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The number of studies on work breaks and the importance of this subject is growing rapidly, with research showing that work breaks increase employees’ wellbeing and performance and workplace safety. However, comparing the results of work break research is difficult since the study designs and methods are heterogeneous and there is no standard theoretical model for work breaks. Based on a systematic literature search, this scoping review included a total of 93 studies on experimental work break research conducted over the last 30 years. This scoping review provides a first structured evaluation regarding the underlying theoretical framework, the variables investigated, and the measurement methods applied. Studies using a combination of measurement methods from the categories “self-report measures,” “performance measures,” and “physiological measures” are most common and to be preferred in work break research. This overview supplies important information for ergonomics researchers allowing them to design work break studies with a more structured and stronger theory-based approach. A standard theoretical model for work breaks is needed in order to further increase the comparability of studies in the field of experimental work break research in the future.
Atmospheric aerosols affect the power production of solar energy systems. Their impact depends on both the atmospheric conditions and the solar technology employed. By being a region with a lack in power production and prone to high solar insolation, West Africa shows high potential for the application of solar power systems. However, dust outbreaks, containing high aerosol loads, occur especially in the Sahel, located between the Saharan desert in the north and the Sudanian Savanna in the south. They might affect the whole region for several days with significant effects on power generation. This study investigates the impact of atmospheric aerosols on solar energy production for the example year 2006 making use of six well instrumented sites in West Africa. Two different solar power technologies, a photovoltaic (PV) and a parabolic through (PT) power plant, are considered. The daily reduction of solar power due to aerosols is determined over mostly clear-sky days in 2006 with a model chain combining radiative transfer and technology specific power generation. For mostly clear days the local daily reduction of PV power (at alternating current) (PVAC) and PT power (PTP) due to the presence of aerosols lies between 13 % and 22 % and between 22 % and 37 %, respectively. In March 2006 a major dust outbreak occurred, which serves as an example to investigate the impact of an aerosol extreme event on solar power. During the dust outbreak, daily reduction of PVAC and PTP of up to 79 % and 100 % occur with a mean reduction of 20 % to 40 % for PVAC and of 32 % to 71 % for PTP during the 12 days of the event.
Healing of large bone defects requires implants or scaffolds that provide structural guidance for cell growth, differentiation, and vascularization. In the present work, an agarose-hydroxyapatite composite scaffold was developed that acts not only as a 3D matrix, but also as a release system. Hydroxyapatite (HA) was incorporated into the agarose gels in situ in various ratios by a simple procedure consisting of precipitation, cooling, washing, and drying. The resulting gels were characterized regarding composition, porosity, mechanical properties, and biocompatibility. A pure phase of carbonated HA was identified in the scaffolds, which had pore sizes of up to several hundred micrometers. Mechanical testing revealed elastic moduli of up to 2.8 MPa for lyophilized composites. MTT testing on Lw35human mesenchymal stem cells (hMSCs) and osteosarcoma MG-63 cells proved the biocompatibility of the scaffolds. Furthermore, scaffolds were loaded with model drug compounds for guided hMSC differentiation. Different release kinetic models were evaluated for adenosine 5′-triphosphate (ATP) and suramin, and data showed a sustained release behavior over four days.
Scratch assays enable the study of the migration process of an injured adherent cell layer in vitro. An apparatus for the reproducible performance of scratch assays and cell harvesting has been developed that meets the requirements for reproducibility in tests as well as easy handling. The entirely autoclavable setup is divided into a sample translation and a scratching system. The translational system is compatible with standard culture dishes and can be modified to adapt to different cell culture systems, while the scratching system can be adjusted according to angle, normal force, shape, and material to adapt to specific questions and demanding substrates. As a result, a fully functional prototype can be presented. This system enables the creation of reproducible and clear scratch edges with a low scratch border roughness within a monolayer of cells. Moreover, the apparatus allows the collection of the migrated cells after scratching for further molecular biological investigations without the need for a second processing step. For comparison, the mechanical properties of manually performed scratch assays are evaluated.
Due to global ecological and economic challenges that have been correlated to the transition from fossil-based to renewable resources, fundamental studies are being performed worldwide to replace fossil fuel raw materials in plastic production. One aspect of current research is the development of lignin-derived polyols to substitute expensive fossil-based polyol components for polyurethane and polyester production. This article describes the synthesis of bioactive lignin-based polyurethane coatings using unmodified and demethylated Kraft lignins. Demethylation was performed to enhance the reaction selectivity toward polyurethane formation. The antimicrobial activity was tested according to a slightly modified standard test (JIS Z 2801:2010). Besides effects caused by the lignins themselves, triphenylmethane derivatives (brilliant green and crystal violet) were used as additional antimicrobial substances. Results showed increased antimicrobial capacity against Staphylococcus aureus. Furthermore, the coating color could be varied from dark brown to green and blue, respectively.
Background: Coniferous woods (Abies nordmanniana (Stev.) Spach, Abies procera Rehd, Picea abies (L.) H.Karst, and Picea pungens Engelm.) could contain useful secondary metabolites to produce sustainable packaging materials, e.g., by substitution of harmful petrol-based additives in plastic packaging. This study aims to characterise the antioxidant and light-absorbing properties and ingredients of different coniferous wood extracts with regard to different plant fragments and drying conditions. Furthermore, the valorisation of used Christmas trees is evaluated. Methods: Different drying and extraction techniques were applied with the extracts being characterised by determining the total phenolic content (TPC), total antioxidant capacity (TAC), and absorbance in the ultraviolet range (UV). Gas chromatography coupled with mass spectrometry (GC-MS) and an acid–butanol assay (ABA) were used to characterise the extract constituents. Results: All the extracts show a considerably high UV absorbance while interspecies differences did occur. All the fresh and some of the dried biomass extracts reached utilisable TAC and TPC values. A simplified extraction setup for industrial application is evaluated; comparable TAC results could be reached with modifications. Conclusion: Coniferous woods are a promising renewable resource for preparation of sustainable antioxidants and photostabilisers. This particularly applies to Christmas trees used for up to 12 days. After extraction, the biomass can be fully valorised by incorporation in paper packaging.
Surface-enhanced Raman spectroscopy (SERS) with subsequent chemometric evaluation was performed for the rapid and non-destructive differentiation of seven important meat-associated microorganisms, namely Brochothrix thermosphacta DSM 20171, Pseudomonas fluorescens DSM 4358, Salmonella enterica subsp. enterica sv. Enteritidis DSM 14221, Listeria monocytogenes DSM 19094, Micrococcus luteus DSM 20030, Escherichia coli HB101 and Bacillus thuringiensis sv. israelensis DSM 5724. A simple method for collecting spectra from commercial paper-based SERS substrates without any laborious pre-treatments was used. In order to prepare the spectroscopic data for classification at genera level with a subsequent chemometric evaluation consisting of principal component analysis and discriminant analysis, a pre-processing method with spike correction and sum normalisation was performed. Because of the spike correction rather than exclusion, and therefore the use of a balanced data set, the multivariate analysis of the data is significantly resilient and meaningful. The analysis showed that the differentiation of meat-associated microorganisms and thereby the detection of important meat-related pathogenic bacteria was successful on genera level and a cross-validation as well as a classification of ungrouped data showed promising results, with 99.5 % and 97.5 %, respectively.
This work thoroughly investigates a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows. In contrast to other LBM for compressible flows, the vertices are organized in cells, and interpolation polynomials up to fourth order are used to attain the off-vertex distribution function values. Differing from the recently introduced Particles on Demand (PoD) method , the method operates in a static, non-moving reference frame. Yet the SLLBM in the present formulation grants supersonic flows and exhibits a high degree of Galilean invariance. The SLLBM solver allows for an independent time step size due to the integration along characteristics and for the use of unusual velocity sets, like the D2Q25, which is constructed by the roots of the fifth-order Hermite polynomial. The properties of the present model are shown in diverse example simulations of a two-dimensional Taylor-Green vortex, a Sod shock tube, a two-dimensional Riemann problem and a shock-vortex interaction. It is shown that the cell-based interpolation and the use of Gauss-Lobatto-Chebyshev support points allow for spatially high-order solutions and minimize the mass loss caused by the interpolation. Transformed grids in the shock-vortex interaction show the general applicability to non-uniform grids.
This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20° N and 20° W to 16° E) and the implications for photovoltaic systems. Here, we use satellite irradiance (Surface Solar Radiation Data Set – Heliosat, Edition 2.1 – SARAH-2.1) and temperature data from a reanalysis (ERA5) to derive photovoltaic yields. Based on 35 years of data (1983–2017), the temporal and regional variability as well as long-term trends in global and direct horizontal irradiance are analyzed. Furthermore, a detailed time series analysis is undertaken at four locations. According to the high spatial resolution SARAH-2.1 data record (0.05°×0.05°), solar irradiance is largest (up to a 300 W m−2 daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W m−2 per decade) and a lower temporal variability (<75 W m−2 between 1983 and 2017 for daily averages). In contrast, the solar irradiance is lower in southern West Africa (between 200 W m−2 and 250 W m−2) with a negative trend (up to −5 W m−2 per decade) and a higher temporal variability (up to 150 W m−2). The positive trend in the north is mostly connected to the dry season, whereas the negative trend in the south occurs during the wet season. Both trends show 95 % significance. Photovoltaic (PV) yields show a strong meridional gradient with the lowest values of around 4 kWh kWp−1 in southern West Africa and values of more than 5.5 kWh kWp−1 in the Sahara and Sahel zone.
Miscanthus crops possess very attractive properties such as high photosynthesis yield and carbon fixation rate. Because of these properties, it is currently considered for use in second-generation biorefineries. Here we analyze the differences in chemical composition between M. x giganteus, a commonly studied Miscanthus genotype, and M. nagara, which is relatively understudied but has useful properties such as increased frost resistance and higher stem stability. Samples of M. x giganteus (Gig35) and M. nagara (NagG10) have been separated by plant portion (leaves and stems) in order to isolate the corresponding lignins. The organosolv process was used for biomass pulping (80% ethanol solution, 170 °C, 15 bar). Biomass composition and lignin structure analysis were performed using composition analysis, Fourier-transform infrared (FTIR), ultraviolet-visible (UV-Vis) and nuclear magnetic resonance (NMR) spectroscopy, thermogravimetric analysis (TGA), size exclusion chromatography (SEC) and pyrolysis gas-chromatography/mass spectrometry (Py-GC/MS) to determine the 3D structure of the isolated lignins, monolignol ratio and most abundant linkages depending on genotype and harvesting season. SEC data showed significant differences in the molecular weight and polydispersity indices for stem versus leaf-derived lignins. Py-GC/MS and hetero-nuclear single quantum correlation (HSQC) NMR revealed different monolignol compositions for the two genotypes (Gig35, NagG10). The monolignol ratio is slightly influenced by the time of harvest: stem-derived lignins of M. nagara showed increasing H and decreasing G unit content over the studied harvesting period (December–April).
Background: Human mesenchymal stem cells (hMSCs) have shown their multipotential including differentiating towards endothelial and smooth muscle cell lineages, which triggers a new interest for using hMSCs as a putative source for cardiovascular regenerative medicine. Our recent publication has shown for the first time that purinergic 2 receptors are key players during hMSC differentiation towards adipocytes and osteoblasts. Purinergic 2 receptors play an important role in cardiovascular function when they bind to extracellular nucleotides. In this study, the possible functional role of purinergic 2 receptors during MSC endothelial and smooth muscle differentiation was investigated. Methods and Results: Human MSCs were isolated from liposuction materials. Then, endothelial and smooth muscle-like cells were differentiated and characterized by specific markers via Reverse Transcriptase-PCR (RT-PCR), Western blot and immunochemical stainings. Interestingly, some purinergic 2 receptor subtypes were found to be differently regulated during these specific lineage commitments: P2Y4 and P2Y14 were involved in the early stage commitment while P2Y1 was the key player in controlling MSC differentiation towards either endothelial or smooth muscle cells. The administration of natural and artificial purinergic 2 receptor agonists and antagonists had a direct influence on these differentiations. Moreover, a feedback loop via exogenous extracellular nucleotides on these particular differentiations was shown by apyrase digest. Conclusions: Purinergic 2 receptors play a crucial role during the differentiation towards endothelial and smooth muscle cell lineages. Some highly selective and potent artificial purinergic 2 ligands can control hMSC differentiation, which might improve the use of adult stem cells in cardiovascular tissue engineering in the future.
Off-lattice Boltzmann methods increase the flexibility and applicability of lattice Boltzmann methods by decoupling the discretizations of time, space, and particle velocities. However, the velocity sets that are mostly used in off-lattice Boltzmann simulations were originally tailored to on-lattice Boltzmann methods. In this contribution, we show how the accuracy and efficiency of weakly and fully compressible semi-Lagrangian off-lattice Boltzmann simulations is increased by velocity sets derived from cubature rules, i.e. multivariate quadratures, which have not been produced by the Gauß-product rule. In particular, simulations of 2D shock-vortex interactions indicate that the cubature-derived degree-nine D2Q19 velocity set is capable to replace the Gauß-product rule-derived D2Q25. Likewise, the degree-five velocity sets D3Q13 and D3Q21, as well as a degree-seven D3V27 velocity set were successfully tested for 3D Taylor–Green vortex flows to challenge and surpass the quality of the customary D3Q27 velocity set. In compressible 3D Taylor–Green vortex flows with Mach numbers on-lattice simulations with velocity sets D3Q103 and D3V107 showed only limited stability, while the off-lattice degree-nine D3Q45 velocity set accurately reproduced the kinetic energy provided by literature.
In this study, we investigate the thermo-mechanical relaxation and crystallization behavior of polyethylene using mesoscale molecular dynamics simulations. Our models specifically mimic constraints that occur in real-life polymer processing: After strong uniaxial stretching of the melt, we quench and release the polymer chains at different loading conditions. These conditions allow for free or hindered shrinkage, respectively. We present the shrinkage and swelling behavior as well as the crystallization kinetics over up to 600 ns simulation time. We are able to precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influences crystallization and relaxation behavior. From our models, we determine the temperature dependent crystallization rate of polyethylene, including crystallization onset temperature.
Different analyses and feasibility studies have been conducted on the plant extracts of thyme (Thymus vulgaris), European horse chestnut (Aesculus hippocastanum), Nordmann fir (Abies nordmanniana), and snowdrop (Galanthus elwesii) to evaluate bio‐based alternatives to common petrol‐based stabilisers. For this purpose, in this study, plant extracts were incorporated into poly‐lactic acid films (PLA) at different concentrations. The films’ UV absorbance and migration into packed food was analysed via photometric assays (ABTS radical cation scavenging capacity assay, β‐carotene assay) and GC–MS analysis. Furthermore, the synergistic antioxidant effects of various combinations of extracts and isolated active compounds were determined. This way, antioxidant effects can be increased, allowing for a highly effective use of resources. All extracts were successfully incorporated into PLA films and showed notable photoabsorbing effects, while no migration risk was observed. Depending on extract combinations, high synergistic effects of up to 726% can be utilised to improve the effectiveness of bio‐based extracts. This applies particularly to tomato paste and Aesculus hippocastanum extracts, which overall show high synergistic and antioxidant effects in combination with each other and with isolated active compounds. The study shows that it is possible to create safe bio‐based antioxidant films which show even improved properties when using highlighted target combinations.
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.
Because the robust and rapid determination of spoilage microorganisms is becoming increasingly important in industry, the use of IR microspectroscopy, and the establishment of robust and versatile chemometric models for data processing and classification, is gaining importance. To further improve the chemometric models, bacterial stress responses were induced, to study the effect on the IR spectra and to improve the chemometric model. Thus, in this work, nine important food-relevant microorganisms were subjected to eight stress conditions, besides the regular culturing as a reference. Spectral changes compared to normal growth conditions without stressors were found in the spectral regions of 900–1500 cm−1 and 1500–1700 cm−1. These differences might stem from changes in the protein secondary structure, exopolymer production, and concentration of nucleic acids, lipids, and polysaccharides. As a result, a model for the discrimination of the studied microorganisms at the genus, species and strain level was established, with an accuracy of 96.6%. This was achieved despite the inclusion of various stress conditions and times after incubation of the bacteria. In addition, a model was developed for each individual microorganism, to separate each stress condition or regular treatment with 100% accuracy.
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.
Dental stem cells have been isolated from the medical waste of various dental tissues. They have been characterized by numerous markers, which are evaluated herein and differentiated into multiple cell types. They can also be used to generate cell lines and iPSCs for long-term in vitro research. Methods for utilizing these stem cells including cellular systems such as organoids or cell sheets, cell-free systems such as exosomes, and scaffold-based approaches with and without drug release concepts are reported in this review and presented with new pictures for clarification. These in vitro applications can be deployed in disease modeling and subsequent pharmaceutical research and also pave the way for tissue regeneration. The main focus herein is on the potential of dental stem cells for hard tissue regeneration, especially bone, by evaluating their potential for osteogenesis and angiogenesis, and the regulation of these two processes by growth factors and environmental stimulators. Current in vitro and in vivo publications show numerous benefits of using dental stem cells for research purposes and hard tissue regeneration. However, only a few clinical trials currently exist. The goal of this review is to pinpoint this imbalance and encourage scientists to pick up this research and proceed one step further to translation.
The analysis of used engine oils from industrial engines enables the study of engine wear and oil degradation in order to evaluate the necessity of oil changes. As the matrix composition of an engine oil strongly depends on its intended application, meaningful diagnostic oil analyses bear considerable challenges. Owing to the broad spectrum of available oil matrices, we have evaluated the applicability of using an internal standard and/or preceding sample digestion for elemental analysis of used engine oils via inductively coupled plasma optical emission spectroscopy (ICP OES). Elements originating from both wear particles and additives as well as particle size influence could be clearly recognized by their distinct digestion behaviour. While a precise determination of most wear elements can be achieved in oily matrix, the measurement of additives is performed preferably after sample digestion. Considering a dataset of physicochemical parameters and elemental composition for several hundred used engine oils, we have further investigated the feasibility of predicting the identity and overall condition of an unknown combustion engine using the machine learning system XGBoost. A maximum accuracy of 89.6% in predicting the engine type was achieved, a mean error of less than 10% of the observed timeframe in predicting the oil running time and even less than 4% for the total engine running time, based purely on common oil check data. Furthermore, obstacles and possibilities to improve the performance of the machine learning models were analysed and the factors that enabled the prediction were explored with SHapley Additive exPlanation (SHAP). Our results demonstrate that both the identification of an unknown engine as well as a lifetime assessment can be performed for a first estimation of the actual sample without requiring meticulous documentation.
In young adulthood, important foundations are laid for health later in life. Hence, more attention should be paid to the health measures concerning students. A research field that is relevant to health but hitherto somewhat neglected in the student context is the phenomenon of presenteeism. Presenteeism refers to working despite illness and is associated with negative health and work-related effects. The study attempts to bridge the research gap regarding students and examines the effects of and reasons for this behavior. The consequences of digital learning on presenteeism behavior are moreover considered. A student survey (N = 1036) and qualitative interviews (N = 11) were conducted. The results of the quantitative study show significant negative relationships between presenteeism and health status, well-being, and ability to study. An increased experience of stress and a low level of detachment as characteristics of digital learning also show significant relationships with presenteeism. The qualitative interviews highlighted the aspect of not wanting to miss anything as the most important reason for presenteeism. The results provide useful insights for developing countermeasures to be easily integrated into university life, such as establishing fixed learning partners or the use of additional digital learning material.
Background: Since presenteeism is related to numerous negative health and work-related effects, measures are required to reduce it. There are initial indications that how an organization deals with health has a decisive influence on employees’ presenteeism behavior.
Aims: The concept of health-promoting collaboration was developed on the basis of these indications. As an extension of healthy leadership it includes not only the leader but also co-workers. In modern forms of collaboration, leaders cannot be assigned sole responsibility for employees’ health, since the leader is often hardly visible (digital leadership) or there is no longer a clear leader (shared leadership). The study examines the concept of health-promoting collaboration in relation to presenteeism. Relationships between health-promoting collaboration, well-being and work ability are also in focus, regarding presenteeism as a mediator.
Methods: The data comprise the findings of a quantitative survey of 308 employees at a German university of applied sciences. Correlation and mediator analyses were conducted.
Results: The results show a significant negative relationship between health-promoting collaboration and presenteeism. Significant positive relationships were found between health-promoting collaboration and both well-being and work ability. Presenteeism was identified as a mediator of these relationships.
Conclusion: The relevance of health-promoting collaboration in reducing presenteeism was demonstrated and various starting points for practice were proposed. Future studies should investigate further this newly developed concept in relation to presenteeism.
Due to the COVID-19 pandemic, health education programs and workplace health promotion (WHP) could only be offered under difficult conditions, if at all. In Germany for example, mandatory lockdowns, working from home, and physical distancing have led to a sharp decline in expenditure on prevention and health promotion from 2019 to 2020. At the same time, the pandemic has negatively affected many people’s mental health. Therefore, our goal was to examine audiovisual stimulation as a possible measure in the context of WHP, because its usage is contact-free, time flexible, and offers, additionally, voice-guided health education programs. In an online survey following a cross-sectional single case study design with 393 study participants, we examined the associations between audiovisual stimulation and mental health, work engagement, and burnout. Using multiple regression analyses, we could identify positive associations between audiovisual stimulation and mental health, burnout, and work engagement. However, longitudinal data are needed to further investigate causal mechanisms between mental health and the use of audiovisual stimulation. Nevertheless, especially with regard to the pandemic, audiovisual stimulation may represent a promising measure for improving mental health at the workplace.
This study investigates the initial stage of the thermo-mechanical crystallization behavior for uni- and biaxially stretched polyethylene. The models are based on a mesoscale molecular dynamics approach. We take constraints that occur in real-life polymer processing into account, especially with respect to the blowing stage of the extrusion blow-molding process. For this purpose, we deform our systems using a wide range of stretching levels before they are quenched. We discuss the effects of the stretching procedures on the micro-mechanical state of the systems, characterized by entanglement behavior and nematic ordering of chain segments. For the cooling stage, we use two different approaches which allow for free or hindered shrinkage, respectively. During cooling, crystallization kinetics are monitored: We precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influence crystallization behavior. Our models reveal that the main stretching direction dominates microscopic states of the different systems. We are able to show that crystallization mainly depends on the (dis-)entanglement behavior. Nematic ordering plays a secondary role.
With the increasing demand for ultrapure water in the pharmaceutical and semiconductor industry, the need for precise measuring instruments for those applications is also growing. One critical parameter of water quality is the amount of total organic carbon (TOC). This work presents a system that uses the advantage of the increased oxidation power achieved with UV/O3 advanced oxidation process (AOP) for TOC measurement in combination with a significant miniaturization compared to the state of the art. The miniaturization is achieved by using polymer-electrolyte membrane (PEM) electrolysis cells for ozone generation in combination with UV-LEDs for irradiation of the measuring solution, as both components are significantly smaller than standard equipment. Conductivity measurement after oxidation is the measuring principle and measurements were carried out in the TOC range between 10 and 1000 ppb TOC. The suitability of the system for TOC measurement is demonstrated using the oxidation by ozonation combined with UV irradiation of defined concentrations of isopropyl alcohol (IPA).
Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy
(2022)
As the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but they are exposed to a variety of stress factors, such as temperature differences, there is a demand for a method that can take these stress factors and the associated reactions of the bacteria into account. Therefore, bacterial stress reactions to lifetime conditions (regular treatment, 25 °C, HCl, 2-propanol, NaOH) and sampling conditions (cold sampling, desiccation, heat drying) were induced to explore the effects on Raman spectra in order to improve the chemometric models. As a result, in this study nine food-relevant bacteria were exposed to seven stress conditions in addition to routine cultivation as a control. Spectral alterations in lipids, polysaccharides, nucleic acids, and proteins were observed when compared to normal growth circumstances without stresses. Regardless of the involvement of several stress factors and storage times, a model for differentiating the analyzed microorganisms from genus down to strain level was developed. Classification of the independent training dataset at genus and species level for Escherichia coli and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%.