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Objective: The objective of this research was to systematically evaluate evidence regarding the correlation between divine proportions and facial esthetics. Materials and Methods: An extensive literature search was performed in multiple electronic databases such as PubMed, Medline, Embase, ScienceDirect, and ProQuest which included articles published from May 1982 to March 2021 in the English language. Furthermore, only randomized clinical trials and original research studies were included. The risk of bias in the included studies was assessed by using the Cochrane risk-of-bias tool ROBVIS (Risk-of-bias VISualization tool). Results: A total of 2,736 articles were retrieved and 974 duplicate records were eliminated; subsequently, articles were screened based on title and abstracts, inclusion and exclusion criteria from which a total of 14 original articles were included in the systematic review. Of the 14 included studies, 5 studies showed a low risk of bias, 6 studies showed a moderate risk of bias, and 3 showed a high risk of bias. Four studies showed a positive correlation and 10 studies showed a negative correlation between divine proportions and facial esthetics. Conclusion: The evidence from this study suggests that there exists a weak correlation between divine proportions and facial esthetics. Hence, divine proportions are not absolute determinants and are only partially related to facial attractiveness. Further high-quality cross-sectional studies with a strong methodology are needed to establish the correlation between divine proportions and facial esthetics and to support this evidence. Trial registration number: PROSPERO CRD42022302308

The day-to-day lives of humans are changing remarkably due to the evolution in tools, techniques and technology across the planet. This evolution is not only impacting the growth of humans but also contributing to the growth and well-being of society and country. The domain of data analytics (DA) and internet of things (IoT) is very much facilitating this growth. But there have been only a handful of innovations and explorations in the field of agriculture, although it being the backbone and largely contributing to the gross domestic product (GDP) of a country like India. The reason for it may be profuse, such as the erratic weather conditions, improper irrigation, farmers being skeptical using modern tools and many more. But being in a developing country that has its primary focus on invention and innovation, a consensus has to be reached so that the modern tools and technologies, abet agriculture throughout the country. In our work, an attempt is made to analyze the different aspects that influences the variable outcomes in agriculture with the aid of various data analytic algorithms. Rainfall, humidity and temperature are some of the variables that determine the type of crop. Therefore, the task of prediction of crop type given these factors using decision trees and support vector machines (SVM) is implemented, and the accuracy of the models are computed. Here, more focus is given to the state of Karnataka and to its major crops. With rice, ragi and maize being some of the predominant crops, an analysis is portrayed considering the yield across the state.

Machining of bulk Ti6Al4V is relatively difficult owing to low elastic modulus, high work hardening tendency, stickiness, poor thermal conductivity besides formation of long continuous chips during machining. Near net shaping through green machining could be a viable alternative to conventional milling procedure. Herein, fabrication of Ti6Al4V dental root and spinal plate equivalents was successfully demonstrated through machining of green Ti6Al4V compacts prepared by plastic dough processing. For process reliability, the green as well as the sintered components were characterized for physico-mechanical properties, defect and shrinkage analysis for dimensional accuracy of the desired objects and Weibull modulus study for ensuring reliability of mechanical properties of the samples. Evidently, green machining could be a simple viable alternative for manufacturing of titanium implants in a cost-effective way.

The Last decade saw significant growth in the digital terrestrial television (DTT) subscribers. The High peak-to-average power ratio (PAPR) of the transmitted signal is implied by the large fluctuations in its amplitude, which is a serious issue in the contemporary and next generation DTT broadcasting systems. These large fluctuations prevent feeding the high power amplifier (HPA) at an operating point near its non-linear (NL) saturation region, thereby lowering its power efficiency. For a better future, energy-efficient green communications is the need of hour. This paper focuses on digital predistortion (DPD), which is among the widely used techniques for HPA linearization in order to minimize the NL effects. DPD technique requires a feedback signal. This paper proposes a novel adding signal-based digital predistortion, where the output of the HPA is gradually linearized by adding a signal at the input in an iterative manner. By Taylor series approximation, the DPD problem can be posed as a convex one. We prove that a tighter upper bound exists for the convergence factor and instead of directly solving the convex problem, we pick a convergence factor value within its bounds that offers a good trade-off between convergence speed and residual error value. The simulation results show that the proposed technique can quickly linearize the HPA with good convergence.

The Filter Bank Multi-Carrier with Offset Quadrature Amplitude Modulation has already gained popularity as one of the alternatives to OFDM for next generation beyond 5G broadband wireless access systems. Like any other multicarrier modulation technique, FBMC is prone to non-linear (NL) effects of high power amplifier (HPA). Then, it is essential to mitigate NL effects to achieve energy efficient radio communications. This paper focuses on HPA linearization, and proposes a novel adding signal based digital predistortion with a quasi-optimal convergence rate. The simulation results show that proposed technique can quickly linearize the HPA.

The aim of this research work is to find the EFGM solutions of the unsteady magnetohydromagnetic natural convection heat transfer flow of a rotating, incompressible, viscous, Boussinesq fluid is presented in this study in the presence of radiative heat transfer. The Rosseland approximation for an optically thick fluid is invoked to describe the radiative flux. Numerical results obtained show that a decrease in the temperature boundary layer occurs when the Prandtl number and the radiation parameter are increased and the flow velocity approaches steady state as the time parameter t is increased. These findings are in quantitative agreement with earlier reported studies.The aim of this research work is to find the EFGM solutions of the unsteady magnetohydromagnetic natural convection heat transfer flow of a rotating, incompressible, viscous, Boussinesq fluid is presented in this study in the presence of radiative heat transfer. The Rosseland approximation for an optically thick fluid is invoked to describe the radiative flux. Numerical results obtained show that a decrease in the temperature boundary layer occurs when the Prandtl number and the radiation parameter are increased and the flow velocity approaches steady state as the time parameter t is increased. These findings are in quantitative agreement with earlier reported studies.

The nature of Casson fluid on MHD free convective flow of over an impulsively started infinite vertically inclined plate in presence of thermal diffusion (Soret), thermal radiation, heat and mass transfer effects is studied. The basic governing nonlinear coupled partial differential equations are solved numerically using finite element method. The relevant physical parameters appearing in velocity, temperature and concentration profiles are analyzed and discussed through graphs. Finally, the results for velocity profiles and the reduced Nusselt and Sherwood numbers are obtained and compared with previous results in the literature and are found to be in excellent agreement. Applications of the present study would be useful in magnetic material processing and chemical engineering systems.

International audience; A common issue in any multicarrier communication system such as the American digital video broadcasting (ATSC 3.0) standard is the high peaks of the transmitted signal. This disadvantage constrains the high power amplifiers to be deployed in their linear region which lowers their power efficiency. To overcome this issue, various techniques aiming at reducing the signal fluctuations have been investigated. Recently, Tone Reservation (TR) based algorithms have been studied and proposed for the second generation of Digital Video Broadcasting (DVB-T2) and ATSC 3.0 standards. The algorithm is essentially based on an iterative gradient approach to cancel one peak of the time-domain signal at each iteration. In this paper, we propose a novel TR-based algorithm implementable and compatible with the ATSC 3.0 standard and named as Grouped Carrier Peak Windowing (GCPW). This algorithm is based on a new kernel definition targeting the cancellation of multiple signal peaks at a time which highly reduces the total number of iterations, therefore reducing the system global latency and being more suited for implementation in today's ATSC 3.0 transmitters. Taking into account hardware resources requirements, we propose a new method to select the highest signal peaks to be considered in the PAPR reduction process. Hence, the system latency, complexity and memory resources are reduced and better performance than the ATSC 3.0 gradient-based algorithm can be offered. The implementation of the GCPW algorithm in fixed-point architectures is also studied and optimized in this paper. We demonstrate through simulation results that the proposed algorithm offers very good performance/latency/complexity/memory trade-off in both floating and fixed point implementations.

International audience; In this paper, the problem of peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) signals is investigated in the context of second generation of digital video broadcasting for terrestrial transmission (DVB-T2) and the American digital video broadcasting standard ATSC3.0. As a multicarrier modulation technique is characterized by a high PAPR of the transmitted signal and OFDM is prone to non-linear (NL) effects of power amplifiers. DVB-T2 and ATSC3.0 have adopted a gradient-based tone reservation (TR) PAPR reduction technique which is based on an iterative process where, at each iteration, a predefined kernel is used to reduce one peak in time domain. Recently, a new TR PAPR reduction technique termed individual carrier allocation for multiple peaks (ICMP), based on a novel kernel definition has been proposed. However, it suffers from latency issues in ATSC3.0 and higher modes of DVB-T2. So, we propose another novel TR technique, grouped ICMP (GICMP). The simulation results show that GICMP offers better performance than the gradient-based DVB-T2 algorithm. Furthermore, it not only yields the same performance as ICMP but also has less latency. © 2017 IEEE.

With the advent of technology, there has been a rapid increase in data acquisition. Among the several types of data gathered, interpreting multimedia data by a machine without human intervention is a challenge. Extracting meaningful content from videos will help provide better solutions in various domains. Banking on processing the videos as our rudimentary concept, this paper intends to detect the expressiveness of an individual. Many traditional approaches exist to address this situation, however Deep learning is used in this work to achieve the goal. LSTM (Long Short Term Memory) is our selected implementation construct. For training the network MIT Affectiva dataset has been chosen, which comprises of videos of individuals responding to Superbowl commercials. Extending this network, two front ends for testing the video sample are provided. One is a web page for uploading the videos and displaying the results and the other is an IoT device. This device records the video of an individual's response and sends it to the processing server. The responses of individuals towards a particular commercial are recorded and the system is tested on it. The results obtained are examined and the scope for various interpretations are shown. The expressiveness detected becomes a pivotal feedback for the makers of commercials, paving the way for their improvement.