Bobby interviews Rita Madden, the author of the new AFP book Food, Faith, and Fasting: A Sacred Journey to Better Health.

Dr. Rossi address issues of the purity of the heart and mind in relation to sexual chastity.

Dr. Albert Rossi interviews Dr. Michael Legaspi about the experience of his daughter becoming a monastic.

Fr. Philip LeMasters explains that our diet and eating habits have a profound spiritual and moral significance as they shape who we become as people and how we relate to others and to the Lord.

In this week’s broadcast, Archimandrite Irenei offers a reflection on a selection of sayings of St John Chrysostom on the pastoral nature of fasting as an act of charity. In what sense does our fast minister to our neighbor?

In this week's broadcast, Fr. Dcn. Matthew offers a reflection on a selection of sayings of St John Chrysostom on the pastoral nature of fasting as an act of charity. In what sense does our fast minister to our neighbor?

Listen to an interview with Bev Cooke about her new book from Conciliar Press: Royal Monastic: Princess Ileana of Romania. This is the true story of a princess who later became Mother Alexandra, the founder of the Holy Transfiguration monastery in Ellwood City, PA.

Bobby Maddex, Operations Manager of Ancient Faith Radio, interviews John Maddex, the CEO of Conciliar Media Ministries, about the recent electrical storm here in Chesterton, IN, that incapacitated our streaming music station. Can you help us with the funds needed to make sure that this situation never occurs again? We would really appreciate it!

On this special episode of Ancient Faith Presents, Mother Abbess Gabriella speaks at the Third Annual Winter Dinner to support Holy Dormition of the Mother of God Monastery in Rives Junction, Michigan. Her talk is titled “Thoughts: A Monastic Perspective.”

On a special edition of Ancient Faith Presents, Elissa Bjeletich, the host of the AFR podcast Raising Saints, interviews Melissa Naasko, the author of Fasting as a Family: Planning and Preparing Delicious Lenten Meals, published by Ancient Faith Publishing.

Bobby Maddex, Operations Manager of Ancient Faith Radio, interviews Melinda Johnson, the Director of Marketing and Development with Ancient Faith Ministries, about our upcoming Ancient Faith Writing and Podcasting Conference.

Bobby Maddex interviews Melinda Johnson, the Marketing Director of Ancient Faith Ministries, about the 2017 Ancient Faith Writing and Podcasting Conference, which will take place at Antiochian Village this coming June 15-17.

Melinda Johnson, the Marketing Director of Ancient Faith Ministries, talks about the Ancient Faith Writing and Podcasting Conference, which will take place June 13-15 at Antiochian Village in Bolivar, Pennsylvania. Click here to register!

Bobby Maddex interviews Katherine Hyde, the Acquisitions Editor of Ancient Faith Publishing, about the Ancient Faith Writing and Podcasting Conference.

Bobby Maddex interviews Rita Madden, a Master of Public Health, a registered dietician, and the host of the AFR podcast Food, Faith, and Fasting, about her upcoming virtual conference.

When fasting, we focus on what goes into our mouths, what we eat. But what about what comes out of our mouths, what we say?

Sometimes we talk about "giving up" something for Lent. Is the Church asking us to give up what we want or inviting us to build the discipline we need to make the right choices?

Why do we fast? What can that teach us about food?

First, let me tell you a little story involving butterflies and bladders. I've spent the past few days at MicroConf. Just a phenomenal conference, full of like-minded folks, loaded with actionable content. Not to get too carried away, but it...

In 2014, shops started charging a minimum of 5p per bag in attempt to reduce waste.

BBC Radio Stoke’s Stuart George discusses the unveiling of Vale Park's John Rudge statue.

Nutcrackers, Snowmen... and A Very Naughty Christmas.

A while back, I blogged about what it means to be Cloud Native. One of the key issues is multi-tenancy. As I discussed in that blog, there is a huge cost benefit in resources to multi-tenancy. This is how we can afford to run http://cloud.wso2.com and offer multi-tenant Tomcat currently for free beta use.

Today Amazon announced Elastic Beanstalk. They call it a PaaS. Unfortunately Elastic Beanstalk is only multi-tenant at the VM layer - in other words it is fundamentally IaaS not PaaS. In other words you don't get the true benefit of PaaS: every Beanstalk user has to pay for at least one EC2 instance. Amazon tries to put this in a nice light:

Each of your Elastic Beanstalk applications will be run on one or more EC2 instances that are provisioned just for your application. 

Since its birth, the stock market has received widespread attention from many scholars and investors. However, there are many factors that affect stock prices, including the company's own internal factors and the impact of external policies. The extent and manner of fundamental impacts also vary, making stock price predictions very difficult. Based on this, this article first introduces the research significance of the stock market prediction framework, and then conducts academic research and analysis on two key sentences of stock market prediction and artificial intelligence in stock market prediction. Then this article proposes a constructive algorithm theory, and finally conducts a simulation comparison experiment and summarises and discusses the experiment. Research results show that the neural network prediction method is more effective in stock market prediction; the minimum training rate is generally 0.9; the agency's expected dilution rate and the published stock market dilution rate are both around 6%.

The supply chains of the Canadian forest products industry are largely dependent on accurate demand forecasts. The USA is the major export market for the Canadian forest products industry, although some Canadian provinces are also exporting forest products to other global markets. However, it is very difficult for each province to develop accurate demand forecasts, given the number of factors determining the demand of the forest products in the global markets. We develop multi-layer feed-forward artificial neural network (ANN) models for demand forecasting of the Canadian forest products industry. We find that the ANN models have lower prediction errors and higher threshold statistics as compared to that of the traditional models for predicting the demand of the Canadian forest products. Accurate future demand forecasts will not only help in improving the short-term profitability of the Canadian forest products industry, but also their long-term competitiveness in the global markets.

Action recognition plays a vital role in analysing human body behaviour and has significant implications for research and education. However, traditional recognition methods often suffer from issues such as inaccurate time and spatial feature vectors. Therefore, this study addresses the problem of inaccurate recognition of aerobic gymnastics action image data and proposes a visualised three-dimensional convolutional neural network algorithm-based action recognition model. This model incorporates unsupervised visualisation methods into the traditional network and enhances data recognition capabilities through the introduction of a random noise perturbation enhancement algorithm. The research results indicate that the data augmented with noise perturbation achieves the lowest mean square error, reducing the error value from 0.3352 to 0.3095. The use of unsupervised visualisation analysis enables clearer recognition of human actions, and the algorithm model is capable of accurately recognising aerobic movements. Compared to traditional algorithms, the new algorithm exhibits higher recognition accuracy and superior performance.

To assess a country's economic outlook and achieve higher economic growth, econometric models and prediction techniques are significant tools. Policymakers are always concerned with the correct future estimates of economic variables to take the right economic decisions, design better policies and effectively implement them. Therefore, there is a need to improve the predictive accuracy of the existing models and to use more sophisticated and superior algorithms for accurate forecasting. Deep learning models like recurrent neural networks are considered superior for forecasting as they provide better predictive results as compared to many of the econometric models. Against this backdrop, this paper presents the feasibility of using different deep-learning neural network architectures for trade forecasting. It predicts export trade using different recurrent neural architectures such as 'vanilla recurrent neural network (VRNN)', 'bi-directional long short-term memory network (Bi-LSTM)', 'bi-directional gated recurrent unit (Bi-GRU)' and a hybrid 'bi-directional LSTM and GRU neural network'. The performances of these models are evaluated and compared using different performance metrics such as Mean Square Error (MSE), Mean Absolute Error (MAE) Root Mean Squared Error (RMSE), Root Mean Squared Logarithmic Error (RMSLE) and coefficient of determination <em>R</em>-squared (<em>R</em>²). The results validated the effective export prediction for India.

Aim/Purpose: In the United States, the Centers for Disease Control and Prevention (CDC) tracks the disease activity using data collected from medical practice's on a weekly basis. Collection of data by CDC from medical practices on a weekly basis leads to a lag time of approximately 2 weeks before any viable action can be planned. The 2-week delay problem was addressed in the study by creating machine learning models to predict flu outbreak. Background: The 2-week delay problem was addressed in the study by correlation of the flu trends identified from Twitter data and official flu data from the Centers for Disease Control and Prevention (CDC) in combination with creating a machine learning model using both data sources to predict flu outbreak. Methodology: A quantitative correlational study was performed using a quasi-experimental design. Flu trends from the CDC portal and tweets with mention of flu and influenza from the state of Georgia were used over a period of 22 weeks from December 29, 2019 to May 30, 2020 for this study. Contribution: This research contributed to the body of knowledge by using a simple bag-of-word method for sentiment analysis followed by the combination of CDC and Twitter data to generate a flu prediction model with higher accuracy than using CDC data only. Findings: The study found that (a) there is no correlation between official flu data from CDC and tweets with mention of flu and (b) there is an improvement in the performance of a flu forecasting model based on a machine learning algorithm using both official flu data from CDC and tweets with mention of flu. Recommendations for Practitioners: In this study, it was found that there was no correlation between the official flu data from the CDC and the count of tweets with mention of flu, which is why tweets alone should be used with caution to predict a flu out-break. Based on the findings of this study, social media data can be used as an additional variable to improve the accuracy of flu prediction models. It is also found that fourth order polynomial and support vector regression models offered the best accuracy of flu prediction models. Recommendations for Researchers: Open-source data, such as Twitter feed, can be mined for useful intelligence benefiting society. Machine learning-based prediction models can be improved by adding open-source data to the primary data set. Impact on Society: Key implication of this study for practitioners in the field were to use social media postings to identify neighborhoods and geographic locations affected by seasonal outbreak, such as influenza, which would help reduce the spread of the disease and ultimately lead to containment. Based on the findings of this study, social media data will help health authorities in detecting seasonal outbreaks earlier than just using official CDC channels of disease and illness reporting from physicians and labs thus, empowering health officials to plan their responses swiftly and allocate their resources optimally for the most affected areas. Future Research: A future researcher could use more complex deep learning algorithms, such as Artificial Neural Networks and Recurrent Neural Networks, to evaluate the accuracy of flu outbreak prediction models as compared to the regression models used in this study. A future researcher could apply other sentiment analysis techniques, such as natural language processing and deep learning techniques, to identify context-sensitive emotion, concept extraction, and sarcasm detection for the identification of self-reporting flu tweets. A future researcher could expand the scope by continuously collecting tweets on a public cloud and applying big data applications, such as Hadoop and MapReduce, to perform predictions using several months of historical data or even years for a larger geographical area.

Aim/Purpose: The purpose of this study is to discover usage differences in task performance by students of different cultures, by examining procrastination patterns from a national cultural perspective and exploring the effect of multicultural virtual teamwork on students’ individual procrastination. Background: This study aims to examine higher-education entrepreneurial learning in the context of multicultural virtual teamwork, as performed during participation on a Global Entrepreneurship course. Methodology: The methodology consists of quantitative comparative data analytics preceding and subsequent to intercultural team activities. This research is based on analyses of objective data collected by Moodle, the LMS used in the In2It project, in its built-in log system from the Global Entrepreneurship course website, which offers students diverse entities of information and tasks. In the examined course, there were 177 participants, from three different countries: United Kingdom, France and Israel. The students were grouped into 40 multicultural virtual (not face-to-face) teams, each one comprised of participants from at least two countries. The primary methodology of this study is analytics of the extracted data, which was transferred into Excel for cleaning purposes and then to SPSS for analysis. Contribution: This study aims to discover the effects of multicultural teamwork on individual procrastination while comparing the differences between cultures, as there are only a few studies exploring this relation. The uniqueness of this study is using and analyzing actual data of student procrastination from logs, whereas other studies of procrastination in multicultural student teams have measured perceived procrastination, collected using surveys. Findings: The results show statistical differences between countries in procrastination of individual assignments before team working: students from UK were the most procrastinators and Israeli students were the least procrastinators, but almost all students procrastinated. However, the outcome of the teamwork was submitted almost without procrastination. Moreover, procrastination in individual assignments performed after finishing the multicultural teamwork dramatically decreased to 10% of the students’ prior individual procrastination. Recommendations for Practitioners: The results from this study, namely, the decline of the procrastination after the multicultural virtual teamwork, can be used by global firms with employees all over the world, working in virtual multicultural teams. Such firms do not need to avoid multicultural teams, working virtually, as they can benefit from this kind of collaboration. Recommendation for Researchers: These results can be also beneficial for academic researchers from different cultures and countries, working together in virtual multicultural teams. Impact on Society: Understanding the positive effect of virtual multicultural teamwork, in mitigating the negative tendency of students from diverse cultures to procrastinate, as concluded in this study, can provide a useful tool for higher education or businesses to mitigate procrastination in teamwork processes. It can also be used as an experiential learning tool for improving task performance and teamwork process. Future Research: The relation between procrastination and motivation should be further examined in relation to multicultural virtual teams. Further research is needed to explore the effect of multicultural virtual teamwork during the teamwork process, and the reasoning for this effect.

The Pakistani drama star expressed her disbelief at being asked to attend a late-night audition in revealing attire.

Plastic pollution hits Southeast Asia, Sub-Saharan Africa, and India hardest, with India leading in production.

Watch the first two practice days from this year's Battle of Hastings. Our bro Felix Prangenberg's got invited from Jordan Godwin to battle the other Teams at this year's Battle of Hastings.



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Kamala Harris's defeat runs deeper for Democrats than its surface appearance. Even at first sight, it was stunning: Ms. Harris didn't just lose the presidency but, unthinkably, the popular vote too.

Two former Olympic champions are in the race to be the next IOC president. So is a prince of a Middle East kingdom and the son of a former president. The global leaders of cycling, gymnastics and skiing also are in play.

Simone Biles simply wanted to mix it up when the gymnastics superstar invited some of the top American men to join her post-Olympic Tour.

He's been tough on Russia, led the charge to put prize money in the pockets of athletes and pushed for a definitive but much-derided resolution in the longstanding debate over transgender athletes.

Stop making excuses, procrastinators. Whether you overestimate your “natural talent”, complaining about “not having enough time” or being “too old to succeed anyway,” there is ... Read more

The post Seven Ways to Procrastinate Less and Do More appeared first on CMUSE.

"Castiglione (Acoustic Demo)" is now available for streaming on Spotify, Apple Music and YouTube.

The post Local band releases song honoring former Red Sox announcer Joe Castiglione appeared first on Boston.com.

"This guy's like one of the greatest resources in football that we have, and they don't tap into any of it."

The post ‘It’s just not good’: Bill Simmons offered a blunt critique of Tom Brady’s broadcasting style appeared first on Boston.com.

This executive order will allow the state to bring more diversity into its hiring processes, benefitting the overall workforce, according to the governor.

The post Healey to drastically limit degree requirements on state job listings appeared first on Boston.com.