Physical and sensory properties of lemon-flavored acidic beverages formulated with nonfat dry milk during storage

Sensory and physical properties of 2 lemon-flavored beverages with 5% and 7.5% wt/wt nonfat dry milk (NFDM) at pH 2.5 were studied during storage. The 2 beverages had similar volatile compounds, but the 5% NFDM had higher aroma and lemon flavor, with a preferred appearance by consumers due to the lower turbidity and viscosity. After 28 d of storage at 4°C, lemon flavor decreased in the 5% NFDM beverage but was still more intense than the 7.5% one. During 70 d of storage, no microorganisms were detected, and the beverages were more stable when stored at 4°C than at room temperature according to changes of physical properties measured for appearance, turbidity, color, particle size, zeta potential, rheological properties, and transmission electron microscopy morphology. Findings of the present study suggest that NFDM may be used at 5% wt/wt to produce stable acidic dairy beverages with low turbidity when stored at 4°C.     

Probabilistic learning on manifolds (PLoM) with partition

The probabilistic learning on manifolds (PLoM) introduced in 2016 has solved difficult supervised problems for the “small data” limit where the number N of points in the training set is small. Many extensions have since been proposed, making it possible to deal with increasingly complex cases. However, the performance limit has been observed and explained for applications for which N is very small and for which the dimension of the diffusion-map basis is close to N. For these cases, we propose a novel extension based on the introduction of a partition in independent random vectors. We take advantage of this development to present improvements of the PLoM such as a simplified algorithm for constructing the diffusion-map basis and a new mathematical result for quantifying the concentration of the probability measure in terms of a probability upper bound. The analysis of the efficiency of this extension is presented through two applications.     

New food safety challenges of viral contamination from a global perspective: Conventional,emerging, and novel methods of viral control

Food- and waterborne viruses, such as human norovirus, hepatitis A virus, hepatitis E virus, rotaviruses, astroviruses, adenoviruses, and enteroviruses, are major contributors to all foodborne illnesses. Their small size, structure, and ability to clump and attach to inanimate surfaces make viruses challenging to reduce or eliminate, especially in the presence of inorganic or organic soils. Besides traditional wet and dry methods of disinfection using chemicals and heat, emerging physical nonthermal decontamination techniques (irradiation, ultraviolet, pulsed light, high hydrostatic pressure, cold atmospheric plasma, and pulsed electric field), novel virucidal surfaces, and bioactive compounds are examined for their potential to inactivate viruses on the surfaces of foods or food contact surfaces (tools, equipment, hands, etc.). Every disinfection technique is discussed based on its efficiency against viruses, specific advantages and disadvantages, and limitations. Structure, genomic organization, and molecular biology of different virus strains are reviewed, as they are key in determining these techniques effectiveness in controlling all or specific foodborne viruses. Selecting suitable viral decontamination techniques requires that their antiviral mechanism of action and ability to reduce virus infectivity must be taken into consideration. Furthermore, details about critical treatments parameters essential to control foodborne viruses in a food production environment are discussed, as they are also determinative in defining best disinfection and hygiene practices preventing viral infection after consuming a food product.     

Sustainable phenolic thermosets coatings derived from urushiol

The over-exploitation of finite fossil resources and/or the increased environmental and sustainable awareness inspire scientists and technologists to search for inexpensive alternatives from renewable chemicals. Phenol formaldehyde (PF) resins, the oldest type of synthetic polymers with good mechanical properties and heat resistance, are widely used in the production of coatings, laminates, molding compositions, and glues. Here, biobased urushiol-derived PF resins were synthesized from the alkali-catalyzed reaction between urushiol and formaldehyde. The chemical compositions and molecular structures of resole resins were characterized by carbon-13 nuclear magnetic resonance and Fourier transform infrared spectroscopy, and their curing behaviors were studied by differential scanning calorimetry. The as-prepared urushiol-derived resole resins had methylol (Ph−CH₂OH), ortho- and para-hemiformal groups (Ph−CH₂OCH₂OH), and the para−para/ortho−para/ortho−ortho links of methylene groups (Ph−CH₂−Ph), whereas the resole resins had low curing temperatures at about 100–113°C. Additionally, given the long side alkyl group moiety on the aromatic rings of urushiol, the films of cured urushiol-derived resole resins had low glass transition temperatures of 132 ± 2°C. Furthermore, the as-prepared urushiol-derived coatings exhibited excellent physical and mechanical properties.     

Various density light field image coding based on distortion minimization interpolation

In recent years, the light field (LF) as a new imaging modality has attracted wide interest. The large data volume of LF images poses great challenge to LF image coding, and the LF images captured by different devices show significant differences in angular domain. In this paper we propose a view prediction framework to handle LF image coding with various sampling density. All LF images are represented as view arrays. We first partition the views into reference view (RV) set and intermediate view (IV) set. The RVs are rearranged into a pseudo sequence and directly compressed by a video encoder. Other views are then predicted by the RVs. To exploit the four dimensional signal structure, we propose the linear approximation prior (LAP) to reveal the correlation among LF views and efficiently remove the LF data redundancy. Based on the LAP, a distortion minimization interpolation (DMI) method is used to predict IVs. To robustly handle the LF images with different sampling density, we propose an Iteratively Updating depth image based rendering (IU-DIBR) method to extend our DMI. Some auxiliary views are generated to cover the target region and then the DMI calculates reconstruction coefficients for the IVs. Different view partition patterns are also explored. Extensive experiments on different types LF images also valid the efficiency of the proposed method.     

Repurposing fish waste into gelatin as a potential alternative for mammalian sources: A review

Mammalian gelatin is extensively utilized in the food industry because of its physicochemical properties. However, its usage is restricted and essentially prohibited for religious people. Fish gelatin is a promising alternative with no religious and social restrictions. The desirable properties of fish gelatin can be significantly improved by various methods, such as the addition of active compounds, enzymes, and natural crosslinking agents (e.g., plant phenolics and genipin), and nonthermal physical treatments (e.g., ionizing radiation and high pressure). The aim of this study was to explore whether the properties of fish gelatin (gel strength, melting or gelling temperature, odor, viscosity, sensory properties, film-forming ability, etc.) could be improved to make it comparable to mammalian gelatin. The structure and properties of gelatins obtained from mammalian and fish sources are summarized. Moreover, the modification methods used to ameliorate the properties of fish gelatin, including rheological (gelling temperature from 13–19°C to 23–25°C), physicochemical (gel strengths from ∼200 to 250 g), and thermal properties (melting points from ∼25 to 30°C), are comprehensively discussed. The relevant literature reviewed and the technological advancements in the industry can propel the development of fish gelatin as a potential alternative to mammalian gelatin, thereby expanding its competitive market share with increasing utility.     

Immiscible PHB/PBS and PHB/PBSA blends: morphology,phase composition and modelling of elastic modulus

This paper reports the thermal, morphological and mechanical properties of environmentally friendly poly(3-hydroxybutyrate) (PHB)/poly(butylene succinate) (PBS) and PHB/poly[(butylene succinate)-co-(butylene adipate)] (PBSA) blends, prepared by melt mixing. The blends are known to be immiscible, as also confirmed by the thermodynamic analysis here presented. A detailed quantification of the crystalline and amorphous fractions was performed, in order to interpret the mechanical properties of the blends. As expected, the ductility increased with increasing PBS or PBSA amount, but in parallel the decrease in the elastic modulus appeared limited. Surprisingly, the elastic modulus was found properly described by the rule of mixtures in the whole composition range, thus attesting mechanical compatibility between the two blend components. This unusual behavior has been explained as due to co-continuous morphology, present in a wide composition range, but also at the same time as the result of shrinkage occurring during sequential crystallization of the two components, which can lead to physical adhesion between matrix and dispersed phase. For the first time, the elastic moduli of the crystalline and mobile amorphous fractions of PBS and PBSA and of the mobile amorphous fraction of PHB at ambient temperature have been estimated through a mechanical modelling approach. © 2021 The Authors. Polymer International published by John Wiley & Sons Ltd on behalf of Society of Industrial Chemistry.     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Packet loss detection in networked control systems

One of the main issues related to the reliable operation of network control systems concerns the design of mechanisms able to detect anomalies in the functioning of the communication network through which the control loops are closed. In this article, we address the problem of detecting the occurrence of packet losses and design a mechanism that can detect the occurrence of packet losses directly from process sensor data. Specifically, we propose a moving‐horizon estimation scheme that permits to detect if the packet‐loss rate exceeds prescribed thresholds, which are representative of stability and performance of the control system. We discuss theoretical properties of the proposed solution along with an approximation scheme with reduced computational burden. A numerical example is discussed to substantiate the analysis.     

煤样多元物性参数在煤与瓦斯突出防治中的应用研究

煤与瓦斯突出是一种复杂的动力现象，突出的类型不同、引起突出的危险因素不同，预测指标对其的敏感性也就不同，选择适应的突出危险性预测敏感指标及突出敏感指标的临界值，研究可靠的突出预测手段和方法来实现对突出危险性的准确预测，是指导突出防治工作的重要技术基础，而为了获得突出敏感指标的临界值就必须对煤的多元物性参数进行实验研究，掌握煤层的各项物化性质，是有效确定防治突出方法体系的关键基础。