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Background: Different progesterone doses and routes are used for luteal phase support in stimulated intrauterine insemination (IUI) cycles, but the optimal supplementation scheme has not yet been determined. Therefore, our aim was to compare the administration of two different doses of vaginal progesterone with two doses of intramuscular (IM) progesterone for luteal phase support in patients undergoing IUI cycles. Methods: In this randomized clinical trial, 312 women with unexplained or male-factor infertility intending to start IUI cycles between April 2015 and January 2018 were included. They were randomized into four groups (n=78/each) including group 1 who received IM progesterone in oil (25 mg daily), group 2 who received IM progesterone in oil (50 mg daily), group 3 who received progesterone suppository (400 mg daily), and group 4 who received progesterone suppository (800 mg daily; 400 mg twice daily). The primary outcome was the clinical pregnancy rate. The ongoing pregnancy rate, abortion rate, and patients’ satisfaction, and convenience the secondary outcomes. Results: In our study, the overall clinical and ongoing pregnancy rates per cycle with COS and IUI were 16.02% and 12.8%, respectively. There were no significant differences in clinical pregnancy, ongoing pregnancy, and abortion rates among groups (p=0.84). The overall patients’ satisfaction and convenience was significantly higher in the vaginal progesterone suppository groups than the IM progesterone groups (p=0.001). Conclusion: The results of this study showed that vaginal progesterone administration provides a more easy-to-use and convenient method than IM progesterone administration for luteal phase support in IUI cycles with comparable pregnancy rates.

This study aimed to optimize hydrogel wound dressings to achieve favorable properties of the water vapor transmission rate (WVTR) and proper degree of swelling ratio (DSR) to overcome the issues often associated with most commercial dressings including improper breathability and insufficient exudate absorption. Artificial neural network and response surface methodologies were utilized to design and model bionanocomposites. Besides, the effect of the ratio of components as input data, and WVTR and DSR properties as output (response) data were investigated. Hydrogel systems were produced via the freeze–thaw method and were identified using infrared spectroscopy, dynamic light scattering, and scanning electron microscopy. To increase the antibacterial property of manufactured specimens, zinc oxide nanoparticles were functionalized with heparin, and, other properties including mechanical properties, in vitro wound healing as well as toxicity analysis were investigated on the optimum formulation. Results showed an improvement in mechanical properties in the presence of nanoparticles and also enhanced antibacterial property after conjugating heparin on nanoparticles. In vitro healing and cell viability results approved the biocompatibility and non-toxicity of the samples. Therefore, manufactured dressings were considered to have good DSR and WVTR, mechanical and biocompatibility properties and they exhibited good ability to heal and protect wounds.

Nanotechnology-based fabricated wound dressings are known as appropriate substrates to enhance healing in both acute and chronic wounds. These types of materials have the ability to deliver therapeutic agents. In this study, a wound dressing including heparinized zinc oxide nanoparticles in combination with chitosan and poly(vinyl alcohol) was developed to investigate its antibacterial and regenerative properties in a rat model of full thickness skin wounds. By adding nanoparticles, the mechanical strength increased up to twice as compared to the sample without nanoparticles. In addition, heparin release profile follows the Hixson-Crowell release kinetic. Protein adsorption enhanced by adding nanoparticles in hydrogels and the prepared wound dressings were completely biocompatible. In terms of antibacterial activity, the minimum inhibitory concentration decreased by conjugation of heparin on the surface of zinc oxide nanoparticles compared to the non-functionalized nanoparticles, and, this shows the increased antibacterial synergistic effect by adding heparin to nanoparticles. Furthermore, it was found that the heparinized zinc oxide nanoparticles effectively accelerate wound closure, re-epithelialization and decrease collagen deposition compared to other groups after implantation. Hence, the prepared wound dressings have the capacity to significantly enhance healing of acute wounds.

The antibacterial property of food packaging materials plays a key role in improving the safety and shelf-life of the food. The aim of this study was to evaluate the antibacterial activity of chitosan/carboxymethyl cellulose/starch biofilms against S. aureus and E. coli microorganisms by using agar diffusion disc and optical density methods. Investigation on the properties of fabricated biofilms, including water vapor transmission rate, water solubility, tensile strength and thermal resistance was carried out. Results exhibited that the antibacterial activity was enhanced by increasing the chitosan content. Besides, increased carboxymethyl cellulose content resulted in a decline in the permeability of water vapor through samples. Furthermore, the presence of carboxymethyl cellulose improved tensile strength and thermal stability and reduced the degradation rate of biofilms within the self-life period. Also, the increased starch content in biofilms led to increased water solubility. These results suggested that chitosan/carboxymethyl cellulose/starch biofilms could be used as food packaging materials.

Recommender systems use intelligent algorithms to learn a user’s preferences and provide them relevant suggestions. Lack of sufficient ratings – also known as data sparsity problem – often results in poor recommendation performance. The existing recommendation methods have mainly focused on designing recommenders with high accuracy without paying much attention to the reliability of the recommendations. On the other hand, the users’ preferences may vary over time and considering the time factor in the design process is crucial, which has been largely ignored in most of the existing recommenders. To deal with these issues, a novel recommendation method is proposed in this paper which incorporates temporal reliability and confidence measures into the recommendation process. First, the effectiveness of the users’ rating is measured using a probabilistic approach and ineffective rating profiles are enriched by adding some implicit ratings to them. The quality of the predictions is evaluated using a temporal reliability measure taking into account the changes of users’ preferences over time. Then, the ratings with low reliability values are recalculated using a novel procedure, which updates the target user’s neighborhood by removing ineffective users. This leads to a temporal confidence measure that is used to update the neighborhood to provide more reliable and accurate recommendations. The superiority of the proposed method over state-of-the-art recommendation methods is shown by conducting extensive experiments on three benchmark datasets.

Available wound dressings have some major deficiencies including low water vapor transmission rate (WVTR), low absorption of wound fluids, and not providing a suitable and moist environment for wound healing. The main advantage of hydrogels is giving aid to the creation of a moist and cool environment for wound healing and providing high water vapor permeability along with preventing penetration of microbes into the wound surface. Therefore, hydrogels of heparinized polyvinyl alcohol (PVA)/chitosan (CS)/nano zinc oxide (nZnO) were prepared to be used as wound dressing. Samples were characterized via infrared spectrometry (FTIR), X-ray diffraction (XRD) and scanning electron microscope (SEM). In addition, other properties including swelling ratio, water vapor transmission rate, the size of pores, mechanical and thermal properties, cell viability, and antibacterial efficiency were investigated. Water vapor permeability, porosity, and swelling ratio showed a wide range of numerical values that facilitate the use of provided samples as ideal wound dressings. Besides, investigating mechanical and thermal properties exhibited the improvement of mentioned properties by adding nano zinc oxide. Furthermore, Heparin loading was conducted on optimum samples. Heparin release rate decreased and was more sustained by adding nanoparticles compared to hydrogel wound dressings without nZnO. Cell viability of bionanocomposite samples showed no toxicity after loading nanoparticles and this value was >70% for all samples. Antibacterial properties of hydrogel samples can effectively protect wounds especially with an increase nZnO content. Hence, these hydrogels were found applicable as robust wound dressings.

The last two decades have seen a surge of data on the Web which causes overwhelming users with huge amount of information. Recommender systems (RSs) help users to efficiently find desirable items among a pool of items. RSs often rely on collaborating filtering (CF), where history of transactions are analyzed in order to recommend items. High accuracy, and low time and implementation complexity are most important factors for evaluating the performance algorithms which current methods have the shortage of all or some of them. In this paper, a probabilistic graph-based recommender system (PGB) is proposed based on graph theory and Markov chain with improved accuracy and low complexity. In the proposed method, selecting each item for recommendation is conditioned by considering recommended items in the previous steps. This approach uses a probabilistic model to consider the items which are likely to be preferred by users in the future. Experimental results performed on two real-world datasets including Movielens and Jester, demonstrate that the proposed method significantly outperforms several traditional and state-of-the-art recommender systems.

Recommender systems attempt to suggest information that is of potential interest to users helping them to quickly find information relevant to them. In addition to historical user–item interaction data, such as users’ ratings on items, social recommendation methods use social relationships between users to improve the accuracy of recommendations. However, the available social relationships are often extremely sparse. Therefore, incorporating implicit relationships into the recommendation process can be effective to improve the performance of social recommender systems, especially for those users whose explicit relationships are insufficient to make accurate recommendations. The existing approaches have not considered reliability of the implicit relationships. In this paper, a social recommender system is proposed based on reliable implicit relationships. To this end, Dempster–Shafer theory is used as a powerful mathematical tool to calculate the implicit relationships. Moreover, a new measure is introduced to evaluate the reliability of predictions, where unreliable predictions are recalculated using a neighborhood improvement mechanism. This mechanism uses a confidence measure between the users to identify ineffective users in the neighborhood set of a target user. Finally, new reliable ratings are calculated by removing the identified ineffective neighbors. Extensive experiments are conducted on three well-known datasets, and the results demonstrate that our approach achieves superior performance to the state-of-the-art recommendation methods.

Composite hydrogels as wound dressings feature healing properties in treating wounds. In this study, polyvinyl (alcohol)/chitosan/nano zinc oxide nanocomposite hydrogels were formed using the freeze-thaw method and essential process parameters including thawing time, thawing temperature, and the number of freeze-thaw cycles was investigated to model nanocomposites employing response surface methodology. Critical properties including water vapor transmission rate, porosity, wound fluid absorption, and gel content were modeled using process parameters. Analysis of morphology, mechanical properties, toxicity, protein absorption, antibacterial activity, and in-vitro wound healing were also performed. Results exhibited that increased freeze-thaw cycles caused reduced pore size and increased porosity and wound fluid absorption. Besides, increased freeze-thaw cycles and reduced thawing temperature resulted in increased elastic modulus and tensile strength, while elongation at break point decreased. Antibacterial properties, biocompatibility, and in-vitro wound healing tests demonstrated that the designed system showed no toxicity and it was able to treat the wounds sufficiently.

Recommender systems aim to suggest relevant items to users among a large number of available items. They have been successfully applied in various industries, such as e-commerce, education and digital health. On the other hand, clustering approaches can help the recommender systems to group users into appropriate clusters, which are considered as neighborhoods in prediction process. Although it is a fact that preferences of users vary over time, traditional clustering approaches fail to consider this important factor. To address this problem, a social recommender system is proposed in this paper, which is based on a temporal clustering approach. Specifically, the temporal information of ratings provided by users on items and also social information among the users are considered in the proposed method. Experimental results on a benchmark dataset show that the quality of recommendations based on the proposed method is significantly higher than the state-of-the-art methods in terms of both accuracy and coverage metrics.

In order to investigate the composition of borage (Borago officinalis L.) seed oil, this research was performed under the field conditions at Shahriyar and Garmsar zones, Iran during the 2012 planting year. The oil yield of borage was 31.46% and 33.7% at Shahriyar and Garmsar zone, respectively, and nine and eight fatty acids were identified in the seed oil of borage at Shahriyar and Garmsar, respectively - palmitic, linoleic, stearic and γ-linolenic acids were dominant in the seed oil of borage from both zones. Unsaturated fatty acid content was more than the saturated fatty acids in both zones. The ratio of linoleic acid and α-linolenic acid in the borage cultivated at Shahriyar and Garmsar zones was 2.13 and 2.29. The fatty acid profile of Garmsar borage, oleic and oleic/linoleic acid ratio, increased. Locations with different ecological conditions resulted in changes in both seed oil content and fatty acid profile of borage.