Effects of vertical vibration on hopper flows of granular material

The discharge of granular material from a hopper subject to vertical sinusoidal oscillations was investigated using experiments and discrete element computer simulations. With the hopper exit closed, side-wall convection cells are observed, oriented such that particles move up along the inclined walls of the hopper and down at the center line. The convection cells are a result of the granular bed dilation during free fall and the subsequent interaction with the hopper walls. The mass discharge rate for a vibrating hopper scaled by the discharge rate without vibration reaches a maximum value at a dimensionless velocity amplitude just greater than 1. Further increases in the velocity decrease the discharge rate. The decrease occurs due to a decrease in the bulk density of the discharging material when vibration is applied

Role of glutathionylation in infection and inflammation

Glutathionylation, that is, the formation of mixed disulfides between protein cysteines and glutathione (GSH) cysteines, is a reversible post-translational modification catalyzed by dierent cellular oxidoreductases, by which the redox state of the cell modulates protein function. So far, most studies on the identification of glutathionylated proteins have focused on cellular proteins, including proteins involved in host response to infection, but there is a growing number of reports showing that microbial proteins also undergo glutathionylation, with modification of their characteristics and functions. In the present review, we highlight the signaling role of GSH through glutathionylation, particularly focusing on microbial (viral and bacterial) glutathionylated proteins (GSSPs) and host GSSPs involved in the immune/inflammatory response to infection; moreover, we discuss the biological role of the process in microbial infections and related host responses

Glutathione increase by the n-butanoyl glutathione derivative (GSH-C4) inhibits viral replication and induces a predominant Th1 immune profile in old mice infected with influenza virus

During aging, glutathione (GSH) content declines and the immune system undergoes a deficiency in the induction of Th1 response. Reduced secretion of Th1 cytokines, which is associated with GSH depletion, could weaken the host defenses against viral infections. We first evaluated the concentration of GSH and cysteine in organs of old mice; then, the effect of the administration of the N-butanoyl GSH derivative (GSH-C4) on the response of aged mice infected with influenza A PR8/H1N1 virus was studied through the determination of GSH concentration in organs, lung viral titer, IgA and IgG1/IgG2a production and Th1/Th2 cytokine profile. Old mice had lower GSH than young mice in organs. Also the gene expression of endoplasmic reticulum (ER) stress markers involved in GSH metabolism and folding of proteins, i.e. Nrf2 and PDI, was reduced. Following infection, GSH content remained low and neither infection nor GSH-C4 treatment affected Nrf2 expression. In contrast, PDI expression was upregulated during infection and appeared counterbalanced by GSH-C4. Moreover, the treatment with GSH-C4 increased GSH content in organs, reduced viral replication and induced a predominant Th1 response. In conclusion, GSH-C4 treatment could be used in the elderly to contrast influenza virus infection by inducing immune response, in particular the Th1 profile

In situ monitoring of moisture uptake of flax fiber reinforced composites under humid/dry conditions

The use of green materials such as natural fiber-reinforced composites represents an increasingly stringent prerogative in the future planning of industrial and non-industrial production. The optimization of these materials is the main aim of the current research, focused on the evaluation of the behavior of flax fiber reinforced composites exposed to isothermal adsorption and desorption cycles, at varying the partial pressure of water vapor (P/P0). For this purpose, the moisture uptake and the morphology changes of the composite material and their constituents were in situ monitored through a measurement protocol, by using a dynamic vapor sorption (DVS) analysis, coupled with an environmental scanning electron microscopy (ESEM) visual investigation. A dependence of moisture uptake and diffusivity on the composite morphology was clearly detected. In particular, no significant variation in the morphology of the specimen is noticed at low water vapor partial pressure (i.e., P/P0 up to 5.4%) due to the limited absorption capacity (i.e., lower than 1%). On the other hand, fibers morphology changes at increasing the partial pressure up to 25.1%, showing a sensitive increase in volume. This phenomenon becomes much more relevant for high relative humidity values (i.e., ~90%), reaching more than 6% of absorption capacity

The Clustering of Extremely Red Objects

We measure the clustering of Extremely Red Objects (EROs) in ~8 deg^2 of the NOAO Deep Wide Field Survey Bo\"otes field in order to establish robust links between ERO z~1.2 and local galaxy z<0.1 populations. Three different color selection criteria from the literature are analyzed to assess the consequences of using different criteria for selecting EROs. Specifically, our samples are (R-K_s)>5.0 (28,724 galaxies), (I-K_s)>4.0 (22,451 galaxies) and (I-[3.6])>5.0 (64,370 galaxies). Magnitude-limited samples show the correlation length (r_0) to increase for more luminous EROs, implying a correlation with stellar mass. We can separate star-forming and passive ERO populations using the (K_s-[24]) and ([3.6]-[24]) colors to K_s=18.4 and [3.6]=17.5, respectively. Star-forming and passive EROs in magnitude limited samples have different clustering properties and host dark halo masses, and cannot be simply understood as a single population. Based on the clustering, we find that bright passive EROs are the likely progenitors of >4L^* elliptical galaxies. Bright EROs with ongoing star formation were found to occupy denser environments than star-forming galaxies in the local Universe, making these the likely progenitors of >L^* local ellipticals. This suggests that the progenitors of massive >4L^* local ellipticals had stopped forming stars by z>1.2, but that the progenitors of less massive ellipticals (down to L^*) can still show significant star formation at this epoch.Comment: 19 pages, 16 figures, 4 tables, Accepted to ApJ 27th November 201

Feasibility of a “Network of Champions” in Implementing a Program to Address Physician Well-being

Introduction: Healthcare leaders have been challenged to mitigate burnout and foster well-being among physicians. Professional societies are beginning to address this in a systematic manner. Methods: In 2014, the American College of Physicians (ACP) endeavored to improve well-being for its 160,000 members of internists and trainees through a Well-being Champion (WBC) program based in the majority of its 85 national and international chapters. The program was supported by an evidence-based curriculum, chapter volunteers who served as champions, and in-person and virtual trainings. Training included a 1-2 day program in 2018 and 2019, focused on educating champions on causes of burnout, means of systematically collecting well-being data, and methods for using data for system change to reduce burnout and improve well-being. Results: Training included 158 WBCs in 8 countries. After training, over 90% of champions in both years of the program felt able to articulate the evidence for burnout prevention and suggest interventions, access resources, and administer well-being surveys. While 58% of champions noted high interest in wellness, only 26% had a budget allocated for this, and most budgets were small. Ninety-one percent in both years felt able to analyze survey data and 90% in both years felt able to enhance their own well-being. Eighty-eight to 90% felt able to foster a well-being community and importantly, 85% felt comfortable engaging leadership in this topic. Since 2017, 639 activities were recorded, accounting for 87/158 Champions in 69 Chapters. Annual direct costs varied each year but remained Conclusion: This report describes a model for building regional networks to address physician burnout while promoting well-being and professional fulfillment. After training, champions felt capable of performing key aspects of burnout reduction, including survey administration, data analysis and engaging leadership in systems change. To our knowledge, this is the first model to scale burnout prevention throughout an entire professional society. Using the included program descriptions and curricula, this program may be generalizable for other large professional groups wishing to measure and enhance well-being among their membership

WARP: a WIMP double phase Argon detector

The WARP programme for dark matter search with a double phase argon detector is presented. In such a detector both excitation and ionization produced by an impinging particle are evaluated by the contemporary measurement of primary scintillation and secondary (proportional) light signal, this latter being produced by extracting and accelerating ionization electrons in the gas phase. The proposed technique, verified on a 2.3 liters prototype, could be used to efficiently discriminate nuclear recoils, induced by WIMP's interactions, and measure their energy spectrum. An overview of the 2.3 liters results and of the proposed 100 liters detector is shown.Comment: Proceeding for IDM200

Fast and accurate long-range phasing in a UK Biobank cohort

Recent work has leveraged the extensive genotyping of the Icelandic population to perform long-range phasing (LRP), enabling accurate imputation and association analysis of rare variants in target samples typed on genotyping arrays. Here, we develop a fast and accurate LRP method, Eagle, that extends this paradigm to populations with much smaller proportions of genotyped samples by harnessing long (>4cM) identical-by-descent (IBD) tracts shared among distantly related individuals. We applied Eagle to N≈150,000 samples (0.2% of the British population) from the UK Biobank, and we determined that it is 1–2 orders of magnitude faster than existing methods while achieving similar or better phasing accuracy (switch error rate ≈0.3%, corresponding to perfect phase in a majority of 10Mb segments). We also observed that when used within an imputation pipeline, Eagle pre-phasing improved downstream imputation accuracy compared to pre-phasing in batches using existing methods (as necessary to achieve comparable computational cost)

Experimental data based machine learning classification models with predictive ability to select in vitro active antiviral and non-toxic essential oils

In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among the prominent studies essential oils are investigated as antibacterial agents alone or in combination with known drugs. Minor studies involved essential oil inspection as potential anticancer and antiviral natural remedies. In line with the authors previous reports the investigation of an in-house library of extracted essential oils as a potential blocker of HSV-1 infection is reported herein. A subset of essential oils was experimentally tested in an in vitro model of HSV-1 infection and the determined IC50s and CC50s values were used in conjunction with the results obtained by gas-chromatography/mass spectrometry chemical analysis to derive machine learning based classification models trained with the partial least square discriminant analysis algorithm. The internally validated models were thus applied on untested essential oils to assess their effective predictive ability in selecting both active and low toxic samples. Five essential oils were selected among a list of 52 and readily assayed for IC50 and CC50 determination. Interestingly, four out of the five selected samples, compared with the potencies of the training set, returned to be highly active and endowed with low toxicity. In particular, sample CJM1 from Calaminta nepeta was the most potent tested essential oil with the highest selectivity index (IC50 = 0.063 mg/mL, SI &gt; 47.5). In conclusion, it was herein demonstrated how multidisciplinary applications involving machine learning could represent a valuable tool in predicting the bioactivity of complex mixtures and in the near future to enable the design of blended essential oil possibly endowed with higher potency and lower toxicity