Extracting Implicit Social Relation for Social Recommendation Techniques in User Rating Prediction

Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users' ratings to items by describing Hellinger distance between users in recommender systems. Then, we propose to incorporate the predicted trust scores into social matrix factorization models. By analyzing social relation extraction from three well-known real-world datasets, which both: trust and recommendation data available, we conclude that using the implicit social relation in social recommendation techniques has almost the same performance compared to the actual trust scores explicitly expressed by users. Hence, we build our method, called Hell-TrustSVD, on top of the state-of-the-art social recommendation technique to incorporate both the extracted implicit social relations and ratings given by users on the prediction of items for an active user. To the best of our knowledge, this is the first work to extend TrustSVD with extracted social trust information. The experimental results support the idea of employing implicit trust into matrix factorization whenever explicit trust is not available, can perform much better than the state-of-the-art approaches in user rating prediction

Hysteresis Nonlinearity Identification Using New Preisach Model-Based Artificial Neural Network Approach

Preisach model is a well-known hysteresis identification method in which the hysteresis is modeled by linear combination of hysteresis operators. Although Preisach model describes the main features of system with hysteresis behavior, due to its rigorous numerical nature, it is not convenient to use in real-time control applications. Here a novel neural network approach based on the Preisach model is addressed, provides accurate hysteresis nonlinearity modeling in comparison with the classical Preisach model and can be used for many applications such as hysteresis nonlinearity control and identification in SMA and Piezo actuators and performance evaluation in some physical systems such as magnetic materials. To evaluate the proposed approach, an experimental apparatus consisting one-dimensional flexible aluminum beam actuated with an SMA wire is used. It is shown that the proposed ANN-based Preisach model can identify hysteresis nonlinearity more accurately than the classical one. It also has powerful ability to precisely predict the higher-order hysteresis minor loops behavior even though only the first-order reversal data are in use. It is also shown that to get the same precise results in the classical Preisach model, many more data should be used, and this directly increases the experimental cost

The Combined Effects of Levothyroxine and Low Level Laser Therapy on Wound Healing in Hypothyroidism Male Rat Model

Introduction: Hypothyroidism is caused by inadequate production and storage of thyroid hormones. Hypothyroidism is associated with delayed wound healing. Laser therapy may stimulate wound regeneration. The aim of this study was to determine the combined effects of levothyroxine and low level laser therapy during the wound healing process on skin of hypothyroidism male rat model.Methods: Thirty male Wistar rats were randomly divided into 5 groups: control group, hypothyroidism group, hypothyroidism group treated by laser, hypothyroidism group treated by levothyroxine, and hypothyroidism group treated by laser and levothyroxine. To induce hypothyroidism, methimazole was given at a dose of 4 mg/100 mL in their drinking water. After hypothyroidism was proven through immunoassay commercial kit, rats were generally anesthetized with ketamine and xylazine, then, an incisional skin wound was created in a length of 1.2 cm on the back of the ribcage. The surgical day is considered as the zero day. The third and fifth groups were treated with a pulse laser, 810 nm wavelength 80 Hz frequency and 0.2 J/cm2 energy densities for 200 seconds. Levothyroxine was injected to the fourth and fifth groups intraperitoneally. On the 14th day, a normal sample of each healing skin wound was harvested for biomechanical examination. The obtained data were analyzed by the SPSS software 21 and reported as a mean ± standard error of mean (SEM). P < 0.05 was considered statistically significant.Results: The results showed that the mean maximum force and the accomplished work (energy) made a significant difference in the group receiving both laser and levothyroxine synchronously rather than the other groups (P ≤ 0.05). The elasticity of the wound healing in the groups that received laser and levothyroxine synchronously was significantly higher in comparison with the control and hypothyroidism groups but the difference was not significant in comparison with the laser or levothyroxine groups.Conclusion: The results of our study showed that the application of laser and levothyroxine synchronously improves the biomechanical parameters of wound during healing in comparison to the use of laser and levothyroxine solel

Promoters and Deterrents of Developing Mechanization of Peanut Cultivation in North of Iran

The increasing cost of peanut production is a major concern in Iran. Therefore, developing the mechanization of peanut production is a necessity. In this regard, a three-phase Delphi study was conducted to identify the promoting and deterring factors affecting peanut cultivation mechanization in Guilan Province, the main peanut-producing region in Iran. After preliminary studies, 26 experts were selected as respondents for the study. Based on the final results, ‘allocating provincial and national funds to develop mechanization’ (with the agreement of 98.07% of respondents), ‘Organizing training programs to increase farmers’ technical knowledge’ (97.12%), and ‘conducting the pilot and model projects’(95.19%) were found to be the most important promoting factors in developing peanut cultivation mechanization in north of Iran. Moreover, ‘the small size and fragmentation of peanut farms’ (with 96.15% of respondents agreeing), ‘problems with the national and provincial programs of peanut mechanization’ (95.19%), and ‘low technical knowledge of farmers and craftsmen about peanut farming mechanization’ (94.23%) were identified as the most important deterring factors in developing peanut cultivation mechanization in north of Iran. Given the small area dedicated to peanut cultivation and the low income levels of peanut farmers in north of Iran, it seems that provincial and national funding allocation and peer-planned programming to import appropriate farm machinery are the most urgent plans to improve the status of mechanization of peanut cultivation in north of Iran

Combined Effect of Low-Level Laser Treatment and Levothyroxine on Wound Healing in Rats With Hypothyroidism

Introduction: Hypothyroidism delays wound healing by reducing the synthesis of keratinocytes, fibroblast cells, and collagen. Methods for enhancement of wound healing include laser therapy and hormone therapy. The current study evaluated the combined effect of laser and levothyroxine therapy to cure wounds in male rats with hypothyroidism.Methods: Sixty male Wistar rats were randomly divided into 5 groups: (1) healthy controls; (2) controls with hypothyroidism; (3) hypothyroidism + laser treatment; (4) hypothyroidism + levothyroxine treatment; (5) hypothyroidism + laser + levothyroxine treatment. Hypothyroidism was induced by dissolving 4 mg of methimazole in 100 mL of drinking water daily for 28 days. After hypothyroidism had been confirmed, a longitudinal incisional wound was created on the dorsal rib cages of the rats. The wounds that received laser treatment were divided into 12 sections and treated at 810 nm wavelength and 0.2 J/cm2 of energy density for 200 seconds. Levothyroxine was administrated in doses of 20 μg/kg/d i.p. All groups were divided into 3 subgroups for testing on days 4, 7 and 14. Samples were collected in all the subgroups.Results: The results showed that hypothyroidism reduced fibrous tissue volume, fibroblasts, and basal cell numbers. The combined effect of laser and levothyroxine improved all parameters.Conclusion: Combined laser and levothyroxine treatment showed the best effect on wound healing and accelerated the closure of the wounds

Protective effect of chronic administration of pelargonidin on neuronal apoptosis and memory process in amyloid-beta-treated rats

Objective: Alzheimer's disease (AD) is a progressive neurodegenerative disorder associated with impaired cognitive skills and learning and memory dysfunctions.  It has been suggested that pelargonidin (PG), as an antioxidant agent, has a neuroprotective effect. PG could prevent damaging effects of amyloid-beta (Aβ) deposition. The aim of this study was to determine the chronic effect of PG on hippocampal neurons and memory processes in a rat model of AD. Materials and Methods: Twenty-eight male adult rats were divided into sham, AD, AD+PG (5 μg, intracerebroventricular), and PG (5 μg, intracerebroventricular) groups. Intracerebroventricular (ICV) injection of Aβ peptides (6 μg) was done using stereotaxic surgery. ICV administration of PG or saline was performed daily for 28 consecutive days. Behavioral analysis was performed using the novel object recognition (NOR) and passive avoidance tests. Neuronal apoptosis was detected using TUNEL assay in the hippocampus. Results: The ICV injection of Aβ reduced step-through latency and discrimination index in behavioral tests (p <0.001). Aβ increased the number of apoptotic neurons (p <0.001). PG treatment decreased the time spent in the dark compartment and neuronal apoptosis in the AD+PG rats (p <0.001). PG increased the discrimination index in the NOR test (p <0.001).  Although PG did not change behavioral variables, it decreased cell death in the PG group. Conclusion: PG attenuated neuronal apoptosis and improved cognition and memory deficiency in AD rats. The protective effect of PG against Aβ may be due to its anti-apoptotic property. It is suggested that PG can be useful to treat AD

ERYTHROCYTE MEMBRANE FATTY ACIDS IN MULTIPLE SCLEROSIS PATIENTS AND HOT-NATURE DIETARY INTERVENTION WITH CO-SUPPLEMENTED HEMP-SEED AND EVENING-PRIMROSE OILS

The risk of developing multiple sclerosis (MS) is associated with increased dietary intake of saturated fatty acids. For many years it has been suspected that this disease might be associated with an imbalance between unsaturated and saturated fatty acids. We determined erythrocyte membrane fatty acids levels in Hot nature dietary intervention with co-supplemented hemp seed and evening primrose oils in multiple sclerosis patients. To determine the erythrocyte membrane fatty acids levels and correlate it with expanded disability status scale (EDSS) at baseline after 6 months intervention in MS patients by gas chromatography, in this double blind, randomized trial, 100 RRMS patients with EDS

Harnessing the Power of Smart and Connected Health to Tackle COVID-19:IoT, AI, Robotics, and Blockchain for a Better World

As COVID-19 hounds the world, the common cause of finding a swift solution to manage the pandemic has brought together researchers, institutions, governments, and society at large. The Internet of Things (IoT), Artificial Intelligence (AI) &#x2014; including Machine Learning (ML) and Big Data analytics &#x2014; as well as Robotics and Blockchain, are the four decisive areas of technological innovation that have been ingenuity harnessed to fight this pandemic and future ones. While these highly interrelated smart and connected health technologies cannot resolve the pandemic overnight and may not be the only answer to the crisis, they can provide greater insight into the disease and support frontline efforts to prevent and control the pandemic. This paper provides a blend of discussions on the contribution of these digital technologies, propose several complementary and multidisciplinary techniques to combat COVID-19, offer opportunities for more holistic studies, and accelerate knowledge acquisition and scientific discoveries in pandemic research. First, four areas where IoT can contribute are discussed, namely, i) tracking and tracing, ii) Remote Patient Monitoring (RPM) by Wearable IoT (WIoT), iii) Personal Digital Twins (PDT), and iv) real-life use case: ICT/IoT solution in Korea. Second, the role and novel applications of AI are explained, namely: i) diagnosis and prognosis, ii) risk prediction, iii) vaccine and drug development, iv) research dataset, v) early warnings and alerts, vi) social control and fake news detection, and vii) communication and chatbot. Third, the main uses of robotics and drone technology are analyzed, including i) crowd surveillance, ii) public announcements, iii) screening and diagnosis, and iv) essential supply delivery. Finally, we discuss how Distributed Ledger Technologies (DLTs), of which blockchain is a common example, can be combined with other technologies for tackling COVID-19