Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local model training servers for each region and a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data Transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and model accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data Transfer and convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.

Alzheimer’s Disease (AD) is the most common form of dementia in the elderly in which an interplay between genes and the environment is supposed to be involved. Mutations in mitochondrial DNA (mtDNA) have been suspected to be causally related since mitochondrial DNA is maternally inherited in a non-Mendelian way. All Mitochondrial tRNA genes of 24 AD patients and 50 healthy controls were investigated by sequencing method. Fifteen variations were found in different mitochondrial tRNA genes. Eleven variations were polymorphic mutations. Four variations {C1631A, T1633A (tRNA Val), T14704C and T14723C (tRNA Glu)} filled the criteria for pathogenicity of mutation because of their: a) heteroplasmic state, b) conserved nucleotide, c) absence in the literature and d) absence in healthy controls. A12308G polymorphic mutation (tRNA Leu (CUN)) was found in 8 patients. This mutation has been reported in different neurodegenerative diseases as well as controls. We believe that these variations may have pathogenic effects in AD or have secondary effects in the disease process. The percentage of hetroplasmy may play a role in signs/symptoms or onset age of the disease.

Background:: It has been suggested that local endometrial injury (LEI) can increase the success rate of assistive reproductive technologies. Previous studies have been resulted in controversial diseases. In current study, we investigated the effect of LEI on the rate of clinical pregnancy and live birth in women undergoing frozen embryo Transfer (FET).Materials and Methods: There were 120 infertile women assigned to two equal groups, randomly: LEI group and control group. Patients underwent FET procedure. The rate of clinical pregnancy and live birth were compared between two groups.Findings: The rate of clinical pregnancy was the same (%35 in LEI group versus %33.3 in control group; p<0.05). Also, the rate of live birth did not significantly differed between two groups (%23.3 in LEI group versus %21.6 in control group; p<0.05).Conclusion: Based on our findings, LEI does not improve the rate of clinical pregnancy and live birth in women undergoing FET.

The most important aim of ART is to increase implantation to physiological levels, the same as a normal cycle. For this aim, two methods are recommended; Transfer of best quality embryos and increase in endometrium receptivity. Materials & Methods: A Clinical trial study was performed on 160 cycles of ART( IVF/ICSI) at the Research and Clinical Center of Infertility and Madar Hospital of Yazd. With this Supposition that two step embryo Transfer may increase the endometrial receptivity, two groups were compared. Both groups were similar in respect to male age, female age and duration and cause of infertility. For Induction -Ovulation using Long Protocol, Buserelin was injected subcutaneously, 0.5 cc daily from day 20 of menstrual cycle and the dose were decreased to 0.25cc daily at start of menstrual bleeding. HMG (225 IV/day) was injected from day 2 of cycle. The measurement of follicle diameter was done serially. After HCG injection (10000IU) and ovarian puncture, the luteal phase was supported by progesterone injection. Then, the patients were divided randomly in two groups. The first group of 80patients had experienced two step embryo Transfer on day 3, and on day 5, two or three embryos was Transferred. In the control group of 80 patients, embryo Transfer was done routinely 48hours after ovarian puncture. The patients were followed up by measurement of 8HCG serum level on day 14 after embryo Transfer. Results: Two patients of first group and 14 patients of control group were left out from the study because of no follow up. The data was analyzed by chi-square and t test. Finally, there was no significant difference in pregnancy rate in the two groups. (P-Value= 1.000). Therefore, Two Step embryo Transfer dose not increase the pregnancy rate more than one step embryo Transfer. Conclusion: There was no significant difference between the two methods and pregnancy rate, number of embryos & pregnancy rate, the female age and pregnancy rate. However, further studies are needed in this field.    

Many women undergoing an Assisted Reproductive Technology (ART) cycle will not achieve a live birth. Failure at the embryo Transfer stage may be due to poor embryo quality, lack of uterine receptivity, or the Transfer technique itself. Embryo Transfer (ET) is the least successful step in ART. Many factors have been proposed to increase the success of this step. The ultimate goal of a successful embryo Transfer is to deliver the embryos a traumatically to the uterine fundus in a location where implantation is maximized, without pain, bleeding, trauma to the endometrium or embryos, and with the absence of uterine contractions.

An experimental investigation on heat Transfer coefficient is presented from three horizontal tubes in a vertical array in a duct for 500<ReD<6000. A mass Transfer measuring technique based on psychrometry chart is used to determine heat Transfer coefficient. The diameter of the tubes is 11 mm each spaced 40 mm apart and in-line pitch ratio varies in the range 0.055<D/W<0.22. The experimental results show that the Nusselt number of each tube increases by increasing D/W. Also the increase of the second tube Nusselt number is more than that of the third one.