Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of growth and electrosynthesis of PolyHydroxyAlcanoates by the thermophilic bacterium Kyrpidia spormannii

The electrosynthesis of valuable compounds by biofilms on electrodes is being intensively studied since few years. However, so far, the actual biofilms growing on cathodes produce mainly small and relatively inexpensive compounds such as acetate or ethanol. Recently, a novel Knallgas bacterium, Kyrpidia spormannii EA-1 has been described to grow on cathodes under thermophilic and microaerophilic conditions, producing significant amounts of PolyHydroxyAlkanoates (PHAs). These PHA are promising sustainable bioplastic polymers with the potential to replace petroleum-derived plastics in a variety of applications. However, the effect of culture conditions and electrode properties on the growth of K. spormannii EA-1 biofilms and PHA production is still unclear. In this study, we report on the optimization of growth and PHA production in liquid culture and on the cathode of a Microbial Electrosynthesis System. Optimization of the preculture allows to obtain high cell density of up to 8.5 Log10 cells·ml-1 in 48h, decreasing the time necessary by a factor of 2.5. With respect to cathodic biofilm formation, this study was focused on the optimization of three main operating parameters, which are the applied cathode potential, buffer pH, and the oxygen concentration in the feed gas. Maximum biofilm formation and PHA production was observed at an applied potential of −844mV vs. SCE, pH 6.5, O2 saturation of 2.5%. The PHA concentration in the biofilm reached a maximum of ≈26.8 μg·cm-2 after optimization, but at 2.9% the coulombic efficiency remains relatively low. We expect that further nutrient limitation will allow the accumulation of more PHA, based on a dense biofilm growth. In conclusion, these findings take microbial electrosynthesis of PHA a step forward towards practical implementation.
Utility of endoscopic retrograde cholangiopancreatography in infant patients with conservational endoscopy

Background The indications for endoscopic retrograde cholangiopancreatography (ERCP) in infant patients (age <1 year) differ from those in adults. A paucity of data and concerns about the potential lower effectiveness and more adverse effects limit its utility, even in tertiary care centres. In this study, we retrospectively analysed the indications, success rates, and adverse effects of ERCP in these groups. Methods From June 2014 to March 2018, 17 ERCPs were performed in 15 children [median age: 10.4 months (6–12 months); median weight: 6.6 kg (3.3–10.7 kg)]. A conventional duodenoscope was utilized in all procedures. All patients were followed up as inpatients. Results Fifteen therapeutic and two diagnostic procedures were managed by licensed paediatric endoscopist. Successful cannulation was obtained in all patients (100%). A high proportion (47.1%) of pancreaticobiliary maljunction (PBM) and therapeutic procedures (88.2%) were identified. Two cases of mild pancreatitis were recorded, accounting for 12.5% of the post-ERCP pancreatitis (PEP) rate. By multivariable analysis, recurrent acute pancreatitis and pancreatic duct (PD) cannulation/injection were identified as PEP-related risk factors. All complications were managed conservatively. Conclusions ERCP in infant patients (0.5< age <1 year) could be safely completed by conservational endoscopy. A high proportion of PBM and therapeutic procedures were identified in our study cohort. The overall adverse-event rate was acceptable, and no serious complication occurred. The PEP-related independent risk factors included recurrent acute pancreatitis and PD cannulation/injection.
How the Updated Earth System Models Project Terrestrial Gross Primary Productivity in China under 1.5 and 2 °C Global Warming

Three Earth system models (ESMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) were chosen to project ecosystem changes under 1.5 and 2 °C global warming targets in the Shared Socioeconomic Pathway 4.5 W m−2 (SSP245) scenario. Annual terrestrial gross primary productivity (GPP) was taken as the representative ecological indicator of the ecosystem. Under 1.5 °C global warming, GPP in four climate zones—i.e., temperate continental; temperate monsoonal; subtropical–tropical monsoonal; high-cold Tibetan Plateau—showed a marked increase, the smallest magnitude of which was around 12.3%. The increase was greater under 2 °C of global warming, which suggests that from the perspective of ecosystem productivity, global warming poses no ecological risk in China. Specifically, in comparison with historical GPP (1986–2005), under 1.5 °C global warming GPP was projected to increase by 16.1–23.8% in the temperate continental zone, 12.3–16.1% in the temperate monsoonal zone, 12.5–14.7% in the subtropical–tropical monsoonal zone, and 20.0–37.0% on the Tibetan Plateau. Under 2 °C global warming, the projected GPP increase was 23.0–34.3% in the temperate continental zone, 21.2–24.4% in the temperate monsoonal zone, 16.1–28.4% in the subtropical–tropical monsoonal zone, and 28.4–63.0% on the Tibetan Plateau. The GPP increase contributed by climate change was further quantified and attributed. The ESM prediction from the Max Planck Institute suggested that the climate contribution could range from −12.8% in the temperate continental zone up to 61.1% on the Tibetan Plateau; however, the ESMs differed markedly regarding their climate contribution to GPP change. Although precipitation has a higher sensitivity coefficient, temperature generally plays a more important role in GPP change, primarily because of the larger relative change in temperature in comparison with that of precipitation.
Systematic identification of molecular mediators underlying sensing of Staphylococcus aureus by Pseudomonas aeruginosa

Bacteria typically exist in dynamic, multispecies communities where polymicrobial interactions influence fitness. Elucidating the molecular mechanisms underlying these interactions is critical for understanding and modulating bacterial behavior in natural environments. While bacterial responses to foreign species are frequently characterized at the molecular and phenotypic level, the exogenous molecules that elicit these responses are understudied. Here we outline a systematic strategy based on transcriptomics combined with genetic and biochemical screens of promoter-reporters to identify the molecules from one species that are sensed by another. We utilized this method to study interactions between the pathogens Pseudomonas aeruginosa and Staphylococcus aureus that are frequently found in co-infections. We discovered that P. aeruginosa senses diverse staphylococcal exoproducts including the metallophore staphylopine, intermediate metabolites citrate and acetoin, and multiple molecules that modulate its iron starvation response. Further, we show that staphylopine inhibits biofilm formation and that P. aeruginosa can utilize citrate and acetoin for growth, revealing that these interactions have both antagonistic and beneficial effects. Our screening approach thus identified multiple S. aureus secreted molecules that are sensed by P. aeruginosa and affect its physiology, demonstrating the efficacy of this approach, and yielding new insight into the molecular basis of interactions between these two species.
Singing and music making: physiological responses across early to later stages of dementia.

Background: Music based interventions have been found to improve the wellbeing of people living with dementia. More recently there has been interest in physiological measures to provide additional information about how music and singing impact this population. Methods: This multiple-case study design explored physiological responses (heart rate-HR, electrodermal activity-EDA, movement, and skin temperature-ST) of nine people with mild-to-moderate dementia during a singing group, and six people in the later stages of dementia during an interactive music group. The interactive music group was also video recorded to provide information about engagement. Data were analysed using simulation modelling analysis. Results: The singing group showed an increase in EDA (p < 0.01 for 8/9 participants) and HR (p < 0.01 for 5/9 participants) as the session began. HR (p < 0.0001 for 5/9 participants) and ST (p < 0.0001 for 6/9 participants) increased during faster paced songs. EDA (p < 0.01 all), movement (p < 0.01 for 8/9 participants) and engagement were higher during an interactive music group compared to a control session (music listening). EDA (p < 0.0001 for 14/18 participants) and ST (p < 0.001 for 10/18 participants) increased and in contrast to the responses during singing, HR decreased as the sessions began (p < 0.002 for 9/18 participants). EDA was higher during slower music (p < 0.0001 for 13/18 participants), however this was less consistent in more interactive sessions than the control. There were no consistent changes in HR and movement responses during different styles of music. Conclusions: Physiological measures may provide valuable information about the experiences of people with dementia participating in arts and other activities, particularly for those with verbal communication difficulties. Future research should consider using physiological measures with video-analysis and observational measures to explore further how engagement in specific activities, wellbeing and physiology interact.
A review of tidal energy - resource, feedbacks, and environmental interactions

The ocean contains a variety of renewable energy resources, little of which has been exploited. Here, we review both tidal range and tidal stream energy, with a focus on the resource, feedbacks, and environmental interactions. The review covers a wide range of timescales of relevance to tidal energy, from fortnightly (spring-neap) and semi-diurnal variability, down to array, and device-scale turbulence. When simulating the regional tidal energy resource, and to assess environmental impacts, it is necessary to account for feedbacks between the tidal array and the resource itself. We critically review various methods for simulating energy extraction, from insights gained through theoretical studies of “tidal fences” in idealized channels, to realistic three-dimensional model studies with complex geometry and arrays of turbines represented by momentum sinks and additional turbulence due to the presence of rotors and support structures. We discuss how variability can be reduced by developing multiple (aggregated) sites with a consideration of the enhanced phase diversity offered by exploiting less energetic tidal currents. This leads to future research questions that have not yet been explored in depth at ﬁrst-generation tidal sites in relatively shel-tered channels (e.g., the interaction of waves with currents). Such enhanced understanding of real sea conditions, including the effects of wind and waves, leads to our other identiﬁed primary future research direction—reduced uncertainties in turbulence predictions, including the development of realistic models that simulate the interaction between ambient turbulence and the turbulence resulting from multiple wakes, and changes to system-wide hydrodynamics, water quality, and sedimentation.
Alkalophiles

Alkalophiles are a class of extremophiles capable of survival in alkaline (pH roughly 8.5–11) environments, growing optimally around a pH of 10. At such high pH, the normal cellular functions are detrimentally affected for mesophilic organisms. The alkalophiles successfully manage stability of DNA, plasma membrane, and function of cytosolic enzymes, as well as other unfavorable physiological changes at such an elevated pH. A recent development in NextGen sequencing technology facilitates identifying uncultivable organisms amongst the extreme environments. In recent years, distribution of alkalophiles was reported from Soda Lake, marine environments, saline deserts, and natural thermal vents to natural water bodies. Although alkalophiles were first reported in 1889, their enzymatic and industrial applications still make them an interesting area of research. This chapter provides basic information on environmental distribution, taxonomy, physiology, bioenergetics, and survival mechanism and enzymes produced by alkalophilic organisms.
Circulating Levels of Bone Markers after Short-Term Intense Training with Increased Dairy Consumption in Adolescent Female Athletes

Thirteen female adolescent soccer players (14.3 ± 1.3 years) participated in a cross-over, double-blind trial examining the effects of Greek yogurt (GY) consumption on bone biomarkers during 5 days of intense soccer training. The study took place over two intervention weeks, which consisted of a pre-training assessment day, 5 training days, and a post-training assessment day. Participants completed the GY condition and a carbohydrate isocaloric placebo control pudding condition (CHO) in random order, 4 weeks apart. Morning, fasted, resting blood samples were collected pre- and post-training in each condition. Total osteocalcin (tOC), undercarboxylated osteocalcin (unOC), C-terminal telopeptide of type 1 collagen (CTX), osteoprotegerin (OPG), and receptor activator nuclear factor kappa-β ligand (RANKL) were measured in serum. The results showed no effects for time (pre- to post-training) or condition, and no interaction for tOC, CTX, OPG, RANKL, and the OPG/RANKL ratio. A time-by-condition interaction (p = 0.011) was observed in unOC, reflecting a post-training decrease in the GY, but not the CHO condition (−26% vs. −3%, respectively). However, relative unOC (% of tOC) decreased post-training (−16%), with no differences between conditions. These findings suggest that short-term high-impact intense training had no direct catabolic impact on bone metabolism, with GY adding no benefit beyond that of the isocaloric CHO control pudding.
Genetic variation and reproductive patterns in wetland mosses suggest efficient initial colonization of disturbed sites

Abstract To understand colonization processes, it is critical to fully assess the role of dispersal in shaping biogeographical patterns at the gene, individual, population, and community levels. We test two alternative hypotheses (H I and H II) for the colonization of disturbed sites by clonal plants, by analyzing intraspecific genetic variation in one and reproductive traits in two typical fen mosses with separate sexes and intermittent spore dispersal, comparing disturbed, early‐succession (limed) fens and late‐successional rich fens. H I suggests initial colonization of disturbed sites by diverse genotypes of which fewer remain in late‐successional fens and an initially balanced sex ratio that develops into a possibly skewed population sex ratio. H II suggests initial colonization by few genotypes and gradual accumulation of additional genotypes and an initially skewed sex ratio that alters into the species‐specific sex ratio, during succession. Under both scenarios, we expect enhanced sexual reproduction in late‐successional fens due to resource gains and decreased intermate distances when clones expand. We show that the intraspecific genetic diversity, assessed by two molecular markers, in Scorpidium cossonii was higher and the genetic variation among sites was smaller in disturbed than late‐successional rich fens. Sex ratio was balanced in S. cossonii and Campylium stellatum in disturbed fens and skewed in C. stellatum in late‐successional fens, thus supporting H I. In line with our prediction, sex expression incidence was higher in, and sporophytes were confined to, late‐succession compared to disturbed rich fens. Late‐successional S. cossonii sites had more within‐site patches with two or more genotypes, and both species displayed higher sex expression levels in late‐successional than in disturbed sites. We conclude that diverse genotypes and both sexes disperse efficiently to, and successfully colonize new sites, while patterns of genetic variation and sexual reproduction in late‐successional rich fens are gradually shaped by local conditions and interactions over extended time periods.
An evolutionary ensemble analogy‐based software effort estimation

Analogy‐based estimation (ABE) is the most commonly applied method for estimating using software. Although there are several analogy‐based estimation techniques, there is no consistent conclusion of which technique is the best in all circumstances. Therefore, this article presents an evolutionary ensemble ABE (EEABE) for software cost estimation. Ensemble effort estimation (EEE) models forecast software development endeavors through using multiple estimation methods. In this article, EEABE combines GA as an evolutionary algorithm with six ABE models. The proposed method has been evaluated on four well‐known datasets comprising Maxwell, Albrecht, Kemerer, and Desharnais, by the k‐fold cross‐validation technique and based on the performance criteria of MRE, MMRE, MDMRE, BMMRE, and PRED(0.25). The simulation results demonstrate that the use of EEABE increases the accuracy of estimation and reduces the cost. Besides, EEABE is a flexible and adaptable model with any type of dataset and software development project, and it has been optimized with the possibility of using various ABE techniques.
Higher order modal dynamics of the flexural ultrasonic transducer

The flexural ultrasonic transducer (FUT) consists of a piezoelectric ceramic bonded to an edge-clamped elastic plate, for both generation and detection of ultrasound waves. It is typically employed for proximity measurement, such as in automotive parking systems, and for flow measurement in gases and liquids. Conventional industrial applications have generally incorporated FUTs with resonance frequencies up to around 50 kHz. However, there have been recent advances in the understanding of the FUT, both in terms of fabrication and operation, enabling the potential for measurement in a wider range of applications, including those of elevated pressure, temperature, and requiring multiple operating frequencies. Ultrasound measurement with FUTs at frequencies greater than 50 kHz is desirable in a range of applications, including gas and water metering in petrochemical plants, district heating, and power industries. The major restricting limitation of designing transducers to operate at these higher frequencies has been a relatively poor understanding of these transducers work, including optimisation of design and performance, and the few reports into how different modes of a FUT can be utilised for practical and reliable measurement. In this study, the higher order modal dynamics of the FUT are investigated through measurement of high frequency ultrasound waves in air, for different fundamental operating modes. A combination of experimental techniques is applied, comprising electrical impedance analysis and laser Doppler vibrometry. The experimental research is supported by analytical solutions to reveal complex higher order modal dynamics of the FUT. This investigation represents further development in widening the industrial application potential of the FUT.
Cold Exposure

Cold exposure in general can affect many body systems. Physiological factors such as strength, power, endurance and aerobic capacity are reduced by a drop in muscle temperature or body core temperature. The combination of cold air and the deep breathing of exercise can trigger an asthma attack (bronchospasm). When the body and clothing are wet (whether from sweat, rain, or snow or immersion), the cooling is even more pronounced due to evaporation of the water held close to the skin by wet clothing. There are two primary issues that we get concerned with when we think of cold exposure.hypothermia and frostbite.
Identification of the Park Grass Experiment soil metaproteome

The Park Grass Experiment, is an international reference soil with an impressive repository of temperate grassland (meta)data, however, it still lacks documentation of its soil metaproteome. The identification of these proteins is crucial to our understanding of soil ecology and their role in major biogeochemical processes. However, protein extraction can be fraught with technical difficulties including co-extraction of humic material and lack of a compatible databases to identify proteins. To address these issues, we used two compatible soil protein extraction techniques on Park Grass soil, one that removed humic material, namely a modified freeze-dry, heat/thaw/phenol/chloroform (HTPC) method and another which co-extracted humic material, namely an established surfactant method. Proteins were identified by matching mass spectra against a tailored Park Grass metagenome database. We identified a broad range of proteins from Park Grass soil, mainly in “protein metabolism”, “membrane transport”, “carbohydrate metabolism”, “respiration” and “ribosome associated” categories, enabling reconstitution of specific processes active in grassland soil. The soil microbiome was dominated by Proteobacteria, Actinobacteria, Acidobacteria and Firmicutes at phyla level and Bradyrhizobium, Rhizobium, Acidobacteria, Streptomyces and Pseudolabrys at genus level. Further functional enrichment analysis enabled us to identify many proteins in regulatory and signalling networks of key biogeochemical cycles such as the nitrogen cycle. The combined extraction methods connected previous Park Grass metadata with the metaproteome, biogeochemistry and soil ecology. This could provide a base on which future targeted studies of important soil processes and their regulation can be built. Highlights Parallel protein extraction methods identified 1266 proteins from Park Grass soil Proteome was enriched in ribosomal and respiration proteins for the surfactant extraction method and nitrogen associated proteins for the modified phenol/chloroform method Identification of regulatory and signalling proteins in key biogeochemical cycles Links metaproteome to microbiome, biogeochemical cycles and Park Grass metadata Provides baseline for future targeted studies
CEC: Constraints based Explanation for Classifications

Explaining the results of data-intensive computation via provenance has been extensively studied in the literature. We focus here on explaining the output of Machine Learning Classifiers, which are main components of many contemporary Data Science applications. We have developed a simple generic approach for explaining classification results, by looking for constrained perturbations to parts of the input that would have the most significant effect on the classification. Our solution requires white-box access to the model internals and a specification of constraints that define which perturbations are "reasonable" in the application domain; both are typically available to the data scientist. We propose to demonstrate CEC, a system prototype that is based on these foundations to provide generic explanations for Neural Networks and Random Forests. We will demonstrate the system usefulness in the context of two application domains: bank marketing campaigns, and visually clear explanations for image classifications. We will highlight the benefit that such explanations could yield to the data scientist and interactively engage the audience in computing and viewing explanations for different cases and different sets of constraints.