Dr. Rossi explores what Jesus meant when he said, "Be ye perfect."

Examining a passage from the anonymous second-century Epistle to Diognetus, Archimandrite Irenei explores the witness borne by the early Christian community and asks: does it reflect our Christian testimony today?

What has a man whose obedience once caused a barren stick to blossom forth a tree in the desert to tell us today about the life of virtue? Is it possible for man today to partake of all the virtues? In this week’s broadcast, Fr. Matthew examines two sayings of Fr. John the Short of Egypt on the accessibility of all the virtues through the foundation of the love of neighbor.

What has a man whose obedience once caused a barren stick to blossom forth a tree in the desert to tell us today about the life of virtue? Is it possible for man today to partake of all the virtues? In this week’s broadcast, Archimandrite Irenei examines two sayings of Fr. John the Short of Egypt on the accessibility of all the virtues through the foundation of the love of neighbor.

Bobby Maddex interviews Chad Marine, the singer songwriter behind the group The Wonderful Mountain, which plays music characterized as Byzanfolk—a style that combines the traditions and teachings of the Orthodox Church with popular music.

On the Sunday of All Saints Fr. Pat looks at three aspects of Christian holiness.

Fr. Pat takes a closer look at the true meaning of Hanukkah.

This week we're answering another of your questions! What should we do when we try showing love to people and don't get anything positive in return?

Scatter the "seeds" the Lord has provided so you may increase the harvest of your righteousness.

In both of these Gospels St. Peter gets out of the boat. Would you? Matthew 14:22-34, John 21:7

How to become a Saint. Focus on Jesus Christ.

Today, I talk to Darrell Vesterfelt, who is a longtime friend who helped grow ConvertKit in our craziest growth times (from $100,000/mo when he joined to $500,000/mo in just over a year). Darrell is one of the best marketers I know. He is the Founder and former CEO of Good People Digital, the Co-Founder of […]

Lost Shore has a wave pool three times the size of Wembley football pitch - but how does it work?

Harris McCutcheon, 17, is representing Scotland on a new Butterfly Conservation panel.

Pop star Robbie Williams will perform at Bath's Royal Crescent in June next year.

Singer Catherine Lawless features in a film about agoraphobia, showing at Headfest in Bedford.

BBC CWR's Clive Eakin chats to the 27-year-old ahead of this weekend versus Caldy!

Ben Elton is bringing his new tour to the county, but says he visits Norfolk regularly.

Microsoft is set to announce at least one, and possibly two new phones this week, a successor to the most popular Windows Phone ever made, the Lumia 520, and if rumors are correct, a successor to the 1320, …

It feels odd, writing your first blog post in seven years. It used to be such a large part of my life—and this blog used to be such a core part of my work and engagement with my community—that you’d think you’d never forget how to do it. I wrote here almost every day for […]

The Santa Stair Climb returns to One Canada Square.

Illuminations to be dotted among the skyscrapers again.

Formula 1 drivers urged the operators of the Interlagos circuit to improve the new surface they laid ahead of this year's event.

In the world of translation, Trados Studio’s PerfectMatch feature is like the overachieving student who always gets straight A’s, and its academic partner is the brilliant but slightly disorganised professor.  PerfectMatch, with its meticulous and precise matching capabilities, often finds itself patiently sorting through the professor’s vast but somewhat chaotic repository of knowledge.  Picture PerfectMatch … Continue reading The PerfectMatch…

Advances in mobile technologies are opening new possibilities to support collaborative activities through mobile devices. Unfortunately, mobile collaborative systems have been difficult to conceive, design and implement. These difficulties are caused in part by their unclear requirements and developers' lack of experience with this type of systems. However, several requirements involved in the collaborative back-end of these products are recurrent and should be considered in every development. This paper introduces a characterization of mobile collaboration and a framework that specifies a list of general requirements to be considered during the conception and design of a system in order to increase its probability of success. This framework was used in the development of two mobile collaborative systems, providing developers with a base of back-end requirements to aid system design and implementation. The systems were positively evaluated by their users.

Visualization of search results is an essential step in the textual Information Retrieval (IR) process. Indeed, Information Retrieval Interfaces (IRIs) are used as a link between users and IR systems, a simple example being the ranked list proposed by common search engines. Due to the importance that takes visualization of search results, many interfaces have been proposed in the last decade (which can be textual, 2D or 3D IRIs). Two kinds of evaluation methods have been developed: (1) various evaluation methods of these interfaces were proposed aiming at validating ergonomic and cognitive aspects; (2) various evaluation methods were applied on information retrieval systems (IRS) aiming at measuring their effectiveness. However, as far as we know, these two kinds of evaluation methods are disjoint. Indeed, considering a given IRI associated to a given IRS, what happens if we associate this IRI to another IRS not having the same effectiveness. In this context, we propose an IRI evaluation framework aimed at evaluating the suitability of any IRI to different IR scenarios. First of all, we define the notion of IR scenario as a combination of features related to users, IR tasks and IR systems. We have implemented the framework through a specific evaluation platform that enables performing IRI evaluations and that helps end-users (e.g. IRS developers or IRI designers) in choosing the most suitable IRI for a specific IR scenario.

The user experience of any software or website consists of elements from the conceptual to the concrete level. These elements of user experience assist in the design and development of user interfaces. On the other hand, ontologies provide a framework for computable representation of user interface elements and underlying data. This paper discusses strategies of introducing ontologies at different user interface layers adapted from user experience elements. These layers range from abstract levels (e.g. User needs/Application Objectives) to concrete levels (e.g. Application User Interface) in terms of data representation. The proposed ontological framework enables device independent, semi-automated GUI construction which we will demonstrate at a personal information management example.

1. Attention, votre airfryer pourrait produire une substance cancérigène dans vos aliments selon une étude  Yahoo Actualités
2. 3 bonnes raisons de choisir un Airfryer en 2024  La Provence
3. Nos 30 recettes rapides et faciles au Airfryer, du plat de résistance au dessert  Le Figaro
4. Les air fryers sont-ils dangereux pour la santé ? Une étude lance l'alerte  Allo Docteurs
5. Airfryer : attention aux acrylamides potentiellement cancérigènes  Pourquoi Docteur ?

1. MSI Katana 15 B13VFK-2201FR, PC portable gamer multimédia performant 15" IPS 144Hz sous GeForce RTX 4060 Core i7-H et SSD 1 To  LaptopSpirit
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3. MSI Thin 15 B12UCX-2412FR, Ultrabook polyvalent 15" évolutif fin et léger sous Intel Core i5-H avec GeForce RTX 2050 pour jouer à des jeux modestes  LaptopSpirit
4. MSI GeForce RTX 4060 : la carte graphique est à son prix le plus bas jamais atteint sur ce site  Le Parisien
5. À moins de 700 euros ce dimanche, cela serait dommage de ne pas se jeter sur ce PC gamer  Ouest-France

TCP BBR is one of the most powerful congestion control algorithms. In this article, we provide a comprehensive review of BBR analysis, expanding on existing knowledge across various fronts. Utilising ns3 simulations, we evaluate BBR's performance under diverse conditions, generating graphical representations. Our findings reveal flaws in the probe's RTT phase duration estimation and unequal bandwidth sharing between BBR and CUBIC protocols. Specifically, we demonstrated that the probe's RTT phase duration estimation algorithm is flawed and that BBR and CUBIC generally do not share bandwidth equally. Towards the end of the article, we propose a new improved version of TCP BBR which minimises these problems of inequity in bandwidth sharing and corrects the inaccuracies of the two key parameters RTprop and cwnd. Consequently, the BBR' protocol maintains very good fairness with the Cubic protocol, with an index that is almost equal to 0.98, and an equity index over 0.95.

A number of studies have applied social network analysis (SNA) to show that the patterns of social interaction between software developers explain important organisational outcomes. However, these insights are based on a single network relation (i.e., uniplex social ties) between software developers and do not consider the multiple network relations (i.e., multiplex social ties) that truly exist among project members. This study reassesses the understanding of software developer networks and what it means for performance in software development settings. A systematic review of SNA studies between 1990 and 2020 across six digital libraries within the IS and management science domain was conducted. The central contributions of this paper are an in-depth overview of SNA studies to date and the establishment of a research agenda to advance our knowledge of the concept of multiplexity on how a multiplex perspective can contribute to a software developer's coordination of tasks and performance advantages.

Pandemic has compelled the entire world to change their way of life and work. To control the infection rate, academic institutes deliver education online similarly. At least one smartphone is available in every home, and students use their smartphones to attend class. The study investigates the link between smartphone usage (SU) and academic performance (AP) during the pandemic. 490 data were obtained from various institutions and undergraduate students using stratified random sampling. These components were identified using factor analysis and descriptive methods, while the relationship of SU and AP based on gender classification was tested using Smart-PLS-SEM. The findings show that SU has a substantial relationship with academic success, whether done in class or outside of it. Even yet, the study found that SU and AP significantly impact both male and female students. Furthermore, the research focuses on SU outside and within the classroom to improve students' AP.

Prior work demonstrates the importance of introducing young children to programming and engineering content before gender stereotypes are fully developed and ingrained in later years. However, very little research on gender and early childhood technology interventions exist. This pilot study looks at N=45 children in kindergarten through second grade who completed an eight-week robotics and programming curriculum using the KIWI robotics kit. KIWI is a developmentally appropriate robotics construction set specifically designed for use with children ages 4 to 7 years old. Qualitative pre-interviews were administered to determine whether participating children had any gender-biased attitudes toward robotics and other engineering tools prior to using KIWI in their classrooms. Post-tests were administered upon completion of the curriculum to determine if any gender differences in achievement were present. Results showed that young children were beginning to form opinions about which technologies and tools would be better suited for boys and girls. While there were no significant differences between boys and girls on the robotics and simple programming tasks, boys performed significantly better than girls on the advanced programming tasks such as, using repeat loops with sensor parameters. Implications for the design of new technological tools and curriculum that are appealing to boys and girls are discussed.

Aim/Purpose: Compared student academic performance on specific course requirements in a C# programming course across three instructional approaches: traditional, online, and flipped. Background: Addressed the following research question: When compared to the online and traditional instructional approaches, does the flipped instructional approach have a greater impact on student academic performance with specific course requirements in a C# programming course? Methodology: Quantitative research design conducted over eight 16-week semesters among a total of 271 participants who were undergraduate students en-rolled in a C# programming course. Data collected were grades earned from specific course requirements and were analyzed with the nonparametric Kruskal Wallis H-Test using IBM SPSS Statistics, Version 23. Contribution: Provides empirical findings related to the impact that different instructional approaches have on student academic performance in a C# programming course. Also describes implications and recommendations for instructors of programming courses regarding instructional approaches that facilitate active learning, student engagement, and self-regulation. Findings: Resulted in four statistically significant findings, indicating that the online and flipped instructional approaches had a greater impact on student academic performance than the traditional approach. Recommendations for Practitioners: Implement instructional approaches such as online, flipped, or blended which foster active learning, student engagement, and self-regulation to increase student academic performance. Recommendation for Researchers: Build upon this study and others similar to it to include factors such as gender, age, ethnicity, and previous academic history. Impact on Society: Acknowledge the growing influence of technology on society as a whole. Higher education coursework and programs are evolving to encompass more digitally-based learning contexts, thus compelling faculty to utilize instructional approaches beyond the traditional, lecture-based approach. Future Research: Increase the number of participants in the flipped instructional approach to see if it has a greater impact on student academic performance. Include factors beyond student academic performance to include gender, age, ethnicity, and previous academic history.

Aim/Purpose: Over the past few years, new approaches to introducing young children to computational thinking have grown in popularity. This paper examines the role that user interfaces have on children’s mastery of computational thinking concepts and positive interpersonal behaviors. Background: There is a growing pressure to begin teaching computational thinking at a young age. This study explores the affordances of two very different programming interfaces for teaching computational thinking: a graphical coding application on the iPad (ScratchJr) and tangible programmable robotics kit (KIBO). Methodology : This study used a mixed-method approach to explore the learning experiences that young children have with tangible and graphical coding interfaces. A sample of children ages four to seven (N = 28) participated. Findings: Results suggest that type of user interface does have an impact on children’s learning, but is only one of many factors that affect positive academic and socio-emotional experiences. Tangible and graphical interfaces each have qualities that foster different types of learning

Aim/Purpose: The goal of this paper is to examine whether having female robotics teachers positively impacts girls’ performance on programming and robotics tasks Background: Women continue to be underrepresented in the technical STEM fields such as engineering and computer science. New programs and initiatives are needed to engage girls in STEM beginning in early childhood. The goal of this work is to explore the impact of teacher gender on young children’s mastery of programming concepts after completing an introductory robotics program. Methodology: A sample of N=105 children from six classrooms (2 Kindergarten, 2 first grade, and 2 second grade classes) from a public school in Somerville, Massachusetts, participated in this research. Children were taught the same robotics curriculum by either an all-male or all-female teaching team. Upon completion of the curriculum, they completed programming knowledge assessments called Solve-Its. Comparisons between the performance of boys and girls in each of the teaching groups were made. Findings: This paper provides preliminary evidence that having a female instructor may positively impact girls’ performance on certain programming tasks and reduce the number of gender differences between boys and girls in their mastery of programming concepts. Recommendations for Practitioners: Practitioners should expose children to STEM role-models from a variety of backgrounds, genders, ethnicities, and experiences. Future Research: Researchers should conduct future studies with larger samples of teachers in order to replicate the findings here. Additionally, future research should focus on collecting data from teachers in the form of interviews and surveys in order to find out more about gender-based differences in teaching style and mentorship and the impact of this on girls' interest and performance in STEM.

Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students’ academic achievement early using Educational Data Mining (EDM). This study aims to predict students’ final grades and identify honorary students at an early stage. Background: EDM research has emerged as an exciting research area, which can unfold valuable knowledge from educational databases for many purposes, such as identifying the dropouts and students who need special attention and discovering honorary students for allocating scholarships. Methodology: In this work, we have collected 300 undergraduate students’ records from three departments of a Computer and Information Science College at a university located in Saudi Arabia. We compared the performance of six data mining methods in predicting academic achievement. Those methods are C4.5, Simple CART, LADTree, Naïve Bayes, Bayes Net with ADTree, and Random Forest. Contribution: We tested the significance of correlation attribute predictors using four different methods. We found 9 out of 18 proposed features with a significant correlation for predicting students’ academic achievement after their 4th semester. Those features are student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses, i.e., database fundamentals, programming language (1), and computer network fundamentals. Findings: The empirical results show the following: (i) the main features that can predict students’ academic achievement are the student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses; (ii) Naïve Bayes classifier performed better than Tree-based Models in predicting students’ academic achievement in general, however, Random Forest outperformed Naïve Bayes in predicting honorary students; (iii) English language skills do not play an essential role in students’ success at the college of Computer and Information Sciences; and (iv) studying an orientation year does not contribute to students’ success. Recommendations for Practitioners: We would recommend instructors to consider using EDM in predicting students’ academic achievement and benefit from that in customizing students’ learning experience based on their different needs. Recommendation for Researchers: We would highly endorse that researchers apply more EDM studies across various universities and compare between them. For example, future research could investigate the effects of offering tutoring sessions for students who fail core courses in their first semesters, examine the role of language skills in social science programs, and examine the role of the orientation year in other programs. Impact on Society: The prediction of academic performance can help both teachers and students in many ways. It also enables the early discovery of honorary students. Thus, well-deserved opportunities can be offered; for example, scholarships, internships, and workshops. It can also help identify students who require special attention to take an appropriate intervention at the earliest stage possible. Moreover, instructors can be aware of each student’s capability and customize the teaching tasks based on students’ needs. Future Research: For future work, the experiment can be repeated with a larger dataset. It could also be extended with more distinctive attributes to reach more accurate results that are useful for improving the students’ learning outcomes. Moreover, experiments could be done using other data mining algorithms to get a broader approach and more valuable and accurate outputs.

This study aims to examine the intellectual capital and its effect on the financial performance of Ethiopian private commercial banks using the pulic model. Quantitative panel data from audited annual reports of Ethiopian private commercial banks from 2011 to 2019 are collected. The robust fixed effect regression model has been adopted to investigate the effect of IC and the financial performance measures of the banks. The study results show a positive relationship between the value added intellectual coefficient (VAIC) and the financial performance of private commercial banks in Ethiopia. The study also revealed that the components of VAIC (i.e., human capital efficiency, capital employed efficiency, and structural capital efficiency) have a positive and significant effect on the financial performance of banks measured by return on asset and return on equity over the study periods. Practically, the results of the study could be useful for shareholders to consider IC as a strategic resource and hence emphasise these intangibles, and to the bank managers to benchmark themselves against the best competitors based on the level of efficiency rankings.

The present study is a modest attempt to investigate the impact of gender diversity on firm performance of BSE 200 listed companies. The study is based on the secondary data collected from the EMIS database and the corporate governance reports for a period of eight years, i.e., from 2012 to 2019. Sample size of the present study is 174 Indian companies listed in the Bombay Stock Exchange. The study has employed multiple regression models by considering the endogeneity issue to empirically test the impact of gender diversity on firm performance in Indian context. Based on the multiple regression models, we find that the impact of gender diversity is positive and significant on the market-based measure of firm performance. However, the impact becomes negative significant when firm performance was measured by accounting based measure of firm performance.

Corporate social responsibility (CSR) and sustainability are gaining worldwide recognition. The question of whether CSR and sustainability programs benefit an organisation's financial success is still being debated. This study aims to verify this phenomenon by examining the current literature pattern on this relationship using bibliometric and systematic review analysis. It further provides a taxonomy for understanding this association. VOSviewer is used to obtain comprehensive dataset mapping and clustering in the field. The manuscript offers promising insights regarding academia by assessing the pattern of publication trends, the most influential author in the area, and analysing the methodological and theoretical underpinnings of CSR, sustainability and firm performance linkage. The outcome of this study provides exploratory insights into research gaps and avenues for future research.

In several manufacturing firms, inventory constitutes most of the current assets, and this underscores the importance of inventory management as a fundamental issue for the majority of the firms irrespective of their sizes. Therefore, the purpose of this research is to assess the factors that influence the effectiveness of inventory management of Malaysian SMEs in the manufacturing sector. The study employs PLS-SEM technique to test the hypotheses. The main findings show that documentation and records, inventory control system and qualified personnel have positive effects on effective inventory management of Malaysian SMEs in the manufacturing sector. The study also reveals that effective inventory management has a mediating effect on the relationship between documentation and records, inventory control system, qualified personnel and organisational performance. Therefore, the study recommends that Malaysian SMEs in the manufacturing sector should improve their approaches to embracing effective inventory management practices in order to enhance organisational performance.

This research investigates the correlation between risk management and supply chain performance (SCP) along with moderation of AI-embedded technologies such as big data analytics, Internet of Things (IoT), virtual reality, and blockchain technologies. To calculate the results, this study utilised 644 questionnaires through the structural equation modelling (SEM) method. It is revealed using SmartPls that financial risk management (FRM) is positively linked with SCP. Second, it was observed that AI significantly moderates the connection between FRM and SCP. In addition, the study presents certain insights into supply chain and AI-enabled technologies and how these capabilities can beneficially advance SCP. Besides, certain implications, both managerial and theoretical are described for the supply chain managers along with limitations for future scholars of the world.

With the rapid development of Artificial Intelligence (AI) technology, significant breakthroughs have been made in its application in many fields. Especially, in the field of enterprise human resource management and employee performance evaluation, AI has demonstrated its powerful ability to optimise and improve performance. This study explores the application of AI in enterprise human resource management and how to use AI to evaluate employee performance. The research includes analysing and comparing existing AI-driven human resource management models, evaluating how AI can help improve employee performance and leadership styles, and designing and developing human resource management computer systems for enterprise employees. Through empirical research and case analysis, this study proposes a new AI-optimised employee performance evaluation model and explores its application and effect in practice. In general, the application of AI can improve the efficiency and accuracy of enterprise human resource management, and provide new possibilities for employee performance evaluation. At present, artificial intelligence technology has been widely used in various fields of daily life, especially in corporate human resource management, providing better support for the development of enterprises.