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Yogurt is one of the most widely consumed fermented products obtained from milk that has a positive effect on health due to its high nutritional value. Yogurt enrichment can play a major role in the developmentof consumers’ health level. Spirulina platensisis a blue-green microalga and is rich in protein, essential fatty acids, vitamins, minerals and antioxidant compounds, such as phycocyanin. The aim of the present study was to investigate the effect of phycocyanin extracted from S. platensis and persimmon powder on physicochemical and sensory characteristics of yogurt. For this purpose, the yoghurt samples were analyzed for their physicochemical characteristics. Samples without persimmon powder and containing higher amounts of phycocyanin (1% and 1.5%) had the highest acidity. The acidity values of all samples increased over time. The highest pH belonged to the control sample and the addition of different amounts of phycocyanin and persimmon powder caused a significant reduction in pH.In all time intervals, with the increase of persimmon powder and phycocyanin, the syneresis rate of samplesincreased though it was not significant compared to the control sample. Samples containing higher amounts of persimmon powder (codes 6 and 7) had higher dry matter, protein, and water holding capacity (WHC).On both studied days, the highest and the lowest viscosity belonged to treatment code 7 andcode 2, respectively (p≤0.05). Additionally, the viscosity of all treatments increased significantly from the first day to the fifteenth day over time (p≤0.05). The control sample had the highest lightness (L* ) and the treatment code 8 had the highest redness (a * ‌). In all time intervals, the highest hardness and springiness belonged to the control sample (p≤0.05). The results of sensory evaluation of the samples showed that on the first day, the color score of the control sample and treatment codes 5, 6 and 7 was significantly higher than other treatments (p≤0.05). On all days studied, the taste scores of the control sample and treatment codes 5 and 6 and the texture score of the control sample and treatment codes 6, 7, and 8 were significantly higher than other treatments (p≤0.05).Considering the sensory evaluation and protein content of the yogurt samples, treatment code 6 was selected as the best treatment. The results showed that phycocyanin extracted from S. platensis and persimmon powder is effective on the physicochemical and sensory properties of yogurt and can be used as an effective additive.

Nonionic lactose fatty acid esters are a class of synthetic biosurfactants with various uses in the food, pharmaceutical, personal care, and cosmetic industries. The objective of this research was the preparation and full characterization of a series of novel metallic encapsulated magnetic core/dendrimer shell composites as catalysts (Co

The proven power of Knowledge Graphs (KGs) to effectively represent lexical and semantic information about numerous and heterogeneous entities and their interconnectedness has led to the growing recognition of their potential in engineering disciplines. Meanwhile, a greater focus has been placed on graph embedding techniques to derive dense vector representations of KGs. Such representations could enable the use of conventional machine learning techniques over the content of KGs. However, in the context of building engineering, the quality of the graph embeddings could be problematic, mainly due to the relatively small size of the KGs that are created for individual buildings. This paper aims to investigate the effectiveness of applying KG embedding methods when the elements of the building are described narrowly within the KG. The results of our experiments confirm that proper use of data transformation techniques can significantly improve the quality of the feature representation for downstream tasks.

In this study, the effect of replacing sucrose with fructose as well as carrageenan gum with maltodextrin and using lactose to produce sweetened condensed milk as a high-consumption dairy dessert was investigated. Physicochemical, microstructural, microbial, and sensory parameters including acidity, pH, viscosity, particle size, color, total viable count (TVC), mold and yeast, odor, taste, color, texture, and overall acceptability were evaluated during the 30-day storage period. The results demonstrated that with increasing the level of maltodextrin and fructose replacement, the acidity, particle size, organoleptic scores, redness and yellowness increased, and the pH, viscosity, and lightness in the product decreased (p

The demand for consuming low‐fat or nonfat dairy products, especially fat‐free yoghurt, has increased considerably because of the effects of high‐fat diet on human health during the two past decades. Generally, consumers prefer low‐fat products to the same high‐fat products. For this reason, manufacturers are looking for an ideal source for replacing fat substitute. In this research, the effect of grape seed oil (GSO) as a fat replacement on different quality attributes of the produced set yoghurt was determined. The effect of diverse ratios (3:0, 1.5:1.5, and 0.5:3%) of milk fat and GSO on the change in the quality attributes of the set yoghurt for up to 22 days of refrigeration period (4 ± 1°C) was investigated. Statistical analysis revealed that increase in GSO concentration leads to a significant increase (p, The use of GSO affected the textural properties and further increased the hardness in set yoghurt containing 3% (w/w) fat replacement. The yoghurt sample viscosity was strongly affected by the total solids content and GSO concentration.

The texture, colour and sensory properties of non-fat yoghurts prepared with different tara gum concentrations (0.25, 0.50 and 1.0 gL-1) and different tara gum (TG) with buttermilk powder (BP) combinations (0.25+10, 0.50+10 and 1.0+10 gL-1) were investigated during storage. While addition of 0.25 and 0.50 gL-1 of tara gum caused an increase in firmness, consistency, cohesiveness, viscosity index of yoghurt samples, use of 1 gL-1 of tara gum and combinations of tara gum with buttermilk powder led to a decrease in these properties. During the storage period, increasing the concentration of tara gum resulted in significant decrease in L* and a* values, significant increase in b* value in yoghurt. Sensory properties of non-fat yoghurts supplemented with 0.25 and 0.50 gL-1 did not significantly differ from those of control yoghurts. In contrast, use of 1 gL-1 of tara gum and combinations of tara gum and buttermilk powder caused a significant decrease of sensory properties of non-fat yoghurt.

Iranian Ultrafiltered White cheese was produced by using different blends of coagulants (100:0, 75:25, 50:50, 25:75 and 0:100; Rhizomucor miehei and camel chymosin, respectively) and ripened for 90 days. The effect of different combinations of these coagulants on chemical composition, proteolysis and residual coagulant activity of the cheeses were studied. The results showed that pH, fat-in-dry matter, salt-in-dry matter and protein contents of the cheeses were significantly influenced by type and concentration of the coagulants. The difference between proteolytic activities of the two coagulants resulted in different levels of proteolysis in the cheeses. A direct relationship was determined between using higher concentrations of R. miehei and increasing the hydrolysis of αs1-casein in the cheeses, during ripening. The residual coagulant activity was influenced by the type and concentration of the coagulant as well. In conclusion, R. miehei provided a higher level of proteolysis and residual coagulant activity compared with camel chymosin.

White-brined cheese is a popular cheese type in many parts of the world. Advances in milk concentration methods have led to the use of ultra-filtered (UF) milk to produce these cheeses besides the usual cheese-making methods. The presence of whey proteins in the UF cheese matrix can cause differences in the quality characteristics of this type of cheese compared with its conventional counterpart. On the other hand, increasing demand for healthy and nutritious food products has made food technologists make innovations in the formulations of different white cheese types. This paper reviews differences and similarities between manufacturing processes and the quality properties of white-UF and conventional cheeses. Emphasis is on recent innovations in the field and their effects on different characteristics of these types of cheeses.

There is a growing demand for the consumption of nutritious and safe food products. Cold plasma is a novel non-thermal technology that in recent years, has found numerous applications in the food industry. Study on the applications of this technology and its effects on food quality is increasing. Like any other technology, using cold plasma for the processing of foods can be associated with food quality challenges. This paper reviews the effect of cold plasma on the chemical structure of different food constituents as well as its influence on food characteristics. The emphasis is on the recent studies about the plasma mechanisms of action and chemical alterations of different food components. The studies show that the interaction of plasma-reactive species with food components depends on process conditions. Developing the functional characteristics and reducing the anti-nutritional compounds are of promising potentials of cold plasma. Finally, the research gaps, the salient drawbacks, and future prospects of this technology are highlighted.

Knowing the near real-time pose of the construction equipment is an important necessity for improving safety and productivity of construction processes. A safer construction site can be achieved by accurately capturing the movements of the equipment and their parts using motion tracking techniques. Recently, the application of Computer Vision (CV) techniques is growing, especially considering that other techniques have difficulties with the deployment and high cost. From the productivity point of view, knowing the pose of the equipment helps to estimate the time that the operator spent on each state of his/her operations. For this purpose, each part or joint of the equipment must be recognized and tracked. Extracting this information requires either using depth sensors or stereo vision, which includes the image information of two or more Red Green Blue (RGB) cameras that have overlapping views. Since the reading range of the common and affordable depth sensors are limited to few meters, this research chooses to use RGB cameras. The most challenging step for this purpose is to process the data of each camera individually for extracting the 2D skeleton of the equipment. After having the 2D skeleton of the equipment from each camera, the 3D pose can be further estimated using the relative rotation and translation information between the cameras coordinate systems. This paper mainly focuses on determining the 2D skeleton of excavators based on the videos received from the cameras available on the site. The method takes advantage of synthetic images of each excavator's part to train the parts' detectors. After detecting the parts, the backgrounds of the detected parts are subtracted. The remaining pixels from the previous step are processed to estimate the skeleton of each part. The final skeleton of the excavator is derived by connecting the individual skeletons of each part to their adjacent parts considering the kinematic information of the excavator.

Finding proper milk fat substitutes for manufacturing of nonfat dairy products is a major challenge for dairy industry in order to respond the consumer' demands. Three different concentrations of tara gum (TG) and three combinations of TG with buttermilk powder (BP) were used as fat replacers for manufacturing of nonfat yogurt. Use of TG (0.25 and 0.50/gl) and a combination of TG (0.25/gl) and BP (10/gl) decreased whey separation while improved the gel firmness and viscosity of nonfat yogurt (p

Various blends of milk coagulants Rhizomucor miehei protease and camel chymosin were mixed at levels of 100:0, 75:25, 50:50, 25:75 and 0:100, respectively and used in the manufacture of Iranian ultrafiltered (UF) White cheese. Effect of different blends of these coagulants on microstructure and rheological properties of Iranian UF White cheese were studied during 90 days of ripening. The results showed that both microstructure and rheology of the cheeses were influenced by type and concentration of these coagulant blends due to their different proteolytic activities. Use of high concentrations of camel chymosin resulted in a more compact protein network and firmer structure in the cheeses. Increasing levels of camel chymosin in the coagulant blends increased the storage ( G′ ) and loss ( G″ ) moduli and decreased loss tangent (δ) in the cheeses. In conclusion, increasing levels of camel chymosin provided less protein breakdown and more solid-like viscoelastic structure in UF cheeses.

Background: Expansion and differentiation of stem cells relies on the soluble materials as well as the physical conditions of their microenvironment. Several methods have been studied in attempt to enhance the growth and differentiation rates of different adult stem cells extracted from different sources. Objectives: The purpose was to improve the three-dimensional (3D) culture condition of the semi-permeable polymeric beads for encapsulation of the human adipose-derived mesenchymal stem cells (hADSCs) by modifying the ratio of the alginate-gelatin composition. Materials and Methods: Following isolation and characterization of hADSCs by flow cytometry and their functional differentiation, encapsulation in the alginate and alginate/gelatin compositions were performed. Moreover, the stability, swelling, size frequency, growth kinetics, and cytotoxicity of the beads were measured to meet proper condition in the designed experimental and control culture conditions. Finally, the growth rates of the cells in different experimental groups and control were measured and analyzed statistically. Results: Viability decreased in 2 and 3 percent alginate once compared to 1% alginate in beads (p£0.05). Moreover swelling of the beads in the alginate/gelatin compositions (50:50 and 70:30) were higher than the pure alginate beads (p£ 0.05). Finally, the cell growth rate in alginate/gelatin (50:50) beads was significantly higher than alginate and alginate/gelatin (70:30) beads (p£0.05). Conclusions: These findings suggested for the first time that the composite of alginate/gelatin beads with the ratio of 50:50 might provide a suitable culture condition for the encapsulation and in vitro expansion of the hADSCs.

The recognition of construction equipment is always necessary and important to monitor the progress and the safety of a construction project. Recently, the potentials of computer vision (CV) techniques have been investigated to facilitate the current equipment recognition method. However, the process of manually collecting and annotating a large image dataset of different equipment is one of the most time-consuming tasks that may delay the application of the CV techniques for construction equipment recognition. Moreover, collecting effective negative samples brings more difficulties for training the object detectors. This research aims to introduce an automated method for creating and annotating synthetic images of construction equipment while significantly reducing the required time. The synthetic images of the equipment are created from the three-dimensional (3D) models of construction machines combined with various background images taken from construction sites. The location of the equipment in the images is known since that equipment is the only object over the single-color background. This location can be extracted by applying segmentation techniques and then used for the annotation purpose. Furthermore, an automated negative image sampler is introduced in this paper to automatically generate many negative samples with different sizes out of one general image of a construction site in a way that the samples do not include the target object. The test results show that the proposed method is able to reduce the required time for annotating the images in comparison with traditional annotation methods while improving the detection accuracy.

We discussed the needs for adding definitions of RFID components to a BIM.We investigated scenarios to identify the related attributes of RFID system components.We investigated the relationships of RFID components with the assets/spaces.We proposed an IFC extension to incorporate the new definitions of RFID components.We validated and demonstrated the applicability of the proposed method through a real-world case study. Building Information Modeling (BIM) is emerging as a method of creating, sharing, exchanging and managing the building information throughout the lifecycle between all stakeholders. Radio Frequency Identification (RFID), on the other hand, has emerged as an automatic data collection and information storage technology, and has been used in different applications in the AEC/FM (Architecture, Engineering, Construction, and Facilities Management) industry. RFID tags are attached to building assets throughout their lifecycle and used to store lifecycle and context aware information taken from a BIM. Consequently, there is a need for a standard and formal definition of RFID technology components in BIM. The goal of this paper is to add the definitions for RFID components to the BIM standard and to map the data to be stored in RFID memory to the associated entries in a BIM database. The paper defines new entities, data types, and properties to be added to the BIM. Furthermore, the paper identifies the relationships between RFID tags and building elements. These predefined relationships facilitate the linkage between BIM data and RFID data. Eventually, the data that are required to be saved on RFID tags can be automatically selected using the defined relationships in a BIM. A real-world case study has been implemented to validate the proposed method using available BIM software.

The application of computer vision (CV) in construction projects has been investigated for many years, resulting in several advanced algorithms and methods. However, there is still a need t...

Asset monitoring in construction sites is an intricate, manually intensive task, that can highly benefit from automated solutions engineered using deep neural networks. We use Single-Shot Multibox Detector --- SSD, for its fine balance between speed and accuracy, to leverage ubiquitously available images and videos from the surveillance cameras on the construction sites and automate the monitoring tasks, hence enabling project managers to better track the performance and optimize the utilization of each resource. We propose to improve the performance of SSD by clustering the predicted boxes instead of a greedy approach like non-maximum suppression. We do so using Affinity Propagation Clustering --- APC to cluster the predicted boxes based on the similarity index computed using the spatial features as well as location of predicted boxes. In our attempts, we have been able to improve the mean average precision of SSD by 3.77% on custom dataset consist of images from construction sites and by 1.67% on PASCAL VOC Challenge., Comment: 6 pages, 4 figures, to appear in the Proceedings of the ISC2 2018, 16-19 September 2018, Kansas, USA

We propose two improvements to the SSD---single shot multibox detector. First, we propose an adaptive approach for default box selection in SSD. This uses data to reduce the uncertainty in the selection of best aspect ratios for the default boxes and improves performance of SSD for datasets containing small and complex objects (e.g., equipments at construction sites). We do so by finding the distribution of aspect ratios of the given training dataset, and then choosing representative values. Secondly, we propose an ensemble algorithm, using SSD as components, which improves the performance of SSD, especially for small amount of training datasets. Compared to the conventional SSD algorithm, adaptive box selection improves mean average precision by 3%, while ensemble-based SSD improves it by 8%., Comment: 6 pages, 2 figures, to appear in the Proceedings of the ISNCC 2018, 19-21 June 2018, Rome, Italy

PubMedID: 26119429 Iranian White cheese was manufactured from ultrafiltered cows' milk using different concentrations of salt consisting of 1, 2·5, 4% and salt free. Chemical composition, proteolysis, counts for lactic acid bacteria and sensory evaluation were examined during 90 d of ripening. It was found that the use of different salt concentrations significantly influenced all chemical composition, proteolysis, total number of lactic acid bacteria and sensory characteristics of the cheeses. Increasing the salt concentrations caused a proportional decrease in proteolysis determined by both urea-PAGE of caseins and RP-HPLC of peptides. With increased salt concentration, total number of lactic acid bacteria decreased. Cheeses with 1 and 2·5% salt were suitable and acceptable in odour and flavour that may be due to the proportional level of proteolysis products. In conclusion, reducing salt concentration from 4 to 2·5 and 1% had no ineligible effect on the quality and acceptability of the cheese. © 2015 Proprietors of Journal of Dairy Research.

Construction sites are changing every day, which brings some difficulties for different contractors to do their tasks properly. One of the key points for all entities who work on the same site is the location of resources including materials, tools, and equipment. Therefore, the lack of an integrated localization system leads to an increase in the time wasted on searching for resources. In this research, a localization method based on Radio Frequency Identification (RFID) systems which does not need infrastructure is proposed to overcome this problem. This paper investigates the usage of active RFID technology for the localization of movable objects (e.g. components, equipment, and tools) equipped with RFID tags using handheld readers by extending a Cluster-based Movable Tag Localization (CMTL) technique which uses a k-Nearest Neighbor (k-NN) algorithm. CMTL uses a multidimensional clustering technique that considers signal pattern similarity between target and reference tags together with spatial distribution of reference tags for detecting the region where the target tag is located. The paper proposes applying an irregular bilinear interpolation method to form a grid of virtual reference tags within the selected cluster of real reference tags. Moreover, the proposed method uses artificial neural networks (ANNs) for positioning the target tag, as opposed to empirical weighted averaging formulas used in similar k-NN based methods. Comparative analysis is performed to quantify the improvement of the proposed method over similar k-NN-based methods using a simulation environment. A case study is performed to analyze the performance of the proposed method.

Sıvı kashk fermente bir süt ürünü olup, endüstriyel sıvı kashk ve geleneksel sıvı kashk olmak üzere iki şekilde üretilmektedir. Her iki sıvı kashk’ın temel hammaddesi yoğurttur. Geleneksel sıvı kashk üretiminde kashk geleneksel olarak üretilen yoğurdun konsantre edilmesiyle elde edilen bir süt ürünü kullanılmaktadır. Endüstriyel sıvı kashk endüstriyel olarak üretilen yoğurdun konsantre hale getirilmesiyle üretilmektedir. Bu araştırma sıvı kashklerin üretim yönteminin tanıtılması ve kalite özelliklerinin belirlenmesi üzerine planlanmıştır. Bu amaçla, 30 adet geleneksel sıvı kashk ve 30 adet endüstriyel sıvı kashk İran’ın 10 eyaletinden tesadüfi olarak toplanmış ve kimyasal, mikrobiyolojik ve duyusal özellikleri incelenmiştir. Elde edilen sonuçlara göre, geleneksel sıvı kashk ve endüstriyel sıvı kashk örneklerinin kalite özellikleri, İran Standart ve Endüstriyel Araştırmalar Enstitüsü (ISIRI) tarafından belirtilen standartlar ile uyumlu olduğu belirlenmiştir.

Iranian Ultrafiltered White cheese was produced by using different blends of coagulants (100:0, 75:25, 50:50, 25:75 and 0:100; Rhizomucor miehei and camel chymosin, respectively) and ripened for 90 days. The effect of different combinations of these coagulants on chemical composition, proteolysis and residual coagulant activity of the cheeses were studied. The results showed that pH, fat-in-dry matter, salt-in-dry matter and protein contents of the cheeses were significantly influenced by type and concentration of the coagulants. The difference between proteolytic activities of the two coagulants resulted in different levels of proteolysis in the cheeses. A direct relationship was determined between using higher concentrations of R. miehei and increasing the hydrolysis of α(s1)-casein in the cheeses, during ripening. The residual coagulant activity was influenced by the type and concentration of the coagulant as well. In conclusion, R. miehei provided a higher level of proteolysis and residual coagulant activity compared with camel chymosin.

Introduction: Allergic asthma is a chronic airway inflammatory disease often determined with degrees of inflammation, hypersensitivity, bronchial constriction, and airway changes. Th1, Th2, and Th17 cells are the main cells involved in asthma pathophysiology. To evaluate Th1, Th2, and Th17 functions by assessing INF-γ, IL-4, and IL-17 gene and protein levels in asthma patients and healthy controls. Materials and Methods: In total, 44 individuals of Iranian ethnicity including 24 patients with allergic asthma and 20 healthy controls were enrolled. Peripheral blood mononuclear cells of all participants were isolated and cDNA was synthesized following RNA extraction. Gene expression and protein levels of INF-γ, IL-4, and IL-17 were evaluated by real-time polymerase chain reaction and sandwich ELISA, respectively. Results: The results of this study showed that the gene expression of IL-4 and IL-17 in patients was increased significantly compared to the control group (p = 0.046 and 0.03, respectively) whereas that of IFN-γ was significantly decreased in the group of patients (p = 0.021). Compared to the healthy controls, serum levels of IL-17 and IL-4 were significantly increased in asthma patients (p = 0.015 and 0.03, respectively). Conclusion: Higher IL-17 and IL-4 mRNA expression and serum levels in asthma patients than healthy controls highlight the role of Th2 and Th17 cells in asthma pathogenesis and their potential as therapeutic targets.

The effect of using various combinations of Rhizomucor miehei protease and camel chymosin (100:0, 75:25, 50:50, 25:75, and 0:100, respectively) on volatile composition and sensory scores in Iranian ultrafiltered white cheese was studied during 90d of ripening. A solid-phase microextraction–gas chromatography-mass spectrometric method was used for determining the volatile compounds of the cheeses. Forty compounds including esters (12), acids (6), ketones (9), alcohols (3), and miscellaneous compounds (10) were identified. The main classes of volatile components in the cheeses are esters, miscellaneous compounds, and ketones. The type and concentration of the coagulants influenced both volatile composition and sensory scores of the cheeses. Principal component analysis separated the cheeses based on the use of 2 coagulants in various combinations and ripening time. The cheeses produced using higher concentrations of R. miehei were separately located on the plot compared with the cheeses produced using higher concentrations of camel chymosin. Sensory evaluation of the cheeses showed that, in general, the cheeses produced using higher concentrations of camel chymosin received higher body and texture and odor and flavor scores than the cheese produced using higher concentrations of R. miehei . In conclusion, 2 combinations of R. miehei and camel chymosin (75:25 and 25:75, respectively) can be successfully used for the production of Iranian ultrafiltered white cheese, considering the results of volatile composition and sensory analysis.