The BFOQ Defense: Title VII’s Concession to Gender Discrimination

Should the BFOQ exception still exist? Because permitting discrimination under Title VII seems fundamentally contrary to the anti-discrimination purpose of the statute, this article questions whether the BFOQ defense is consistent with the aims of Title VII or whether, in actuality, the defense undermines the Act\u27s effectiveness by providing a loophole for employers to participate in the discriminatory practices Title VII seeks to forbid

Simulating peak ground acceleration by general regression and radial basis function and other neural networks in some regions of the world

Recording of ground motions with high amplitudes of  acceleration and velocity play a key role for designing engineering projects.Here we try to represent a reasonable prediction of peak ground acceleration which may create more than 1g acceleration in different regions. In this study, applying different structures of Neural Networks and using four key parameters , moment magnitude, rupture distance,  site class , style of faulting which an earthquake may cause serious effects on a site. We introduced a Radial Basis Function Network(RBF) with mean error of 14×10-3,as the best network for estimating the occurance probability of an earthquake with large value of PGA ?1g in a region. Also the result of applying Back propagation feed forward neural network(FFBP) for predicting high value of PGA, with Mean error of 17×10-3 , show a good coincidence with the result of the designed RBF Network. Keywords:Peak ground acceleration, Moment magnitude, Rupture distance, site class, Radial basis function, General regression neural network,

The intersection of blockchain technology and circular economy in the agri-food sector

A transition towards a circular economy within the agri-food sector requires the improvement of efficiency in resource utilization, the prevention of food loss or waste, whilst adopting regenerative agricultural practices. In addition to the technical challenges, the agri-food industry needs to address the food safety concerns resulting from biomass recycling processes. Increasingly, blockchain technology is gaining traction, moving towards more sustainable and precision agriculture. The blockchain is a decentralized, immutable, and shared database that records the provenance of digital assets, making it a suitable platform for traceability and food supply chain management. Despite its growing importance, the existing literature regarding these themes and the empirical evidence of blockchain-based solutions for a circular economy is rather fragmented. This paper offers a scoping review regarding the role of blockchain technology in the transition towards a circular food system. A total of 44 papers published in peer-reviewed journals were reviewed to identify new scientific insights into the application of blockchains within the agricultural sector. The results indicate that blockchain technology has a great potential in reducing food loss through optimized eco-efficiency (e.g., digitalization and integration with the Internet of Things) and by alleviating asymmetric information (by increasing transparency and reducing dependence on intermediaries). However, in the case of recycling efficiency, despite its potential, there remains a paucity of evidence regarding the use of blockchain technology in improving the residual valorization processes. Furthermore, there is a stream of literature focusing on the ability of blockchain-enabled traceability (e.g., for organic production or supply chain management). Yet, the role of blockchain traceability in the monitoring of risks from recycled biomass and the reporting of the sustainability performance in the supply chain has received scant attention within research literature. These results provide insights for supply chain management operations with the view of shifting towards a circular economy whilst also suggesting an agenda for future research areas

A Time-Sensitive IoT Data Analysis Framework

This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that meets the time-bound requirements of time-sensitive IoT applications. The proposed framework includes a novel task sizing and dynamic distribution technique that performs the following: 1) measures the computing and network resources required by the data analysis tasks of a time-sensitive IoT application when executed on available IoT devices, edge computers and cloud, and 2) distributes the data analysis tasks in a way that it meets the time-bound requirement of the IoT application. The TIDA framework includes a TIDA platform that implements the above techniques using Microsoft’s Orleans framework. The paper also presents an experimental evaluation that validates the TIDA framework’s ability to meet the time-bound requirements of IoT applications in the smart cities domain. Evaluation results show that TIDA outperforms traditional cloud-based IoT data processing approaches in meeting IoT application time-bounds and reduces the total IoT data analysis execution time by 46.96%

ConTaaS: An Approach to Internet-Scale Contextualisation for Developing Efficient Internet of Things Applications

The Internet of Things (IoT) is a new internet evolution that involves connecting billions of sensors and other devices to the Internet. Such IoT devices or IoT things can communicate directly. They also allow Internet users and applications to access and distil their data, control their functions, and harness the information and functionality provided by multiple IoT devices to offer novel smart services. IoT devices collectively generate massive amounts of data with an incredible velocity. Processing IoT device data and distilling high-value information from them presents an Internet-scale computational challenge. Contextualisation of IoT data can help improve the value of information extracted from IoT. However, existing contextualisation techniques can only handle small datasets from a modest number of IoT devices. In this paper, we propose a general-purpose architecture and related techniques for the contextualisation of IoT data. In particular, we introduce a Contextualisation-as-a-Service (ConTaaS) architecture that incorporates scalability improving techniques, as well as a proof-of-concept implementation of all these that utilises elastic cloud-based infrastructure to achieve near real-time contextualisation of IoT data. Experimental evaluations validating the efficiency of ConTaaS are also provided in this paper

The Effects of Different Agitation Techniques of Canal Irrigant on Tubular Penetration of a Bioceramic Sealer

Introduction: This study aimed to compare the effects of different agitation techniques of sodium hypochlorite (NaOCL) as the final irrigation with XP-Finisher file, passive ultrasonic irrigation (PUI), Er:YAG laser and irrigation with conventional syringes, on penetration of Sure Seal Root bioceramic sealer into dentinal tubules. Methods and Materials: Forty freshly extracted single-rooted human teeth were included in the present in vitro study. All the teeth were prepared up to #40 (4%) with Bio Race rotary file system, using crown-down technique. After chemomechanical preparation, the teeth were randomly assigned to 4 groups based on the agitation protocol: conventional needle irrigation (CNI) with a 30-G needle in a syringe, PUI, Er:YAG laser and XP-Finisher file, Subsequent to the agitation procedure, the root canals were obturated with tapered bioceramic-covered gutta-percha point and, bioceramic sealer, using the single-cone technique. The maximum penetration of the sealer into the dentinal tubules was determined in the coronal, middle and apical thirds using the scanning electron microscope (SEM) technique. After confirmation of the normal distribution of data with Shapiro-Wilk test, Data were analyzed using the one-way ANOVA and Tukey tests. Results: The mean penetration depth of the bioceramic sealer into the dentinal tubules in the PUI group was greater than that of other groups; however, the difference between the two PUI and Er:YAG laser groups in the apical third was not significant (P=0.078). Er:YAG laser, PUI and XP-Finisher file agitation techniques resulted in significantly greater penetration of the bioceramic sealer into the dentinal tubules compared to the CNI (P<0.001). The XP-Finisher file technique in the apical (P=0.752) and middle thirds (P=0.339) and the Er:YAG laser technique in the apical thirds (P=0.086) were not significantly different from the conventional irrigation technique. Conclusion: The PUI technique resulted in significantly deeper penetration of the Bioceramic sealer into the dentinal tubules compared to the three other techniques. Keywords: Endodontics; Lasers; Root Canal Preparation; Ultrasonic; XP Endo Finisher

GWO-FI: A novel machine learning framework by combining Gray Wolf Optimizer and Frequent Itemsets to diagnose and investigate effective factors on In-Hospital Mortality and Length of Stay among Kermanshahian Cardiovascular Disease patients

Investigation and analysis of patient outcomes, including in-hospital mortality and length of stay, are crucial for assisting clinicians in determining a patient's result at the outset of their hospitalization and for assisting hospitals in allocating their resources. This paper proposes an approach based on combining the well-known gray wolf algorithm with frequent items extracted by association rule mining algorithms. First, original features are combined with the discriminative extracted frequent items. The best subset of these features is then chosen, and the parameters of the used classification algorithms are also adjusted, using the gray wolf algorithm. This framework was evaluated using a real dataset made up of 2816 patients from the Imam Ali Kermanshah Hospital in Iran. The study's findings indicate that low Ejection Fraction, old age, high CPK values, and high Creatinine levels are the main contributors to patients' mortality. Several significant and interesting rules related to mortality in hospitals and length of stay have also been extracted and presented. Additionally, the accuracy, sensitivity, specificity, and auroc of the proposed framework for the diagnosis of mortality in the hospital using the SVM classifier were 0.9961, 0.9477, 0.9992, and 0.9734, respectively. According to the framework's findings, adding frequent items as features considerably improves classification accuracy.Comment: 14 pages, 2 figures, 9 table

Investigating the Effect of Structural Transformation on the Efficiency of VAT Collection in the Provinces in Iran

Value-added tax is levied at various stages of the import, production, distribution, and consumption chain based on a percentage of the value of goods sold or services provided at each stage and ultimately paid by the final consumer. Structural transformation is considered as one of the variables affecting the efficiency of VAT collection often has led to an increase in the share of services in the total value added of the economy. In this study, the effect of structural transformation on the efficiency of VAT collection in provinces of Iran during 2008-2016. The results indicate that the ratio of value added of the service sector to total value added has a negative and significant effect on the efficiency of VAT collection. The value-added ratio of the services sector to the value added of the industrial sector has a negative and significant effect on the efficiency of VAT collection. Also, GDP growth per capita, Gini coefficient and the interval of value-added ratio of the agricultural sector of total value added has a negative effect on the efficiency of VAT collection. The rate of urbanization and the ratio of construction expenditures to total government expenditures have a positive and significant effect on the efficiency of VAT collection in the provinces

The Relationship between the Aspects of Learning Organization on Empowering the Employees in Amin Police University

The development of intangible assets (knowledge) has a basic role in the success of organizations in face of changes and evolutions. Todays, proper management of human resources is so important that to train human resources, the procurement of conditions that empower the learning organization has become a basic necessity. The goal of the present paper is to analyze the relationship between aspects of a learning organization on the empowerment of the employees of Amin Police University. The statistical subject group consisted of all the employees of Amin Police University, including employees of deputy offices, centers and staff offices of the university, which added up to 450 employees. Using the Cochran formula, 207 people were selected in classification sampling method as the sample. The present study is a description of the type of coordination and it is a practical study. The data collection tool is a standard questionnaire that includes the two parts of demographic questions and the main part that included 45 questions (30 questions of learning organization and 15 questions of empowerment) that were used based on Senge's model and also Spritzer's psychological empowerment. Their justifiability was confirmed by professors and experts of management and their stability was also confirmed using the Cronbach's Alpha test with 89 percent. To analyze the data, regression analysis was utilized. Results showed that in the studied subject group, there is a significant relationship between the factors of the aspects of a learning organization and the empowerment of the employees at Amin Police University. Therefore, it is suggested that such a study be done in the other universities and its results be compared with this research