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In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
Subject of this case is Deutsche Telekom Services Europe (DTSE), a service center for administrative processes. Due to the high volume of repetitive tasks (e.g., 100k manual uploads of offer documents into SAP per year), automation was identified as an important strategic target with a high management attention and commitment. DTSE has to work with various backend application systems without any possibility to change those systems. Furthermore, the complexity of administrative processes differed. When it comes to the transfer of unstructured data (e.g., offer documents) to structured data (e.g., MS Excel files), further cognitive technologies were needed.
Robotic process automation (RPA) has attracted increasing attention in research and practice. This chapter positions, structures, and frames the topic as an introduction to this book. RPA is understood as a broad concept that comprises a variety of concrete solutions. From a management perspective RPA offers an innovative approach for realizing automation potentials, whereas from a technical perspective the implementation based on software products and the impact of artificial intelligence (AI) and machine learning (ML) are relevant. RPA is industry-independent and can be used, for example, in finance, telecommunications, and the public sector. With respect to RPA this chapter discusses definitions, related approaches, a structuring framework, a research framework, and an inside as well as outside architectural view. Furthermore, it provides an overview of the book combined with short summaries of each chapter.
Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today’s corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.
One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments.
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of the process equipment and multiple and simultaneous release of hazardous substances in industrial facilities. Nevertheless, the design of industrial plants is inadequately described in recent codes and guidelines, as they do not consider the dynamic interaction between the structure and the installations and thus the effect of seismic response of the installations on the response of the structure and vice versa. The current code-based approach for the seismic design of industrial facilities is considered not enough for ensure proper safety conditions against exceptional event entailing loss of content and related consequences. Accordingly, SPIF project (Seismic Performance of Multi- Component Systems in Special Risk Industrial Facilities) was proposed within the framework of the European H2020 - SERA funding scheme (Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe). The objective of the SPIF project is the investigation of the seismic behavior of a representative industrial structure equipped with complex process technology by means of shaking table tests. The test structure is a three-story moment resisting steel frame with vertical and horizontal vessels and cabinets, arranged on the three levels and connected by pipes. The dynamic behavior of the test structure and installations is investigated with and without base isolation. Furthermore, both firmly anchored and isolated components are taken into account to compare their dynamic behavior and interactions with each other. Artificial and synthetic ground motions are applied to study the seismic response at different PGA levels. After each test, dynamic identification measurements are carried out to characterize the system condition. The contribution presents the numerical simulations to calibrate the tests on the prototype, the experimental setup of the investigated structure and installations, selected measurement data and finally describes preliminary experimental results.
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of process equipment and multiple and simultaneous release of hazardous substances. Nonetheless, current standards for seismic design of industrial facilities are considered inadequate to guarantee proper safety conditions against exceptional events entailing loss of containment and related consequences. On these premises, the SPIF project -Seismic Performance of Multi-Component Systems in Special Risk Industrial Facilities- was proposed within the framework of the European H2020 SERA funding scheme. In detail, the objective of the SPIF project is the investigation of the seismic behaviour of a representative industrial multi-storey frame structure equipped with complex process components by means of shaking table tests. Along this main vein and in a performance-based design perspective, the issues investigated in depth are the interaction between a primary moment resisting frame (MRF) steel structure and secondary process components that influence the performance of the whole system; and a proper check of floor spectra predictions. The evaluation of experimental data clearly shows a favourable performance of the MRF structure, some weaknesses of local details due to the interaction between floor crossbeams and process components and, finally, the overconservatism of current design standards w.r.t. floor spectra predictions.
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of the process equipment and multiple and simultaneous release of hazardous substances in industrial facilities. Nevertheless, the design of industrial plants is inadequately described in recent codes and guidelines, as they do not consider the dynamic interaction between the structure and the installations and thus the effect of seismic response of the installations on the response of the structure and vice versa. The current code-based approach for the seismic design of industrial facilities is considered not enough for ensure proper safety conditions against exceptional event entailing loss of content and related consequences. Accordingly, SPIF project (Seismic Performance of Multi-Component Systems in Special Risk Industrial Facilities) was proposed within the framework of the European H2020 - SERA funding scheme (Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe). The objective of the SPIF project is the investigation of the seismic behaviour of a representative industrial structure equipped with complex process technology by means of shaking table tests. The test structure is a three-story moment resisting steel frame with vertical and horizontal vessels and cabinets, arranged on the three levels and connected by pipes. The dynamic behaviour of the test structure and of its relative several installations is investigated. Furthermore, both process components and primary structure interactions are considered and analyzed. Several PGA-scaled artificial ground motions are applied to study the seismic response at different levels. After each test, dynamic identification measurements are carried out to characterize the system condition. The contribution presents the experimental setup of the investigated structure and installations, selected measurement data and describes the obtained damage. Furthermore, important findings for the definition of performance limits, the effectiveness of floor response spectra in industrial facilities will be presented and discussed.
Nowadays modern high-performance buildings and facilities are equipped with monitoring systems and sensors to control building characteristics like energy consumption, temperature pattern and structural safety. The visualization and interpretation of sensor data is typically based on simple spreadsheets and non-standardized user-oriented solutions, which makes it difficult for building owners, facility managers and decision-makers to evaluate and understand the data. The solution of this problem in the future are integrated BIM-Sensor approaches which allow the generation of BIM models incorporating all relevant information of monitoring systems. These approaches support both the dynamic visualization of key structural performance parameters, the effective long-term management of sensor data based on BIM and provide a user-friendly interface to communicate with various stakeholders. A major benefit for the end user is the use of the BIM software architecture, which is the future standard anyway. In the following, the application of the integrated BIM-Sensor approach is illustrated for a typical industrial facility as a part of an early warning and rapid response system for earthquake events currently developed in the research project “ROBUST” with financial support by the German Federal Ministry for Economic Affairs and Energy (BMWI).
The investigation of the possibility to determine various characteristics of powder heparin (n = 115) was carried out with infrared spectroscopy. The evaluation of heparin samples included several parameters such as purity grade, distributing company, animal source as well as heparin species (i.e. Na-heparin, Ca-heparin, and heparinoids). Multivariate analysis using principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and partial least squares – discriminant analysis (PLS-DA) were applied for the modelling of spectral data. Different pre-processing methods were applied to IR spectral data; multiplicative scatter correction (MSC) was chosen as the most relevant.
Obtained results were confirmed by nuclear magnetic resonance (NMR) spectroscopy. Good predictive ability of this approach demonstrates the potential of IR spectroscopy and chemometrics for screening of heparin quality. This approach, however, is designed as a screening tool and is not considered as a replacement for either of the methods required by USP and FDA.
The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (Mw and Mn) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7–9 and 14–16% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography.
The low-pressure system Bernd involved extreme rainfalls in the Western part of Germany in July 2021,
resulting in major floods, severe damages and a tremendous number of casualties. Such extreme events
are rare and full flood protection can never be ensured with reasonable financial means. But still, this
event must be starting point to reconsider current design concepts. This article aims at sharing some
thoughts on potential hazards, the selection of return periods and remaining risk with the focus on Germany.
Thrombogenic complications are a main issue in mechanical circulatory support (MCS). There is no validated in vitro method available to quantitatively assess the thrombogenic performance of pulsatile MCS devices under realistic hemodynamic conditions. The aim of this study is to propose a method to evaluate the thrombogenic potential of new designs without the use of complex in-vivo trials. This study presents a novel in vitro method for reproducible thrombogenicity testing of pulsatile MCS systems using low molecular weight heparinized porcine blood. Blood parameters are continuously measured with full blood thromboelastometry (ROTEM; EXTEM, FIBTEM and a custom-made analysis HEPNATEM). Thrombus formation is optically observed after four hours of testing. The results of three experiments are presented each with two parallel loops. The area of thrombus formation inside the MCS device was reproducible. The implantation of a filter inside the loop catches embolizing thrombi without a measurable increase of platelet activation, allowing conclusions of the place of origin of thrombi inside the device. EXTEM and FIBTEM parameters such as clotting velocity (α) and maximum clot firmness (MCF) show a total decrease by around 6% with a characteristic kink after 180 minutes. HEPNATEM α and MCF rise within the first 180 minutes indicate a continuously increasing activation level of coagulation. After 180 minutes, the consumption of clotting factors prevails, resulting in a decrease of α and MCF. With the designed mock loop and the presented protocol we are able to identify thrombogenic hot spots inside a pulsatile pump and characterize their thrombogenic potential.
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
How different diversity factors affect the perception of first-year requirements in higher education
(2021)
In the light of growing university entry rates, higher education institutions not only serve larger numbers of students, but also seek to meet first-year students’ ever more diverse needs. Yet to inform universities how to support the transition to higher education, research only offers limited insights. Current studies tend to either focus on the individual factors that affect student success or they highlight students’ social background and their educational biography in order to examine the achievement of selected, non-traditional groups of students. Both lines of research appear to lack integration and often fail to take organisational diversity into account, such as different types of higher education institutions or degree programmes. For a more comprehensive understanding of student diversity, the present study includes individual, social and organisational factors. To gain insights into their role for the transition to higher education, we examine how the different factors affect the students’ perception of the formal and informal requirements of the first year as more or less difficult to cope with. As the perceived requirements result from both the characteristics of the students and the institutional context, they allow to investigate transition at the interface of the micro and the meso level of higher education. Latent profile analyses revealed that there are no profiles with complex patterns of perception of the first-year requirements, but the identified groups rather differ in the overall level of perceived challenges. Moreover, SEM indicates that the differences in the perception largely depend on the individual factors self-efficacy and volition.
Previous studies optimized the dimensions of coaxial heat exchangers using constant mass fow rates as a boundary condition. They show a thermal optimal circular ring width of nearly zero. Hydraulically optimal is an inner to outer pipe radius ratio of 0.65 for turbulent and 0.68 for laminar fow types. In contrast, in this study, fow conditions in the circular ring are kept constant (a set of fxed Reynolds numbers) during optimization. This approach ensures fxed fow conditions and prevents inappropriately high or low mass fow rates. The optimization is carried out for three objectives: Maximum energy gain, minimum hydraulic efort and eventually optimum net-exergy balance. The optimization changes the inner pipe radius and mass fow rate but not the Reynolds number of the circular ring. The thermal calculations base on Hellström’s borehole resistance and the hydraulic optimization on individually calculated linear loss of head coefcients. Increasing the inner pipe radius results in decreased hydraulic losses in the inner pipe but increased losses in the circular ring. The net-exergy diference is a key performance indicator and combines thermal and hydraulic calculations. It is the difference between thermal exergy fux and hydraulic efort. The Reynolds number in the circular ring is instead of the mass fow rate constant during all optimizations. The result from a thermal perspective is an optimal width of the circular ring of nearly zero. The hydraulically optimal inner pipe radius is 54% of the outer pipe radius for laminar fow and 60% for turbulent fow scenarios. Net-exergetic optimization shows a predominant infuence of hydraulic losses, especially for small temperature gains. The exact result depends on the earth’s thermal properties and the fow type. Conclusively, coaxial geothermal probes’ design should focus on the hydraulic optimum and take the thermal optimum as a secondary criterion due to the dominating hydraulics.
The presented paper gives an overview of the most important and most common theories and concepts from the economic field of organisational change and is also enriched with quantitative publication data, which underlines the relevance of the topic. In particular, the topic presented is interwoven in an interdisciplinary way with economic psychological models, which are underpinned within the models with content from leading scholars in the field. The pace of change in companies is accelerating, as is technological change in our society. Adaptations of the corporate structure, but also of management techniques and tasks, are therefore indispensable. This includes not only the right approaches to employee motivation, but also the correct use of intrinsic and extrinsic motivational factors. Based on the hypothesis put forward by the scientist and researcher Rollinson in his book “Organisational behaviour and analysis” that managers believe motivational resources are available at all times, socio-economic and economic psychological theories are contrasted here in order to critically examine this statement. In addition, a fictitious company was created as a model for this work in order to illustrate the effects of motivational deficits in practice. In this context, the theories presented are applied to concrete problems within the model and conclusions are drawn about their influence and applicability. This led to the conclusion that motivation is a very individual challenge for each employee, which requires adapted and personalised approaches. On the other hand, the recommendations for action for supervisors in the case of motivation deficits also cannot be answered in a blanket manner, but can only be solved with the help of professional, expert-supported processing due to the economic-psychological realities of motivation. Identifying, analysing and remedying individual employee motivation deficits is, according to the authors, a problem and a challenge of great importance, especially in the context of rapidly changing ecosystems in modern companies, as motivation also influences other factors such as individual productivity. The authors therefore conclude that good motivation through the individual and customised promotion and further training of employees is an important point for achieving important corporate goals in order to remain competitive on the one hand and to create a productive and pleasant working environment on the other.
The following article deals with the basic principles of intercultural management and possible improvements in terms of cultural, ethnic and gender diversification. The results are exemplarily applied to a bank located in Germany. The aim of this paper is to find out to what extent intercultural management could improve the productivity of Relatos-Bank in dealing with foreign employees or employees with a different cultural background. To achieve this goal, the authors con-duct a literature research. The main sources of information are books, journal articles and internet sources. It becomes clear that especially the different perceptions of different generations have a potential for conflict, which can be counteracted by applying presented scientific models. Equalizing the salaries of female and male employees and equalizing the rights and distribution of power could also be the key to becoming an open-minded, dynamic and fair organization that is pre-pared for the rapidly changing environment in which it operates.
As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: β-O-4 linkage, B: phenylcoumaran, C: resinol, D: β-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70% and significantly lower in stem and mixture lignins at around 60% and almost 65%. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20% or more (maximum is M. sinensis Sin2 with over 30%). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27%. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.
The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated
structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.
Most drugs are no longer produced in their own countries by the pharmaceutical companies, but by contract manufacturers or at manufacturing sites in countries that can produce more cheaply. This not only makes it difficult to trace them back but also leaves room for criminal organizations to fake them unnoticed. For these reasons, it is becoming increasingly difficult to determine the exact origin of drugs. The goal of this work was to investigate how exactly this is possible by using different spectroscopic methods like nuclear magnetic resonance and near- and mid-infrared spectroscopy in combination with multivariate data analysis. As an example, 56 out of 64 different paracetamol preparations, collected from 19 countries around the world, were chosen to investigate whether it is possible to determine the pharmaceutical company, manufacturing site, or country of origin. By means of suitable pre-processing of the spectra and the different information contained in each method, principal component analysis was able to evaluate manufacturing relationships between individual companies and to differentiate between production sites or formulations. Linear discriminant analysis showed different results depending on the spectral method and purpose. For all spectroscopic methods, it was found that the classification of the preparations to their manufacturer achieves better results than the classification to their pharmaceutical company. The best results were obtained with nuclear magnetic resonance and near-infrared data, with 94.6%/99.6% and 98.7/100% of the spectra of the preparations correctly assigned to their pharmaceutical company or manufacturer.
This paper describes the concept of an innovative, interdisciplinary, user-oriented earthquake warning and rapid response system coupled with a structural health monitoring system (SHM), capable to detect structural damages in real time. The novel system is based on interconnected decentralized seismic and structural health monitoring sensors. It is developed and will be exemplarily applied on critical infrastructures in Lower Rhine Region, in particular on a road bridge and within a chemical industrial facility. A communication network is responsible to exchange information between sensors and forward warnings and status reports about infrastructures’health condition to the concerned recipients (e.g., facility operators, local authorities). Safety measures such as emergency shutdowns are activated to mitigate structural damages and damage propagation. Local monitoring systems of the infrastructures are integrated in BIM models. The visualization of sensor data and the graphic representation of the detected damages provide spatial content to sensors data and serve as a useful and effective tool for the decision-making processes after an earthquake in the region under consideration.
Microbial diversity studies regarding the aquatic communities that experienced or are experiencing environmental problems are essential for the comprehension of the remediation dynamics. In this pilot study, we present data on the phylogenetic and ecological structure of microorganisms from epipelagic water samples collected in the Small Aral Sea (SAS). The raw data were generated by massive parallel sequencing using the shotgun approach. As expected, most of the identified DNA sequences belonged to Terrabacteria and Actinobacteria (40% and 37% of the total reads, respectively). The occurrence of Deinococcus-Thermus, Armatimonadetes, Chloroflexi in the epipelagic SAS waters was less anticipated. Surprising was also the detection of sequences, which are characteristic for strict anaerobes—Ignavibacteria, hydrogen-oxidizing bacteria, and archaeal methanogenic species. We suppose that the observed very broad range of phylogenetic and ecological features displayed by the SAS reads demonstrates a more intensive mixing of water masses originating from diverse ecological niches of the Aral-Syr Darya River basin than presumed before.
Delayed cerebral ischemia (DCI) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) and can lead to infarction and poor clinical outcome. The underlying mechanisms are still incompletely understood, but animal models indicate that vasoactive metabolites and inflammatory cytokines produced within the subarachnoid space may progressively impair and partially invert neurovascular coupling (NVC) in the brain. Because cerebral and retinal microvasculature are governed by comparable regulatory mechanisms and may be connected by perivascular pathways, retinal vascular changes are increasingly recognized as a potential surrogate for altered NVC in the brain. Here, we used non-invasive retinal vessel analysis (RVA) to assess microvascular function in aSAH patients at different times after the ictus.
Humic substances (HS), as important environmental components, are essential to soil health and agricultural sustainability. The usage of low-rank coal (LRC) for energy generation has declined considerably due to the growing popularity of renewable energy sources and gas. However, their potential as soil amendment aimed to maintain soil quality and productivity deserves more recognition. LRC, a highly heterogeneous material in nature, contains large quantities of HS and may effectively help to restore the physicochemical, biological, and ecological functionality of soil. Multiple emerging studies support the view that LRC and its derivatives can positively impact the soil microclimate, nutrient status, and organic matter turnover. Moreover, the phytotoxic effects of some pollutants can be reduced by subsequent LRC application. Broad geographical availability, relatively low cost, and good technical applicability of LRC offer the advantage of easy fulfilling soil amendment and conditioner requirements worldwide. This review analyzes and emphasizes the potential of LRC and its numerous forms/combinations for soil amelioration and crop production. A great benefit would be a systematic investment strategy implicating safe utilization and long-term application of LRC for sustainable agricultural production.
Lignite biosolubilization and bioconversion by Bacillus sp.: the collation of analytical data
(2021)
The vast metabolic potential of microbes in brown coal (lignite) processing and utilization can greatly contribute to innovative approaches to sustainable production of high-value products from coal. In this study, the multi-faceted and complex coal biosolubilization process by Bacillus sp. RKB 7 isolate from the Kazakhstan coal-mining soil is reported, and the derived products are characterized. Lignite solubilization tests performed for surface and suspension cultures testify to the formation of numerous soluble lignite-derived substances. Almost 24% of crude lignite (5% w/v) was solubilized within 14 days under slightly alkaline conditions (pH 8.2). FTIR analysis revealed various functional groups in the obtained biosolubilization products. Analyses of the lignite-derived humic products by UV-Vis and fluorescence spectrometry as well as elemental analysis yielded compatible results indicating the emerging products had a lower molecular weight and degree of aromaticity. Furthermore, XRD and SEM analyses were used to evaluate the biosolubilization processes from mineralogical and microscopic points of view. The findings not only contribute to a deeper understanding of microbe–mineral interactions in coal environments, but also contribute to knowledge of coal biosolubilization and bioconversion with regard to sustainable production of humic substances. The detailed and comprehensive analyses demonstrate the huge biotechnological potential of Bacillus sp. for agricultural productivity and environmental health.