Zein-based anti-browning cling wraps for fresh-cut apple slices

The usage of cling wraps is emerging as an easy and cost-effective approach to protect fresh-cut fruits and vegetables from dust, whilst improving visual appeal on retail counters. This study focused on developing an alternate, protein-based packaging material as a food grade cling wrap for food packaging applications. Zein-based cling wraps were produced, and their physical and mechanical characteristics were evaluated and compared with conventionally used chitosan biopolymer films and commercial synthetic polymer films. Antioxidant potential of the prepared films was studied, and the effectiveness of the developed films as anti-browning cling wraps was evaluated using studies conducted on fresh-cut apple slices at ambient conditions. Anti-browning effects were in par with polymeric counterparts; however, zein cling wraps could better prevent weight loss in apple slices. Zein-based films can be adopted as biodegradable food grade cling wraps as an alternative to chitosan and synthetic polymeric materials.     

A visual tool for computer supported learning: The robot motion planning example

We introduce an effective computer aided learning visual tool (CALVT) to teach graph-based applications. We present the robot motion planning problem as an example of such applications. The proposed tool can be used to simulate and/or further to implement practical systems in different areas of computer science such as graphics, computational geometry, robotics and networking. In the robot motion planning example, CALVT enables users to setup the working environment by creating obstacles and a robot of different shapes, specifying starting and goal positions, and setting other path or environment parameters from a user-friendly interface. The path planning system involves several phases. Each of these modules is complex and therefore we provide the possibility of visualizing graphically the output of each phase. Based on our experience, this tool has been an effective one in classroom teaching. It not only cuts down, significantly, on the instructor’s time and effort but also motivates senior/graduate students to pursue work in this specific area of research.     

Synthesis and characterization of electrically conducting copolymer of aniline and o‐bromoaniline using methane sulfonic acid as dopant

Polyaniline (PAN), poly(o‐bromoaniline) (POBA), and poly(aniline‐co‐o‐bromoaniline) (PABA) were synthesized by oxidative coupling. These polymers are protonated by 10–20% methane sulfonic acid (MSA) and 1M HCl. The new polymer bases have greater solubility than that of PAN in common polar organic solvents; PAN–MSA was observed to be the most thermally stable of these polymers. POBA is associated with residual quinoid diimine units as illustrated in the IR and UV‐vis spectra, after reduction with hydrazine dihydrochloride. Both the doping agents cause a downward shift of the quinoid absorption in the IR spectra. MSA‐ and HCl‐doped PAN and PABA polymers exhibit a coil‐like conformation in DMSO, whereas only MSA‐doped PAN and PABA show an “expanded coil‐like” conformation in m‐cresol with a “free carrier tail” above 800 nm in their electronic spectra. XPS spectra indicated the presence of covalent bromine in the POBA and PABA polymers. Bromine retention was greater in the homopolymer as evidenced by the IR studies after aging at 350°C. Compared to HCl, MSA is found to be a more effective dopant, enhancing the conductivity of the copolymers by 10²–10³ times in magnitude. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2662–2669, 2002     

Developing human factors/ergonomics as a design discipline

This paper deals with internal challenges that the human factors/ergonomics (HFE) research faces when wishing to strengthen its contribution to development of work systems. Three established characteristics of high-quality HFE, i.e., HFE takes a systems approach, HFE is design-driven, and HFE focuses on two closely related outcomes, performance and well-being, are taken as a starting point of a methodological discussion, in which conceptual innovations, e.g. adopting the technology-in-use perspective, are proposed to support development of HFE towards the high-quality aims. The feasibility of the proposed conceptual choices is demonstrated by introducing a naturalistic HFE analysis approach including four HFE functions. The gained experience of the use of this approach in a number of complex work domains allows the conclusion that becoming design-driven appears as that most difficult quality target for HFE to reach. Creating an own design discipline identity in a multi-voiced collaboration is the key internal challenge for human factors/ergonomics.     

Generalizing Multi-agent Graph Exploration Techniques

International Journal of Control, Automation and Systems - The system of multiple agents working in coordination for a given task has several advantages on faster completion, fault-tolerance, etc....     

An International Collaborative Study on Trypsin Inhibitor Assay for Legumes,Cereals, and Related Products

For determining trypsin inhibitor activity (TIA) in soy products, the American Oil Chemists' Society (AOCS) Method Ba 12-75 has been used. It measures differences in absorbance at 410 nm of bovine trypsin activity toward a synthetic substrate (Nα-benzoyl-DL-arginine-p-nitroanilide) in the absence and presence of an inhibitor. Recently, a significantly improved method was developed (JAOCS, 2019, 96:635–645), featuring 5 mL of total assay volume, enzyme-last sequence, and single inhibitor level in duplicate. It is proposed as the AOCS Method Ba 12a-2020. As a part of the AOCS method approval process, a collaborative study involving 12 international laboratories was conducted to evaluate the performance of the proposed method. The study involved measuring TIA in 10 selected test samples plus a blind duplicate. They included soybeans, pulses, cereals, and their processed products (flours, concentrates, and isolates). After rigorous statistical treatment of the data, only three outliers were removed from the data of two samples. Repeatability relative standard deviations (RSDr) for the 11 samples ranged from 0.99% to 5.52%. Reproducibility RSD (RSD_R) ranged from 7.07% to 22.92%, with seven samples having RSD_R around 10% or less. The remaining four samples had very low TIA, and their RSD_R values ranged from 13.34% to 22.92%. The study has demonstrated reliable performance of the proposed AOCS method. Several collaborators carried out additional experiments addressing some aspects of the method, leading to further refinements. The proposed method is undergoing evaluation by the AOCS Uniform Methods Committee for adoption as an Official Method for measuring TIA in various legume and grain products.     

Imagined community and death

This paper addresses the limits of net discourse in virtual communities. I will analyse incidents of death that shattered the 'rhetorical vision' of one particular virtual community, Xena: Warrior Palace. The observations will trace some characteristics of the community's vision of itself, how vulnerable that vision can be and how it can be maintained or revised after some unexpected occurrence shatters it. I argue that even though the rhetorical vision of virtual community can be imagined, it has to stay in touch with the 'real world' in order to have real influence on constructed online culture.     

Mammogram Learning System for Breast Cancer Diagnosis Using Deep Learning SVM

The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces system complexity. The softmax layer in VGG assumes that the training samples belong to exactly only one class, which is not valid in a real situation, such as in medical image diagnosis. To overcome this situation, SVM is employed instead of the softmax layer in VGG. Data augmentation is also employed as DLA usually requires a large number of samples. VGG model with different SVM kernels is built to classify the mammograms. Results show that the VGG-SVM model has good potential for the classification of Mammographic Image Analysis Society (MIAS) database images with an accuracy of 98.67%, sensitivity of 99.32%, and specificity of 98.34%.