In aerobic environments, bacteria are exposed to reactive oxygen species (ROS). To avoid an excess of ROS, microorganisms are equipped with powerful enzymatic and non-enzymatic antioxidants. Corynebacterium glutamicum, a widely used industrial platform organism, uses mycothiol (MSH) as major low molecular weight (LMW) thiol and non-enzymatic antioxidant. In aerobic bioreactor cultivations C. glutamicum becomes exposed to oxygen concentrations surpassing the air saturation, which are supposed to constitute a challenge for the intracellular MSH redox balance. In this study, the role of MSH was investigated at different oxygen levels (pO2) in bioreactor cultivations in C. glutamicum. Despite the presence of other highly efficient antioxidant systems, such as catalase, the MSH deficient ΔmshC mutant was impaired in growth in bioreactor experiments performed at pO2 values of 30%. At a pO2 level of 20% this growth defect was abolished, indicating a high susceptibility of the MSH-deficient mutant towards elevated oxygen concentrations. Bioreactor experiments with C. glutamicum expressing the Mrx1-roGFP2 redox biosensor revealed a strong oxidative shift in the MSH redox potential (EMSH) at pO2 values above 20%. This indicates, that the LMW thiol MSH is an essential antioxidant to maintain the robustness and industrial performance of C. glutamicum during aerobic fermentation processes.

Physics-informed neural networks are a promising method to yield surrogate models of flow fields. We present a metamodeling technique for variable geometries based on physics-informed neural networks. The method was applied to the DU99W350 airfoil at a Reynolds number of 1×10⁵. The model predicted the Reynolds-averaged velocity and pressure field around the airfoil for arbitrary angles of attack between 10.0° and 17.5°. The model was trained with data from CFD simulations for a limited set of angles of attack. Additionally, satisfaction of the a priori known boundary conditions as well as the Reynolds-averaged Navier-Stokes equations were trained. A sensitivity analysis concerning the Reynolds number, the amount and distribution of training data, and the turbulence model was conducted showing the superiority of the pseudo-Reynolds stress method and the demand of labeled training data in the domain. The trained network was capable of predicting the developing flow separation on the suction surface and exhibited excellent agreement with CFD results even in the proximity to the wall for interpolations as well as extrapolations from the labeled data set.

In post mortem analyses, SARS-CoV-2 was found in the middle ear of some, but not all patients with COVID-19 disease. It is not clear whether SARS-CoV-2 penetrated the ear passively post mortem, or existed in the middle ear of living patients during, and perhaps also after infection. This study investigates whether SARS-CoV-2 can be found in the middle ear of living patients during ear surgery. Swabs from the nasopharynx, the filter connected to the tracheal tube and secretion from the middle ear were collected during middle ear surgery. All samples were tested for the presence of SARS-CoV-2 with PCR. History of vaccination, COVID-19 and contact with SARS-CoV-2-positive individuals were recorded preoperatively. Postoperative SARS-CoV-2 infection was noted at the follow-up visit. Overall 63 participants (62%) were children and 39 (38%) were adults. SARS-CoV-2 was found in the middle ear and in the nasopharynx of two and four CovEar Study participants, respectively. The filter connected to the tracheal tube was sterile in all cases. Cycle threshold (ct) values of the PCR test were between 25.94 and 37.06. SARS-CoV-2 penetrates into the middle ear of living patients and can be found in asymptomatic patients. The presence of SARS-CoV-2 in the middle ear may have implications for ear surgery and can pose a risk of infection for operating room staff. It may also directly affect the audio-vestibular system.

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature’s treasures, however, could be used more effectively. Yet, reliable pipelines for large scale target prediction of natural products are still rare. We have developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs) – a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β- hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target prediction and guidance on using the respective tools.

This review considers the generation of relatively simple biomolecules, e.g., primary amino acids, resulting from the rapid collapse of bubbles in aqueous solutions containing various, low molar mass, gases. Some of the possible primary reactions occurring to produce the biomolecules are introduced and discussed. A brief discussion is included on the possible involvement of hydrodynamic cavitation, at the primordial seashore, as the initiating processes for the formation of the first organic molecules on prebiotic earth and the origins of life on Earth some 4 billion years ago.

When phenomena in quantum mechanics are interpreted from the perspective of bio-psychology, wave function collapse from several to a single eigenstate must be plausibly explained. Quantum mechanics requires a context, yet the context of an observer is rarely considered. On the other hand, in bio-psychology, the observer context is examined to explain superposition and collapse by different mental functions used in everyday life. Three mental functions are described, one of which is responsible for observation, and the others for conservation and treatment of information in mental representation. Whereas observation produces information with certainty, the subsequent processes result in uncertain potentiality. In order to encompass uncertainty, multiple possibilities are simultaneously considered in mental superposition, one of which should represent the unknown future outcome. During observation, all suggested potentialities necessarily collapse to one real outcome. The collapse of superposition does not occur in observable physical reality, but in its mental representation. Some physical principles—such as superposition, infinity and nothingness before the Big Bang—are pure phenomena of mental representation, which will always remain unverifiable by observation. This argument proves that mental representation brought about by the observer context participates in the production of mental models for the best approximation of physical reality.

Unsupervised physics-informed deep learning can be used to solve computational physics problems by training neural networks to satisfy the underlying equations and boundary conditions without labeled data. Parameters such as network architecture and training method determine the training success. However, the best choice is unknown a priori as it is case specific. Here, we investigated network shapes, sizes, and types for unsupervised physics-informed deep learning of the two-dimensional Reynolds-averaged flow around cylinders. We trained mixed-variable networks and compared them to traditional models. Several network architectures with different shape factors and sizes were evaluated. The models were trained to solve the Reynolds-averaged Navier-Stokes equations incorporating Prandtl's mixing length turbulence model. No training data were deployed to train the models. The superiority of the mixed-variable approach was confirmed for the investigated high Reynolds number flow. The mixed-variable models were sensitive to the network shape. For the two cylinders, differently deep networks showed superior performance. The best fitting models were able to capture important flow phenomena such as stagnation regions, boundary layers, flow separation, and recirculation. We also encountered difficulties when predicting high Reynolds number flows without training data

A major parameter controlling the extent and rate of oral drug absorption is permeability through the lipid bilayer of intestinal epithelial cells. Here, a biomimetic artificial membrane permeability assay (Franz-Bampa) was validated using Franz cells apparatus. Both high and low permeability drugs (metoprolol and mannitol, respectively) were used as external standards. Biomimetic properties of Franz-Bampa were also characterized by electron paramagnetic resonance spectroscopy (EPR). Moreover, the permeation profile for the 14 BCS class I-IV drugs cited in the FDA guidance (including other drugs as acyclovir, cimetidine, diclofenac, ibuprofen, piroxicam, and trimethoprim) were measured across Franz-Bampa. Apparent permeability (Papp) was compared to literature fraction dose absorbed in humans (Fa%). Papp in Caco-2 cells and Corti artificial membrane were likewise compared to Fa% to assess Franz-Bampa performance. Mannitol and metoprolol Papp values across Franz-Bampa were lower (3.20 x 10-7 and 1.61 x 10-5 cm/s, respectively) than those obtained across non-impregnated membrane (2.27 x 10-5 and 2.55 x 10-5 cm/s, respectively), confirming lipidic barrier resistivity. Performance of the Franz cell permeation apparatus using an artificial membrane showed similar log linear correlation (R2 = 0.664) with Fa%, as seen for Papp in Caco-2 cells (R2 = 0.805). Data support the validation of the Franz-Bampa method for use during drug discovery process.

There is little doubt that final victories over pandemics, such as COVID-19, are attributed to herd immunity, either through post-disease convalescence or active immunization of a high percentage of the world's population with vaccines, demonstrating protection from infection and transmission, being available in large quantities and at reasonable prices. However, it is assumable that humans with immune defects or immune suppression, e.g., as a consequence of allograft transplantation, cannot be immunized actively nor produce sufficient immune responses to prevent SARS-CoV-2 infections. These subjects desperately need other strategies, such as sophisticated protection measures and active immunization. Hypertonic salt solutions attack vulnerable core areas of viruses, i.e., salt denatures surface proteins and thus prohibits virus penetration of somatic cells. It has to be ensured that somatic proteins are not affected by denaturation regarding this unspecific virus protection. Impregnating filtering facepieces with hypertonic salt solutions is a straightforward way to inactivate viruses and other potential pathogens. As a result of the contact of salt crystals on the filtering facepiece, these pathogens become denatured and inactivated almost quantitatively. Such a strategy could be easily applied to fight against the COVID-19 pandemic and other ones that may occur in the future. Another possible tool to fight the COVID-19 pandemic is passive immunization with antibodies against SARS-CoV-2, preferably from human origin. Such antibodies can be harvested from patients´ human sera, which have successfully survived their SARS-CoV-2 infection. The disadvantage of a rapid decrease of the immunoglobulin titer after infection ends can be overcome by immortalizing antibody-producing B-cells via fusion with, e.g., mouse myeloma cells. The resulting monoclonal antibodies are then of human origin and available in, at least theoretically, unlimited amounts. Finally, dry blood spots are a valuable tool for surveilling the population´s immunity.

Physics-informed neural networks can be trained to serve as surrogate models by learning how spatial physical fields develop with change of parameters. This is an advantage over traditional numerical methods that can only be used to calculate a single solution field for a single discrete setting of a parameter. While many studies report accurate results of physics-informed deep learning of laminar flows, evaluations of surrogate modeling of high Reynolds number flows remain sparse. To contribute to this question, we here explore the capabilities and limits of physics-informed deep learning to solve the Reynolds-averaged Navier-Stokes equations for the flow around two airfoils under variable angles of attack. No labeled training data were provided and a single network was trained to simultaneously learn several solution fields in a single training run. The network captured essential flow features such as boundary layers and high and low pressure regions. Moreover, the qualitative correlations of lift and drag with the angle of attack and the higher drag of the thicker airfoil were captured. However, comparisons with reference simulations revealed an underestimation of the shear layer gradients as well as deviations of the fields' extrema. Thus, we also debate potential future improvements to increase the accuracy of the predicted flow. This work offers a prospect on the capabilities and current limitations of physics-informed neural networks for surrogate modeling of high Reynolds number flows. We argue that the method is promising and this work is aimed to encourage further research and development of the method when applied to Reynolds-averaged flows at high Reynolds numbers.

We discuss two methods to detect the presence and location of a person in a small-scale room and compare the performances. The first method is Direct Intersection, which determines a coordinate point based on the intersection of spheroids defined by observed distances of high-intensity reverberations. The second method, Sonogram analysis, overlays all channel’s room impulse responses to generate an intensity map for the observed environment. We demonstrate that the former method has lower computation complexity and higher accuracy for small numbers of channels, while the latter performs more robustly.

In bioprocess engineering the Qualtiy by Design (QbD) initiative encourages the use of models to define design spaces. However, clear guides on how models for QbD are validated are still missing. In this review we provide a comprehensive overview about validation methods, mathematical approaches and metrics currently applied in bioprocess modeling. The methods cover analytics for data used for modeling, model training and selection, measures for predictiveness and model uncertainties. We point out general issues in model validation and calibration for different types of models and put this into context of existing health authority recommendations. This review provides the start-point for developing a guidance for model validation approaches. There is no one-fits-all approach but this review shall help to identify the best fitting validation method or combination of methods for the specific task and type of bioprocess models that is developed.

We propose an asynchronous acoustic chirp slope keying to map bit sequences on single or multiple bands without preamble or error correction coding on the physical layer. Details of the implementation are disclosed and discussed, the performance verified on laboratory scale in a pool measurement, as well as simulated for a channel containing Rayleigh fading and Additive White Gaussian Noise. For time-bandwidth products of 50 in single band mode, a raw data rate of 100~bit/s is simulated to achieve bit error rates below 0.001 for signal-to-noise ratios above -6~dB. In dual-band mode and a data rate of 200~bit/s, this bit error level was achieved for signal-to-noise ratios above 0~dB for time-bandwidth product of 25. The packet error rates follow this behavior with an offset of 1~dB.

The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy system models. An increasing complexity constitutes a high computational load that can limit the scale of the energy system model. Especially in microgrid optimisation problems with multiple buildings and energy systems with a number of rival supply, distribution and storage technologies, methods are sought to reduce this complexity. In this paper, we present a new 2-Level Approach to MILP energy system models that determine the system design through a combination of continuous and discrete decisions. On the first level, data reduction methods are used to determine the discrete design decisions in a simplified solution space. Those decisions are then fixed, and on the second level the full dataset is used to extract the exact scaling of the chosen technologies. The performance of the new 2-Level Approach is evaluated for a case study of an urban energy system with six buildings and an island system based on a high share of renewable energy technologies. The results of the studies show a high accuracy with respect to the total annual costs, chosen system structure, installed capacities and peak load with the 2-Level Approach compared to the results of a single level optimization. The computational load is thereby reduced by more than one order of magnitude, while a significantly higher accuracy is reached in comparison to the common time series aggregation approach.

The following guide is aimed at aiding in the curation of herbarium collections in Melastomataceae, with an emphasis on the New World species. It contains a summary of the taxonomic realignments at the tribal and generic level within Neotropical taxa of Melastomataceae, as well as some general comments for other groups. A table with a generic linear sequence is also provided, as well as tables with new and synonymized New World genera since 2005 and all currently accepted species. Lastly, a table with the synonyms of over 1000 accepted Neotropical species that have been impacted by these generic realignments is also provided.

Cryptocurrencies like Bitcoin rely on a proof-of-work system to validate transactions and prevent attacks or double-spending. A new proof-of-work is introduced which seems to be the first number theoretic proof-of-work unrelated to primes: it is based on a new metric associated to the Collatz algorithm whose natural generalization is algorithmically undecidable: the inflation propensity is defined as the cardinality of new maxima in a developing Collatz orbit. It is numerically verified that the distribution of inflation propensity slowly converges to a geometric distribution of parameter $0.714 \approx \frac{(\pi - 1)}{3}$ as the sample size increases. This pseudo-randomness opens the door to a new class of proofs-of-work based on congruential graphs.

Theories of quantum gravity suggest that Lorentz invariance, the fundamental symmetry of the Theory of Relativity, may be broken at the Planck energy scale. While any deviation from conventional Physics must be minuscule in particular at attainable energies, this hypothesis motivates ever more sensitive tests of Lorentz symmetry. In the photon sector, astrophysical observations, in particular polarization measurements, are a very powerful tool because tiny deviations from Lorentz invariance will accumulate as photons propagate over cosmological distances. The Standard-Model Extension (SME) provides a theoretical framework in the form of an effective field theory that describes low-energy effects due to a more fundamental quantum gravity theory by adding additional terms to the Standard Model Lagrangian. These terms can be ordered by the mass dimension d of the corresponding operator and lead to a wavelength, polarization, and direction dependent phase velocity of light. In this paper, we analyze optical polarization measurements from 63 Active Galactic Nuclei (AGN) and Gamma-ray Bursts (GRBs) in order to search for Lorentz violating signals. We derive the first set limits on each of the 10 individual birefringent coefficients of the minimal SME with d = 4, with 95% confidence limits on the order of 10⁻³⁴ on the dimensionless coefficients.

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

In this study, we investigate the magnetization behavior of coaxial nanowires fabricated through the sol-gel electrospinning method. Our analysis uncovers a significant reduction in coercivity for CoFe2O4 nanowires when BaTiO3 is used as the shell material, effectively transforming them from hard to soft magnetic. This intriguing behavior is attributed to the magnetization reversal effect at the interface between ferromagnetic and paramagnetic regions, and it is also observed in NiFe2O4 and Fe2O3 nanowires. Surprisingly, introducing a GdBa2Cu3O7 shell induces a similar effect. Additionally, we employ magnetic impedance measurements on the coaxial nanowires, unveiling their potential for magnetic field sensing applications.

This paper discusses the potential and limitations of the Normalized Difference Vegetation Index (NDVI) in environmental justice, health and inequality studies in urban areas. Very often the NDVI is correlated with socioeconomic and/or sociodemographic data to demonstrate the inequality in environmental settings that themselves influence individual health and questions of environmental justice. This paper addresses the limits of the NDVI for such applications and as well its potential, if applied properly. The overall goal is to make people of disciplines other than those that are geo-related aware of the characteristics, limits and potentials of satellite image-based information layers such as NDVI.

Transarterial chemoembolization (TACE) has been used to treat hepatocellular carcinoma (HCC) for more than 4 decades. So far, there is no consensus on which substances and which method should be used for the most effective treatment. A publication commissioned by CIRSE 2021 attempted to formulate recommendations. However, only the spectrum of currently implemented procedures is outlined. No recommendation was made as to how the various patients should be treated. In this article, therefore, basic considerations regarding the technique of chemoembolization are presented. Additionally, the authors discuss fundamental considerations about the embolism materials used, the cytostatic drugs and their dosage, as well as about pain therapy during treatment. Then, a technique is presented which used degradable starch microspheres (DSM) as an embolic agent. This technique allows multiple treatments over a longer period. The aim is to provide interventionalists with a decision-making aid for the TACE technique. A major problem when evaluating publications from different working groups is that the technology used is not adequately described and the individual studies are therefore not comparable. Therefore, a classification is presented that systematizes the possible different techniques. Future randomized trials should use this classification. Hopefully, if they are carried out on a sufficient number of patients, it will finally be possible to identify what is the best TACE procedure for individual patients. Until then the technique proposed by the authors can be applied.

Immunosuppressed individuals, such as people living with HIV (PLWH), remain vulnerable to severe COVID-19. We analyzed the persistence of specific SARS-CoV-2 humoral and cellular immune responses in a retrospective, cross-sectional study in PLWH on antiretroviral therapy. Among 104 participants, 70.2% had anti-S IgG antibodies and 55.8% had significant neutralizing activity against the Omicron variant in a surrogate virus neutralization test. Only 38.5% were vaccinated (8.76 ± 4.1 months prior), all displaying anti-S IgG, 75% with neutralizing antibodies and anti-S IgA. 29.8% had no SARS-CoV-2 serologic markers and displayed significantly lower CD4 counts and HIV viral load. Severe immunosuppression (present in 12.5% of participants) was linked to lower levels of detectable anti-S IgG (0.0003), anti-S IgA (p < 0.0001) and lack of neutralizing activity against Omicron variant (p < 0.0001). T-cell responses were present in 86.7% of tested participants, even in those lacking serological markers. In PLWH without severe immunosuppression, neutralizing antibodies and T-cell responses persisted for up to 9 months post-infection or vaccination. Advanced immunosuppression led to diminished humoral immunity, but retained cellular immune.

Operational weather and also flood forecasting has been performed successfully for decades and is of great socioeconomic importance. Up to now, forecast products focus on atmospheric variables, such as precipitation, air temperature and, in hydrology, on river discharge. Considering the full terrestrial system from groundwater across the land surface into the atmosphere, a number of important hydrologic variables are missing especially with regard to the shallow and deeper subsurface (e.g. groundwater), which are gaining considerable attention in the context of global change. In this study, we propose a terrestrial monitoring/forecasting system using the Terrestrial Systems Modeling Platform (TSMP) that predicts all essential states and fluxes of the terrestrial hydrologic and energy cycles from groundwater into the atmosphere. Closure of the terrestrial cycles provides a physically consistent picture of the terrestrial system in TSMP. TSMP has been implemented over a regional domain over North Rhine-Westphalia and a continental domain over European in a real-time forecast/monitoring workflow. Applying a real-time forecasting/monitoring workflow over both domains, experimental forecasts are being produced with different lead times since the beginning of 2016. Real-time forecast/monitoring products encompass all compartments of the terrestrial system including additional hydrologic variables, such as plant available soil water, groundwater table depth, and groundwater recharge and storage.

During an epidemic outbreak it is useful for planners and responsible authorities to be able to plan ahead to estimate when an outbreak of an epidemic is likely to ease and when the last case can be predicted in their area of responsibility. Theoretically this could be done for a point source epidemic using epidemic curve forecasting. The extensive data now coming out of China makes it possible to test if this can be done using MS Excel a standard spreadsheet program available to most offices. The available data is divided up for whole China and the different provinces. This and the high number of cases makes the analysis possible. Data for new confirmed infections for Hubei, Hubei outside Wuhan, China excluding Hubei as well as Zhejiang and Fujian provinces all follow a log-normal distribution that can be used to make a rough estimate for the date of the last new confirmed cases in respective areas. In the version 2 continuation work, 9 additional days were added for the Chinese data to evaluate the previous predictions. The extra data then available from China follows the previous predicted trend supporting the usefulness of this simple technique. In the version 2 we also tested the feasibility for a non-specialist to make similar predictions using additional data from S Korea now available. In this third continuation the predictions for Version 2 are evaluated for S Korea and fits well the beginning of the decline but it seems to be difficult to bring down numbers of cases per day under about 100 new cases per day, potential reasons for this is discussed. To further evaluate when in a prediction becomes reliable the Chinese data was used to evaluate to make predictions for each day around the peak in number of cases and after2-3 consecutive days of decreasing new cases per day the prediction becomes reliable. In version 3 data for Italy just reaching this point was used to make further predictions for that country. A second new analysis was also added to use the fitted equation to detect when the acceleration of new cases per day stopped increasing exponentially. In the Chinese case this measured point coincides with the date of the complete Hubei lockdown and in the new Italian analysis it coincides with the mandatory Italian lockdown. Predicted dates for the end of the Italian outbreak is also added. In version 4 we expand the analysis to selected European countries, USA and the World as a whole and try to predict the end of the outbreak. We further discuss the apparent success of the used techniques that might work to introduce a “new normal” not very different to the previous to stop secondary outbreaks of COVID19 and future COVIDs that are sure to come.

Tropical storm Nate, which was a powerful hurricane prior to landfall along the Alabama coast, traversed north towards our instrumented site in Hunstville, AL. The rain bands lasted 18 h and the 2D-video disdrometer (2DVD) captured the event which was shallow and indicative of pure warm rain processes. Measurements of raindrop size, shape and velocity distributions are quite rare in pure warm rain and are expected to differ from cold rain processes. In particular, asymmetric shapes due to drop oscillations and their impact on polarimetric radar signatures in warm rain have not been studied so far. Recently, the 2DVD data has been used for 3D reconstruction of asymmetric raindrop shapes but their fraction (relative to the more common oblate shapes) in warm rain has yet to be ascertained. Here we compute the scattering matrix drop-by-drop using Computer Simulation Technology integral equation solver for drop sizes>2.5 mm. From the scattering matrix elements, the polarimetric radar observables are simulated by integrating over 1 minute consecutive segments of the event. These simulated values are compared with dual-polarized C-band radar data located at 15 km range from the 2DVD site to evaluate the contribution of the asymmetric drop shapes.

Abstract: Short-chain fatty acids (SCFAs) are the major microbial metabolites produced in the gut through the fermentation of non-digestible fibers. SCFAs act through free fatty acid receptor 2 and 3 (FFAR2 and 3), which are known to be expressed on glucagon-like peptide-1 (GLP-1)-secreting L-cells. This pathway is suggested to protect the intestinal mucosa. We aimed to investigate how lack of fiber affects the production of SCFAs and the vulnerability of the co-lon. Additionally, the involvement of FFAR2 and 3 in GLP-1 secretion and intestinal protection. SCFA concentrations in luminal contents from chow- or fiber-free diet-fed mice were analysed by LC‒MS. SCFAs were applied to isolated perfused colons from FFAR2/3 double KO and WT mice, and the secretion of GLP-1 was measured. Dextran sulfate sodium (DSS) colitis was induced in chow- or fiber-free diet-fed mice as well as in FFAR2/3 KO and WT mice. The removal of die-tary fiber significantly decreased total colonic SCFA concentrations, with specific decreases in acetate, propionate, and butyrate. SCFAs significantly increased colonic GLP-1 secretion but not in FFAR2/3 KO mice. In the DSS model, the removal of dietary fiber increased the severity and delayed recovery. Colitis severity was independent of FFAR2 and FFAR3 signaling.

The adoption of harmful postures due to a sedentary lifestyle, which involves long periods at work in offices, is a factor that exacerbates musculoskeletal risks. To examine these risks, there are numerous postures analysis methods, such as Rapid Upper Limb Assessment (RULA) and Rapid Office Strain Assessment (ROSA). RULA is a consolidated method to evaluate the exposure of individual workers to ergonomic risk factors associated with upper extremity musculoskeletal disorders. In turn, ROSA is a more recent method that quantifies exposure to risk factors in an office work environment. This research aims to identify whether there is harmony between these two methods, ROSA and RULA. Through applied research, from a qualitative perspective, the scientific procedures adopted were direct observation and ROSA and RULA postural assessment instruments. The study was conducted in the radiology service and focused on the outpatient reception workstation. Results indicated that further investigation must occur to make working conditions changes as soon as possible and that both methods are harmonic. As contributions of the analysis, we have discussed the working conditions and suggested improvements to reduce the risks of musculoskeletal morbidity symptoms. We recommend future studies aimed at measuring the levels of complementarity between these methods by quantitative approaches.

Semisolid casting can provide excellent castings, but the nature of the pore-forming mechanisms has not been properly clarified. In the current communication, it was suggested that hydrogen precipitated during slurry making might have a decisive role in the formation of both gas and shrinkage porosity. Intensive stirring at the end of the slurry making process may act as a degassing step. Without the intense stirring, structures of primary slurry particles form around the hydrogen pores, strongly affecting pore formation and feeding during the intensification stage.

This article presents raw data of biaxial tensile measurements of rat heart passive myocardium conducted in lab scale environment. The passive myocardium of the rat was divided into three regions, namely: left ventricle, mid-wall and right ventricle. The biaxial dataset of passive rat myocardia is presented as stress vs strain of the passive rat myocardium in various regions. The determination of valid material properties of the heart plays an important role in the development computational models. These computational models are useful in studying various scenarios and mechanisms of heart diseases. In addition, valid and accurate materials are critical in the development of new therapies. The dataset presented here is useful in the area of soft tissue mechanics including studying the mechanisms of heart diseases such as myocardial infarction. Accordingly, the evaluation of stress and strain in left ventricle, mid-wall and right ventricle was performed.

MicroRNAs are tissue-specifically expressed short RNAs that serve post-transcriptional gene reg-ulation. A specific microRNA can bind to mRNAs of different genes and thereby suppress their protein production. In the context of the complex phenotype of fibromyalgia, we used the Axiom miRNA Target Site Genotyping Array to search genome-wide for DNA variations in microRNA genes, their regulatory regions and in the 3'UTR of protein-coding genes. To identify dis-ease-relevant DNA polymorphisms, a cohort of 176 female fibromyalgia patients was studied in comparison to a cohort of 162 healthy women. The association between 48.329 markers and fibromyalgia was investigated using logistic regression adjusted for population stratification. 29 markers had p-values < 1 × 10-3 and the strongest asso-ciation was observed for rs758459 (p-value of 0.0001), located in the Neurogenin 1 gene, targeted by hsa-miR-130a-3p. Furthermore, we identified a gene locus (rs2295963) predicted to disrupt binding of hsa-miR-1-3p. Both microRNAs were previously reported to be differentially expressed in fi-bromyalgia patients. Despite its limited statistical power, this study reports two microRNA-related polymorphisms which may play a functional role in the pathogenesis of fibromyalgia. For a better understanding of the disease pattern, further functional analyses on the biological significance of microRNAs and microRNA-related polymorphisms are required.

Immune checkpoint inhibitors (ICI) are currently use in a wide range of tumors, but only 20-40% of patients achieve clinical benefit. Aim of our study was to find predictive biomarkers of ICI treatment. We analyzed by immunohistochemistry various cell subsets, including CD3+ cells, CD8+ cells, CD68+ cells, CD20+ cells, FoxP3+ cells, and molecules as LAG-3, IDO1, TGfβ. Comprehensive genomic profiles were analyzed. Correlation of various biomarkers with efficacy of ICI treatment in patients with advanced solid tumors was evaluated. We evaluated 56 patients treated with ICI monotherapy. Longer median progression-free survival (PFS) was found in tumors negative for nuclear FoxP3 (P = 0.002, HR 0.14) and in TMB-high tumors (P = 0.024, HR 0.38). Longer overall survival (OS) was found in patient with intraepithelial CD8 negativity (P = 0.045, HR 0.47). In malignant melanoma CD68 negativity, FoxP3 negativity and PDL TPS ≥ 1 was associated with longer PFS. In NSCLC FoxP3 was associated with longer PFS and OS. We found that absence of expression of several biomarkers such as CD68 and FoxP3 is associated with better survival. TMB-high and PD-L1 expression not universally but in certain disease could predict response.

The residual multiparticle entropy (RMPE) of a fluid is defined as the difference, Δs, between the excess entropy per particle (relative to an ideal gas with the same temperature and density), s_ex, and the pair-correlation contribution, s₂. Thus, the RMPE represents the net contribution to s_ex due to spatial correlations involving three, four, or more particles. A heuristic “ordering” criterion identifies the vanishing of the RMPE as an underlying signature of an impending structural or thermodynamic transition of the system from a less ordered to a more spatially organized condition (freezing is a typical example). Regardless of this, the knowledge of the RMPE is important to assess the impact of non-pair multiparticle correlations on the entropy of the fluid. Recently, an accurate and simple proposal for the thermodynamic and structural properties of a hard-sphere fluid in fractional dimension 1 < d < 3 has been proposed [Santos, A.; López de Haro, M. Phys. Rev. E 2016, 93, 062126]. The aim of this work is to use this approach to evaluate the RMPE as a function of both d and the packing fraction ϕ. It is observed that, for any given dimensionality d, the RMPE takes negative values for small densities, reaches a negative minimum Δs_min at a packing fraction ϕ_min, and then rapidly increases, becoming positive beyond a certain packing fraction ϕ₀. Interestingly, while both ϕ_min and ϕ₀ monotonically decrease as dimensionality increases, the value of Δs_min exhibits a nonmonotonic behavior, reaching an absolute minimum at a fractional dimensionality d ≃ 2.38. A plot of the scaled RMPE Δs/|Δs_min| shows a quasiuniversal behavior in the region −0.14 ≲ ϕ − ϕ₀ ≲ 0.02.

The excitation of the visual system increases with increasing retinal illumination. At the same time, the sensitivity of the system decreases (light adaptation). Higher excitation automatically results in a lower sensitivity. This study investigates whether this parallelism between the excitation and the sensitivity also applies in the dynamic case, that is, during the transition to a higher excitation level after an increase in the retinal illuminance. For this purpose, the courses of the subjective and the electroretinographic threshold during the transitional phase after a step of the adaptation illumination was determined by means of a special light-stimulation apparatus. As a measure of the course of the excitation during this time, the response ERG on the adaptation step was recorded with a special amplifier. The threshold curve always has an overswing, which shows subjectively very strong differences. It can be concluded that the glare caused by a sudden increase in illuminance is subjectively very different. The comparison between the response ERG on the adaptation step and the course of the electroretinographic increment threshold during this time shows a broad agreement between the two courses. It can thus be assumed that the sensitivity of the visual system follows the course of the excitation also in the dynamic case. In addition, the investigation shows that the glare experienced after a step in the illuminance clearly shows great subjective differences.

The investigation of membrane proteins, key constituents of cells, is hampered by the difficulty and complexity of their in vitro synthesis, of unpredictable yield. Cell-free synthesis is herein employed to unravel the impact of the expression construct on gene transcription and translation, without the complex regulatory mechanisms of cellular systems. Through the systematic design of plasmids in the immediacy of the start of the target gene, it was possible to identify translation initiation and the conformation of mRNA as the main factors governing the cell-free expression efficiency of the human voltage dependent anion channel (VDAC), a relevant membrane protein in drug-based therapy. A simple translation initiation model was developed to quantitatively assess the expression potential for the designed constructs. A scoring function is proposed that quantifies the feasibility of formation of the translation initiation complex through the ribosome-mRNA hybridization energy and the accessibility of the mRNA segment binding to the ribosome. The scoring function enables to optimize plasmid sequences and semi-quantitatively predict protein expression efficiencies. This scoring function is publicly available as webservice XenoExpressO at rna.tbi.univie.ac.at.

In this study, a new approach to pesticide permeation through the apple peel into the pulp is discussed. The tested compounds can be classified, based on mode of action, as systemic (boscalid, cyprodinil, pirimicarb, propiconazole and tebuconazole) or contact (captan, cypermethrin and fludioxonil) pesticides. The barrier effect was assessed using a Franz flow-type vertical diffusion cell system. Residue analysis was performed using a modified quick, easy, cheap, efficient, rugged and safe (QuEChERS) extraction method coupled to gas chromatography with tandem mass spectrometry (GC-MS/MS). The limits of detection (LODs) ranged between 2.6 µg kg-1 (pirimicarb) and 17 µg kg-1 (captan), with the coefficient of variability (CV) lower than 6%, while recoveries ranged from 85% (boscalid) to 112% (captan) at 0.1 and 1 mg kg-1 spiked levels. The highest peel penetration was observed for pirimicarb, captan and cyprodinil, with cumulative permeation of 90, 19 and 17 µg cm-2, respectively. The total absorption was in the range from 0.32% (tebuconazole) to 32% (pirimicarb). Only cypermethrin was not quantitatively detected in the pulp and its use can be recommended in crop protection techniques. The obtained results indicate that molecular weight, octanol-water partition coefficient and water solubility are important parameters determining the process of pesticide absorption.

The European Bioeconomy Strategy aims to strengthen and boost biobased sectors, unlocking investments and markets while rapidly deploying local bioeconomies across Europe and improving compliance with environmental and social sustainability goals. Current biomass provision structures and infrastructure might not be able to tap the sustainable potential of forestry-, agricultural residues and biogenic waste envisaged forming the biogenic feedstock base of the Circular Bioeconomy of tomorrow. Therefore, for the present paper, we assess mobilization strategies, their current status, opportunities, and barriers for local low value and heterogenous biomass resources. Based on discussions with bioenergy supply chain experts, we cluster mobilization measures into three assessment levels; the legislative framework, market structures and technological innovation. Scientific literature research on the respective keywords is performed, the European policy landscape mapped, and the results are enriched with anecdotal evidence, especially for recent and running projects and market developments that lack in published track records. We can identify research needs on all three assessment levels. Still, technological development and legislative frameworks are providing support for heterogeneous biomass mobilization. Market creation, however, represents a bottleneck. We provide novel perspectives, how physical- and virtual bio-hubs and crediting stake- and shareholder variety could create added-value based on sustainable primary economic activities and their cascading activities.

Elevated carbon dioxide (eCO₂) stimulates wheat grain yield, but simultaneously reduces protein (N) concentration. Also other essential nutrients are subject to change. This study is a comprehensive synthesis of wheat experiments with eCO₂, estimating effects on N, minerals (B, Ca, Cd, Fe, K, Mg, Mn, Na, P, S, Zn), and starch. Analysis was made by i) deriving response functions for the relative effect on element concentration in relation to CO₂ concentration, ii) meta-analysis to test the magnitude and significance of observed effects, and iii) relating CO₂ effects on minerals to effects on N and grain yield. Responses range from zero to strong negative effects of eCO₂ on mineral concentration, with largest reductions for the nutritionally important elements N, Fe, S, Zn and Mg. Together with the positive but small and non-significant effect on starch concentration, the large variation in effects suggests that CO₂-induced responses cannot be explained by a simple dilution model. To explain the observed pattern, uptake and transport mechanisms may have to be considered, along with the link of different elements to N uptake. Our study shows that eCO₂ has a significant effect on wheat grain stoichiometry, with implications for human nutrition in a world of rising CO₂.

Ammonium ion is a chemical species that is found in abundance in natural waters, whether underground or surface, but also in wastewater resulting from agricultural and industrial activities. Even if the removal of the ammonium ion from water has been studied for a very long time, it has been found that its removal is far from being solved. In this study, we evaluated the performance of the ammonium ions adsorption process on two adsorbents, zeolite clinoptilolite, ZR, (manufacturer Zeolite Develop-ment SRL, Rupea, Brasov, Romania) and the other granular activated carbon type Norit GAC 830 W. In the first step the paper presents the mineralogical (XRD) and structural (SEM and EDX) characterization of the ZR and determination of the pH zero-point charge, pHZPC, for all the adsorbents. Studies were carried out in equilibrium and kinetic conditions. The efficiency of the adsorbent was investigated in different experimental conditions by varying the initial concentration, particle size, temperature, pH, ionic strength and contact time. The mathematical models and parameters specific to the adsorption isotherms that best describe the experimental results were identified. Langmuir, Freundlich, Temkin and Dubinin-Radushkevich mathematical models were used for comparison. The Langmuir isotherm proved to be the most appropriate to describe the adsorption of ammonium ions on all types of adsorbents used. The adsorption capacity of ammonium ion from synthetic solutions, at 20 °C, pH = 6.09, for the range of initial concentrations 0 - 50 mg/L for Rupea Zeolite is in the range of 10.46 mg/g -12.34 mg/g and for granular activated carbon GAC W830 is 16.64 mg/g. It was found that the increase in temperature and pH have a positive effect on the adsorption capacity of the ammonium ion on the studied adsorbents, and the ionic strength determines the decrease in the adsorption capacity. Kinetic models were also identified that best describe the experimental processes. In this sense, pseudo first order, pseudo second order, intraparticle diffusion and the Elovich model were used. The results of the investigation showed that second-order kinetics governs the adsorption process on ZR zeolites and pseudo-first order for activated carbon.

Barchan dune fields are a dominant landscape feature in SE Qatar and a key element of the peninsula’s geodiversity. The migration of barchan dunes is mainly controlled by dune size, wind pattern, vegetation cover and human impact. We investigate the variability of dune migration in Qatar over a time period of 50 years using high-resolution satellite and aerial imagery and explore its relation to the regional Shamal wind system, teleconnection patterns, and limitations in sand supply associated with the transgression of the Arabian Gulf. We detect strong size-dependent differences in migration rates of individual dunes as well as significant decadal variability on a dune-field scale, which was found to be correlating with the intensity of the North Atlantic Oscillation (NAO) and the Indian Summer Monsoon (ISM). High uncertainties associated with the extrapolation of migration rates back into the Holocene, however, do not permit to further specify the timing of the loss of sand supply and the onset of the mid-Holocene relative sea-level (RSL) highstand. For the youngest phase considered in this study (2006–2015), human impact is anticipated to have accelerated dune migration under a weakening Shamal regime through sand mining and excessive vehicle frequentation upwind of the core study area.

Nonequilibrium work switching simulations and Jarzynski’s equation are a reliable method to compute free energy differences, ΔAlow→high, between two levels of theory, such as a pure molecular mechanical (MM) and a quantum mechanical/molecular mechanical (QM/MM) description of a system of interest. Despite the inherent parallelism, the computational cost of this approach can quickly get very high. This is particularly true for systems where the core region, the part of the system to be described at different levels of theory, is embedded in an environment, such as explicit solvent water. We find that even for relatively simple solute–water systems, switching lengths of at least 5 ps are necessary to compute ΔAlow→high reliably. In this study, we investigate two approaches towards an affordable protocol, with emphasis on keeping the switching length well below 5 ps. Inserting a hybrid charge intermediate state with modified partial charges which resembles the charge distribution of the desired high level makes it possible to obtain reliable calculations with 2 ps switches. Attempts using step-wise linear switching paths, on the other hand, did not lead to improvement, i.e., faster convergence for all systems. To understand these findings, we analyzed the solutes’ properties as a function of partial charges used, the number of waters in direct contact with the solute, and studied the time needed for water molecules to reorient themselves upon a change in the solute’s charge distribution.

The Hertzian contact theory, as well as most of the other classical theories of normal and tangential contact, provides displacements and the distribution of normal and tangential stress components directly in the contact surface. However, other components of the full stress tensor in the material may essentially influence the material behaviour in contact. Of particular interest are principal stresses and the equivalent von Mises stress, as well as the gradient of the hydrostatic pressure. For many engineering and biomechanical problems, it would be important to find these stress characteristics at least in the contact plane. In the present paper, we show that the complete stress state in the contact plane can be easily found for axially symmetric contacts under very general assumptions. We provide simple explicit equations for all stress components and the normal component of the gradient of hydrostatic pressure in the form of one-dimensional integrals.

Transient conjugate heat transfer measurements under varying temperature and velocity inlet boundary conditions at incompressible flow conditions were performed for flat plate and ribbed channel geometries. Therefrom local adiabatic wall temperatures and heat transfer coefficients are determined. Those data are analyzed using typical heat transfer correlations, e.g. Nu=CRe^mPr^n determining the local distribution of C and m. It is shown that they are closely linked. A relationship lnC=A−mB is observed with A and B as modeling parameters. They could be related to parameters in log law or power law representations for turbulent boundary layer flows. The parameter m is shown to have a close link to local pressure gradients and therewith near wall streamlines as well as friction factor distributions. A normalization of the C parameter allows to derive a Reynolds analogy factor and therefrom local wall shear stresses.

Development of the central nervous system (CNS) depends on accurate spatiotemporal control of signalling pathways and transcription programs. Forkhead Box G1 (FOXG1) is one of the master regulators that plays fundamental roles in forebrain development, from the timing of neurogenesis to the patterning of the cerebral cortex. Mutations in the FOXG1 gene cause a rare neurodevelopmental disorder called FOXG1 syndrome, also known as congenital form of Rett syndrome. Patients presenting with FOXG1 syndrome manifest a spectrum of phenotypes ranging from severe cognitive dysfunction and microcephaly to social withdrawal and communication deficits with varying severities. To develop and improve therapeutic interventions, there has been considerable progress towards unravelling the multi-faceted functions of FOXG1 in neurodevelopment and pathogenesis of FOXG1 syndrome. Moreover, recent advances in genome editing and stem cell technologies, as well as increased yield of information from high throughput omics opened promising and important new avenues in FOXG1 research. In this review, we provide a summary of clinical features and emerging molecular mechanisms underlying FOXG1 syndrome, and explore disease-modelling approaches in animals and human-based systems to highlight prospects of research and possible clinical interventions.

In the context of the COVID-19 pandemic, countries around the world varied in the strength and timeliness of their responses. In Romania, specific challenges were faced with regards to managing the spread and limiting the impact of the disease, ranging from healthcare infrastructure to demographic and sociocultural aspects. As the country has a sizeable diaspora, major difficulties were faced when large numbers of individuals from highly affected areas returned to Romania. However, the fast implementation of control measures successfully averted a surge in the number of COVID-19 cases. This delayed the overburdening of an already challenged healthcare system during the initial phases of the epidemic. Furthermore, early control was facilitated by the exploitation of communication channels that penetrated all layers of society, from ordinary citizens to governmental authorities and high-ranking religious figures. The management of the COVID-19 crisis in Romania illustrates the importance of a fast initial response which takes into account the role played by sociocultural aspects in the context of an epidemic. As the challenges faced by Romania are not unique, these results could inform future public health strategies worldwide.

Zika virus (ZIKV), without a vaccine or no effective treatment approved as yet, have globally spread since the past century. The infection caused by ZIKV in humans has changed progressively from mild to subclinical in the last years, causing epidemics with greater infectivity, tropism towards new tissues, and other related symptoms as a product of various emergent ZIKV-host cell interactions. However, it is still unknown why or how the RNA genome structure impacts those interactions in differential evolutionary origin strains. Moreover, genomic comparison of ZIKV strains from the sequence-based phylogenetic analysis is well known, but differences from RNA structure comparisons are less known. Thus, in order to understand the RNA genome variability of lineages of various geographic distributions better, 412 complete genomes in a phylogenomic scanning were used for studying the conservation of structured RNAs. We found specific genomic regions, which highlight their patterns of conserved RNA structures at the level of inter-geographical comparisons. We have proposed these structures as candidates for further experimental validation to establish their potential role in vital functions of the viral cycle of ZIKV and their possible associations with the singularities of different outbreaks that occurred in specific geographic regions.

Objective: To perform a systematic review of real-world outcomes for anti-CGRP-mAbs. Methods: Following the PRISMA guidelines, we searched PubMed for real-world data of Erenumab, Galcanezumab, Fremanezumab, or Eptinezumab in patients with migraine. Results: We identified 104 publications (73 retrospective), comprising 8 pharmaco-epidemiologic and 63 clinic-based studies, 30 case reports and 3 other articles. None of the clinic-based studies provided follow-up data over more than one year in more than 200 patients. Findings suggest reductions in health insurance claims and days with sick-leave as well as better treatment adherence with anti-CGRP-mAbss. Effectiveness, reported in 59 clinic-based studies, was comparable to randomized controlled trials. A treatment pause was associated with an increase in migraine frequency and switching to another antibody resulted in a better response in some of the patients. Adverse events and safety issues were addressed in 70 papers including 22 single case reports. Conclusion: Real-world data on anti-CGRP-mAbs are limited by retrospective data collection, small patient numbers and short follow-up periods. The majority of papers seem to support good effectiveness and tolerability of anti-CGRP-mAbs in the real-world setting. There is an unmet need for large prospective real-world studies providing long-term follow-up of patients treated with anti-CGRP-mAbs.

Short-term (hours) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their geostationary orbits permit the collection of multiple images throughout each day. To assess the capability to detect changes in water properties caused by these processes, however, requires an understaning of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the variability during the day over a water region of low-productivity with the assumption that only small changes in the water properties occur during the day over the area of study. The complete GOCI mission data were processed using the SeaDAS/l2gen package. Filtering criteria were applied to assure the quality of the data. Relative differences with respect to the midday value were calculated for each hourly observation of the day. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was analyzed. We determined that the uncertainties in water-leaving “remote-sensing” reflectance ($R_\text{rs}$) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05$\times10^{-4}$, 5.49$\times10^{-4}$, 4.48$\times10^{-4}$, 2.51$\times10^{-4}$, 8.83$\times10^{-5}$, and 1.36$\times10^{-4}$ sr$^{-1}$, respectively, and 1.09$\times10^{-2}$ mg m$^{-3}$ for the chlorophyll-a concentration (Chl-{\it a}), 2.09$\times10^{-3}$ m$^{-1}$ for the absorption coefficient of chromophoric dissolved organic matter at 412 nm ($a_{\text{g}}(412)$), and 3.7 mg m$^{-3}$ for particulate organic carbon (POC). We consider these to be the floor values for detectable changes in the water properties due to biological, physical or chemical processes.

The UV/Vis absorption energies (νmax) of different solvatochromic probes measured in co-solvent/water mixtures are analysed as a function of the average molar concentration (Nav) of the solvent composition. Nav is discussed in terms of the underlying average molar mass (mol average or mass average) of the mixture. ET(30) of Reichardt`s dye B30 is the focus of the analysis. Methanol, ethanol, 1,2-ethanediol, 2-propanol, 2-methyl-2-propanol, 2-butoxyethanol, formamide, N-methylformamide (NMF), dimethylformamide (DMF), N-formylmorpholine (NFM), 1,4-dioxane and DMSO were used as co-solvents. Significant linear dependencies of ET(30) as a function of Nav can be demonstrated for formamide/water, 1,2-ethanediol/water, NMF/water and DMSO/water mixtures over the whole composition range. These mixtures belong to the group of solvents that do not enhance the water structure according to the Marcus classification. The specifics of the 1,4-dioxane/water mixtures are discussed. For alcohol/water mixtures with enhanced water structure, the influence of the solvent microstructure on ET(30) is particularly evident.

The leather industry is one of the most polluting industries in the world due to the large amounts of waste following the raw hides processing, but also due to the high content of chemicals present in their composition. The main problem of chromium-tanned leather solid waste is related to their storage, because of the ability of chromium to leach in soil or water, and also owing to the high ability of trivalent chromium to oxidize to its toxic form, hexavalent chromium. The purpose of this study is to present the latest methods for extracting trivalent chromium from the composition of solid leather wastes. The extraction methods identified in the present study are based on acid/basic/enzymatic hydrolysis and substitution with the help of organic chelators (organic acids and organic acid salts). In addition, the study includes a comparative analysis between the advantages and disadvantages of each identified extraction method. At the same time, the study also presentes alternative chromium extraction methods based on the combination of conventional extraction methods and ultrasound-assisted extraction.

African swine fever (ASF) is a viral infection of pigs and represents a major threat to animal health and trade. Due to the high tenacity of the causative virus also in carcasses of wild boar, contacts of wild boar with infectious carcasses are regarded an important driver of the so-called habitat cycle. The latter is believed to play a major role in maintaining the present ASF situation in wild boar in Europe. Therefore, search campaigns and timely removal and disposal of carcasses are considered important disease control approaches. If timely disposal is not feasible due to logistic reasons, deterrence of wild boar could be a provisionary option. The performance of seven deterrents (physical and chemical) was tested in a forest near Greifswald, Germany. Carcasses as entities of attraction for wild boar were substituted by luring sites. It could be demonstrated that certain physical (LED-Blinkers, aluminum stripes) and chemical (Wildschwein-Stopp™, Hukinol™) deterrents are capable of reducing significantly the odds of wild boar contacts to one third. It is recommended to carry a choice of the aforementioned, reasonable and easy to apply deterrents, when carcass search campaigns are launched in case of an outbreak of ASF in wild boar.

Ninety percent of the existing building stock in Europe was built before 1990. These buildings are in urgent need for a significant improvement of energy-efficiency through renovation. Regrettably, so far only five percent of renovation projects have been able to yield energy-saving at deep renovation level. State-of-the-art renovation solutions are available, but costly and lengthy renovation processes and incomprehensible technical complexities hinder the achievement of a wide impact at a European scale. This paper presents research on Plug-and-Play (PnP) technologies supported by Building Information Modelling (BIM) to provide affordable, interchangeable and quick-installation solutions to overcome the main barriers of building deep renovation.

Lithium-metal batteries offer high energy density, but are challenged by dendrite growth, which can lead to short circuits and battery failure. Various models with varying degrees of accuracy and computational cost have been developed to understand and predict dendrite growth. In this study, a simple simulation model to predict macroscale dendrite growth on lithium metal electrodes is presented. The model uses a 3D single-particle diffusion-limited aggregation (DLA) algorithm, biased by the electric field, to simulate dendrite growth. The model was validated using 3D MRI of dendrite growth in a lithium symmetric cell. It was used to simulate deposition between consecutive measured dendrite structures. The model also introduces an important parameter, namely the biasing factor c, which determines the balance between diffusion and electric field effects. This parameter was calibrated using the overlap and displacement of deposition sites metrics, achieving optimal results at c = 0.7. The model predictions were in good agreement with experimental data confirmed by fractal dimension analysis. This model provides a useful tool for predicting and studying dendrite formation in lithium and other metal batteries.

The potential of metallic lithium to become the anode material for next-generation batteries is hampered by significant challenges, chief among which is dendrite growth during battery charging. These dendritic structures not only impair battery performance but also pose safety risks. Among the non-destructive analytical techniques in battery research, Magnetic Resonance Imaging (MRI) stands out as a promising tool. However, the direct imaging of lithium by 7Li MRI is hindered by its low sensitivity and spatial resolution, making its use for of dendritic growth imaging very difficult. Instead, a recently introduced indirect imaging approach based on 1H MRI of the electrolyte was used in this study. This method was used for sequential 3D imaging to monitor the charging process of lithium metal symmetric cells in three different electrical circuits: single cell, four cells in parallel, four cells in series. The measured sequential images allowed measurement of dendrite growth in each cell using volumetric analysis. The growth results confirmed the theoretical expectation that growth across cells is uneven in a parallel circuit and even in a series circuit. The methods presented in this study can be applied also to many other dendrite-related issues in batteries.

The Covid-19 crisis has been one of the most relevant economic shocks in the history of the modern economy, mainly due to the restrictions on travel and social interaction taken by the authorities (quarantines, closure of schools, artistic activities, bars, and restaurants, capacity in stores), to reduce the transmission of the virus (Sars-Cov2), having consequences on the national productions of all countries (about 7% for the loss of GDP worldwide). In our study, we analyze, through clustering methods, the effects of the level of contagion, economic projections, and economic mitigation measures taken by governments for managing the pandemic. According to the analyses, it can be concluded that a low infection rate implies a lower loss of product and economic savings when applying economic mitigation measures, taking relevance in the management of sanitary measures to reduce the transmission of the virus (and the temporality of these).

Coronaviruses are a large family of diverse enveloped RNA viruses found in numerous animal species. They are well-known for their ability to cross species barriers and have been transmitted from bats or intermediate hosts to humans on several occasions. Four of the seven human coronaviruses (hCoVs) are responsible for approximately 20% of common colds (hCoV-229E, -NL63, -OC43, -HKU1). Two others (SARS-CoV-1 and MERS-CoV) cause severe and frequently lethal respiratory syndromes but have only spread to very limited extents in human populations. In contrast, SARS-CoV-2, while exhibiting intermediate pathogenicity, has a profound impact on public health due to its enormous spread. In this review, we discuss which initial features of the SARS-CoV-2 Spike protein and subsequent adaptations to the new human host may have helped this pathogen to cause the COVID-19 pandemic. Our focus is on host forces driving changes in the Spike protein and their consequences for virus infectivity, pathogenicity, immune evasion and resistance to preventive or therapeutic agents. In addition, we discuss the significance and perspectives of broad-spectrum therapeutics and vaccines.

This paper presents a new low-voltage versatile mixed-mode filter which uses a multi-ple-input/output differential difference transconductance amplifier (MIMO-DDTA). The multi-ple-input of the DDTA is realized using a multiple-input bulk-driven MOS transistor (MI-BD-MOST) technique to maintain a single differential pair, thereby achieving simple structure with minimal power consumption. In a single topology, the proposed filter can provide five standard filtering functions (low-pass, high-pass, band-pass, band-stop, and all-pass) in four modes: voltage (VM), current (CM), transadmittance (TAM), and transimpedance (TIM). This provides the full capability of a mixed mode filter (i.e., twenty filter functions). Moreover, the VM filter offers high-input and low-output impedances and the CM filter offers high-output impedance; therefore, no buffer circuit is needed. The natural frequency of all filtering functions can be electronically controlled by a setting current. The voltage supply is 0.5 V and for a 4 nA setting current, the power consumption of the filter was 281 nW. The filter is suitable for low-frequency biomedical and sensor applications that require extremely low supply voltages and nano-watt power consumption. For the VM low-pass filter, the dynamic range was 58.23 dB @ 1 % total harmonic distortion. The proposed filter was designed and simulated in the Cadence Virtuoso System Design Platform using the 0.18 µm TSMC CMOS technology.

Ovarian tissue cryopreservation (OTC) or testicular tissue cryopreservation (TTC) are effective and often the only options for fertility preservation in female or male patients due to oncological, medical, or social aspects. While TTC and resumption of spermatogenesis, either in vivo or in vitro, has still be considered an experimental approach in humans, OTC and autotransplantation has been applied increasingly to preserve fertility with more than 200 live births worldwide. However, the cryopreservation of reproductive cells followed by the resumption of gametogenesis, either in vivo or in vitro, may interfere with sensitive and highly regulated cellular processes. In particular, the epigenetic profile, which includes not just reversible modifications of the DNA itself but also post-translational histone modifications, small non-coding RNAs, gene expression and availability, and storage of related proteins or transcripts, have to be considered in this context. Due to complex reprogramming and maintenance mechanisms of the epigenome in germ cells, growing embryos, and offspring, OTC and TTC are carried out at very critical moments early in the life cycle. Given this background, the safety of OTC and TTC taking into account the epigenetic profile has to be clarified. Cryopreservation of mature germ cells (including Metaphase II oocytes and mature spermatozoa collected via ejaculation or more invasively after testicular biopsy) or embryos has been used successfully for many years in Medically Assisted Reproduction (MAR). However, tissue freezing followed by in vitro or in vivo gametogenesis has become more attractive in the past, while few human studies have analysed the epigenetic effects, with most data deriving from animal studies. In this review, we highlight the potential influence of the cryopreservation of immature germ cells and subsequent in vivo or in vitro growth and differentiation on the epigenetic profile in humans and animals.

The Solvency II regulatory framework specifies procedures and parameters for determining solvency capital requirements (SCRs) for insurance companies. The proposed standard SCR calculations involve two steps. The Value–at–Risk (VaR) of each risk driver is measured and, in a second step, all components are aggregated to the company’s overall SCR, using the Standard Formula. This formula has two inputs: the VaRs of the individual risk drivers and their correlations. The appropriate calibration of these input parameters has been the purpose of various Quantitative Impact Studies that have been conducted during recent years. This paper demonstrates that the parameter calibration for the equity–risk module—overall, with about 25%, the most significant risk component—is seriously flawed, giving rise to spurious and highly erratic parameter values. As a consequence, an implementation of the Standard Formula with the currently proposed calibration settings for equity–risk is likely to produce inaccurate, biased and, over time, highly erratic capital requirements.

Immunosorbent turnip vein clearing virus (TVCV) particles displaying the IgG-binding domains D and E of Staphylococcus aureus protein A (PA) on every coat protein (CP) subunit (TVCVPA) were purified from plants via optimized and new protocols. The latter used polyethylene glycol (PEG) raw precipitates, from which virions were selectively re-solubilized in reverse PEG concentration gradients. This procedure improved the integrity of both TVCVPA and the wildtype subgroup 3 tobamovirus. TVCVPA could be loaded with more than 500 IgGs per virion, which mediated the immunocapture of fluorescent dyes, GFP and active enzymes. Bi-enzyme ensembles of cooperating glucose oxidase and horseradish peroxidase were tethered together on the TVCVPA carriers by a single antibody type, with one enzyme conjugated chemically to its Fc region, and the other one bound as target, yielding synthetic multienzyme-complexes. In microtiter plates, the TVCVPA-displayed sugar-sensing system possessed a considerably increased reusability upon repeated testing, compared to the IgG-bound enzyme pair in the absence of the virus. A high coverage of the viral adapters was achieved also on Ta2O5 sensor chip surfaces coated with a polyelectrolyte interlayer, as a prerequisite for durable, TVCVPA-assisted electrochemical biosensing through modularly IgG-assembled sensor enzymes.

Electrochemical-mechanical interactions, in particular pressure-induced ones, have been identified to be a cause for lithium-plating in lithium-ion cells. Mechanically-induced porosity inhomogeneities in the separator layers due to electrode expansion during charging especially lead to cell internal balancing currents and can cause localized plating. To identify cell-format and cell-material dependent mechanical weak spots, a layer-resolved mechanical simulation of different cell types and cell-material combinations is presented in this work. The simulation results show distinctive layer strain patterns for different cell-types that coincide with localized lithium-plating found in post-mortem cells. Additionally, the effects of cell bracing in battery modules is investigated and a method to mitigate the increased layer strain due to bracing counterforces is proposed that also increases cell energy density for hardcase-type automotive cells.

Growing interest has accrued in the co-existence of cardiac amyloidosis and valvular heart disease. Amyloid infiltration from either transthyretin (ATTR) or light chain (AL) origin may affect any structure of the heart, including the valves. Recent literature has mainly focused on aortic stenosis and cardiac amyloidosis, improving our understanding of epidemiology, diagnosis, treatment and prognosis of this dual pathology. Even though of high clinical relevance, data on mitral/tricuspid regurgitation and cardiac amyloidosis is rather scarce and mostly limited to case reports and small cases series. It is the aim of this review article to summarize the current evidence of concomitant valvular heart disease and cardiac amyloidosis including epidemiology, diagnostic approaches, screening possibilities, therapeutic management, and prognostic implications.

Radial basis function (RBF) networks are often viewed as instable when used in multi-layered architectures and therefore are mostly used in a single-layered manner. Universal approximation theorems for single-layered RBF networks further render deeper architectures useless. However, deep neural networks have proven their effectiveness on many different tasks. We show that deeper RBF architectures with multiple radial basis function layers are achievable and able to learn. We introduce an initialization scheme for deep RBF networks based on k-means clustering and covariance estimation. We further show how to make use of convolutions to speed up the calculation of a Mahalanobis distance in a partially-connected fashion, similar to convolutional neural networks (CNNs). Finally, we evaluate our approach on image classification as well as speech emotion recognition tasks. Our results show that deep RBF networks perform similar to simple CNNs.

Metal-catalyzed lipid oxidation is a major factor in food waste, as it reduces shelf life. Addressing this issue, our study investigates the potential of hydrolysates derived from potato protein, a by-product of potato starch production, as metal chelating antioxidants. Through sequential enzymatic hydrolysis using Alcalase or Trypsin combined with Flavourzyme, we produced various hydrolysates, which were then fractionated via ultrafiltration. Using a combination of peptidomics and bioinformatics, we predicted the presence of metal-chelating and free radical scavenging peptides across all hydrolysate fractions, with a trend indicating a higher content of antioxidant peptides in lower molecular weight fractions. To validate these predictions, we utilized Surface Plasmon Resonance (SPR) and a 9-day emulsion storage experiment. While SPR demonstrated potential in identifying antioxidant activity, it faced challenges in differentiating between hydrolysate fractions due to significant standard errors. In the storage experiment, all hydrolysates showed lipid oxidation inhibition, though not as effectively as EDTA. Remarkably, one fraction (AF13) was not significantly different (p < 0.05) from EDTA in suppressing hexanal formation. These results highlight SPR and peptidomics/bioinformatics as promising yet limited methods for antioxidant screening. Importantly, this study reveals the potential of potato protein hydrolysates as antioxidants in food products, warranting further research.

: Over time, we have come to recognize a very complex network of physiological changes enabling wound healing. An immunological process enables the body to distinguish damaged cells and begin a cleaning mechanism by separating damaged proteins and cells with matrix metallopro-teinases, a complement reaction, and free radicals. A wide variety of cell functions help to rebuild new tissue, dependent on energy provision and oxygen supply. Like in an optimized "biorector," disturbance can lead to prolonged healing. One of the earliest investigated local factors is the pH of wounds, studied in close relation to the local perfusion, oxygen tension, and lactate concentration. Granulation tissue with the wrong pH can hinder fibroblast and keratinocyte division and pro-liferation, as well as skin graft takes. Methods for influencing the pH have been tested, such as occlusion and acidification by the topical application of acidic media. In most trials, this has not changed the wound's pH to an acidic one, but it has reduced the strong alkalinity of deeper or chronic wound. Energy provision is essential for all repair processes. New insights into the metabolism of cells have changed the definition of lactate from a waste product to an indispensable energy provider in normoxic and hypoxic conditions. Neovascularization depends on oxygen provision and lactate, signaling hypoxic conditions even under normoxic conditions. An appropriate pH is necessary for successful skin grafting; hypoxia can change the pH of wounds. This review describes the close interconnections between the local lactate levels, metabolism, healing mechanisms, and pH. Furthermore, it analyzes and evaluates the different possible ways to support metabolism, such as lactate enhancement and pH adjustment. The aim of wound treatment must be the optimization of all these components. Therefore, the role of lactate and its influence on wound healing in acute and chronic wounds will be assessed.

The results of the investigation showed that second-order kinetics govern the adsorption process, and the corresponding rate constants were found. To evaluate the parameters related to the adsorption process, the adsorption equilibrium was examined using a variety of mathematical models, such as the Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich isotherm models. The Langmuir isotherm was found to be the best appropriate among all models for describing the adsorption of Cu2+ and Ni2+ ions using bio-nanocomposite beads. The positive values of ΔH° indicate that the adsorption is physical and endothermic, in agreement with experimental results. The negative value of ∆G° shows that the adsorption process is spontaneous. Positive ΔS° values indicate increased randomness at the solid/liquid interface, during adsorption of Cu2+ and Ni2+ cations onto the engineered bio-nanocomposite. The maximum adsorbed amounts of metal ions by the bio-nanocomposite used were 370.37 mg/g for Ni2+ and 454.54 mg/g for Cu2+ from single system. For the binary system, according to the Langmuir isotherm, the maximum adsorbed amounts of Ni2+ and Cu2+ were 357.14 mg/g and 370,37 mg/g, respectively. There is proof that Alginate-Moroccan clay bio-nanocomposites can serve as a different, less expensive source of sorbents for the removal of metal ions from single and binary systems.

Introduction: This review explores the literature and presents institutional cases of concurrent robotic multisite surgery—in particular, robot-assisted radical prostatectomy (RARP) and robot-assisted partial nephrectomy (RAPN) for synchronous prostate and kidney cancers. We highlight dual-console synchronous robotic procedures, emphasizing the unique docking tech-nique developed. Aim: The aims of the study were to evaluate the feasibility, safety, and clinical outcomes of concurrent RARP and RAPN for synchronous prostate cancer and small renal tumors, as well as other concurrent robotic multisite surgeries, and to compare institutional findings with the existing literature. Materials and Methods: We describe the unique docking technique used in our procedures, which facilitates atraumatic transitions between surgeries using the same port sites. Additionally, eligible studies on concurrent robotic multisite surgery that were published in English were retrieved from the MEDLINE, Embase, and Cochrane Library databases. Data on operative time, blood loss, complications, and postoperative outcomes were extracted. Results: Eight cases from our institution demonstrated the feasibility and safety of the proposed approach, which is consistent with previous reports. The unique docking technique and dual-console setup enhance surgical precision, offering significant benefits in patient outcomes. As part of the litera-ture review, nine retrospective studies involving 40 cases of concurrent RARP and RAPN were reviewed. Additionally, eleven retrospective studies involving 392 cases of concomitant RARP and robotic transabdominal preperitoneal inguinal hernia repair (RTAPPIHR) were analyzed. Conclusions: Concurrent RARP and RAPN for synchronous prostate and kidney tumors is a viable and effective approach. Our early experience suggests that this and other combined procedures can optimize patient care and reduce costs. Prospective trials are needed to validate these findings and further refine the techniques.

Using geometric considerations, we provide a clear derivation of the integral representation for the error function, known as the Craig formula. We calculate the corresponding power series expansion and prove the convergence. The same geometric means finally help to systematically derive handy formulas that approximate the inverse error function. Our approach can be used for applications in e.g. high-speed Monte Carlo simulations where this function is used extensively.

Tinnitus is a complex and heterogeneous psycho-physiological disorder responsible for causing a phantom ringing or buzzing sound albeit the absence of an external sound source. It has a direct influence on affecting the quality of life of its sufferers. Despite being around for a while, there hasn’t been a cure for tinnitus, and the usual course of action for its treatment involves use of tinnitus retaining and sound therapy, or Cognitive Behavioral Therapy (CBT). One positive aspect about these therapies is that they can be administered face-to-face as well as delivered via internet or smartphone. Smartphones are especially helpful as they are highly personalized devices, and offer a well-established ecosystem of apps, accessible via respective marketplaces of differing mobile platforms. Note that current therapeutic treatments such as CBT have shown to be effective in suppressing the tinnitus symptoms when administered face-to-face, their effectiveness when being delivered using smartphones is not known so far. A quick search on the prominent market places of popular mobile platforms (Android and iOS) yielded roughly 250 smartphone apps offering tinnitus-related therapies and tinnitus management. As this number is expected to steadily increase due to high interest in smartphone app development, a contemporary review of such apps is crucial. In this paper, we aim to review scientific studies validating the smartphone apps, particularly to test their effectiveness in tinnitus management and treatment. We use the PRISMA guidelines for systematic identification of studies on major scientific literature sources and delineate the outcomes of identified studies.

This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of the inputs/outputs, the finite element model, and the application of evolutionary algorithms. A novel approach is proposed to find the values of inertia, stiffness, and damping parameters by minimizing the difference between the numerical model’s outputs and the testbed’s outputs, considering the joint position and acceleration of the link’s tip. The dynamic model is initially obtained using the finite element method and the Lagrange principle. A prototype of a single one-link flexible manipulator is used in the experimental application wherein the servomotor applies the input torque, and the outputs are the joint angle and the link’s tip acceleration. Then, an optimization problem minimizes the difference between numerical and experimental outputs to determine the set of parameters using evolutionary algorithms. A comparative analysis to obtain the identified parameters is established using genetic algorithms, particle swarm optimization, and differential evolution. The proposed identification approach permitted the determination of the dynamic parameters based on the complete dynamic model of the flexible-link manipulator, which is different from the approaches reported in the literature that identify a simplified model. This information is essential for the design of the motion and vibration control laws.

When oxidizing reduced sulfur compounds, the phototrophic sulfur bacterium Allochromatium vinosum forms spectacular sulfur globules as obligatory intracellular – but extracytoplasmic – intermediates. The globule envelope consists of three extremely hydrophobic proteins: SgpA and SgpB are very similar and can functionally replace each other. SgpC is involved in the expansion of the sulfur globules. The presence of a fourth protein, SgpD, has been suggested by comparative transcriptomics and proteomics of enriched sulfur globules. Here, we investigated the in vivo function of SgpD by coupling its carboxy-terminus to mCherry. This fluorescent protein requires oxygen for chromophore maturation, but we were able to use it in anaerobically growing A. vinosum provided the cells were exposed to oxygen for one hour prior to imaging. While mCherry lacking a signal peptide resulted in low fluorescence evenly distributed throughout the cell, fusion with SgpD carrying its original Sec-dependent signal peptide targeted mCherry to the periplasm and co-localized it exactly with the highly light-refractive sulfur deposits seen in sulfide-fed A. vinosum cells. Insertional inactivation of the sgpD gene showed that the protein is not essential for the formation and degradation of sulfur globules.

In this article, we delve into the intricate behavior of electronic mechanisms underlying NMR magnetic shieldings, σ, in molecules containing heavy atoms such as cadmium, platinum, and mercury. Specifically, we explore PtXn^{−2} (X = F, Cl, Br, I; n = 4, 6) and XCl2 Te2 Y2 H6 (X = Cd, Hg; Y = N, P) molecular systems. It is known that the leading electronic mechanisms responsible for the relativistic effects on σ are well characterized by the linear response with elimination of small components model (LRESC). In this study, we present results obtained from the innovative LRESC-Loc model, which offers the same outcomes as the LRESC model but employs localized molecular orbitals (LMOs) instead of canonical MOs. These LMOs provide a chemist’s representation of atomic core, lone pairs, and bonds. The whole set of electronic mechanisms responsible of the relativistic effects can be expressed in terms of both non-ligand-dependent and ligand-dependent contributions. We elucidate the electronic origins of trends and behaviors exhibited by these di- verse mechanisms in the aforementioned molecular systems. In PtX4^{−2} molecules, the predominant relativistic mechanism is the well-established one-body spin-orbit (σ^SO(1) ) mechanism, while the paramagnetic mass-velocity (σ^Mv ) and Darwin (σ^Dw ) contributing mechanisms also demand con- sideration. However, in PtX6−2 molecules, the σ Mv+ Dw contribution surpasses that of the SO(1) mechanism, thus influencing the overall ligand-dependent contributions. As for complexes con- taining Cd and Hg, the ligand-dependent contributions exhibit similar magnitudes when nitrogen is substituted with phosphorus. The only discrepancy arises from the σ^SO(1) contribution, which changes sign between the two molecules due to the contribution of bond orbitals between the metal and tellurium atoms.

The ability to identify and rank risk is essential for efficient and effective supervision of financial service firms, such as banks and insurers. Risk ranking ensures limited resources are allocated where they are most needed. Today, automatic risk identification within insurance supervision primarily relies on quantitative metrics based on numerical data (e.g. returns). The purpose of this work is to assess whether Natural Language Processing (NLP) and cognitive networks can achieve similar automated risk ranking and identification by analysing textual data, i.e. NIDT=829 investor transcripts from Bloomberg. To this aim, this work explores and tunes 3 NLP techniques: (1) keyword extraction enhanced by cognitive network analysis; (2) valence/sentiment analysis; and (3) topic modelling. Results highlight that keyword analysis, enriched by term frequency-inverse document frequency scores and semantic framing through cognitive networks, could detect events of relevance for the insurance system like cyber-attacks or the COVID-19 pandemic. Cognitive networks were found to highlight events that related to specific financial transitions: The semantic frame of "climate" grew in size by +538% between 2018 and 2020 and outlined an increased awareness that agents and insurers expressed towards climate change. A lexicon-based sentiment analysis achieved a Pearson’s correlation of ρ=0.16 (p&lt;0.001,N=829) between sentiment levels and daily share prices. Although relatively weak, this finding indicates that insurance jargon is insightful to support risk supervision. Topic modelling is considered less amenable to support supervision, because of a lack of results’ stability and an intrinsic difficulty to interpret risk patterns. We discuss how these automatic methods could complement existing supervisory tools in automated risk ranking.

FinTech has been in the focus of the discussion for quite some time. However, the market share of FinTech companies is still relatively small in compared to more traditional financial services. The purpose of this paper is to analyse the status quo, current developments and challenges ahead for the Latvian FinTech sector. We combine three analyses: the political and legal, the economic, the social and the technological environment (PEST) analysis, an analysis of the size and performance of FinTech companies during the last 10 years, and a survey among FinTech companies. We find that the current status of regulation is one of the main obstacles to FinTech development, because it does not sufficiently consider FinTech-specific aspects. Problems in attracting skilled workforce, and an environment that is not very supportive of new developments in finance are further challenges and might explain at least part of the growth and performance difficulties. A revision, modernization and harmonization of regulation is essential to create a level playing field for all market participants: FinTech companies, traditional financial service providers and those originally traditional players that are integrating FinTech solutions in their business model. Further efforts are also required to foster the Latvia’s attractiveness for skilled workforce. We hope that this study helps increase the visibility of Latvian FinTech and contributes to the development of the new Latvian FinTech strategy.

Although CAD/CAM ceramics present a promising alternative to metal-ceramic fixed dental prostheses, little is known about their mid- and long-term clinical performance. This systematic review aims to estimate the survival and success rates and describes the underlying complication characteristics for CAD/CAM tooth-supported fixed dental prostheses (FDPs). We systematically searched MEDLINE and Web of Science to find relevant prospective studies with a follow-up of at least one year. We estimated pooled 1-, 5- and 10-year survival and success rates by combining the collected data in a Poisson regression model. Descriptive statistics were conducted to evaluate the distribution of failures and complications in the included studies. Risk of bias for the included studies was assessed with an adapted checklist for single-arm trials. Pooled estimated 1-, 5-, and 10-year survival rates ranged from 93.80% to 94.66%, 89.67% to 91.1%, and 79.33% to 82.20%, respectively. The corresponding success rates, excluding failures but including any other types of intervention, were 94.53% to 96.77%, 90.89% to 94.62%, and 81.78% to 89.25%. Secondary caries was the most frequent cause of failure, followed by chipping of the veneering. The most common cause of complication, excluding failures but requiring intervention, was chipping of the veneering. Risk of bias was generally acceptable for the included studies, with 7 studies associated with low risk of bias, 8 studies with a moderate risk of bias, and 3 studies with serious risk of bias. The current meta-analysis on CAD/CAM supported FDPs revealed satisfying survival and success rates for up to 10 years of exposure. More prospective studies focusing on long-term performance are needed to strengthen the evidence currently available in the literature.

Bisphenol-A (BPA) represents an important co-monomer for obtaining polycarbonate, epoxy resins, flame retardants, in paint, and other chemicals products. Products containing BPA are widely used, and thus, we can find it in the environment: in the air, in the soil, in natural surface water and in sediments, underground water in landfills, and in wastewater. BPA disturbs human and animals’ health. This influences the enzymatic, androgenic, neurological, liver and reproductive systems at different stages of human life: like in fetal stage, children and adults’ stages. Taking these inconveniences into account, it is very important to remove BPA from water. Ultrasonic technology can be considered a verry sustainable and efficient method to remove BPA from water. The advantages of this method is easy to implement on existing water treatment and purification facilities, it does not produce residual compounds that produce sludge, the time required for degradation is of the order of 1-2 hours and the level of degradation is very high. In this work, we presented the studies on the efficiency of ultrasonics under air atmosphere on the degradation of BPA. The influence of the frequency and of some additional compounds such as carbon tetrachloride, FeSO4 7H2O (FS), and ethyl anthraquinone (EAC) was studied. Three different frequencies were used: 1146 KHz, 864 KHz, 580 KHz, at a power of 50 W. It was identified the efficiency of BPA degradation over a period of 60 minutes, with sampling every 15 minutes. Using the LC-MS/MS technique, the degradation compounds were identified that result from the application of ultrasound processes. Pathways of BPA degradation were also proposed.

The dynamic interplay of signaling networks in most major cellular processes is characterized by the orchestration of reversible protein phosphorylation. Consequently, analytic methods like quantitative phospho-peptidomics has been pushed forward from a highly specialized edge-technique to a powerful and versatile platform for comprehensively analyzing the phosphorylation profile of living organisms. Despite enormous progress in instrumentation and bioinformatics, a major problem remains a high number of missing values caused by the experimental procedure due to either a random phospho-peptide enrichment selectivity or borderline signal intensities, which both cause the exclusion for fragmentation using the commonly applied data dependent acquisition (DDA) mode. Consequently, an incomplete dataset reduces confidence in the subsequent statistical bioinformatic processing. Here, we successfully applied data independent acquisition (DIA) by using the filamentous fungus Magnaporthe oryzae as model organism and could prove that while maintaining data quality (such as phosphosite and peptide sequence confidence), the data completeness increases dramatically. Since the method presented here reduces the LC-MS/MS analysis from 3 h to 1 h and increases the number of phoshosites identified up to 10-fold in contrast to published studies in fungi, we pushed the phospho-proteomic technique beyond its current limits and could provide a sophisticated resource for investigation of signaling processes in filamentous fungi.

We prove a quasi-pseudometric version of the strong Ekeland principle proved by P. Georgiev and T. Suzuki.

Precise and fast position tracking is essential for the correct operation of many industrial robots and CNC machine tools. This subject is also important in the control of the mount of the astronomical telescope, especially for the tracking of artificial satellites. As system parameters can change, a control method that is robust to changes in parameters must be used. Such a method is the sliding control, which, however, ensures the robustness only after reaching the sliding surface. Therefore, a new method was proposed in the paper, which eliminates the phase of reaching the sliding surface. The method consists of using a reference trajectory generator and determining the generalized error in relation to this trajectory. The procedure for designing the control system is presented. Next, the proposed method was verified on the laboratory stand. The described control method provides a robust system operation and can be easily implemented in the control system.

The conceptual reconstruction of Neiwan powerhouse is one of the key activities under the current ongoing mapping project of Taiwanese hydropower plants that mainly took place between 2013 and 2015 and is now focused on micro, pico, and historical power plants. Judging from the fact that the oldest hydropower plant in Taiwan named Guishan starts its operation in 1905, Neiwan powerhouse was among the very first powerhouses that were built across the island to support the electrification of Taiwan. However, the main function of the single turbine equipped Neiwan micro powerhouse was to support mainly the military needs and protect the territories occupied by Japanese troops. Since the powerhouse was built in 1909 and operates only something about 10 year there are very little physical materials or evidence along with contemporaries. Therefore the further reconstruction is based mainly on physical observation of the remains located at the site, old photographs, related articles, treatises and typology of mechanical and civil constructions of other hydropower plant cases in Taiwan hence this paper´s main intention is to pitch a concept reconstruction rather than definite conclusion.

The growing integration of renewable energy sources (RES) into the power system causes congestion to occur more frequently. In order to reduce congestion in the short term and to make the utilization of the power system more efficient in the long term, power flow control (PFC) in the transmission system has been proposed. However, exemplary studies show that congestion will increase also in the distribution system if the transmission system is expanded. For this reason, the potential of PFC to reduce congestion in a model of a real 110 kV distribution system is investigated. Several Unified Power Flow Controller (UPFC) devices are optimized in terms of their number and placement in the power system, their size, control parameters, and costs, by using a Parallel Tempering approach as well as a greedy algorithm. Two optimization variants are considered, one reducing the number of degrees of freedom by integrating system knowledge while the other is not. We find that near a critical grid state and disregarding costs, PFC can reduce congestion significantly (99.13 %). When costs of the UPFCs are taken into account, PFC can reduce congestion by 73.2 %. A basic economic analysis of the costs reveals that the usage of UPFCs is profitable. Furthermore, it is found that the reduction of the solution space of the optimization problem leads to better results faster and that, contrary to expectations, the optimization problem is simple to solve. The developed methods allow not only for the determination of the optimal use of UPFCs to minimize congestion, but also to estimate their profitability.

Enormous quantities of softwood and hardwood tree bark are generated yearly in the pulp and woodworking industry. Chemical compounds which can be found in bark extracts have important biological properties and therefore a high potential for using in the production of special formulations. In the present study, extraction of Picea abies bark with organosolv solvents was investigated to achieve a high yield of desirable compounds. For the extraction four different solvent ratios of ethanol and water were applied. The temperature range of extraction was set between 40 and 100 °C and stirring velocity of 400 rpm. Extractions were performed with a solid/liquid ratio of 1:20. Yields of phenolics, flavonoids and tannins were determined using gallic acid for total phenolic content (TPC), quercetin for total flavonoid content (TFC) and tannic acid for total tannins content (TTC) as calibration compounds. Qualitative analysis of phenolic constituents was performed after their derivatization, by gas chromatography coupled with mass spectrometry identification. The total yield of bark extract of 14.75 wt.% was achieved by using an ethanol/water ratio of 50% (v/v) and a temperature of 100 °C. Gas chromatography results show 9 aromatic carboxylic acids as phenolic acids and quercetin and (+)-catechin as flavonoid compounds. Highest concentrations of TPC = 3.21 mg gallic acid equivalent/g, TCF = 0.62 mg quercetin equivalent/g and TTC = 0.84 tannic acid equivalent/g were determined at the same process conditions by photometric method. This study determined the conditions for organosolv extraction of useful compounds and suggests that some of extractives, e.g., taxifolin and rhamnetin presented in the spruce bark extracts, have antiviral (SARS-CoV-2) effects. Therefore, this warrants further evaluation of the antiviral properties of spruce bark constituents.

The financial sector, too, is developing innovative services and products that have the potential to make a more positive impact on global environmental goals. However, research sheds little light on environmental attitudes and behavioral patterns of employees in this sector. There are multiple factors promoting or inhibiting environmental behavior. Those factors may be rooted in individual or subjective norms, but also social influence and to some extent financial incentives and benefits. A survey concerning the intention to improve and actually show ‘green behavior’ was developed based on widely used acceptance models which differentiate between desirable behavior and the intention to show such behavior. Employees are predominately responsive towards environmental behavior: 20% are convinced of the need to act in a “green” and sustainable manner, only 5% are hard to win over or are not accessible at all. Financial loss or benefits combined with social motives contribute to sustainable living whereas financial benefits alone actually hinder such behavior. The study underlines the existence of a intention-behavior gap: The intention to behave sustainably is built somewhat separately from various influences. There are moderating factors like sex, age and family status that influence the decisions. This then leads to a gap between intention and actual behavior.

Degradation is an inevitable companion in the operation of solid oxide fuel cell (SOFC) systems since it directly deteriorates the reliability of the system’s operation and the system’s durability. Both are seen as barriers that limit the extensive commercial use of SOFC systems. Therefore diagnosis and prognosis are valuable tools that can contribute to raising the reliability of the system operation, efficient health management, increased durability and implementation of predictive maintenance techniques. Remaining useful life (RUL) prediction has been extensively studied in many areas like batteries and proton-exchange membrane fuel cell (PEM) systems, and a range of different approaches has been proposed. On the other hand, results available in the domain of SOFC systems are still relatively limited. Moreover, methods relying on detailed process models and models of degradation turned out to have limited applicability for in-field applications. Therefore, in this paper, we propose an effective, data-driven approach to predicting RUL where the trend of the health index is modelled by an adaptive linear model, which is updated at all times during the system operation. This allows for a closed-form solution of the probability distribution of the RUL, which is the main novelty of this paper. Such a solution requires no computational load and is as such very convenient for the application in ordinary low-cost control systems. The performance of the approach is demonstrated first on the simulated case studies and then on the data obtained from a long-term experiment on a laboratory SOFC system. From the tests conducted so far it turns out that, the quality of the RUL prediction is usually rather low at the beginning of the system operation, but then gradually improves while the system is approaching the end-of-life (EOL), making it a viable tool for prognosis.

Glioblastoma (GBM) still presents as one of the most aggressive tumors in the brain, which despite enormous research efforts remains incurable until today. As many theories evolve around the persistent recurrence of this malignancy the assumption of a small population of cells with a stem-like phenotype remains as a key driver of its infiltrative nature. In this article we research Chordin-like 1 (CHRDL1), a secreted protein, as a potential key regulator of the glioma stem-like cell (GSC) phenotype. It has been shown that CHRDL1 antagonizes the function of Bone Morphogenic Protein 4 (BMP4), which induces GSC differentiation and hence reduces tumorigenicity. We therefore employed two previously described GSCs spheroid cultures and depleted them of CHRDL1 using stable transduction of a CHRDL1-targeting shRNA. We show with in vitro cell based assays (MTT, limiting dilution and sphere formation assays), western blots, irradiation procedures and quantitative real-time PCR that depletion of the secreted BMP4 antagonist CHRDL1 prominently decreases functional and molecular stemness traits resulting in enhanced radiation sensitivity. As a result, we postulate CHRDL1 as an enforcer of stemness in GSCs and find additional evidence that high CHRDL1-expression might also serve as a marker protein to determine BMP4-susceptibility.

Terahertz tomography is a promising method among non-destructive inspection techniques to detect faults and defects in dielectric samples. Image quality recently significantly improved through the incorporation of a priori information and off-axis data. However, this improvement has come at the cost of increased measurement time. To aim toward industrial applications, it is therefore necessary to speed up the measurement by parallelizing the data acquisition employing multi-channel setups. In this work, we present two tomographic frequency-modulated continuous wave (FMCW) systems working at a bandwidth of 230-320 GHz, equipped with an eight-channel detector array, and compare their imaging results with a single-pixel setup. While in the first system, the additional channels are used exclusively to detect radiation refracted by the sample, the second system features an f-θ lens, focusing the beam at different positions on its flat focal plane, and thus utilizing the whole detector array directly. The usage of the f-θ lens in combination with a scanning mirror eliminates the necessity of the formerly used slow translation of a single-pixel transmitter. This opens up the potential for a significant increase in acquisition speed, in our case by a factor of four to five, respectively.

The increase in pandemics caused by RNA viruses of zoonotic origin highlights the urgent need for broad-spectrum antivirals against novel and re-emerging RNA viruses. Broad-spectrum antivirals could be deployed as first-line interventions during an outbreak while virus-specific drugs and vaccines are developed and rolled out. Viruses depend on the host’s protein synthesis machinery for replication. Several natural compounds that target the cellular DEAD-box RNA helicase eIF4A, a key component of the eukaryotic translation initiation complex eIF4F, have emerged as potential broad-spectrum antivirals. Rocaglates, a group of flavaglines of plant origin that clamp mRNAs with highly structured 5’UTRs onto the surface of eIF4A through specific stacking interactions, exhibit the largest selectivity and potential therapeutic indices among all known eIF4A inhibitors. Their unique mechanism of action limits the inhibitory effect of rocaglates to the translation of eIF4A-dependent viral mRNAs and a minor fraction of host mRNAs exhibiting stable RNA secondary structures and/or polypurine sequence stretches in their 5´UTRs, resulting in minimal potential toxic side effects. Maintaining a favorable safety profile while inducing efficient inhibition of a broad-spectrum of RNA viruses makes rocaglates into primary candidates for further development as pan-antiviral therapeutics.

The quasi-two-dimensional organic charge-transfer salt κ-(BEDT-TTF)₂Cu₂(CN)₃ is one of the prime candidates for a quantum spin-liquid due the strong spin frustration of its anisotropic triangular lattice in combination with its proximity to the Mott transition. Despite intensive investigations of the material's low-temperature properties, several important questions remain to be answered. Particularly puzzling are the 6 K anomaly and the enigmatic effects observed in magnetic fields. Here we report on low-temperature measurements of lattice effects which were shown to be particularly strongly pronounced in this material (R. S. Manna et al., Phys. Rev. Lett. 104, 016403 (2010)). A special focus of our study lies on sample-to-sample variations of these effects and their implications on the interpretation of experimental data. By investigating overall nine single crystals from two different batches, we can state that there are considerable differences in the size of the second-order phase transition anomaly around 6 K, varying within a factor of 3. In addition, we find field-induced anomalies giving rise to pronounced features in the sample length for two out of these nine crystals for temperatures T < 9 K. We tentatively assign the latter effects to B-induced magnetic clusters suspected to nucleate around crystal imperfections. These B-induced effects are absent for the crystals where the 6 K anomaly is most strongly pronounced. The large lattice effects observed at 6 K are consistent with proposed pairing instabilities of fermionic excitations breaking the lattice symmetry. The strong sample-to-sample variation in the size of the phase transition anomaly suggests that the conversion of the fermions to bosons at the instability is only partial and to some extent influenced by not yet identified sample-specific parameters.

The wind industry is looking for ways to accurately predict the reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique utilized for determining the critical subsystems of wind turbines. There are several studies which applied FMECA for wind turbines in the literature, but no studies so far have considered different weather conditions or climatic regions. Furthermore, various design types of wind turbines have been analyzed applying FMECA but no study so far has applied FMECA to compare the reliability of geared and direct-drive wind turbines. We propose to fill these gaps by using Koppen-Geiger climatic regions and two different turbine models of direct-drive and geared-drive concepts. A case study is applied on German wind farms utilizing the WMEP database which contains wind turbine failure data from 1989 to 2008. This proposed methodology increases the accuracy of reliability and availability predictions and compares different wind turbine design types and eliminates underestimation of impacts of different weather conditions.

Full Matrix Capture is a multi-channel data acquisition method which enables flexible, high resolution imaging using ultrasound arrays. However, the measurement time and data volume are increased considerably. Both of these costs can be circumvented via compressed sensing, which exploits prior knowledge of the underlying model and its sparsity to reduce the amount of data needed to produce a high resolution image. In order to design compression matrices that are physically realizable without sophisticated hardware constraints, structured subsampling patterns are designed and evaluated in this work. The design is based on the analysis of the Cramér-Rao Bound of a single scatterer in a homogeneous, isotropic medium. A numerical comparison of the point spread functions obtained with different compression matrices and the Fast Iterative Shrinkage/Thresholding Algorithm shows that the best performance is achieved when each transmit event can use a different subset of receiving elements and each receiving element uses a different section of the echo signal spectrum. Such a design has the advantage of outperforming other structured patterns to the extent that suboptimal selection matrices provide a good performance and can be efficiently computed with greedy approaches.

Background and Objectives: The COVID-19 pandemic influenced the management of patients with immune mediated rheumatic and musculoskeletal diseases (imRMDs) in various ways. The goal of our systematic review was to determine the influence of the first period of the COVID-19 pandemic on the management of imRMDs. Materials and Methods: Systematic literature search of PubMed, Cochrane and Embase databases, including studies with adult patients on the influence of the COVID-19 pandemic on management of imRMDs. There were no restrictions regarding to study-design except for systematic reviews and case reports that were excluded as well as articles on the disease outcomes in case of SARS-CoV-2 infection. Two reviewers screened the studies for inclusion, and, in case of disagreement, consensus was reached after discussion. Results: A total of 5969 potentially relevant studies were found, and, after title, abstract and full-text screening, 35 studies were included with data from 182’746 patients and 2018 rheumatologists. Non-availability of drugs, e.g., hydroxychloroquine and tocilizuab, was frequent (16–69% of patients). Further, medication non-adherence was reported among patients with different RMDs and between different drugs in 4–46% of patients. Changes to preexisting medication were reported in up to 33% of patients (e.g. reducing dose of steroids or cessation of biological disease-modifying antirheumatic drugs). Physical in-office consultations and laboratory testing decreased and as a consequence newly implemented remote consultations increased greatly with an increase of up to 80%. Conclusion: The COVID-19 pandemic influenced the management of imRMDs, especially at the beginning. Influences were wide-ranging, affecting availability of pharmacies, adherence to medication or medication changes, doctor visits and laboratory testing. New systems of care were set up, including virtual clinics and video consultations. These new forms of health care delivery should be spread and implemented worldwide to routine clinical practice to be ready for future pandemics.

The sustainability of agriculture depends as much on the natural resources required for production as it does on the stakeholders that manage those resources. It is thus essential to understand the variables that influence the decision-making process of agricultural stakeholders to design educational programs, interventions, and policies geared towards their specific needs, a required step to enhance agricultural sustainability. We examined the perceptions, experiences, and priorities that influence management decisions of five major groups of agricultural stakeholders (conventional small grain producers, organic small grain producers, organic vegetable producers, extension agents and agro-industry crop consultants, and researchers) across the Montana, United States. Results revealed that while stakeholder groups have distinct perceptions, experiences, and priorities, there were similarities across groups. Specifically, organic vegetable and organic small grain producers showed similar responses that were, in turn, divergent of conventional producers, researchers, and crop consultants. Conventional small grain producers and researchers showed overlapping response patterns while crop consultants formed an isolated group. Our results reinforce the need for agricultural education and programs that address unique and shared experiences, priorities, and concerns of multiple stakeholder groups. This study endorses the call for a paradigm shift from the traditional top-down agricultural extension model to one that accounts for participants’ socio-ecological contexts to facilitate the adoption of sustainable agricultural systems that support environmental and human wellbeing.

Heart myocardia are critical to the facilitation of heart pumping and blood circulating around the body. The biaxial mechanical testing of the Left Ventricle (RV) is utilised to build the computa-tional model of the whole heart with little importance given to the unique mechanical properties of Right Ventricle (RV) and Mid-wall (MDW). Most of those studies focussed on the LV of the heart, and then apply the obtained characteristics with a few modifications to the right side of the heart. However, that view has been contested over time with the realisation that the right side of the heart possesses its own unique mechanical properties that are widely distinct from that of the left side of the heart. This paper is aimed at reporting and evaluating the passive mechanical property dif-ferences in the three main walls of the rat heart based on biaxial tensile test data. Fifteen mature Wistar rats weighing 225 ± 25 g were euthanised by inhalation of 5 % halothane. The hearts were excised after which all the top chambers comprising the two atria, pulmonary and vena cava trunks, aorta and valves are all dissected out. Then 5 x 5 mm sections from the middle of each wall were carefully dissected with a surgical knife to avoid over-prestraining the specimens. The specimens were subjected tensile test. The elastic moduli, peak stresses in the toe region and stresses at 40 % strain, anisotropy indices as well as the stored strain energy in the toe and linear region up to 40 % strain are used for statistical significance tests. The following are the main findings of this study: (1) LV and MDW tissues have relatively shorter toe regions of 10 - 15 % strain as compared to RV tissue whose toe region extends up to twice as much as that (2) LV tissues have higher strain energy storage in the linear region despite being lower in stiffness than the RV (3) the MDW has the highest strain energy storage along both directions which might be directly related to its high level of anisotropy. These findings, though for a specific animal species at similar age and around the same body mass, emphasize the importance of application of wall specific material parameters to obtain accurate ventricular hyperelastic models. The findings further enhance our understanding of the desired mechanical behaviour of the different ventricle walls.

Considering increasingly ambitious pledges by countries, pressure from society, investors, and clients further up the supply chain, the question for companies is not so much whether to take decarbonisation action, but what action and by when. However, determining an ideal mix of measures to apply ‘decarbonisation efficiency’ requires more than knowledge of technically feasible measures and how to combine them to achieve the most economic outcome: In this paper, the author describes seven aspects which heavily influence the composition of an ‘ideal mix’ that executive leadership needs to take a (strategic) position on. These aspects consider underlying motivations and span across (socio-)economic, technical, regulatory, strategic, corporate culture and environmental factors and further underline the necessity of clarity of definitions. How these decisions influence the determination of the decarbonisation-efficient ideal mix of measures, both in principle but also in terms of specific impact is further explored by providing examples. What choices are taken by German manufacturers in several of the aspects is disclosed by insights from about 850 responses to the ‘Energy Efficiency Index of German Industry’. Knowledge of the status quo, and clarity in definitions, objectives, time frames and scope are key.

Several studies have shown that tapering or stopping disease-modifying anti-rheumatic drugs (DMARDs) in rheumatoid arthritis (RA) patients in sustained remission is feasible. However, tapering/stopping bears the risk of decline in physical function as some patients may relapse and face increased disease activity. Here we analysed the impact of tapering or stopping DMARD treatment on the physical function of RA patients. The study was a posthoc analysis of physical functional worsening for 282 patients with RA in sustained remission tapering and stopping DMARD treatment in the prospective randomized RETRO study. HAQ and DAS-28 scores were determined in baseline samples of patients continuing DMARD (arm 1), tapering their dose by 50% (arm 2), or stopping after tapering (arm 3). Patients were followed over 1 year, and HAQ and DAS-28 scores were evaluated every 3 months. The effect of treatment reduction strategy on functional worsening was assessed in a recurrent-event Cox regression model with a study-group (control, taper, taper/stop) as the predictor. 282 patients were analysed. In 58 patients, functional worsening was observed. The incidences suggest a higher probability of functional worsening in patients tapering and/or stopping DMARDs, which is likely due to higher relapse rates in these individuals. At the end of the study, however, functional worsening was similar among the groups. Point estimates and survival curves show that functional decline after tapering or stopping DMARDs in RA patients with stable remission is small and related to relapses but to on overall functional decline.

There is an increased interest in the district-scale energy transition within interdisciplinary research community. Agent-based modelling presents a suitable approach to address variety of questions related to policies, technologies, processes, and the different stakeholder roles that can foster such transition. This state-of-the-art review focuses on the application of agent-based modelling for exploring policy interventions that facilitate the decarbonisation (i.e., energy transition) of districts and neighbourhoods while considering stakeholders’ social characteristics and interactions. We systematically select and analyse peer-reviewed literature and discuss the key modelling aspects, such as model purpose, agents and decision-making logic, spatial and temporal aspects, and empirical grounding. The analysis reveals that the most established agent-based models’ focus on innovation diffusion (e.g., adoption of solar panels) and dissemination of energy-saving behaviour among a group of buildings in urban areas. We see a considerable gap in exploring the decisions and interactions of agents other than residential households, such as commercial and even industrial energy consumers (and prosumers). Moreover, measures such as building retrofits and conversion to district energy systems involve many stakeholders and complex interactions between them that up to now have hardly been represented in the agent-based modelling environment.

Different external stimuli are perceived by multiple sensor histidine kinases and transmitted by phosphorylation via the phosphotransfer protein Ypd1p in the multistep phosphorelay system of the high osmolarity glycerol signaling pathway of filamentous fungi. How the signal propagation takes place is still not known in detail, since multiple sensor histidine kinase genes in most filamentous fungi are coded in the genome, whereas only one gene for Ypd1 exists. That raises the hypothesis that various Ypd1 isoforms are produced from a single gene sequence, perhaps by alternative splicing, facilitating a higher variability in signal transduction. We found that the mRNA of MoYPD1 in the rice blast fungus Magnaporthe oryzae is subjected to an increased structural variation and amplified putative isoforms on a cDNA level. We then generated mutant strains overexpressing these isoforms, purified the products and present here one previously unknown MoYpd1 isoform on a proteome level. Alternative splicing was found to be a valid molecular mechanism to increase the signal diversity in eukaryotic multistep phosphorelay systems.

A thorough understanding of nuclear reaction rates at low energies is essential for improving our understanding of energy generation in stars and primordial and stellar nucleosynthesis. At low energies, fusion reactions between charged particles are strongly suppressed by the presence of the Coulomb barrier which classically inhibits the penetration of one nucleus into another. The barrier penetration causes the cross section to have a steep energy dependence at low energies, making cross section measurements very challenging. Furthermore, little is known about the impact of surrounding electrons in stellar plasmas that are currently beyond the reach of experiments. As a result, measuring the bare cross sections as accurately as possible is essential. Reaction rate measurements at very low energies have been made possible in recent years by the development of high-current low-energy accelerators as well as enhanced target and detection methods. Nevertheless, the presence of atomic electrons, which alter the Coulomb barrier by screening the nuclear charge and increase the cross section at low energies compared to the case of bare nuclei, complicates these observations. A review of the experimental and corresponding theoretical work on laboratory electron screening performed so far will be presented.

We prove a version of Ekeland Variational Principle (EkVP) in a weighted graph $G$ and its equivalence to Caristi fixed point theorem and to Takahashi minimization principle. The usual completeness and topological notions are replaced with some weaker versions expressed in terms of the graph $G$. The main tool used in the proof is the OSC property for sequences in a graph. Converse results, meaning the completeness of graphs for which one of these principles holds is also considered.

Coronavirus Disease 2019 (COVID-19) is an infectious respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease, first identified in the Chinese city of Wuhan in November 2019 and has since spread worldwide, is the latest human pandemic, and has officially infected over 800 million people and has caused nearly seven million deaths to date. Although SARS-CoV-2 belongs to the large family of coronaviruses, it has some unique biological characteristics in its interplay with the human host. Therefore, this narrative review aims to provide an up-to-date overview of the structure of the virus, incubation and shedding in the human host, infectivity and biological evolution over time, as well as the main mechanisms for invading human host cells and replicating within. We also proffer that ongoing epidemiological surveillance of newly emerged variants must always be accompanied by biological studies aimed at deciphering new advantageous traits that may contribute to increasing virulence and pathogenicity, such that the most appropriate strategies for establishing a (relatively) safe coexistence with the human host can be implemented.

Globally, over the past several months millions of persons contracted the coronavirus disease 2019 (COVID-19) resulting in significant mortality. Health care systems are negatively impacted including the care of individuals with cancers and other chronic diseases such as chronic active hepatitis, cirrhosis and hepatocellular carcinoma. There are various probable pathogenic mechanisms that have been presented to account for liver injury in COVID-19 patients such as hepatotoxicity cause by therapeutic drugs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of the bile duct cells and hepatocytes, hypoxia and systemic inflammatory response. Liver biochemistry tests such as AST, ALT, GGT and ALP are deranged in COVID-19 patients with liver injury. Hepatocellular damage results in the elevation of serum AST and ALT levels in early onset disease while a cholestatic pattern that develops as the disease progress causes higher levels of ALP, GGT, direct and total bilirubin. These liver biochemistry tests are prognostic markers of disease severity and should be carefully monitored in COVID-19 patients. We conducted a systematic review of abnormal liver biochemistry tests in COVID-19 and the possible pathogenesis involved. Significant findings regarding the severity, hepatocellular pattern, incidence and related clinical outcomes in COVID-19 patients are highlighted.