In the second part of his reflection on St. John Chrysostom’s famed Nativity Homily, Fr. Irenei examines the concluding segments of the sermon, in which the Saint draws our hearts into the experience of the One who brought joy into the midst of the earth.

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?

In Mark 9, just after the Transfiguration, Jesus addresses the faith of the crowds surrounding the disciples as well as that of a man whose son He then heals. As we look toward the last weeks of Lent, Fr. Pat helps us think about our own faith.

Fr. Josiah Trenham, member of the Secretariat of the Canonical Assembly of Orthodox Bishops of North and South America and podcaster on Ancient Faith Radio ("The Arena") talks with Kevin and the listeners about the Church today, its standing in the culture, and the recent work of the Canonical Assembly of Orthodox Bishops in America, which just met for the third time in September.

In today’s digital world, information spreads like wildfire. That includes information about you. What people read about you online—whether accurate or not—impacts your reputation and potentially all aspects of your life. You want the things people read about you to be true. But keeping track of everything that appears online […]

The post How to Automate Your Personal Reputation Management appeared first on .

During lockdown Tony Fowler has offered help to isolated older customers who have been advised to stay indoors.

One nurse said welfare packs at work made her job "a little bit easier in a difficult time".

Bosses must pass on all tips and service charges to staff under new employment rules.

VW Finance showed "a lack of empathy", according to the Financial Conduct Authority.

People can attend a virtual meeting to ask questions about the firm and its £1.9m five-year plan.

Should have gone to....

Dee Harrison thought she saw a "mystical" aurora above Suffolk but it turned out to be LED lighting.

About 700 patients have been identified as being at risk of developing serious liver problems.

Disgraced surgeon Paterson gives evidence in Birmingham on the death of Gladys Currall, aged 82.

Customers are some of your best leads. According to a 2022 HubSpot Blog survey of more than 500 sales professionals, more than 70 percent said that upsell and cross-sell drives up to 30 percent of their revenue.

Personalisation in marketing works because personal connections matter. That extends beyond your customers, too. Personal connections include the relationships you have with your suppliers, your stakeholders, your employees, industry peers… the list goes on.

Panto is back - oh yes it is!

A feature model (FM) defines the valid combinations of features, whose combinations correspond to a program in a Software Product Line (SPL). FMs may evolve, for instance, during refactoring activities. Developers may use a catalog of refactorings as support. However, the catalog is incomplete in principle. Additionally, it is non-trivial to propose correct refactorings. To our knowledge, no previous analysis technique for FMs is used for checking properties of general FM refactorings (a transformation that can be applied to a number of FMs) containing a representative number of features. We propose an efficient encoding of FMs in the Alloy formal specification language. Based on this encoding, we show how the Alloy Analyzer tool, which performs analysis on Alloy models, can be used to automatically check whether encoded general and specific FM refactorings are correct. Our approach can analyze general transformations automatically to a significant scale in a few seconds. In order to evaluate the analysis performance of our encoding, we evaluated in automatically generated FMs ranging from 500 to 2,000 features. Furthermore, we analyze the soundness of general transformations.

Il y a quelques jours, je parlais d’émergence d’un nouveau monde bipolaire. Le hasard des écrits faisant parfois bien les choses, depuis quelques jours est apparu dans notre vocabulaire, les Gilets Jaunes. Il ne se passe plus un jour, sans qu’on essaye...

Trump confie l'immigration à Tom Homan, le "tsar des frontières"

1. What is walking pneumonia? As cases rise in Canada, the symptoms to look out for  The Globe and Mail
2. Walking pneumonia on the rise in Kingston, but treatable  The Kingston Whig-Standard
3. What parents need to know about walking pneumonia in kids  FingerLakes1.com
4. Pediatric pneumonia is surging in Central Ohio  MSN
5. Walking Pneumonia is spiking right now. How do you know you have it?  CBS 6 News Richmond WTVR

1. The Stanchies: Canucks stomp out Flames in 3-1 victory  Canucks Army
2. Pettersson, Canucks having fun again with bounce-back win over Flames  Sportsnet.ca
3. Three takeaways as Flames cap gruelling stretch with loss to Canucks  Calgary Herald
4. Pettersson has goal, assist to lift Canucks past Flames  NHL.com
5. I Watched This Game: Brännström gets first goal as a Canuck in comfy win over Flames  Vancouver Is Awesome

Les pycnogonides, une espèce marine apparentée aux araignées, peuvent faire repousser des parties du corps après amputation, et pas seulement de simples membres, selon une étude publiée lundi, ouvrant la voie à de nouvelles découvertes sur la régénération.

"Personne ne s'attendait à cela", a déclaré Gerhard Scholtz de la prestigieuse université Humboldt à Berlin, et l'un des auteurs principaux de cette étude parue dans la revue Proceedings of the National Academy of Sciences. "Nous avons été les premiers à démontrer que c'était possible", a-t-il ajouté. Il est connu qu'une multitude d'espèces d'arthropodes tels que les mille-pattes, les araignées ou d'autres insectes peuvent faire repousser une patte après l'avoir perdue.

"Les crabes peuvent même se débarrasser automatiquement de leurs membres s'ils sont attaqués", a déclaré Gerhard Scholtz, précisant: "ils les remplacent par un nouveau membre". Ce que les chercheurs ont découvert à travers leurs expériences avec ces minuscules créatures à huit pattes, est qu'elles sont capables de régénérer même d'autres parties du corps. Pour l'étude, ils ont amputé différents membres et parties postérieures du corps de 23 pycnogonides juvéniles et adultes, et ont observé les résultats.

Repousse d'un corps à partir de seulement quelques cellules

Aucune régénération de parties du corps n'a été constatée dans les spécimens adultes, mais certains étaient toujours en vie après deux ans. Les spécimens juvéniles, en revanche, ont connu une régénération complète ou quasi-complète des parties du corps manquantes, y compris l'intestin postérieur, l'anus, la musculature, et certaines parties d'organes génitaux.

A long terme, 90% des pycnogonides ont survécu, et 16 spécimens juvéniles ont effectué leur mue par la suite au moins une fois. La régénération postérieure a ainsi été constatée chez 14 des spécimens juvéniles tandis qu'aucun des spécimens adultes n'a mué ou ne s'est régénéré. Les capacités de régénération varient à travers le règne animal.

Les vers plats, par exemple, peuvent faire repousser leur corps à partir de seulement quelques cellules. Les vertébrés, dont les hommes, n'ont quasiment aucune capacité de régénération à l'exception de quelques espèces comme les lézards, qui peuvent faire repousser leurs queues.

Selon Gerhard Scholz, les résultats de l'étude ouvrent de nouvelles voies de recherche dans le domaine. "Une multitude d'espèces différentes peuvent être testées de cette manière", dit-il, ce qui pourrait permettre de comparer les mécanismes de régénération. "Au bout du compte, peut-être que les mécanismes que nous découvrons chez les arthropodes nous aiderons dans les traitements médicaux après la perte d'un membre, d'un doigt, etc... chez les humains", espère le chercheur.

Drawing on the MOA framework, this study establishes a research model that explains the usage intention of robo-advisors. In the model, three predictors that consist of technology relative advantage, technology herding, and technology familiarity influence usage intention of robo-advisors directly and indirectly via the partial mediation of trust. At the same time, the effects of the three predictors on trust are hypothetically moderated by learning goal orientation and perceived performance risk respectively. Statistical analyses are provided using the data of working professionals from the insurance industry in Taiwan. Based on its empirical findings, this study discusses important theoretical and practical implications.

Aiming at the problem of aggravation of traffic congestion caused by unstable signal control of traffic signal control system, the Multi-Agent Deep Deterministic Policy Gradient-based Traffic Cyclic Signal (MADDPG-TCS) control algorithm is used to control the time and data dimensions of the signal control scheme. The results show that the maximum vehicle delay time and vehicle queue length of the proposed algorithm are 11.33 s and 27.18 m, which are lower than those of the traditional control methods. Therefore, this method can effectively reduce the delay of traffic signal control and improve the stability of signal control.

In the context of smart city development, the managed pressure drilling (MPD) drilling process faces many uncertainties, but the characteristics of the process are complex and require accurate wellbore pressure control. However, this process runs the risk of introducing un-modelled dynamics into the system. To this problem, this paper employs neural network control techniques to construct a dual-network system for throttle pressure control, the design encompasses both the controller and identifier components. The radial basis function (RBF) network and proportional features are connected in parallel in the controller structure, and the RBF network learning algorithm is used to train the identifier structure. The simulation results show that the actual wellbore pressure can quickly track the reference pressure value when the pressure setpoint changes. In addition, the controller based on neural network realises effective control, which enables the system to track the input target quickly and achieve stable convergence.

Physical and social aspects each make up a separate part of servicescape. Together, these make up the servicescape. Although previous research has frequently investigated these aspects separately, the purpose of this study is to simultaneously find out the impact of both aspects within the casual dining restaurants' context. In total, 462 customers in Delhi were polled for this study, and structural equation modelling was used to analyse the data. According to the results, both the social and physical parts of the servicescape have the ability to affect how satisfied customers are, which in turn can affect how they behave in the future.

In this paper we discuss the use of automated assessment in a variety of computer science courses that have been taught at Israel Academic College by the authors. The course assignments were assessed entirely automatically using Checkpoint, a web-based automated assessment framework. The assignments all used free-text questions (where the students type in their own answers). Students were allowed to correct errors based on feedback provided by the system and resubmit their answers. A total of 141 students were surveyed to assess their opinions of this approach, and we analysed their responses. Analysis of the questionnaire showed a low correlation between questions, indicating the statistical independence of the individual questions. As a whole, student feedback on using Checkpoint was very positive, emphasizing the benefits of multiple attempts, impartial marking, and a quick turnaround time for submissions. Many students said that Checkpoint gave them confidence in learning and motivation to practise. Students also said that the detailed feedback that Checkpoint generated when their programs failed helped them understand their mistakes and how to correct them.

Aim/Purpose: The aims of this study were to investigate the feasibility of automatic assessment of programming tasks and to compare manual assessment with automatic assessment in terms of the effect of the different assessment methods on the marks of the students. Background: Manual assessment of programs written by students can be tedious. The assistance of automatic assessment methods might possibly assist in reducing the assessment burden, but there may be drawbacks diminishing the benefits of applying automatic assessment. The paper reports on the experience of a lecturer trying to introduce automated grading. Students’ solutions to a practical Java programming test were assessed both manually and automatically and the lecturer tied the experience to the unified theory of acceptance and use of technology (UTAUT). Methodology: The participants were 226 first-year students registered for a Java programming course. Of the tests the participants submitted, 214 were assessed both manually and automatically. Various statistical methods were used to compare the manual assessment of student’s solutions with the automatic assessment of the same solutions. A detailed investigation of reasons for differences was also carried out. A further data collection method was the lecturer’s reflection on the feasibility of automatic assessment of programming tasks based on the UTAUT. Contribution: This study enhances the knowledge regarding benefits and drawbacks of automatic assessment of students’ programming tasks. The research contributes to the UTAUT by applying it in a context where it has hardly been used. Furthermore, the study is a confirmation of previous work stating that automatic assessment may be less reliable for students with lower marks, but more trustworthy for the high achieving students. Findings: An automatic assessment tool verifying functional correctness might be feasible for assessment of programs written during practical lab sessions but could be less useful for practical tests and exams where functional, conceptual and structural correctness should be evaluated. In addition, the researchers found that automatic assessment seemed to be more suitable for assessing high achieving students. Recommendations for Practitioners: This paper makes it clear that lecturers should know what assessment goals they want to achieve. The appropriate method of assessment should be chosen wisely. In addition, practitioners should be aware of the drawbacks of automatic assessment before choosing it. Recommendation for Researchers: This work serves as an example of how researchers can apply the UTAUT theory when conducting qualitative research in different contexts. Impact on Society: The study would be of interest to lecturers considering automated assessment. The two assessments used in the study are typical of the way grading takes place in practice and may help lecturers understand what could happen if they switch from manual to automatic assessment. Future Research: Investigate the feasibility of automatic assessment of students’ programming tasks in a practical lab environment while accounting for structural, functional and conceptual assessment goals.

This study focuses on the importance of monitoring student attendance in education and the challenges faced by educators in doing so. Existing methods for attendance tracking have drawbacks, including high costs, long processing times, and inaccuracies, while security and privacy concerns have often been overlooked. To address these issues, the authors present a novel internet of things (IoT)-based self-lecture attendance system (SLAS) that leverages smartphones and QR codes. This system effectively addresses security and privacy concerns while providing streamlined attendance tracking. It offers several advantages such as compact size, affordability, scalability, and flexible features for teachers and students. Empirical research conducted in a live lecture setting demonstrates the efficacy and precision of the SLAS system. The authors believe that their system will be valuable for educational institutions aiming to streamline attendance tracking while ensuring security and privacy.

This study examines the relationships between ICTs (e.g., chatbots, virtual assistants, social media platforms, e-mail marketing, mobile marketing, data analytics, interactive voice response, big data analytics, push notifications, cloud computing, and augmented reality) and e-customer relationship management (e-CRM) from the banking industry of China. Similarly, this study unfolds the moderation interference of trust and risk between the association of ICTs and e-CRM, respectively. The study provided a positive nexus between ICTs and e-CRM. On the other side, a significant moderation of trust, as well as financial risk was observed between the correlation of ICTs and customer relationship management. This study endows with insights into ICTs which are critical for achieving e-CRM by streamlining interactions and enhancing their experience. Similarly, trust and financial risk were observed as potential forces that sway the association between ICTs and e-CRM.

Human behaviour, which is led by the human, emotional and occasionally fallible brain, is highly influenced by the environment in which choices are presented. This research paper explores the synergistic potential of the Internet of Behaviours (IoB) and digital nudges in the financial sector as new avenues for intervention while shedding light on the IoB benefits and the digital nudges' added value in these financial settings. Afterward, it proposes an IoB-Nudges conceptual model to explain how these two concepts would be incorporated and investigates their complementary relationship and benefits for this sector. Finally, the paper also discusses key challenges to be addressed by the IoB framework.

In order to overcome the problems of poor evaluation accuracy and long evaluation time in traditional customer relationship evaluation methods, this study proposes a new customer relationship evaluation method for e-commerce platform based on decision tree algorithm. Firstly, analyse the connotation and characteristics of customer relationship; secondly, the importance of customer relationship in e-commerce platform is determined by using decision tree algorithm by selecting and dividing attributes according to the information gain results. Finally, the decision tree algorithm is used to design the classifier, the weighted sampling method is used to obtain the training samples of the base classifier, and the multi-period excess income method is used to construct the customer relationship evaluation function to achieve customer relationship evaluation. The experimental results show that the accuracy of the customer relationship evaluation results of this method is 99.8%, and the evaluation time is only 51 minutes.

In order to solve the problems of large generalisation error, low recall rate and low retrieval accuracy of customer evaluation information in traditional trust evaluation methods, an evaluation method of customer trust in e-commerce market based on entropy weight analytic hierarchy process was designed. Firstly, build an evaluation index system of customer trust in e-commerce market. Secondly, the customer trust matrix is established, and the index weight is calculated by using the analytic hierarchy process and entropy weight method. Finally, five-scale Likert method is used to analyse the indicator factors and establish a comment set, and the trust evaluation value is obtained by combining the indicator membership. The experiment shows that the maximum generalisation error of this method is only 0.029, the recall rate is 97.5%, and the retrieval accuracy of customer evaluation information is closer to 1.

Aim/Purpose: The aim of this study was to develop a prototype of an information-generating computer tool designed to automatically map the dental restorations in a panoramic radiograph. Background: A panoramic radiograph is an external dental radiograph of the oro-maxillofacial region, obtained with minimal discomfort and significantly lower radiation dose compared to full mouth intra-oral radiographs or cone-beam computed tomography (CBCT) imaging. Currently, however, a radiologic informative report is not regularly designed for a panoramic radiograph, and the referring doctor needs to interpret the panoramic radiograph manually, according to his own judgment. Methodology: An algorithm, based on techniques of computer vision and machine learning, was developed to automatically detect and classify dental restorations in a panoramic radiograph, such as fillings, crowns, root canal treatments and implants. An experienced dentist evaluated 63 panoramic anonymized images and marked on them, manually, 316 various restorations. The images were automatically cropped to obtain a region of interest (ROI) containing only the upper and lower alveolar ridges. The algorithm automatically segmented the restorations using a local adaptive threshold. In order to improve detection of the dental restorations, morphological operations such as opening, closing and hole-filling were employed. Since each restoration is characterized by a unique shape and unique gray level distribution, 20 numerical features describing the contour and the texture were extracted in order to classify the restorations. Twenty-two different machine learning models were evaluated, using a cross-validation approach, to automatically classify the dental restorations into 9 categories. Contribution: The computer tool will provide automatic detection and classification of dental restorations, as an initial step toward automatic detection of oral pathologies in a panoramic radiograph. The use of this algorithm will aid in generating a radiologic report which includes all the information required to improve patient management and treatment outcome. Findings: The automatic cropping of the ROI in the panoramic radiographs, in order to include only the alveolar ridges, was successful in 97% of the cases. The developed algorithm for detection and classification of the dental restorations correctly detected 95% of the restorations. ‘Weighted k-NN’ was the machine-learning model that yielded the best classification rate of the dental restorations - 92%. Impact on Society: Information that will be extracted automatically from the panoramic image will provide a reliable, reproducible radiographic report, currently unavailable, which will assist the clinician as well as improve patients’ reliance on the diagnosis. Future Research: The algorithm for automatic detection and classification of dental restorations in panoramic imaging must be trained on a larger dataset to improve the results. This algorithm will then be used as a preliminary stage for automatically detecting incidental oral pathologies exhibited in the panoramic images.