Challenges and practices in Halal meat preparation: a case study investigation of a UK slaughterhouse

Consumer concerns over the provenance of food that has been prepared in accordance with religious requirements has risen in importance. Instances of improper identification and sale of Halal meat-based products in particular have given rise to questions over the authenticity of such foods. Despite this and the rising demand for Halal foods across the globe, little research has been conducted around the specific issues that arise during their production. This paper presents a case study investigation of a slaughterhouse in the UK that prepares both Halal and non-Halal meat products. It aims to improve our understanding of the challenges that Halal food production presents. The extra requirements of Halal food preparation place additional burdens especially upon smaller processors. Future development of quality standards should take account of the abilities of smaller organisations and the constraints under which they operate. Additionally, food quality assurance standards and systems should highlight the specific requirements of food that has been prepared in accordance with religious requirements. While this study has highlighted the complexities of Halal food production, similar issues are likely to be present in the production of Kosher food, and such compliances may also be required of foods consumed by people of other faiths

SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

BACKGROUND: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. METHODS: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FINDINGS: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. INTERPRETATION: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. FUNDING: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain–gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials

Expert system development and testing: A knowledge engineer's perspective

This article discusses the problems found in the validation and verification of a knowledge-based system for equity selection. These problems include the selection of test data, poor methodology, and the difficulties associated with using prototypes. The article then examines the possible techniques available to the knowledge engineer for improving validation and verification. The article discusses exhaustive testing, case-based testing, formal specifications, functional programming, critical testing, mutation testing, and reliability. Finally the article discusses the approach that the knowledge engineer would take in rewriting the equity selection system, one based on a rigorous development methodology that uses as many formal validation techniques as possible to raise the quality of the software produced

Rule-based systems formalized within a software architectural style

This article considers the utilization of architectural styles in the formal design of knowledge-based systems. The formal model of a style is an approach to systems modeling that allows software developers to understand and prove properties about the system design in terms of its components, connectors, configurations, and constraints. This allows commonality of design to be easily understood and captured, leading to a better understanding of the role that an architectural abstraction would have in another complex system, embedded context, or system integration. In this article, a formal rule-based architectural style is presented in detail using the Z notation. The benefits of depicting the rule-based system as an architectural style include reusability, understandability, and the allowance for formal software analysis and integration techniques. The ability to define the rule-based architectural style in this way, illustrates the power, clarity, and flexibility of this specification form over traditional formal specification approaches. In addition, it extends current verification approaches for knowledge-based systems beyond the knowledge base only

Using KBS verification techniques to demonstrate the existence of rule anomalies in ADBs

As the field of verification and validation for knowledge-based systems (KBSs) has matured, much information, technology, and theory has become available. Though not all of the problems with respect to KBSs have been solved, many have been identified with solutions that can be used in an analogous manner in situations where the application is not necessarily a traditional KBS. As one example, the “active” component in an active database (ADB) consists of rules that execute as a result of database accesses and updates. In this paper, we demonstrate that anomalies found to impact the correctness of a KBS can also exist in ADBs. We first compare the rule structure of a KBS with the rule structures of various ADBs. To show their existence, we convert the rule syntax of the ADBs into a consistent format for analysis and anomaly detection. Once converted, we apply KBS verification techniques to isolate these anomalies. Due to the more increasing use of triggered rules in ADBs, this work illustrates the danger these anomalies can pose and the ever increasing need for ADB verification techniques to exist

Green Supply Chain Management in Chinese Electronic Manufacturing Organisations: An Analysis of Senior Managements' Perceptions

Green supply chain management and reverse logistics has emerged as a key area of research interest. Recent environmental regulations have also stimulated interest in this field. However, information sharing is a prerequisite to efficient and effective logistics utilisation. Manufacturing organisations in China were argued to be 10-20 years behind their Western counterparts in relation to information sharing in their supply chains (). This barrier needs to be addressed if China is going to maintain and grow its manufacturing position in the world, attempt to address green supply chain issues and their negative externalities. A systematic literature review was undertaken and green supply chain management theoretical framework adopted. The paper explores the perceptions of senior management toward green logistics and information sharing in Chinese electronic manufacturers. Previous research has concentrated on the focal companies (brand owners). This research concentrated on SME organisations further up the supply chain. Semi-structured interviews of eighteen senior managers of electronic manufactures in Jiangsu province China were conducted in 2012. Thematic analysis is applied and the findings contrasted to other research. The paper provides insight to the current status of managers' views on information sharing and green supply chain initiatives. Information platform, skills, investment, and trust emerged as key influences on their willing to engage in information sharing in relation to green supply chains. This research, among others, assists to inform policy for optimal evidence based intervention. Future research directions are also considered

Toward a Methodology for AI Architecture Evaluation: Comparing Soar and CLIPS

. We propose a methodology that can be used to compare and evaluate Artificial Intelligence architectures and is motivated by fundamental properties required by general intelligent systems. We examine an initial application of this method used to compare Soar and CLIPS in two simple domains. Results gathered from our tests indicate both qualitative and quantitative differences in these architectures and are used to explore how aspects of the architectures may affect the agent design process and the performance of agents implemented within each architecture. 1 Introduction Development of autonomous intelligent systems has been a primary goal of Artificial Intelligence. A number of symbolic architectures have been developed to support the low level, domain independent functionality that is commonly required in such systems. Although some studies have examined what types of agent behaviors are most appropriate within a given domain (e.g., Pollack and Ringuette [12]), only seconda..