While imprisoned in Caesarea, St. Paul, influenced by the medical expertise of his companion Luke, contemplates the armor of the soldier guarding him.

Mark’s account of the Lord’s questions about baptism and the cup (Mark 10:32-45) are especially poignant for the Christians at Rome, who are thereby instructed about an important dimension of their own participation in the sacraments.

Scotland are the great entertainers when they really need to be the great executioners, writes Tom English.

Jon Rahm’s play-off defeat in the Spanish Open by the world number 398 shows golf’s enduring capacity to yield upsets - but this trait rarely extends to the Presidents Cup, writes Iain Carter.

Andy Murray endured a bout of nerves when he played in the BMW PGA Championship pro-am with fellow Scot Bob MacIntyre on Wednesday.

The traditional 11 November two-minute period of remembrance took place at 11:00 across the country.

Crowds gather at Douglas cenotaph in its 100th year to pay tribute to those killed in world wars.

Landward takes a trip to Galloway to see the efforts to farm flowers.

Scotland fell silent at 11:00 to commemorate those who died in conflicts around the world.

Andrew Muir says Labour's first budget in 14 years is "bad" for farmers.

Proposals for renewable energy schemes in Wales could be sped up under new plans.

CPRE Surrey is opposing planning permission given to University of Surrey to build a solar facility.

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

Dr Noweed Ahmad performs life-changing surgery that allows deaf people to hear.

Their owner thanks people for their help after finding the birds three miles away.

A council delays a decision on the Saunton Sands beach proposal for additional survey work.

Memorial services across the South West take place for Armistice Day on Monday.

Tania Cork felt she might need an inhaler for the rest of her life after catching flu last year.

Sir Lee Pearson says he fears noise emanating from a new storage building will impact his training.

Civic leaders led tributes in scores of ceremonies to mark the occasion across north-west England.

Community officers discover the factory spread across three rooms in a terraced house, say police.

The operation was uncovered following a search of a disused office building in Morecambe.

Preston is one of 23 councils facing legal action from a council in Essex over botched investments.

A single protester has a sign wrestled off her during the silence at Forbury Gardens in Reading.

Gadebridge Pharmacy was used as a location for a scene in the film, Paddington in Peru.

Events take place across the region to mark the armistice at the end of World War One.

The group also rammed a farmer's vehicle in a "terrifying" incident in Wiltshire, police said.

Bedworth has marked 11 November on the actual day every year for more than 100 years.

The Budget saw the Labour government announce the reintroduction of inheritance tax for farmers.

Igloos, rooftops and ski lodges.

The Notting Hill pub gets its festive glow-up.

No Comment : commémoration du 106e anniversaire de l'Armistice 

Les enfants ukrainiens enlevés par la Russie destinés à servir son armée ?

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

by Dr Kim Barker (University of Stirling) & Dr Olga Jurasz (Open University) The UK Government has recently published an Online Harms White Paper: initial consultation response. It is the cornerstone of the Government’s ongoing reform package which aims to

A chaque jour, une nouvelle annonce. Cet ￜtￜ, le ministre de l'Intￜrieur, Gￜrald Darmanin, a multipliￜ les dￜplacements sur le terrain et les annonces. Pour lutter contre les pyromanes ￜ...

This study aimed to assess the level of GW in Jordanian university students and compare the level of awareness of students according to their academic level (high and low), faculty (science and humanities), gender (male and female), and year of study (first and final years). This study is quantitative research that provides a comprehensive view of GW in Jordanian universities. A total of 383 university students of currently registered undergraduate programs from six independent universities in Jordan were recruited. An online questionnaire covering three aspects of GW was sent to participants in December 2020. Inferential and descriptive statistics were used to analyse data. Participants had 'good' (67%) overall knowledge about GW, a 'very good' level of GW causes (81%), and a 'poor' level of knowledge about the GW impacts on humans and the environment (47%) and knowledge about GW possible solutions (59%). Significant differences were founded between males and females, students from scientific faculties and students from other faculties, students with higher academic achievement than lower achievement in the total GW knowledge. But no significant differences were between students in the first year and the final years.

Green entrepreneurial intention (GEI) in the agriculture sector signifies agricultural businesses' strong determination to embrace environmentally sustainable practices and innovative eco-friendly approaches. To understand farmers' GEI, the research applied theories of entrepreneurial events and institutional theory. A model was developed and empirically validated through structural equation modelling (SEM). A questionnaire survey was used to collect data from 211 farmers from the southern region of India. Findings revealed that perceived desirability, perceived feasibility, mimetic pressure, and entrepreneurial mindset positively influenced GEI. Entrepreneurial mindset played a mediating role in strengthening the farmers GEI. This study contributes to understanding GEI in agriculture and informs strategies for promoting sustainable farming practices.

Knowledge management research applied to the development of real-time research capability, or capability to solve societal problems in hours and days instead of years and decades, is perhaps increasingly important, given persistent global problems such as the Zika virus and rapidly developing antibiotic resistance. Drawing on swarm intelligence theory, this paper presents an approach to real-time research problem-solving in the form of a framework for understanding the complexity of real-time research and the challenges associated with maximizing collaboration. The objective of this research is to make explicit certain theoretical, methodological, and practical implications deriving from new literature on emerging technologies and new forms of problem solving and to offer a model of real-time problem solving based on a synthesis of the literature. Drawing from ant colony, bee colony, and particle swarm optimization, as well as other population-based metaheuristics, swarm intelligence principles are derived in support of improved effectiveness and efficiency for multidisciplinary human swarm problem-solving. This synthesis seeks to offer useful insights into the research process, by offering a perspective of what maximized collaboration, as a system, implies for real-time problem solving.

Aim/Purpose: This paper aims to analyze the availability and pricing of perishable farm produce before and during the lockdown restrictions imposed due to Covid-19. This paper also proposes machine learning and deep learning models to help the farmers decide on an appropriate market to sell their farm produce and get a fair price for their product. Background: Developing countries like India have regulated agricultural markets governed by country-specific protective laws like the Essential Commodities Act and the Agricultural Produce Market Committee (APMC) Act. These regulations restrict the sale of agricultural produce to a predefined set of local markets. Covid-19 pandemic led to a lockdown during the first half of 2020 which resulted in supply disruption and demand-supply mismatch of agricultural commodities at these local markets. These demand-supply dynamics led to disruptions in the pricing of the farm produce leading to a lower price realization for farmers. Hence it is essential to analyze the impact of this disruption on the pricing of farm produce at a granular level. Moreover, the farmers need a tool that guides them with the most suitable market/city/town to sell their farm produce to get a fair price. Methodology: One hundred and fifty thousand samples from the agricultural dataset, released by the Government of India, were used to perform statistical analysis and identify the supply disruptions as well as price disruptions of perishable agricultural produce. In addition, more than seventeen thousand samples were used to implement and train machine learning and deep learning models that can predict and guide the farmers about the appropriate market to sell their farm produce. In essence, the paper uses descriptive analytics to analyze the impact of COVID-19 on agricultural produce pricing. The paper explores the usage of prescriptive analytics to recommend an appropriate market to sell agricultural produce. Contribution: Five machine learning models based on Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, and Gradient Boosting, and three deep learning models based on Artificial Neural Networks were implemented. The performance of these models was compared using metrics like Precision, Recall, Accuracy, and F1-Score. Findings: Among the five classification models, the Gradient Boosting classifier was the optimal classifier that achieved precision, recall, accuracy, and F1 score of 99%. Out of the three deep learning models, the Adam optimizer-based deep neural network achieved precision, recall, accuracy, and F1 score of 99%. Recommendations for Practitioners: Gradient boosting technique and Adam-based deep learning model should be the preferred choice for analyzing agricultural pricing-related problems. Recommendation for Researchers: Ensemble learning techniques like Random Forest and Gradient boosting perform better than non-Ensemble classification techniques. Hyperparameter tuning is an essential step in developing these models and it improves the performance of the model. Impact on Society: Statistical analysis of the data revealed the true nature of demand and supply and price disruption. This analysis helps to assess the revenue impact borne by the farmers due to Covid-19. The machine learning and deep learning models help the farmers to get a better price for their crops. Though the da-taset used in this paper is related to India, the outcome of this research work applies to many developing countries that have similar regulated markets. Hence farmers from developing countries across the world can benefit from the outcome of this research work. Future Research: The machine learning and deep learning models were implemented and tested for markets in and around Bangalore. The model can be expanded to cover other markets within India.

Aim/Purpose: This research aims to develop a smart agricultural knowledge management framework to empower emergent farmers and extension officers (advisors to farmers) in developing countries as part of a smart farming lab (SFL). The framework utilizes knowledge objects (KOs) to capture information and knowledge of different forms, including indigenous knowledge. It builds upon a foundation of established agricultural knowledge management (AKM) models and serves as the cornerstone for an envisioned SFL. This framework facilitates optimal decision support by fostering linkages between these KOs and relevant organizations, knowledge holders, and knowledge seekers within the SFL environment. Background: Emergent farmers and extension officers encounter numerous obstacles in their knowledge operations and decision-making. This includes limited access to agricultural information and difficulties in applying it effectively. Many lack reliable sources of support, and even when information is available, understanding and applying it to specific situations can be challenging. Additionally, extension offices struggle with operational decisions and knowledge management due to agricultural organizations operating isolated in silos, hindering their access to necessary knowledge. This research introduces an SFL with a proposed AKM process model aimed at transforming emergent farmers into smart, innovative entities by addressing these challenges. Methodology: This study is presented as a theory-concept paper and utilizes a literature review to evaluate and synthesize three distinct AKM models using several approaches. The results of the analysis are used to design a new AKM process model. Contribution: This research culminates in a new AKM process framework that incorporates the strengths of various existing AKM models and supports emergent farmers and extension officers to become smart, innovative entities. One main difference between the three models analyzed, and the one proposed in this research, is the deployment and use of knowledge assets in the form of KOs. The proposed framework also incorporates metadata and annotations to enhance knowledge discoverability and enable AI-powered applications to leverage captured knowledge effectively. In practical terms, it contributes by further motivating the use of KOs to enable the transfer and the capturing of organizational knowledge. Findings: A model for an SFL that incorporates the proposed agricultural knowledge management framework is presented. This model is part of a larger knowledge factory (KF). It includes feedback loops, KOs, and mechanisms to facilitate intelligent decision-making. The significance of fostering interconnected communities is emphasized through the creation of linkages. These communities consist of knowledge seekers and bearers, with information disseminated through social media and other communication integration platforms. Recommendations for Practitioners: Practitioners and other scholars should consider implementing the proposed AKM process model as part of a larger SFL to support emergent farmers and extension officers in making operational decisions and applying knowledge management strategies. Recommendation for Researchers: The AKM process model is only presented in conceptual form. Therefore, researchers can practically test and assess the new framework in an agricultural setting. They can also further explore the potential of social media integration platforms to connect knowledge seekers with knowledge holders. Impact on Society: The proposed AKM process model has the potential to support emergent farmers and extension officers in becoming smart, innovative entities, leading to improved agricultural practices and potentially contributing to food security. Future Research: This paper discusses the AKM process model in an agrarian setting, but it can also be applied in other domains, such as education and the healthcare sector. Future research can evaluate the model’s effectiveness and explore and further investigate the semantic web and social media integration.