Genetic diversity of commercial chickens consumed in Selangor, Malaysia

Chickens represent the most widely consumed meat in the world. Modern breeds are generally from a narrow genetic base. The genetic diversity of chickens consumed in urban areas of Malaysia has not been previously investigated. The aim of this study was to investigate the genetic diversity of chickens available for purchase in urban areas of Selangor adjacent to Kuala Lumpur. DNA of chickens were isolated from meats and livers. Seven microsatellite markers were selected and fluorescently labeled to allow the identification of each individual chicken from the seventeen populations based on the amplification of target DNA. A total of 52 different alleles was observed for the seven markers, giving a mean of 7.1 alleles per marker. The cumulative power of discrimination (CPd) of the seven microsatellites used was 0.999 based upon our population study. The data showed that most of the chickens consumed in the urban areas came from a very narrow genetic base. The supply is thus vulnerable to disruption caused by outbreaks of disease. Furthermore the data obtained illustrates the potential of this system to be used in chicken lineage identification. This would help to resolve uncertainties over the origin of the chickens. This system could be used for product assurance as well as safety

Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders

A Multispecialty Evaluation of Thiel Cadavers for Surgical Training

Background: Changes in UK legislation allow for surgical procedures to be performed on cadavers. The aim of this study was to assess Thiel cadavers as high-fidelity simulators and to examine their suitability for surgical training. Methods: Surgeons from various specialties were invited to attend a 1 day dissection workshop using Thiel cadavers. The surgeons completed a baseline questionnaire on cadaveric simulation. At the end of the workshop, they completed a similar questionnaire based on their experience with Thiel cadavers. Comparing the answers in the pre- and post-workshop questionnaires assessed whether using Thiel cadavers had changed the surgeons’ opinions of cadaveric simulation. Results: According to the 27 participants, simulation is important for surgical training and a full-procedure model is beneficial for all levels of training. Currently, there is dissatisfaction with existing models and a need for high-fidelity alternatives. After the workshop, surgeons concluded that Thiel cadavers are suitable for surgical simulation (p = 0.015). Thiel were found to be realistic (p < 0.001) to have reduced odour (p = 0.002) and be more cost-effective (p = 0.003). Ethical constraints were considered to be small. Conclusion: Thiel cadavers are suitable for training in most surgical specialties

Explainable Artificial Intelligence (XAI) 2.0: a manifesto of open challenges and interdisciplinary research directions

Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper highlights the advancements in XAI and its application in real-world scenarios and addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. We aim to develop a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 28 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders

Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders

Cultivating loyalty in fast food through marketing cues

Purpose – Cultivating customerloyalty is extremely crucial forfast-food players to remain competitive in the industry. This research is discovering the path to cultivate customer loyalty through experience that is built based on auditory, gustatory, haptic, olfactory and visual cues. Design/methodology/approach – Quantitative research has been conducted by distributing survey questionnaires to customers at selected fast-food restaurants in urban areas. The collected data has been analyzed by descriptive and structural equation modeling analysis. Findings –The customers’ loyalty to fast food can be cultivated through gustatory, haptic and olfactory cues. However, auditory and visual are not functioning as marketing cues to cultivate customer loyalty. Practical implications – The fast-food players may emphasize gustatory, haptic and olfactory marketing cues to cultivate customer loyalty. These cues can be shared through experience. Originality/value – This study has discovered the potential ways to cultivate customer loyalty in dining at fast-food restaurants within the Malaysian market

Guaranteeing QoS using unlicensed TV white space for smart grid applications

In this article, we consider the utilization of TVWS by small CR network operators to support the communication needs of various smart grid applications. We first propose a multi-Tier communication network architecture for smart metering applications in dense urban environments. Our measurement campaign, without any competition from other CR operators, reveals that the communication architecture can achieve more than 1 Mb/s data rates using the free unlicensed TVWS spectrum. However, anticipating stiff competition for the unlicensed TVWS spectrum among CR operators and to support smart grid applications with stringent QoS requirements, we further exploit the novel idea of high priority channels (HPCs) that a CR operator can temporarily lease by paying a small fee. This poses several new challenges for CR operators, such as their economic viability while providing QoS guarantees. We develop a real-Time decision support framework with several adjustable parameters for CR operators that enables them to trade off HPC leasing cost and QoS. The developed algorithms are simple rules that provide significant opportunities to CR operators to maintain a balance between spectrum cost and QoS depending on dynamic spectrum availability and smart grid application requirements