A Survey on Some Parameters of Beef and Buffalo Meat Quality

A survey was carried out on 13 Vietnamese Yellow cattle, 14 LaiSind cattle and 18 buffalos in Hanoi to estimate the quality of longissimus dorsi in terms of pH, color, drip loss, cooking loss and tenderness at 6 different postmortem intervals. It was found that the pH value of longissimus dorsi was not significantly different among the 3 breeds (P>0.05), being reduced rapidly during the first 36 hours postmortem, and then stayed stable. The value was in the range that was considered to be normal. Conversely, the color values L*, a* and b* tended to increase and also stable at 36 hours postmortem, except that for LaiSind cattle at 48 hours. According to L* scale, the meat of Yellow and LaiSind cattle met the normal quality but the buffalo meat was considered to be dark cutters. The tenderness of longissimus dorsi was significantly different among the breeds (P<0.05). The value was highest at 48 hours and then decreased for LaiSind and buffalo, but for Yellow cattle the value decreased continuously after slaughtering In terms of tenderness buffalo meat and Yellow cattle meat were classified as “intermediate”, while LaiSind meat was out of this interval and classified as “tough”. Drip loss ratio was increased with the time of preservation (P<0.05). The cooking loss ratio was lowest at 12 hours and higher at the next period, but there was no significant difference among the periods after 36 hours postmotem.Peer reviewe

PILOT SCALE STUDY ON AMMONIUM REMOVAL IN PHAP VAN WATER PLANT, HANOI CITY

Joint Research on Environmental Science and Technology for the Eart

Multivariate Relations Aggregation Learning in Social Networks

Multivariate relations are general in various types of networks, such as biological networks, social networks, transportation networks, and academic networks. Due to the principle of ternary closures and the trend of group formation, the multivariate relationships in social networks are complex and rich. Therefore, in graph learning tasks of social networks, the identification and utilization of multivariate relationship information are more important. Existing graph learning methods are based on the neighborhood information diffusion mechanism, which often leads to partial omission or even lack of multivariate relationship information, and ultimately affects the accuracy and execution efficiency of the task. To address these challenges, this paper proposes the multivariate relationship aggregation learning (MORE) method, which can effectively capture the multivariate relationship information in the network environment. By aggregating node attribute features and structural features, MORE achieves higher accuracy and faster convergence speed. We conducted experiments on one citation network and five social networks. The experimental results show that the MORE model has higher accuracy than the GCN (Graph Convolutional Network) model in node classification tasks, and can significantly reduce time cost.Comment: 11 pages, 6 figure

Clinical implications of reduced susceptibility to fluoroquinolones in paediatric Shigella sonnei and Shigella flexneri infections.

OBJECTIVES: We aimed to quantify the impact of fluoroquinolone resistance on the clinical outcome of paediatric shigellosis patients treated with fluoroquinolones in southern Vietnam. Such information is important to inform therapeutic management for infections caused by this increasingly drug-resistant pathogen, responsible for high morbidity and mortality in young children globally. METHODS: Clinical information and bacterial isolates were derived from a randomized controlled trial comparing gatifloxacin with ciprofloxacin for the treatment of paediatric shigellosis. Time-kill experiments were performed to evaluate the impact of MIC on the in vitro growth of Shigella and Cox regression modelling was used to compare clinical outcome between treatments and Shigella species. RESULTS: Shigella flexneri patients treated with gatifloxacin had significantly worse outcomes than those treated with ciprofloxacin. However, the MICs of fluoroquinolones were not significantly associated with poorer outcome. The presence of S83L and A87T mutations in the gyrA gene significantly increased MICs of fluoroquinolones. Finally, elevated MICs and the presence of the qnrS gene allowed Shigella to replicate efficiently in vitro in high concentrations of ciprofloxacin. CONCLUSIONS: We found that below the CLSI breakpoint, there was no association between MIC and clinical outcome in paediatric shigellosis infections. However, S. flexneri patients had worse clinical outcomes when treated with gatifloxacin in this study regardless of MIC. Additionally, Shigella harbouring the qnrS gene are able to replicate efficiently in high concentrations of ciprofloxacin and we hypothesize that such strains possess a competitive advantage against fluoroquinolone-susceptible strains due to enhanced shedding and transmission

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Band gap modification and ferroelectric properties of Bi0.5(Na,K)0.5TiO3-based by Li substitution

We report on the reduction of band gap in Bi0.5(Na0.82-xLixK0.18)0.5(Ti0.95Sn0.05)O3 from 2.99 eV to 2.84 eV due to the substitutions of Li+ ions to Na+ sites. In addition, the lithium substitution samples exhibit an increasing of the maximal polarizations from 21.8 to 25.7 μC/cm2. The polarization enhancement of ferroelectric and reduction of the band gaps are strongly related to the Li substitution concentration as evaluated via the electronegative between A-site and oxygen and tolerance factor. The results are promising for photovoltaic and photocatalytic applications

Discrete element modeling of granular flows of polyhedral particles

We investigate the flow behavior of granular materials composed of polyhedral particles using an in-house code based on polyhedral representation of particle shapes and a rigorous contact detection algorithm. This algorithm is able to distinguish different types of contact (face-face, face-edge, face-vertex, edge-edge, edge-vertex, vertex-vertex). A linear force law based on normal overlaps at the contact points between particles is used and face-face and face-edge contacts are represented by at least three and two contact points, respectively. Furthermore, to reduce the effect of sharp corners and edges, a small Minkowsky radius is added. This approach is applied to simulate the flow behavior in rotating drums in the cascading flow regime. This geometry is extensively applied in industrial processes such as mixing, grinding, and granulation. Nevertheless, the rheology and scaling behavior for aspherical particles has not been investigated on a systematic basis. In fact, most previous studies have concerned either the rolling regime or the flow of spherical particles. In our simulations, we used icosahedral particle shapes and a broad range of the values of rotation speed, drum and particle diameters, and filling heights. We analyzed the evolution of flow variables including both macroscopic and microscopic properties such as the active layer thickness, the shape of free surface in terms of its average slope and the steepest slope, coordination number, forces, and shear rate of the active layer. We show that the flow behavior can be described in terms of a single dimensionless upscaling parameter combining different system parameters. We consider also the effect of particle coarsening on the flow characteristics. Interestingly, our simulations show that wall slip scales with the same upscaling parameter, meaning that wall slip should be treated with the same status as other flow variables

Rheology and scaling behavior of polyhedral particle flows in rotating drums

International audienceWe use particle dynamics simulations to investigate the rheology of granular flows composed of regular octahedral particles in a rotating drum. We focus on the cascading regime and perform an extensive parametric study by varying drum size, particle size, rotation speed, and filling degree. Our simulations indicate that the passive layer undergoes quasistatic shearing and, in contrast to spherical particle flows, no sliding occurs at the drum wall due to the angular particle shape. A scaling parameter combining the Froude number, the ratio of drum to particle size, and the filling degree captures the kinematic and dynamic characteristics of the granular flow such as free surface shape, shear velocity, flow thickness, and inertial number. This scaling suggests simple linear correlations between free surface curvature, flow thickness, and inertial number. We also show that this scaling is fully consistent with the expected effects of increasing particle size