentoring practices positively predicted student success and belonging, including frequent one-on-one meetings, empathetic and constructive feedback, and relationships with other peer or faculty mentors. Our study highlights the need to renovate graduate education with a focus on retention-not just recruitment-to best prepare students for success in scientific careers.