Fluctuation enhanced gas detector for wireless sensor networks

Spontaneously produced Unfilled Pauses (UPs) andFilled Pauses (FPs) were played to subjects in an fMRI experiment. While both stimuli resulted in increased activity in the Primary Auditory Cortex, FPs, unlike UPs, also elicited modulation in the Supplementary Motor Area, Brodmann Area 6. This observation provides neurocognitive confirmation of the oft-reported difference between FPs and other kinds of speech disfluency and also could provide a partial explanation for the previously reported beneficial effect of FPs on reaction times in speech perception. The results are discussed in the light of the suggested role of FPs as floor-holding devices in human polylogs

Monitoring of soybean germination process by near-infrared spectroscopy

Abstract Soybean seeds were germinated on an industrial scale after soaking for 0–56 h to produce a special additive for food industrial use. The germination process of three soybean varieties was monitored with near-infrared (NIR) spectroscopy based on changes in the amount, status, or character of the water. This paper evaluates the “waterless” NIR spectra of sound, germinated, and heat treated seeds to try to follow the fine details of the germination process. The germination process was analysed with the help of cluster analysis (CA), principal component analysis (PCA), and polar qualification system (PQS) as statistical and chemometric methods. PCA proved to be the most sensitive spectrum evaluation method to follow the fine details of germination. The applied NIR method is suitable for non-destructively, real-time monitoring of the non-linear nature of germination

Enhancing ultrafiltration performance for dairy wastewater treatment using a 3D printed turbulence promoter

Dairy factories annually generate an increasing amount of wastewater, which can cause eutrophication due to high concentrations of amino acids and lipids. To address this issue, membrane technology has emerged as a promising solution, but membrane fouling remains a significant challenge, since it can cause decreased flux, decrease membrane rejection performance, and increased energy demand. This study aimed to reduce membrane fouling by integrated a three-dimensional printed (3DP) turbulence promoter into an ultrafiltration dead-end cell and varying stirring speeds. Two mathematical models, Hermia and resistance-in-series, were used to analyze the fouling process. According to both models, the cake layer formation model indicated the most prevalent fouling mechanism. Specific energy demand, permeate flux, membrane rejection, and membrane reversible and irreversible resistances were measured, calculated, and compared. The results suggest that the combination of an integrated 3DP turbulence promoter and high stirring speeds can effectively reduce membrane fouling in a dairy wastewater treatment module

Investigation of Different Pre-Treatment Techniques and 3D Printed Turbulence Promoter to Mitigate Membrane Fouling in Dairy Wastewater Module

This study investigates the enhancement of dairy wastewater treatment using chemical and physical pre-treatments coupled with membrane separation techniques to reduce membrane fouling. Two mathematical models, namely the Hermia and resistance-in-series module, were utilized to comprehend the mechanisms of ultrafiltration (UF) membrane fouling. The predominant fouling mechanism was identified by fitting experimental data into four models. The study calculated and compared permeate flux, membrane rejection, and membrane reversible and irreversible resistance values. The gas formation was also evaluated as a post-treatment. The results showed that the pre-treatments improved UF efficiency for flux, retention, and resistance values compared to the control. Chemical pre-treatment was identified as the most effective approach to improve filtration efficiency. Physical treatments after microfiltration (MF) and UF showed better fluxes, retention, and resistance results than ultrasonic pre-treatment followed by UF. The efficacy of a three-dimensionally printed (3DP) turbulence promoter was also examined to mitigate membrane fouling. The integration of the 3DP turbulence promoter enhanced hydrodynamic conditions and increased the shear rate on the membrane surface, shortening filtration time and increasing permeate flux values. This study provides valuable insights into optimizing dairy wastewater treatment and membrane separation techniques, which can have significant implications for sustainable water resource management. The present outcomes clearly recommend the application of hybrid pre-, main- and post-treatments coupled with module-integrated turbulence promoters in dairy wastewater ultrafiltration membrane modules to increase membrane separation efficiencies

Enhancing ultrafiltration performance for dairy wastewater treatment using a 3D printed turbulence promoter

Dairy factories annually generate an increasing amount of wastewater, which can cause eutrophication due to high concentrations of amino acids and lipids. To address this issue, membrane technology has emerged as a promising solution, but membrane fouling remains a significant challenge, since it can cause decreased flux, decrease membrane rejection performance, and increased energy demand. This study aimed to reduce membrane fouling by integrated a three-dimensional printed (3DP) turbulence promoter into an ultrafiltration dead-end cell and varying stirring speeds. Two mathematical models, Hermia and resistance-in-series, were used to analyze the fouling process. According to both models, the cake layer formation model indicated the most prevalent fouling mechanism. Specific energy demand, permeate flux, membrane rejection, and membrane reversible and irreversible resistances were measured, calculated, and compared. The results suggest that the combination of an integrated 3DP turbulence promoter and high stirring speeds can effectively reduce membrane fouling in a dairy wastewater treatment module

Toll-like receptor 4 signaling in liver injury and hepatic fibrogenesis

Toll-like receptors (TLRs) are a family of transmembrane pattern recognition receptors (PRR) that play a key role in innate and adaptive immunity by recognizing structural components unique to bacteria, fungi and viruses. TLR4 is the most studied of the TLRs, and its primary exogenous ligand is lipopolysaccharide, a component of Gram-negative bacterial walls. In the absence of exogenous microbes, endogenous ligands including damage-associated molecular pattern molecules from damaged matrix and injured cells can also activate TLR4 signaling. In humans, single nucleotide polymorphisms of the TLR4 gene have an effect on its signal transduction and on associated risks of specific diseases, including cirrhosis. In liver, TLR4 is expressed by all parenchymal and non-parenchymal cell types, and contributes to tissue damage caused by a variety of etiologies. Intact TLR4 signaling was identified in hepatic stellate cells (HSCs), the major fibrogenic cell type in injured liver, and mediates key responses including an inflammatory phenotype, fibrogenesis and anti-apoptotic properties. Further clarification of the function and endogenous ligands of TLR4 signaling in HSCs and other liver cells could uncover novel mechanisms of fibrogenesis and facilitate the development of therapeutic strategies

Evaluation of a Partial Genome Screening of Two Asthma Susceptibility Regions Using Bayesian Network Based Bayesian Multilevel Analysis of Relevance

Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA). This method uses Bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the Bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated. With frequentist methods one SNP (rs3751464 in the FRMD6 gene) provided evidence for an association with asthma (OR = 1.43(1.2–1.8); p = 3×10−4). The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics. In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta