The assessment of commercial beef and chicken bouillons in terms of heterocyclic aromatic amines and some of their precursors

Herein, the assessment of commercial beef and chicken bouillons in terms of heterocyclic aromatic amines (HAAs) and some of their precursors was evaluated. Creatine and creatinine levels were ranged between 0.57–0.80 and 0.28–0.94 mg g⁻¹, respectively. Glutamic acid was found to be the most abundant amino acid in both bouillons. 2-amino-3,7,8-trimethylimidazo[4,5-ƒ]quinoxaline (7,8-DiMeIQx, up to 0.03 ng g⁻¹) was the only quantified analyte in beef bouillons, whereas it (up to 0.08 ng g⁻¹) was determined in addition to 2-amino-3-methylimidazo[4,5-ƒ]quinoxaline (IQx, up to 0.08 ng g⁻¹) in chicken bouillons. Creatine, creatinine and free amino acid composition did not have the capacity to initiate the formation of HAAs. Therefore, bouillons do not pose risk in terms of HAAs. However, it should be noted that multiple factors, such as the substrate amount and production conditions, may affect the results. Glutamic acid content is remarkable in commercial bouillons sold in Turkey.     

Achieving real-time object detection and tracking under extreme conditions

In this survey, we present a brief analysis of single camera object detection and tracking methods. We also give a comparison of their computational complexities. These methods are designed to accurately perform under difficult conditions such as erratic motion, drastic illumination change, and noise contamination.     

Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells

The aim of this study is to investigate the effects of non-uniform solar irradiation distribution on energy output of different interconnected configurations in photovoltaic (PV) arrays. In order to find which configuration is less susceptible to mismatch effects, a PV module model is developed. This model can take into consideration the effects of bypass diodes and the variation of the equivalent circuit parameters with respect to operating conditions. The proposed model can provide sufficient degree of precision as well as solar cell-based analysis in analyzing large scale PV arrays without increasing the computational effort. In order to produce more reliable and robust simulations, improved and extended algorithms are presented. Some results are discussed in detail and some recommendations are extracted by testing several shading scenarios.     

A network view of business systems

In this paper, we present a novel business network construction approach, where the nodes of the network correspond to the names of the companies in a particular stock market index, and its links show the co-occurrence of two company names in daily news. Our approach consists of two phases, in which search for the company names in the news articles and network construction operations are performed, respectively. To increase the quality of results, each article is classified as business news or not business news before these operations, and only the articles that are classified as business news are considered for network construction. The resulting network presents a visualization of the business events and company relationships during the corresponding time period. We study both co-occurrences as well as single occurrences of company names in the articles scanned in our analysis.     

Electrochemical synthesis of polyindole on 304-stainless steel in LiClO4–acetonitrile solution and its corrosion performance

The use of electrochemically synthesized polyindole (PIN) film was investigated for protective coating on 304-stainless steel (SS). Polyindole was deposited via anodic oxidation of the corresponding monomer, indole in acetonitrile (ACN) solution containing LiClO₄. It provided an adherent and stable coating on SS. The corrosion performance of coated and uncoated SS was investigated in 3.5% NaCl solution using electrochemical impedance spectroscopy (EIS), anodic polarization curves and open-circuit potential–time (E_ocp–t) diagrams. These tests demonstrated that PIN coating provided important barrier effect to SS for important immersion times in aggressive medium.     

Synthesis and properties of chitosan-modified poly(vinyl butyrate)

Modification of chitosan by grafting of vinyl butyrate was carried out in homogeneous phase using potassium persulfate as redox initator and 1.5% acetic acid as solvent. The percent grafting and grafting efficiency were analysed and the high grafting efficiency up to 94% was observed. The effects of reaction variables such as monomer concentration, initiator concentration, temperature and reaction time were investigated. It was observed that the solubility of chitosan was markedly reduced after grafting with vinyl butyrate. The grafted product is insoluble in common organic solvents as well in dilute organic and inorganic acids. Characterization of the graft copolymers were carried out by using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and Scanning Electron Microscopy (SEM) technics. Characteristic signal of carbonyl group was observed at 1,731 cm⁻¹ which belongs to the poly vinyl butyrate segments in the graft copolymer. The melting transition of the chitosan main chain in the copolymer shifted to 124°C from its original value 101°C. In addition to these, we have also studied topology of the graft copolymer and the SEM micrograph showed continuous homogenous matrix which means there is no phase separation.     

Chemical,thermal, and mechanical properties and ultraviolet transmittance of novel nano-hydroxyapatite/polyethylene terephthalate milk bottles

Polyethylene terephthalate (PET)/nano-hydroxyapatite (nHAp) composite granules were obtained using twin-screw extruder. Preforms were prepared by injection molding and then PET/nHAp bottles were produced by blow molding. For PET bottles with nHAp, the migration amounts of carboxylic acid (COOH), acetaldehyde (AA), diethylene glycol (DEG), and isophthalic acid (IPA); glass transition temperature (T_g); melting temperature (T_m); and the maximum crystallization temperature (T_cry) were measured. The load-carrying capacity, burst strength, stress cracking, and regional material distribution tests were carried out on the bottles. X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, differential scanning calorimetry, and ultraviolet transmittance analyses were conducted to explain the changes in mechanical, chemical, physical properties, and light transmission of bottles. It was found out that the COOH amount increased and the AA content decreased with increasing nHAp amount. On the other hand, no change was observed in the amounts of DEG and IPA. Although the mechanical properties such as load-carrying capacity and burst strength of the bottles have improved, it has been determined that the standard environmental stress crack resistance test procedure cannot be applied to such a composite. Experimental findings indicate that nHAp disrupts the chemical structure of PET and it isolates harmful chemicals such as AA by forming intermolecular bonds. Moreover, with the addition of up to 0.8% nHAp, PET bottles block the light transmission approximately 80% within 400–700 nm wave length zone. The study demonstrates that the PET/nHAp composite bottles can be used in the food industry, particularly in the packaging of milk and milk products which are vulnerable to light exposure.     

Evolutionary design of neural network architectures: a review of three decades of research

We present a comprehensive review of the evolutionary design of neural network architectures. This work is motivated by the fact that the success of an Artificial Neural Network (ANN) highly depends on its architecture and among many approaches Evolutionary Computation, which is a set of global-search methods inspired by biological evolution has been proved to be an efficient approach for optimizing neural network structures. Initial attempts for automating architecture design by applying evolutionary approaches start in the late 1980s and have attracted significant interest until today. In this context, we examined the historical progress and analyzed all relevant scientific papers with a special emphasis on how evolutionary computation techniques were adopted and various encoding strategies proposed. We summarized key aspects of methodology, discussed common challenges, and investigated the works in chronological order by dividing the entire timeframe into three periods. The first period covers early works focusing on the optimization of simple ANN architectures with a variety of solutions proposed on chromosome representation. In the second period, the rise of more powerful methods and hybrid approaches were surveyed. In parallel with the recent advances, the last period covers the Deep Learning Era, in which research direction is shifted towards configuring advanced models of deep neural networks. Finally, we propose open problems for future research in the field of neural architecture search and provide insights for fully automated machine learning. Our aim is to provide a complete reference of works in this subject and guide researchers towards promising directions.