Nutritional Content and Health Profile of Single-Serve Non-Dairy Plant-Based Beverages

A growing number of people are seeking a non-dairy plant-based beverage both for their personal health, and for the health of the planet. The aim of this study was to conduct a cross-sectional survey of single-serve plant-based beverages to assess their nutritional content and health profile. A total of 51 non-dairy plant-based beverages were analyzed from the nutrition label listed on the commercial package. The various beverages contained extracts of soy (n = 14), almonds (n = 13), oats (n = 12), peas (n = 7), banana (n = 2), coconut (n = 2), and rice (n = 1). Almost one-half (45%) of the single-serve beverages had 5 g or more of protein/serving. A total of 75% and 65% of the single-serve beverages had calcium and vitamin B12 levels, respectively, fortified to at least 20% of the Daily Value (DV), while only 28% had vitamin D fortification at the 20% DV level. Two-thirds of the single-serve beverages had high sugar levels, while 39% were low in sodium, 63% were low in fat, and 96% were low in saturated fat. The single-serve plant-based beverages had more protein, calcium, vitamin B12, and sugar but less fat than the non-dairy, multi-serve plant-based beverages/ serving. A limited number of single-serve beverages met the requirements of school meal programs.

Nutritional Content and Health Profile of Non-Dairy Plant-Based Yogurt Alternatives

Yogurt is considered a healthy, nutritious food in many cultures. With a significant number of people experiencing dairy intolerance, and support for a more sustainable diet, consumer demand for dairy alternatives has surged. The aim of this study was to conduct a cross-sectional survey of plant-based yogurt alternatives to assess their nutritional content and health profile. A total of 249 non-dairy yogurt alternatives were analyzed from the nutrition label listed on the commercial package. The various yogurt alternatives contained extracts of coconut (n = 79), almonds (n = 62), other nuts or seeds (n = 20), oats (n = 20), legumes (n = 16), and mixed blends (n = 52). At least one-third of the yogurt alternatives had 5 g or more of protein/serving. Only 45% of the yogurt alternatives had calcium levels fortified to at least 10% of daily value (DV), while only about one in five had adequate vitamin D and B12 fortification at the 10% DV level. One-half of the yogurt alternatives had high sugar levels, while 93% were low in sodium. Except for the coconut-based products, the yogurts were not high in fat or saturated fat. The yogurt alternatives were not fortified as frequently or to the same levels as the corresponding non-dairy, plant-based beverages.

THEORETICAL STUDY FOR REDESIGN OF AN AGRICULTURAL PACKAGE APPLYING ECODESIGN STRATEGIES AND CAD/CAE TOOLS

Plastic waste derived from the packaging industry currently represents an important environmental problem. Therefore, it is necessary for product designers and engineers to become aware of this fact and seek to incorporate the environmental vector when designing, redesigning, and developing containers and packaging, so that they are more sustainable and eco-effectiveness. Starting from this premise, the following objectives have been proposed in this work: (1) study and identification of possible Ecodesign strategies to apply to an existing agricultural package (model used in the collection and distribution of fruit and vegetable products); (2) to propose a redesign of the package studied, applying the information and knowledge obtained previously; (3) comparative analysis between the existing (commercial) package and the redesign proposal developed. In order to respond to this approach, work has been carried out with CAD/CAE tools (SolidWorks 3D CADTM software). The results obtained from the case study developed in this work indicate that the application of CAD/CAE tools supported by the proposed Ecodesign strategies can be a very useful and effective instrument in the design and development of this type of packaging, for practical application in the agro-food and packaging industry, which can facilitate in the short to medium term the transition to a circular economy model, based on the "Cradle to Cradle" concept.

Selecting a Mix of Dispatching Rules for a Job Shop by Using Artificial Neural Networks

Dispatching rules are a popular and commonly researched technique for scheduling tasks in job shops. Much of the past research has looked at the performance of various dispatching rules when a single rule is applied in common to all machines. However, better schedules can frequently be obtained if the machines are allowed to use different rules from one another. This research investigates an intelligent system that selects dispatching rules to use on each machine in the shop, based on a statistical description of the routings, processing times and mix of the jobs to be processed. Randomly generated problems are scheduled using permutations of three different dispatching rules on five machines. A neural network is then trained by using a commercial package to associate the statistical description of each problem with its best solution. Once trained, a network is able to recommend for new problems a dispatching rule to use on each machine. Two networks were trained separately for minimizing makespan and the total flowtime in the job shop. Test results showed that the combination of dispatching rules suggested by the trained networks produced better results for both objectives than the alternative of using the one identical rule on all machines.

Selecting a Mix of Dispatching Rules for a Job Shop by Using Artificial Neural Networks

Dispatching rules are a popular and commonly researched technique for scheduling tasks in job shops. Much of the past research has looked at the performance of various dispatching rules when a single rule is applied in common to all machines. However, better schedules can frequently be obtained if the machines are allowed to use different rules from one another. This research investigates an intelligent system that selects dispatching rules to use on each machine in the shop, based on a statistical description of the routings, processing times and mix of the jobs to be processed. Randomly generated problems are scheduled using permutations of three different dispatching rules on five machines. A neural network is then trained by using a commercial package to associate the statistical description of each problem with its best solution. Once trained, a network is able to recommend for new problems a dispatching rule to use on each machine. Two networks were trained separately for minimizing makespan and the total flowtime in the job shop. Test results showed that the combination of dispatching rules suggested by the trained networks produced better results for both objectives than the alternative of using the one identical rule on all machines.

Wave Analysis for In-Plane Vibration of Angular and Curved Frames

In many structural applications like bridges, arches, etc., frames are used, and it is important to study their dynamic behavior. Finite element method (FEM) is usually used for computational simulation of vibration for such frame structures. However, FEM simulations for high frequency are computationally intensive and lack accuracy. This paper proposes a wave propagation-based approach for the vibration analysis of a frame having angular and curved joints. The reflection and transmission matrices for the joints are derived using the kinematic compatibility and equilibrium conditions. Reflection, transmission, and propagation matrices are assembled leading to matrix equation terms of the wave amplitudes. Modal analysis and harmonic analysis of frames having curved and angular joints are performed using the present formulation. The frequency response function for point harmonic forcing acting on such structures is also presented. The formulation and the results are non-dimensionalized for wider applicability. The results obtained using the present formulation are compared with those obtained through FEM simulation in a commercial package. It is found that the results obtained using the two methods are in excellent correlation. The computational efficiency of the present method over FEM simulation is also reported.

Comparison of Jet Pump Numerical Calculation Results in ANSYS and Openfoam CFD Packages

Currently, among the most popular computational fluid dynamics software packages are commercial CFD packages – ANSYS CFX, ANSYS Fluent, STAR-CCM+ and several others. In contrast to the above-mentioned commercial CFD packages, there is an OpenFOAM, a non-commercial, freely distributed, integrated platform for numerical modeling of solid-state mechanics tasks (including CFD tasks), and it is becoming more and more popular. In addition to being a non-commercial package, OpenFOAM also has open-source code, which allows users to write their own algorithms for solving highly specialized tasks. A comparison of ANSYS and OpenFOAM in the application to CFD problems of incompressible turbulent flow in this article is given by the example of jet pump calculation, which was tested in the Laboratory of Hydraulic Machinery of Peter the Great St.Petersburg Polytechnic University.

OPTIMIZATION OF INTEGRATED PRODUCTION MODEL CALCULATIONS

The article discusses a new technique for optimizing the calculations of the integrated model, all stages of the calculations are analyzed. The analysis of the necessary input data for the integrated model is carried out and the definition of the calculation results according to the obtained method is given. Comparison of calculations using the developed method and a commercial package is obtained. Opportunities for applying the obtained solution are proposed.

A Simple Mechanistic Model Used For Tool Wear in Turning AISI 4340 Steel

Determining correct tool life is a key to efficient machining, which makes tool wear extremely important. Development of new and exotic tool materials like ceramics, carbides, nitrides, cermet, diamonds, etc. has intensified research activities in the area of modeling and optimization of turning process. Building an ideal theoretical model is considerably complex because of involvement of multiple physics and absence of readily available data on material property. This paper describes an attempt of building a simple mechanistic model for turning AISI 4340 steel by an uncoated carbide insert using a commercial package ABAQUS/CAE. The tool wear rate is computed using USUI’s wear model on the results found after running simulation. The predicted tool wear data were found in close agreement with the experimental findings.