Effect of starter cultures on properties of soft white cheese made from camel (Camelus dromedarius) milk

This experiment was conducted to investigate the effect of starter cultures on the physicochemical properties, texture, and consumer preferences of soft white cheese (SWC) made from camel (Camelus dromedarius) milk. The experiment was laid out in a completely randomized design with 5 treatments [starter cultures; i.e., 1 thermophilic (STI-12), 2 blended (RST-743 and XPL-2), and 2 mesophilic (R-707 and CHN-22) cultures]. Starter cultures STI-12 and RST-743 were inoculated at 37°C, whereas XPL-2, R-707, and CHN-22 were inoculated at 30°C. Camel milk inoculated using STI-12 and RST-743 cultures resulted in faster acidification than XPL-2, R-707, and CHN-22 cultures. Camel milk SWC made using STI-12 and CHN-22 cultures gave lower pH (4.54) and titratable acidity (0.59), respectively, whereas R-707 culture resulted in high cheese yield (13.44 g/100 g). In addition, high fat (20.91 g/100 g), protein (17.49 g/100 g), total solids (43.44 g/100 g), and ash (2.40 g/100 g) contents were recorded for SWC made from camel milk made using RST-743 culture. Instrumental analysis of cheese texture revealed differences in resistance to deformation in which camel milk SWC made using RST-743 culture gave higher firmness (3.20 N) and brittleness (3.12 N). However, no significant difference was observed among camel milk SWC adhesiveness made using different starter cultures. Consumer preference for appearance, aroma, taste, and overall acceptances of SWC were affected by inoculation of starter cultures. Considering curd firmness, cheese yield, compositional quality, and textures using STI-12, RST-743, and R-707, these cultures were found to be better for the manufacture of camel milk SWC.     

Asymptotic results for Fourier‐PARMA time series

Periodically stationary times series are useful to model physical systems whose mean behavior and covariance structure varies with the season. The Periodic Auto‐Regressive Moving Average (PARMA) process provides a powerful tool for modelling periodically stationary series. Since the process is non‐stationary, the innovations algorithm is useful to obtain parameter estimates. Fitting a PARMA model to high‐resolution data, such as weekly or daily time series, is problematic because of the large number of parameters. To obtain a more parsimonious model, the discrete Fourier transform (DFT) can be used to represent the model parameters. This article proves asymptotic results for the DFT coefficients, which allow identification of the statistically significant frequencies to be included in the PARMA model.     

Fingerprint‐Inspired Conducting Hierarchical Wrinkles for Energy‐Harvesting E‐Skin

In the field of bionics, sophisticated and multifunctional electronic skins with a mechanosensing function that are inspired by nature are developed. Here, an energy‐harvesting electronic skin (energy‐E‐skin), i.e., a pressure sensor with energy‐harvesting functions is demonstrated, based on fingerprint‐inspired conducting hierarchical wrinkles. The conducting hierarchical wrinkles, fabricated via 2D stretching and subsequent Ar plasma treatment, are composed of polydimethylsiloxane (PDMS) wrinkles as the primary microstructure and embedded Ag nanowires (AgNWs) as the secondary nanostructure. The structure and resistance of the conducting hierarchical wrinkles are deterministically controlled by varying the stretching direction, Ar plasma power, and treatment time. This hierarchical‐wrinkle‐based conductor successfully harvests mechanical energy via contact electrification and electrostatic induction and also realizes self‐powered pressure sensing. The energy‐E‐skin delivers an average output power of 3.5 mW with an open‐circuit voltage of 300 V and a short‐circuit current of 35 µA; this power is sufficient to drive commercial light‐emitting diodes and portable electronic devices. The hierarchical‐wrinkle‐based conductor is also utilized as a self‐powered tactile pressure sensor with a sensitivity of 1.187 mV Pa^‐1 in both contact‐separation mode and the single‐electrode mode. The proposed energy‐E‐skin has great potential for use as a next‐generation multifunctional artificial skin, self‐powered human–machine interface, wearable thin‐film power source, and so on.     

Vertical Heterophase for Electrical,Electrochemical, and Mechanical Manipulations of Layered MoTe2

Phase engineering is a breakthrough for various electronic and energy device applications with transition metal dichalcogenides (TMDs). Chemical methods, such as lithium intercalation, are mostly used for phase engineering, which achieves atomically thin flakes and high catalytic performances in several group 6 TMDs including MoS₂. However, chemical methods cannot be applied to MoTe₂, a widely investigated group 6 TMD with intriguing semiconducting, topological, and catalytic properties. The lack of modifying MoTe₂ by chemical methods remains a puzzling issue considering the small energy difference between the polymorphs of MoTe₂. Here, a convection‐assisted lithium ion intercalation and phase transition is reported to achieve a vertical heterophase in a MoTe₂ crystal. The vertical heterophase in MoTe₂ reduces the Schottky barrier with metal electrodes down to 66 meV, enhancing the overall ion conductance for electrochemical hydrogen production. Moreover, the weakened adhesion of the 1T' phase layers on the top and bottom surfaces in the vertical heterophase, formed by the intercalation, enables a unique surface tension‐driven exfoliation of MoTe₂ flakes. The heterophase chemical engineering suggests a new platform for hybrid catalysts and next‐generation electronic devices based on 2D materials.     

Model Induction with Support Vector Machines: Introduction and Applications

The rapid advance in information processing systems in recent decades had directed engineering research towards the development of intelligent systems that can evolve models of natural phenomena automatically—“by themselves,” so to speak. In this respect, a wide range of machine learning techniques like decision trees, artificial neural networks (ANNs), Bayesian methods, fuzzy-rule based systems, and evolutionary algorithms have been successfully applied to model different civil engineering systems. In this study, the possibility of using yet another machine learning paradigm that is firmly based on the theory of statistical learning, namely that of the support vector machine (SVM), is investigated. An interesting property of this approach is that it is an approximate implementation of a structural risk minimization (SRM) induction principle that aims at minimizing a bound on the generalization error of a model, rather than minimizing only the mean square error over the data set. In this paper, the basic ideas underlying statistical learning theory and SVM are reviewed, and the potential of the SVM for feature classification and multiple regression (modeling) problems is demonstrated by applying the method to two different cases of model induction from empirical data. The relative performance of the SVM is then analyzed by comparing its results with that of ANNs on the same data sets.     

The influence of apolipoprotein e genotype on visuospatial attention dissipates after age 80.

Although it is established that apolipoprotein E (APOE) e4 allele increases the risk of Alzheimer's disease (AD), epidemiological studies indicate that genetic risk decreases late in life. This raises the question of whether the effects of APOE on cognition that are seen in midlife arise from a cognitive phenotype of APOE or from the presence of early AD in some APOE-e4 carriers. The authors addressed this question by comparing the cognitive consequences of variation in the APOE gene between individuals over the age of 80 (old-old) and middle-aged and young-old individuals. A spatially cued discrimination paradigm--previously shown to be sensitive to AD and to APOE genotype--required a speeded categorization of a target letter following cues that were valid, invalid, or neutral in predicting target location. Results revealed greater costs of invalid cues in the APOE-e4 carriers of middle-aged and young-old, but not old-old, groups. The dissipation of the APOE effect in old-old individuals at lower risk of AD suggests that visuospatial attention impairments seen as early as midlife in APOE-e4 carriers may be a preclinical marker of AD. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluation of cerebral blood flow and hemodynamic reserve in symptomatic moyamoya disease using stable Xenon-CT blood flow

Moyamoya disease is a vascular abnormality seen in children and adults characterized by progressive narrowing of the internal carotid, middle, anterior, and posterior cerebral arteries and the development of leptomeningeal and proximal internal carotid artery collaterals, which appear diaphanous on angiogram. Although adults tend to present with subarachnoid hemorrhage and children with ischemic events, the clinical sequelae in these two populations overlap. Expanding upon work done at this institution using stable xenon computer tomographic blood flow determinations with acetazolamide and carbon dioxide challenge to predict which population of patients with severe carotid disease and hemodynamic compromise would benefit from surgical intervention, we used similar rationale to determine which patients with moyamoya disease would likely benefit from revascularization. Data and outcome concerning four such patients make up the body of this report.     

Einsatz eines Ultraschall‐Durchflussmessgerätes zur Regelung des Volumenstroms in der Hochgradienten‐Magnetseparation

Within the application of high‐gradient magnetic separation (HGMS) in bioprocess engineering, peristaltic pumps are usually used for fluid transport. If the pump rotates with a constant revolution speed, the flow rate through the HGMS filter descends. This is because the free flow cross section decreases with increasing filter loading. As a result the particle loading of the HGMS filter does not occur constantly. In this work an ultrasonic flow meter was tested for the dynamic adjustment of the revolution speed, in order to stabilize the flow rate during magnetic separation.