Mesoscale finite element modelling of failure behaviour of steel-bar reinforced UHPFRC beams with randomly distributed fibres

This study develops a nonlinear finite element model for simulation of complicated failure behaviour of ultra high performance fibre reinforced concrete (UHPFRC) beams reinforced with steel bars and stirrups. In this model, the continuum damage plasticity model is used as the constitutive law for the UHPC matrix, and cohesive elements are used to simulate the softening bond-slip behaviour of the steel fibres/bars-UHPC matrix interfaces. Both the steel fibres and bars are modelled by elastic-plastic beam elements. As such, all the potential failure modes, including the matrix cracking and crushing, yielding and breakage of steel bars and fibres, and debonding of interfaces, can be simulated. A beam under four-point loading with various shear span versus beam depth ratios was simulated to validate the model. The results were compared well with experiments in terms of load-deflection curves and failure behaviour

Selective laser sintering of hydroxyapatite reinforced polyethylene composites for bioactive implants and tissue scaffold development

Selective laser sintering (SLS) has been investigated for the production of bioactive implants and tissue scaffolds using composites of high-density polyethylene (HDPE) reinforced with hydroxyapatite (HA) with the aim of achieving the rapid manufacturing of customized implants. Single-layer and multilayer block specimens made of HA-HDPE composites with 30 and 40 vol % HA were sintered successfully using a CO2 laser sintering system. Laser power and scanning speed had a significant effect on the sintering behaviour. The degree of particle fusion and porosity were influenced by the laser processing parameters, hence control can be attained by varying these parameters. Moreover, the SLS processing allowed exposure of HA particles on the surface of the composites and thereby should provide bioactive products. Pores existed in the SLS-fabricated composite parts and at certain processing parameters a significant fraction of the pores were within the optimal sizes for tissue regeneration. The results indicate that the SLS technique has the potential not only to fabricate HA-HDPE composite products but also to produce appropriate features for their application as bioactive implants and tissue scaffolds

Effects of material morphology and processing conditions on the characteristics of hydroxyapatite and high-density polyethylene biocomposites by selective laser sintering

Hydroxyapatite (HA), a ceramic to which bone inherently bonds, incorporated into a polymer matrix enhances the bioactivity of implants. In order to rapid-manufacture bioactive implants, selective laser sintering (SLS) has been used to fabricate HA and high-density polyethylene (HDPE) composite (HA-HDPE). The properties of SLS-fabricated specimens have been investigated. The main aspects to be considered in the SLS technology are the properties of the materials used in the process and processing parameters (PPs). HA-HDPE composite specimens have been fabricated using five different powders with variations in particle size (PS), PS distribution, and five different laser PPs. The sintering height, the width, and the shrinkage of the specimens were determined and the effects of the particles and PPs on the physical properties were investigated. The HA-HDPE specimens were found to be highly porous and the sintered density and porosity of the specimens were influenced by the PS and PPs. The interparticle connectivity and the pore size range of the specimens were found to be predominantly determined by the PS and to a lesser extent also influenced by the PPs. The strength of these specimens and the relationship with porosity are discussed

Social capital in a syndicate investment platform - Effects on syndicate lead performance

ABSTRACT Investors on equity crowdfunding platform often face an information asymmetry problem due to the lack of information on assessing the true value of new ventures (Agrawal, Catalini, & Goldfarb, 2016). Moreover, average crowd investors may be either unqualified or unwilling to conduct the requisite due diligence. Equity crowdfunding syndicates emerged in recent years as an innovative form of entrepreneurial financing to overcome these challenges. They serve as a way for “syndicate leads” to leverage their knowledge and bring in substantial funds from a crowd of “backers” (Agrawal et al., 2016). Syndicate leads source investments and secure allocations of funds for investment while conducting due diligence. In exchange, backers pay the syndicate lead a fee (carried interest) for any subsequently profitable investment. This whole process is facilitated on platforms such as AngelList and SyndicateRoom. Despite the growing popularity of equity crowdfunding syndicates, scholarly understanding of the phenomenon is currently limited. Prior research shows equity crowdfunding syndicates shift the focal investment activities of the crowd from startups to syndicate leads (Agrawal et al., 2016). Given the important role played by syndicate leads, it is vital to develop theory-based understandings of their performances. Our study uses social capital theory to examine the effects of syndicate leads’ social capital within and beyond the platform on the performance of syndicate leads. Using data from a sample of 181 syndicate leads on AngelList, a world leading equity crowdfunding platform in the US, our study offers two contributions to social capital literature in the entrepreneurial finance context. First, we differentiate syndicate platform with non-syndicate platform social capital, based on the categories of bonding/internal social capital and bridging/external social capital (Adler & Kwon, 2002). Second, we build upon multidimensional social capital theory and distinguish syndicate leads’ social capital into structural, relational and cognitive aspects (Nahapiet and Ghoshal, 1998). This study represents a first attempt to understand this new form of entrepreneurial financing. We provide a research model with related hypotheses for how syndicate platform multidimensional social capital and non-syndicate platform multidimensional social capital of syndicate leads are related to their performance

Characterizing bi-temporal patterns of land surface temperature using landscape metrics based on sub-pixel classifications from Landsat TM/ETM+

Landscape patterns in a region have different sizes, shapes and spatial arrangements, which contribute to the spatial heterogeneity of the landscape and are linked to the distinct behavior of thermal environments. There is a lack of research generating landscape metrics from discretized percent impervious surface area data (ISA), which can be used as an indicator of urban spatial structure and level of development, and quantitatively characterizing the spatial patterns of landscapes and land surface temperatures (LST). In this study, linear spectral mixture analysis (LSMA) is used to derive sub-pixel ISA. Continuous fractional cover thresholds are used to discretize percent ISA into different categories related to urban land cover patterns. Landscape metrics are calculated based on different ISA categories and used to quantify urban landscape patterns and LST configurations. The characteristics of LST and percent ISA are quantified by landscape metrics such as indices of patch density, aggregation, connectedness, shape and shape complexity. The urban thermal intensity is also analyzed based on percent ISA. The results indicate that landscape metrics are sensitive to the variation of pixel values of fractional ISA, and the integration of LST, LSMA. Landscape metrics provide a quantitative method for describing the spatial distribution and seasonal variation in urban thermal patterns in response to associated urban land cover patterns

Accelerated digestion of nucleic acids by pepsin from the stomach of chicken

<p></p><p>Nucleic acids have become an important nutritional supplement in poultry feed; however, the digestion of nucleic acids in poultry is unclear. The objective of this study was to investigate the digestion of nucleic acids by chicken pepsin <i>in vitro</i>.</p><p>The extracted pepsinogen from the stomach of the chicken was purified to homogeneity. Upon activation at pH 2.0, chicken pepsinogen was converted to its active form.</p><p>Nucleic acids, including λ-DNA, salmon sperm DNA and single-strand DNA (ssDNA), can be used as substrates and digested into short-chain oligonucleotides by pepsin.</p><p>Interestingly, the digestion of the nucleic acids was inhibited when pepsin was treated by alkaline solution (pH 8.0) or pepstatin A. Also, the digestion of the nucleic acids was not affected by the addition of haemoglobin or bovine serum albumin.</p><p>The results suggested that nucleic acids could be digested by chicken pepsin. Thus pepsin may have a role in digesting nucleic acids <i>in vivo</i>. Nucleic acids added to poultry fed may be digested, starting from the stomach.</p><p></p> <p>Nucleic acids have become an important nutritional supplement in poultry feed; however, the digestion of nucleic acids in poultry is unclear. The objective of this study was to investigate the digestion of nucleic acids by chicken pepsin <i>in vitro</i>.</p> <p>The extracted pepsinogen from the stomach of the chicken was purified to homogeneity. Upon activation at pH 2.0, chicken pepsinogen was converted to its active form.</p> <p>Nucleic acids, including λ-DNA, salmon sperm DNA and single-strand DNA (ssDNA), can be used as substrates and digested into short-chain oligonucleotides by pepsin.</p> <p>Interestingly, the digestion of the nucleic acids was inhibited when pepsin was treated by alkaline solution (pH 8.0) or pepstatin A. Also, the digestion of the nucleic acids was not affected by the addition of haemoglobin or bovine serum albumin.</p> <p>The results suggested that nucleic acids could be digested by chicken pepsin. Thus pepsin may have a role in digesting nucleic acids <i>in vivo</i>. Nucleic acids added to poultry fed may be digested, starting from the stomach.</p

LiFePO4 – 3 D carbon nanofiber composites as cathode materials for Li-ions batteries

The characterization of carbon nanofiber 3D nonwovens, prepared by electrospinning process, coated with olivine structured lithium iron phosphate is reported. The LiFePO4 as cathode material for lithium ion batteries was prepared by a Pechini-assisted reversed polyol process. The coating has been successfully performed on carbon nanofiber 3D nonwovens by soaking in aqueous solution containing lithium, iron salts and phosphates at 70°C for 2-4 h. After drying-out, the composites were annealed at 600°C for 5 h under nitrogen. The surface investigation of the prepared composites showed a uniform coating of the carbon nonwoven nanofibers as well as the formation of cauliflowers-like crystalline structures which are uniformly distributed all over the surface area of the carbon nanofibers. The electrochemical measurements on the composites showed good performances delivering a discharge specific capacity of 156mAhg-1 at a discharging rate of C/25 and 152mAhg-1 at a discharging rate of C/10 at room temperature

A DFT-Based Analysis of the NMR Fermi Contact Shifts in Tavorite-like LiMPO₄·OH and MPO₄·H₂O (M = Fe, Mn, V)

Complementing our work on the experimental measurements and DFT calculations of the NMR Fermi contact shifts for ⁷Li, ³¹P, and ¹H in the tavorite LiFePO₄·OH and homeotypic FePO₄·H₂O, LiMnPO₄·OH, MnPO₄·H₂O, and VPO₄·H₂O phases, we aim to understand the origin of those shifts. Using FP-LAPW calculations that were validated by reproducing correctly the experimental shifts, we analyze the electronic spin-transfer mechanisms from the transition metal M to the probed nucleus in relation with the electronic configuration of the M³⁺ ions and the nature of the chemical bonds in the compounds, by plotting the spin DOS and 2D or 3D spin density maps in selected energy domains. These mechanisms are analyzed in detail for the two Fe³⁺ phases, and the differences occurring for the Mn and V phases are discussed further

Effects of photoperiod on broodiness, egg-laying and endocrine responses in native laying hens

<div><p></p><p>1. The effects of photoperiod on broodiness, egg-laying and endocrine responses in native laying hens were investigated. A total of 648, 18-week-old native laying hens (Beijing You Chicken, BYC) were randomly allocated to 6 groups with 3 replicates. The birds were exposed to 1 of 6 different photoperiods, including 16L:8D (06:00 to 22:00 h) for group 1; 12L:2D:4L:6D for group 2; 8L:4D:4L:8D for group 3; 16L:8D (03:00 to 19:00 h) for group 4; 14L:10D for group 5; and 18L:6D for group 6.</p><p>2. The broodiness rate and egg-laying rate for weeks 20–26, 27–33, 34–40, 41–47, 48–54 and 55–61 were calculated, and serum prolactin (PRL), luteinising hormone (LH), 17-beta-oestradiol (E2), melatonin (Mel) and progesterone (P4) concentrations were measured at the end of each stage.</p><p>3. Significant effects were observed on the rate of broodiness by the photoperiod and stage, but the interaction of photoperiod and stage was not significant. The rate of broodiness for group 3 (5.9%) was significantly higher than other groups, with group 2 being the lowest (2.8%). Broodiness rate was the highest for weeks 41–47 (9.9%). Significant effects were observed on average egg-laying rate by photoperiod and stage: the rate of egg-laying of groups 2 and 5 were significantly higher than groups 1, 4 and 6.</p><p>4. There were no significant effects of photoperiod on PRL, LH and Mel concentrations at 26, 33, 40 and 54 weeks of age (<i>P ></i> 0.05), but at 47 weeks of age, PRL and LH concentrations of group 1 were significantly lower than those in other groups.</p><p>5. The study suggests that the photoperiod of group 2 (12L:2D:4L:6D) is optimal for the birds’ performance to give the lowest broodiness rate and the highest egg-laying rate during the whole laying period, and 41–47 weeks may be a key stage for the photomodulation of broodiness.</p></div

QSAR models for predicting octanol/water and organic carbon/water partition coefficients of polychlorinated biphenyls

<p>Quantitative structure–property relationship modelling can be a valuable alternative method to replace or reduce experimental testing. In particular, some endpoints such as octanol–water (<i>K</i>_OW) and organic carbon–water (<i>K</i>_OC) partition coefficients of polychlorinated biphenyls (PCBs) are easier to predict and various models have been already developed. In this paper, two different methods, which are multiple linear regression based on the descriptors generated using Dragon software and hologram quantitative structure–activity relationships, were employed to predict suspended particulate matter (SPM) derived log <i>K</i>_OC and generator column, shake flask and slow stirring method derived log <i>K</i>_OW values of 209 PCBs. The predictive ability of the derived models was validated using a test set. The performances of all these models were compared with EPI Suite™ software. The results indicated that the proposed models were robust and satisfactory, and could provide feasible and promising tools for the rapid assessment of the SPM derived log <i>K</i>_OC and generator column, shake flask and slow stirring method derived log <i>K</i>_OW values of PCBs.</p