Comparative Study of the Dynamics of Cosmic Rays for the Pakistan and China Atmospheric Regions

This paper presents an analysis of cosmic ray intensity in Pakistan air space using spatial interpolation, comparing it with Chinese cosmic ray records from 1984 to 1993. The Exploratory Data Analytic (EDA) approach was applied to compare the cosmic ray fluctuations in both countries. The time series plot of the monthly cosmic rays showed relatively flatter counts in Pakistan than in China. The cosmic ray data for the years 1984 to 1993 fell within Solar Cycle 22, which lasted from 1986 to 1996, with its maximum phase in 1989 to 1991. The cosmic radiation varies between the atmospheric regions of Pakistan and China due to modulations in intensity that are accessible accordingly. It can be explained by purely astrophysical phenomena: (1) the source of emission of cosmic radiation may be different, (2) the rate at which emanation takes place depends on bursts of deep space dynamical objects from their sources that may be affected by solar wind and other solar radiations. Therefore, modulations in intensity are not only due to different geophysical locations. This study will help government organizations to predict and forecast cosmic rays values

Some Remarks on Results Related to ∇-Convex Function

In the present article, we give new techniques for proving general identities of the Popoviciu type for discrete cases of sums for two dimensions using higher-order ∇-divided difference. Also, integral cases are deduced by different methods for differentiable functions of higher-order for two variables. These identities are a generalization of various previously established results. An application for the mean value theorem is also presented

Comparing the Effectiveness of Different Reinforcement Stimuli in a Robotic Therapy for Children With ASD

Recent research has shown reliability in robotic therapies for improvement in core impairments of autism. To improve the efficiency of communication using robots, this study evaluates the effectiveness of three different stimuli in a robotic intervention for children with autism spectrum disorder. Three different reinforcement stimuli presented in least-to-most (LTM) order introduced in this therapy using NAO robot are: visual (color variation), auditory and motion cues. The therapy was tested on 12 ASD children, 4 out of 12 children fall under mild category whereas 8 fall under the minimal category of autism. The experimentation was conducted for 2 months. Total 8 experiments were conducted with 1 trial per week. Total 12 cues were given per trial, 4 cues corresponding to each category. In total 96 cues were given per subject, 32 cues from each category. The results indicate a general trend for linking a particular autism category with the most effective stimulus for that category. It can be concluded that visual cue (color variation) is the most effective reinforcement stimulus for children with minimal autism as 8 out of 8 i.e., 100% were more responsive to visual cues whereas for children with mild autism category, 3 out of 4 i.e., 75% are more receptive towards the motion stimulus. The parameters used for assessment were joint attention and the time eye contact is maintained. Single factor ANOVA was used for the statistical analysis of results with alpha is 0.05 and p-value 0.0342, F value is 3.7456 and F critical value is 3.2834. The test was performed on 96 ( $8\times 12$ ) trails in total, therefore ensuring the significance and reliability of our results

Board gender diversity and stock price crash risk: Going beyond tokenism

Abstract We empirically examine the role of board gender diversity in influencing stock price crash risk at the firm-level in twelve (12) Asia-Pacific Markets. Using a dataset comprising data from 1021 listed firms over the period 2006–2016, we employ a random effect model in a regression setting. Controlling for the firm and market-level variables, we find that board gender diversity results in lowering the stock price crash risk of the firm. Bifurcating women directors on corporate board into numerical representation (token and critical mass representation), the results support our main conjectures and suggest that the economic significance of this relationship is higher for firms that have three or more women directors on the board as compared to the firms that have less than three women directors on the corporate board. Our results are robust to alternative measures of stock price crash risk, potential endogeneity and selection biases

Comorbidities Associated With Attention-Deficit/Hyperactivity Disorder in Children and Adolescents at a Tertiary Care Setting

Studies have revealed high rates of neurodevelopmental and psychiatric comorbid conditions among individuals diagnosed with attention-deficit/hyperactivity disorder (ADHD). However, research on this topic in the Arab world has been limited. This study evaluates the medical, neurodevelopmental, and psychiatric comorbidities in children and adolescents diagnosed with ADHD in Dubai, United Arab Emirates (UAE). A total of 428 pediatric patients diagnosed with ADHD were included. Children and adolescents with ADHD had high rates of comorbid disorders. Twenty comorbid conditions were identified. More than 3 quarters of the study sample had at least 1 comorbid disorder. The most common comorbidity among children was autism spectrum disorder, and among adolescents was anxiety disorders. Comprehensive assessments are highly warranted to identify and manage associated comorbid conditions. Further research is needed in exploring the biopsychosocial factors contributing to the elevated rate of comorbidity in children and adolescents with ADHD

Development of a cost-based design model for spread footings in cohesive soils

The use of cost-effective construction design approaches is an emerging concept in the field of sustainable environments. The design of the foundation for the construction of any infrastructure-related building entails three basic requirements, i.e., serviceability limit state (SLS), ultimate limit state (ULS), and economics. Engineering economy coupled with safety are the two main essentials for a successful construction project. The conventional design approaches are based on hit and trial methods to approach cost-effective design. Additionally, safety requirements are prioritized over the economic aspect of foundation design and do not consider safety requirements and cost simultaneously. This study presents a design approach that considers foundation construction costs while satisfying all the technical requirements of a shallow foundation design. This approach is called an optimization process in which the cost-based isolated foundation design charts were developed based on the field SPT N data. The design charts are the first of their kind for the robust design of foundations and can be used to compare the economic impact of different bearing capacity models. Furthermore, the design framework considers the quantitative impact of the different applied factors of safety values in terms of cost. The results show that Vesic’s equation yields higher values of bearing capacities than Terzaghi and Meyerhof. On the other hand, Vesic’s theory offers a 37.5% reduction in cost as compared to the conventional design approach of the foundation for isolated footing

A hybrid group-based movie recommendation framework with overlapping memberships

Recommender Systems (RS) are widely used to help people or group of people in finding their required information amid the issue of ever-growing information overload. The existing group recommender approaches consider users to be part of a single group only, but in real life a user may be associated with multiple groups having conflicting preferences. For instance, a person may have different preferences in watching movies with friends than with family. In this paper, we address this problem by proposing a Hybrid Two-phase Group Recommender Framework (HTGF) that takes into consideration the possibility of users having simultaneous membership of multiple groups. Unlike the existing group recommender systems that use traditional methods like K-Means, Pearson correlation, and cosine similarity to form groups, we use Fuzzy C-means clustering which assigns a degree of membership to each user for each group, and then Pearson similarity is used to form groups. We demonstrate the usefulness of our proposed framework using a movies data set. The experiments were conducted on MovieLens 1M dataset where we used Neural Collaborative Filtering to recommend Top-k movies to each group. The results demonstrate that our proposed framework outperforms the traditional approaches when compared in terms of group satisfaction parameters, as well as the conventional metrics of precision, recall, and F-measure

A Preliminary Study on Effectiveness of a Standardized Multi-Robot Therapy for Improvement in Collaborative Multi-Human Interaction of Children with ASD

This research article presents a preliminary longitudinal study to check the improvement in multi-human communication of children with Autism Spectrum Disorder (ASD) using a standardized multirobot therapy. The research is based on a 3 step framework: 1) Human-Human Interaction, Stage-1 (HHIS1), 2) Human-Robot Interaction, Stage-2 (HRI-S2), and 3) Human-Human Interaction, Stage-3 (HHI-S3). All three stages of the therapy consist of two command sets: 1) Controls commands and 2) Evaluation commands (auditory commands, visual commands, and combination of both). The concept of multiple robots is introduced to help multi-human communication and discourage isolation in ASD children. The joint attention of an ASD child is improved by the robotic therapy in stage 2 considering it as a key parameter for a multi-human communication scenario. The improvement in joint attention results in better command following in a triad multi-human communication scenario in stage 3 as compared to stage 1. The proposed intervention has been tested on 8 ASD subjects with 10 sessions over a period of two and a half months (10 weeks). Each session of human-human interaction (stage 1 and 3) consisted of 14 cues whereas 18 cues were presented by each robot for human-robot interaction (stage 2). The results indicate an overall 86improvement in the social communication skills of ASD children in case of a multi-human scenario. Validation of results and effectiveness of the therapy has been further accomplished through the use of the Childhood Autism Rating Scale (CARS) score

Blockchain enabled data security in vehicular networks

Recently, researchers have applied blockchain technology in vehicular networks to take benefit of its security features, such as confidentiality, authenticity, immutability, integrity, and non-repudiation. The resource-intensive nature of the blockchain consensus algorithm makes it a challenge to integrate it with vehicular networks due to the time-sensitive message dissemination requirements. Moreover, most of the researchers have used the Proof-of-Work consensus algorithm, or its variant to add a block to a blockchain, which is a highly resource-intensive process with greater latency. In this paper, we propose a consensus algorithm for vehicular networks named as Vehicular network Based Consensus Algorithm (VBCA) to ensure data security across the network using blockchain that maintains a secured pool of confirmed messages exchanged in the network. The proposed scheme, based on a consortium blockchain, reduces average transaction latency, and increases the number of confirmed transactions in a decentralized manner, without compromising the integrity and security of data. The simulation results show improved performance in terms of confirmed transactions, transaction latency, number of blocks, and block creation time