Predictive formulas for different measures of cheese yield using milk composition from individual goat samples

The objective of this study was to develop formulas based on milk composition of individual goat samples for predicting cheese yield (%CY) traits (fresh curd, milk solids, and water retained in the curd). The specific aims were to assess and quantify (1) the contribution of major milk components (fat, protein, and casein) and udder health indicators (lactose, somatic cell count, pH, and bacterial count) on %CY traits (fresh curd, milk solids, and water retained in the curd); (2) the cheese-making method; and (3) goat breed effects on prediction accuracy of the %CY formulas. The %CY traits were analyzed in duplicate from 600 goats, using an individual laboratory cheese-making procedure (9-MilCA method; 9 mL of milk per observation) for a total of 1,200 observations. Goats were reared in 36 herds and belonged to 6 breeds (Saanen, Murciano-Granadina, Camosciata delle Alpi, Maltese, Sarda, and Sarda Primitiva). Fresh %CY (%CY_CURD), total solids (%CY_SOLIDS), and water retained (%CY_WATER) in the curd were used as response variables. Single and multiple linear regression models were tested via different combinations of standard milk components (fat, protein, casein) and indirect udder health indicators (UHI; lactose, somatic cell count, pH, and bacterial count). The 2 %CY observations within animal were averaged, and a cross-validation (CrV) scheme was adopted, in which 80% of observations were randomly assigned to the calibration (CAL) set and 20% to the validation (VAL) set. The procedure was repeated 10 times to account for sampling variability. Further, the model presenting the best prediction accuracy in CrV (i.e., comprehensive formula) was used in a secondary analysis to assess the accuracy of the %CY predictive formulas as part of the laboratory cheese-making procedure (within-animal validation, WAV), in which the first %CY observation within animal was assigned to CAL, and the second to the VAL set. Finally, a stratified CrV (SCrV) was adopted to assess the %CY traits prediction accuracy across goat breeds, again using the best model, in which 5 breeds were included in CAL and the remaining one in the VAL set. Fitting statistics of the formulas were assessed by coefficient of determination of validation (R²_VAL) and the root mean square error of validation (RMSE_VAL). In CrV, the formula with the best prediction accuracy for all %CY traits included fat, casein, and UHI (R²_VAL = 0.65, 0.96, and 0.23 for %CY_CURD, %CY_SOLIDS, and %CY_WATER, respectively). The WAV procedure showed R²_VAL higher than those obtained in CrV, evidencing a low effect of the 9-MilCA method and, indirectly, its high repeatability. In the SCrV, large differences for %CY_CURD and %CY_WATER among breeds evidenced that the breed is a fundamental factor to consider in %CY predictive formulas. These results may be useful to monitor milk composition and quantify the influence of milk traits in the composite selection indices of specific breeds, and for the direct genetic improvement of cheese production.     

Facile synthesis of a carbon-rich SiAlCN precursor and investigation of its structural evolution during the polymer-ceramic conversion process

A liquid carbon-rich SiAlCN precursor is facilely synthetized by hydrosilylation between liquid polyaluminocarbosilane (LPACS) and 1,3,5,7-tetravinyl- 1,3,5,7-tetramethylcyclotetrasilazane {[CH₃(CH₂CH₂)SiNH]₄} (TeVSZ). The structural evolution during the polymer-ceramic conversion process is investigated by various methods. The results show that the main cured mechanism is β-addition on hydrosilylation, although α-addition on hydrosilylation, polymerization of vinyl groups and dehydrocoupling reaction between N–H bonds also occur during the cured process. During the pyrolysis process, dehydrogenation and dehydrocarbonation condensation reactions, transamination reactions occur, leading to formation of a three-dimensional network inorganic structure at 400–800 °C, where part of Al–O bonds convert to Al–N bonds. Then the network inorganic structure undergoes demixing and separation into amorphous SiAlCN(O) phase, where the amorphous turbostratic free carbon phase also form at 800–1200 °C. With demixing and decomposition of the amorphous carbon-rich SiAlCN(O) phase, the crystalline β-SiC and graphitic carbon start to form at about 1400 °C, the crystalline sizes of them both enlarge with increasing temperature. However, the crystal growth of β-SiC is distinctly inhibited due to existence of the rich carbon phase, tiny amounts of Al₂O₃ and AlN. In addition, a small amount of AlN can promote the formation of α-SiC at 1800 °C.     

Influence of applied voltage and conductive material in DIET promotion for methane generation

The utilization of biological-, electrode- and conductive material-mediated direct interspecies electron transfer (DIET) between exoelectrogenic bacteria and methanogenic archaea for enhancing methane productivity is widely reported in the literature. However, two cardinal questions are still controversial, i.e., which applied voltage value would be more recommended to enhance methane generation? and how the DIET over IIET has the upper hand in enhancing methane productivity? Herein, the influence of different applied voltages to promote biological-, conductive- and electrode-mediated DIET was investigated in MEC-AD reactors with conductive material. Polarized bioelectrodes induced electrode-mediated DIET (eDIET) and biological DIET (bDIET), in addition to cDIET (conductive material-mediated DIET), improved the methane yield to 315.40 mL/g COD_r with an applied voltage of 0.9 V. Whereas further increase of applied voltage 1.2 V, lessened methane production efficiency due to high-voltage inhibition and adverse effect on DIET promotion. The anaerobic digestion coupled microbial electrolysis cells with optimal electric potential selectively promotes the DIET through polarized electrodes were confirmed through microbial analysis. As the contribution of DIET increased to 80%, the methane yield increased, and the substrate residue decreased, resulting in a significant improvement in methane production.     

Thermal and photon effects on the reaction of H2 and O2 to water over Ag–Pd/TiO2

The reaction of H₂ and O₂ to water are studied over a Ag–Pd/TiO₂ anatase catalyst, under dark and photo-irradiation conditions in the gas and liquid phases. The catalyst consisted of metal particles of mean size of ca.1 nm dispersed over 10–15 nm TiO₂ particles. Kinetic parameters including order of reaction (n), rate constant (k), and activation energy (E_a), were evaluated. E_a for the thermal reaction was found to be 49-47 kJ mol^?1. The oxidation reaction rate constant was found to be ca. 3 times higher in the presence of photons when compared to dark reaction at room temperature. The overall quantum yield of the reaction in the slurry phase was found to be 0.09. Considering the number of metal particles on TiO₂, the photon yield per metal particle was found to be 0.16. A possible explanation of the changes in kinetics with respect to experimental conditions is given.     

A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

Research and development of liquid hydrogen (LH2) temperature monitoring system for marine applications

Monitoring the temperature in liquid hydrogen (LH₂) storage tanks on ships is important for the safety of maritime navigation. In addition, accurate temperature measurement is also required for commercial transactions. Temperature and pressure define the density of liquid hydrogen, which is directly linked to trading interests. In this study, we developed and tested a liquid hydrogen temperature monitoring system that uses platinum resistance sensors with a nominal electrical resistance of approximately 1000 Ω at room temperature, PT-1000, for marine applications. The temperature measurements were carried out using a newly developed temperature monitoring system under different pressure conditions. The measured values are compared with a calibrated reference PT-1000 resistance thermometer. We confirm a measurement accuracy of ±50 mK in a pressure range of 0.1 MPa–0.5 MPa.     

Coagulation process in Manchega sheep milk from Spain: A path analysis approach

Characteristics of sheep milk are of great interest for the dairy industry, as almost the totality of production is intended for cheesemaking. However, the existing relationships between these variables are complex. This study assessed composition, hygienic quality, coagulation properties, and curd yield of 1,200 individual Manchega sheep milk samples. The aim was to compare the effect of composition and hygienic quality on coagulation and curdling, and to evaluate the relationship between curd yields and the coagulation process and the effect of other features by using path analysis methodologies. Outcomes proved path analysis to be a useful and effective tool to assess these relationships through direct and indirect paths within the same model. Results showed that the factors that had a direct influence on milk coagulation were lactose concentration, casein content, and initial pH of milk. Contrastingly, somatic cells did not seem to have any effect (direct or indirect) on the coagulation process. Factors that directly affected curd yield were fat content, lactose concentration, casein content, and curd moisture. However, technological parameters showed little effect over curd yield.     

Enhancing the Yield Stress in Liquid Polydimethylsiloxane to Allow Its 3D Printing: Hydrogels as Removable Fillers

For manufacturing parts of very soft materials by liquid deposition modeling (e.g., to mimic living soft tissues), formulations of 3D-printable polydimethylsiloxane have been developed, with the aim of increasing the yield stress of the liquid and reducing the final mechanical modulus. In the present work, suspensions of solid-like hydrogel particles, which are easily 3D-printable, are prepared in order to generate yield stress, and the suspended phase is removed after manufacturing by taking advantage of the thermo-reversibility of the hydrogel behavior, resulting in porosity, which reduces the final rigidity. The reported approach is even more efficient than a previous approach based on emulsion formulations.     

Ti-xCr-yCu钛基材料的制备及组织性能研究

通过粉末冶金法制备了Ti-xCr、Ti-yCu及Ti-xCr-yCu钛基材料,研究了Cr、Cu含量对其相组成、显微组织、压缩屈服强度、弹性模量以及切削加工性能的影响规律。结果表明:随Cr含量的增加,Ti-xCr钛基材料依次出现了Ti_4Cr、TiCr_2及Cr相,其压缩屈服强度表现出先增大后减小的趋势,当Cr含量为10%时其屈服强度达到最大值(710 MPa),同时,添加Cr元素有利于降低钛基材料的弹性模量,最低可达25 GPa。添加Cu元素的钛基材料,随Cu含量的增加,Ti_2Cu相增加,并且显微组织细化,屈服强度降低;弹性模量受Cu含量影响较小而受烧结温度影响较大。添加Cr和Cu元素的钛基材料,其显微组织主要为网篮组织,弹性模量低于纯钛,其中添加Cu元素有利于细化层片,添加Cr元素有利于细化等轴组织。此外,Cr含量为5%时,钛基材料具有较佳的切削加工性能。