Group sequential crossover trial designs with strong control of the familywise error rate

Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%.     

Nutrient digestibility and endogenous protein losses in the foregut and small intestine of weaned dairy calves fed calf starters with conventional or enzyme-treated soybean meal

The aims of this experiment were (1) to compare the effects of a soybean meal with an enzymatic treatment (ESBM) to reduce the concentration of antinutritional factors versus a standard soybean meal (SBM) on foregut and small intestine digestion in weaned dairy calves and (2) to estimate the endogenous losses of crude protein (CP) in the small intestine. Our hypothesis was that a diet containing ESBM instead of SBM would improve ruminal and small intestine digestion and absorption of nutrients. A T-cannula was placed in the duodenum, and a second T-cannula was installed in the distal ileum of 12 Holstein calves at approximately 3 wk of age. Calves were weaned on d 42, and on d 50 they were assigned randomly to a quadruplicated 3 × 3 Latin square with 10-d periods. Digesta samples were collected on d 7 and 8 from the ileum and d 9 and 10 from the duodenum. The diets were fed for ad libitum intake and consisted of a calf starter (CS) of 20% CP with SBM as the main source of protein (CTRL), and an isonitrogenous CS with an ESBM instead of SBM (ENZT). A third diet with a low content of CP (10%) and no soy protein was fed to estimate endogenous N losses and digestibilities of test ingredients. Flows and digestibilities of nutrients were compared between CTRL and ENZT and their test ingredients (SBM vs. ESBM, respectively). Duodenal net flows of CP and total AA as well as ruminal microbial protein synthesis per kilogram of digested CP were greater, and flow of nonprotein N and CP true (corrected by endogenous and microbial flows) foregut digestibility were lower with ENZT than CTRL. The apparent small intestine digestibilities of CP and total AA were greater for ESBM than SBM, but there were no differences between the CTRL and ENZT diets. We observed no differences in digestibilities at the duodenum or ileum of starch or NDF, but true small intestine digestibilities of CP and all AA were greater with ENZT than CTRL. Total endogenous protein losses in the small intestine estimated from calves fed the low-CP with no soy protein diet were 37 ± 1.5 g of CP and 29 ± 1.4 g of AA/kg of DMI. These values may be considered the basal endogenous losses as they are similar to values obtained with the regression method, which estimates N losses when dietary N is null. Our results indicated that the inclusion of an ESBM improved the efficiency of ruminal microbial protein synthesis per digested kilogram of organic matter and CP, and increased CP and AA absorption in the small intestine despite a greater proportion of undigested dietary protein entering the duodenum.     

Hydrotreatment of jatropha oil over noble metal catalysts

Jatropha oil is a promising nonedible feedstock for producing renewable diesel. In this work, the hydrotreatment processing of jatropha oil was investigated. Instead of using conventional alumina-supported Co–Mo, Ni–Mo, and Ni–W catalysts that need sulfidation pretreatment, noble metals such as Pd and Ru were chosen. Trials were performed in an isothermal trickle-bed reactor and the reaction conditions were as follows: temperature 603–663?K, weight hourly space velocity (WHSV) 1 to 4/h, pressure 1.5–3?MPa, and H₂/oil ratio 200–800 (v/v). Yield of n-C₁₅ to n-C₁₈ hydrocarbons was maximized (70.3 and 43.8% for Pd/Al₂O₃ and Ru/Al₂O₃, respectively) at the following conditions: T?=?663 K, WHSV?=?2/h, P?=?3?MPa, and H₂/oil ratio?=?600 (v/v). Since Ru favored cracking reactions to a larger extent than Pd, the yield of C₁₅ to C₁₈ hydrocarbons over Ru/Al₂O₃ was lowered. Using simple first-order plots for oil conversion, activation energies for the hydrotreating process over Pd/Al₂O₃ and Ru/Al₂O₃ were found and they were equal to 109 and 121?kJ/mol, correspondingly.     

Cultivation and downstream processing of microalgae and cyanobacteria to generate protein-based technofunctional food ingredients

Abstract

Microalgae are unicellular microorganisms that can be rich in proteins and are therefore a valuable ingredient in different foods. So far microalgae are mainly utilized in foods in low concentrations as a whole-cell ingredient even though it is known that proteins extracted from microalgae can possibly posess various technofunctional properties, such as high protein solubility, emulsification, foaming, and gelation properties. The widespread usage of protein-rich ingredients obtained from microalgae is for the most part prevented by the high price of the biomass, the lack of efficient downstream processes, and the adverse taste. The aim of this review is to give insights into the fundamental properties of the growth and processing of microalgae, highlight the advantages of microalgae ingredients and show potential applications based on the technofunctional, nutritional and sensory properties that were reported. Moreover, the existing challenges and knowledge gaps that hinder the application of microalgal proteins in foods are discussed.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Monolithically-integrated BiVO4/p+-n GaAs1-xPx tandem photoanodes capable of unassisted solar water splitting

Monolithically-integrated tandem photoanodes were fabricated on substrates consisting of epitaxial n-GaAs_1-xP_x (x ? 0.32) grown on n⁺-GaAs wafers. A p⁺-n junction photovoltaic (PV) cell was first formed by zinc diffusion into the n-GaAs_0.68P_0.32 from a deposited ZnO coating. After diffusion the ZnO serves as a transparent electrical contact to the resulting p⁺-GaAs_0.68P_0.32 surface layer. Transparent, conducting SnO₂:F provides chemical and mechanical protection for the ZnO and the underlying PV cell, and it electrically connects this cell to a top BiVO₄ photocatalyst layer. In some photoanodes, a WO₃ thin film was interposed between the SnO₂:F and BiVO₄. All oxide coatings were produced by ultrasonic spray pyrolysis except WO₃, which was spin coated. Unassisted (unbiased) solar water splitting was achieved, with a solar-to-hydrogen efficiency approaching 2%, without addition of any co-catalyst to the BiVO₄ surface. This work can provide insights to other researchers regarding scalable, low cost approaches for the planar monolithic integration of oxide photoanode materials with PV cells to create new tandem devices.     

Real-time organic aerosol chemical speciation in the indoor environment using extractive electrospray ionization mass spectrometry

Understanding the sources and composition of organic aerosol (OA) in indoor environments requires rapid measurements, since many emissions and processes have short timescales. However, real-time molecular-level OA measurements have not been reported indoors. Here, we present quantitative measurements, at a time resolution of five seconds, of molecular ions corresponding to diverse aerosol-phase species, by applying extractive electrospray ionization mass spectrometry (EESI-MS) to indoor air analysis for the first time, as part of the highly instrumented HOMEChem field study. We demonstrate how the complex spectra of EESI-MS are screened in order to extract chemical information and investigate the possibility of interference from gas-phase semivolatile species. During experiments that simulated the Thanksgiving US holiday meal preparation, EESI-MS quantified multiple species, including fatty acids, carbohydrates, siloxanes, and phthalates. Intercomparisons with Aerosol Mass Spectrometer (AMS) and Scanning Mobility Particle Sizer suggest that EESI-MS quantified a large fraction of OA. Comparisons with FIGAERO-CIMS shows similar signal levels and good correlation, with a range of 100 for the relative sensitivities. Comparisons with SV-TAG for phthalates and with SV-TAG and AMS for total siloxanes also show strong correlation. EESI-MS observations can be used with gas-phase measurements to identify co-emitted gas- and aerosol-phase species, and this is demonstrated using complementary gas-phase PTR-MS observations.     

Owner’s Risk Allocation and Contractor’s Role Behavior in a Project: A Parallel-mediation Model

Risk allocation decisions are of critical importance in project management. The present study proposes an explanation for how risk allocation in a contract motivates a contractor to cooperate with a project owner. Theories of risk allocation and trust were used to motivate the research. Using a survey methodology, we collected data concerning 124 construction projects in China. We found that risk allocation influenced the contractor’s role behavior through the contractor’s feeling of being trusted but not the contractor’s trust in the owner. Feeling of being trusted partially mediated the effect of risk allocation on the contractor’s in-role (i.e., contractual) behavior and fully mediated the effect on extra-role behavior. The study introduces a social and psychological view of the impacts of risk allocation to the project and engineering management literature. We contribute to theory by arguing and demonstrating the mediating effect of trust on the relationship between risk allocation and contractor behavior. From a practical standpoint, we conclude that contractual risk allocation has a significant impact on building a trusting relationship between owners and contractors and that contractors who feel trusted perform both contractually mandated actions and actions external to the contract more diligently, resulting in the likelihood of improved outcomes for both parties.     

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.