Recent advances on happiness

Happiness plays essential role on building prosperity and success in any society. Happiness is one of the essential factors to reach prosperity and success in people’s life and jobs but happiness is not always the same as capability, but they may be correlated while capability is a necessary for having a happy life and happiness feeds back on capability in different ways. People who feel happy could better contribute to society and help other people build better future. This study performs a review on recently completed studies on factors, which influence happiness, new definitions of happiness. The study concentrates more on empirical investigations on the concept of happiness

Antiaflatoxigenic activity of Carum copticum essential oil

Plants are unique sources of useful metabolites. Plant essential oils display a wide range of antimicrobial effects against various pathogens. Here, we studied the essential oil from the seeds of Carum copticum. We monitored aflatoxin by high-performance liquid chromatography. Results show that Carum copticum essential oil inhibits Asergillus parasiticus growth and prevents aflatoxin production. The half-maximal inhibitory concentration (IC(50)) is 127.5 μg mL(−1) for aflatoxin B(1) and 23.22 μg mL(−1) for aflatoxin G(1). Our findings show that Carum copticum essential oil is a potential candidate for the protection of foodstuff and feeds from toxigenic fungus growth and their subsequent aflatoxin contamination

Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm

Aspect-oriented software engineering provides new ways to produce and deliver products and ultimately leads to reliable software. Reliability is an important issue contributing to the quality of software. Thus, software engineers need proven mechanisms to determine the extent of software reliability. In this paper, a method for measuring reliability is proposed which takes advantage of a Multilayer Perceptron Artificial Neural Network (MLPANN). Furthermore, an Imperialist Competitive Algorithm (ICA) is used to optimize the weights to improve network performance. Finally, relying on Root Mean Square Error (RMSE), the proposed approach is compared to a hybrid Genetic Algorithm- Artificial Neural Network (GA-ANN) method. The results show that the proposed approach exhibits lower error

Evaluation of Rotation Effects in Steel Structures with Irregular Plan Under Earthquake in Project Management

Abstract. Because of lacking specific relationships and criteria for steel structures with bending frames and braces along with the uneven bearing system in Iranian regulations, the need to study the behavior of such structures has been considered by researchers. In this paper, with three-dimensional modeling of steel structures with six types of plans, each of which indicates a degree of asymmetry of the load-bearing system, a total of 18 models of structures under two types of linear dynamic loading and overload were studied. It is indicated that with increasing unevenness of the load-bearing system, the rotation of the structures also increases. This increase is up to 18 times more for short-term structures and up to five times more than for parallel structures than parallel structures. The discrepancy causes unexpected results. Increasing the height of the structure reduces the rotation in the diaphragm. There is no difference between the rotation of the diaphragms in terms of elastic and inelastic, while the load in the other direction of these changes for the inelastic state is sometimes up to more than 50 times the elastic state

Cognitive State Inference and Neuromodulation Effects on Decision-Making in Parkinson's Disease

Human cognition is characterized by an intricate blend of neural and behavioral signals arising from dynamic interactions within distributed brain networks. Grasping these hidden cognitive states is essential, particularly for neurological conditions like Parkinson's disease (PD), which affect decision-making when faced with conflicting sensory inputs and disrupt normal brain function. This thesis aims to create computational models to infer cognitive states linked to decision-making, especially conflict states, from intricate neural and behavioral datasets, and also to assess the effects of deep brain stimulation (DBS) on decision-making processes. Initially, we examine the limitations inherent in existing computational models when it comes to deciphering cognitive states involved in decision-making and conflict states. In response to these shortcomings, we propose an innovative framework, the High-Dimensional Generative Dynamics (HI-DGD) model. This model adeptly infers conflict states from multimodal data sources such as local field potentials (LFP) and electroencephalograms (EEG). The HI-DGD model's effectiveness has been confirmed in decision-making tasks like the verbal Stroop task, which monitors conflict states throughout conflict processing. The thesis subsequently explores the temporal effects of DBS on decision-making in PD patients under both high-conflict and no-conflict conditions. We introduce the Cognet model, which replicates the temporal influences of DBS on decision processes. The Cognet model adeptly captures the temporal effects of DBS on decision-making, providing significant insights into the timing and modulation strategies to boost cognitive performance during choices. These models provide new avenues for understanding the neural and behavioral signal mechanisms and the impact of neuromodulation on cognitive functions. This research contributes to neuroscience by advancing methods for deducing cognitive states.Ph.D

Secrecy Throughput Maximization for Full-Duplex Wireless Powered IoT Networks under Fairness Constraints

In this paper, we study the secrecy throughput of a full-duplex wireless powered communication network (WPCN) for internet of things (IoT). The WPCN consists of a full-duplex multi-antenna base station (BS) and a number of sensor nodes. The BS transmits energy all the time, and each node harvests energy prior to its transmission time slot. The nodes sequentially transmit their confidential information to the BS, and the other nodes are considered as potential eavesdroppers. We first formulate the sum secrecy throughput optimization problem of all the nodes. The optimization variables are the duration of the time slots and the BS beamforming vectors in different time slots. The problem is shown to be non-convex. To tackle the problem, we propose a suboptimal two stage approach, referred to as sum secrecy throughput maximization (SSTM). In the first stage, the BS focuses its beamforming to blind the potential eavesdroppers (other nodes) during information transmission time slots. Then, the optimal beamforming vector in the initial non-information transmission time slot and the optimal time slots are derived. We then consider fairness among the nodes and propose max-min fair (MMF) and proportional fair (PLF) algorithms. The MMF algorithm maximizes the minimum secrecy throughput of the nodes, while the PLF tries to achieve a good trade-off between the sum secrecy throughput and fairness among the nodes. Through numerical simulations, we first demonstrate the superior performance of the SSTM to uniform time slotting and beamforming in different settings. Then, we show the effectiveness of the proposed fair algorithms

Evaluation of the Effects of Photobiomodulation on Partial Osteotomy in Streptozotocin-Induced Diabetes in Rats

Objective: We examined the effects of photobiomodulation (PBM) on stereological parameters, and gene expression of Runt-related transcription factor 2 (RUNX2), osteocalcin, and receptor activator of nuclear factor kappa-B ligand (RANKL) in repairing tissue of tibial bone defect in streptozotocin (STZ)-induced type 1 diabetes mellitus (TIDM) in rats during catabolic response of fracture healing. Background data: There were conflicting results regarding the efficacy of PBM on bone healing process in healthy and diabetic animals. Materials and methods: Forty-eight rats have been distributed into four groups: group 1 (healthy control, no TIDM and no PBM), group 2 (healthy test, no TIDM and PBM), group 3 (diabetic control, TIDM and no PBM), and group 4 (diabetic test, no TIDM and PBM). TIDM was induced in the groups 3 and 4. A partial bone defect in tibia was made in all groups. The bone defects of groups second and fourth were irradiated by a laser (890 nm, 80 Hz, 1.5 J/cm2 ). Thirty days after the surgery, all bone defects were extracted and were submitted to stereological examination and real-time polymerase chain reaction (RT-PCR). Results: PBM significantly increased volumes of total callus, total bone, bone marrow, trabecular bone, and cortical bone, and the numbers of osteocytes and osteoblasts of callus in TIDM rats compared to those of callus in diabetic control. In addition, TIDM increased RUNX2, and osteocalcin in callus of tibial bone defect compared to healthy group. PBM significantly decreased osteocalcin gene expression in TIDM rats. Conclusions: PBM significantly increased many stereological parameters of bone repair in an STZ-induced TIDM during catabolic response of fracture healing. Further RT-PCR test demonstrated that bone repair was modulated in diabetic rats during catabolic response of fracture healing by significant increase in mRNA expression of RUNX2, and osteocalcin compared to healthy control rats. PBM also decreased osteocalcin mRNA expression in TIDM rats

The Relationship between Working Capital Management Components and Profitability: Evidence from Iran

The purpose of this study is to investigate the relationship between working capital management components with firms’ profitability. Our sample includes 98 Iranian firms accepted at Tehran Stock Exchange (TSE) during 6 years from 2008 to 2012.This research is empirical in term of goal and is descriptive in term of methods. Required data are extracted Using the "library" method. Inventory turnover period, receivables collection period, accounts payable period and cash conversion cycle are used as criteria of working capital management and return on equity used as a measure for profitability. In this research, financial ratios are calculated using the software Excel. Eviews software is used to test the hypotheses. Research findings show that there is a significant negative relationship between measures of working capital management and corporate profitability