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The diagnosis of psychosis in individuals with autism spectrum disorder (ASD) poses a unique clinical challenge. The presence of intellectual disability (ID) further complicates the diagnostic picture. Reliable and timely diagnosis of psychosis in such individuals minimises the duration of untreated psychotic symptoms and the subsequent impact on the quality of life of the patients concerned. The paper aims to discuss this issue.

The authors present four patients with psychosis, ASD and ID, who have received care within forensic mental health and ID settings. These examples demonstrate the interaction between these conditions, as well as issues pertaining to diagnosis and management.

In all four patients, sustained use of antipsychotic medication was objectively associated with an improvement in psychotic symptoms and quality of life. In instances where autistic phenomena were accentuated upon development of psychosis, such features returned to the baseline levels evident prior to the onset of psychosis.

The discussion and related case examples could improve the understanding of the possibility of psychosis in individuals with ASD and ID, and increase awareness of this diagnostic possibility among healthcare professionals.

This is the first published case series illustrating the challenges of diagnosing psychosis in individuals with ASD and ID.

This paper aims to clarify the relationship between mechanical behaviors and the underlying geometry of periodic cellular structures. Particularly, the answer to the following research question is investigated: Can seemingly different geometries of the repeating unit cells of periodic cellular structure result in similar functional behaviors? The study aims to cluster the geometry-functional behavior relationship into different categories.

Specifically, the effects of the geometry on the compressive deformation (mechanical behavior) responses of multiple standardized cubic periodic cellular structures (CPCS) at macro scales are investigated through both physical tests and finite element simulations of three-dimensional (3D) printed samples. Additionally, these multiple CPCS can be further nested into the shell of 3D models of various mechanical domain parts to demonstrate the influence of their geometries in practical applications.

The paper provides insights into how different CPCS (geometrically different unit cells) influence their compressive deformation behaviors. It suggests a standardized strategy for comparing mechanical behaviors of different CPCS.

This paper is the first work in the research domain to investigate if seemingly different geometries of the underlying unit cell can result in similar mechanical behaviors. It also fulfills the need to infill and lattify real functional parts with geometrically complex unit cells. Existing work mainly focused on simple shapes such as basic trusses or cubes with spherical holes.

Part quality inspection is playing a critical role in the metal additive manufacturing (AM) industry. It produces a part quality analysis report which can be adopted to further improve the overall part quality. However, the part quality inspection process puts heavy reliance on the engineer’s background and experience. This manual process suffers from both low efficiency and potential errors and, therefore, cannot meet the requirement of real-time detection. The purpose of this paper is to look into a deep neural network, Convolutional Neural Network (CNN), towards a robust method for online monitoring of AM parts.

The proposed online monitoring method relies on a deep CNN that takes a real metal AM part’s images as inputs and the part quality categories as network outputs. The authors validate the efficacy of the proposed methodology by recognizing the “beautiful-weld” category from material CoCrMo top surface images. The images of “beautiful-weld” parts that show even hatch lines and appropriate overlaps indicate a good quality of an AM part.

The classification accuracy of the developed method using limited information of a small local block of an image is 82 per cent. The classification accuracy using the full image and the ensemble of model outputs is 100 per cent.

A real-world data set of high resolution images of ASTM F75 I CoCrMo-based three-dimensional printed parts (Top surface images with magnification 63×) annotated with categories labels. Development of a CNN-based classification model for the supervised learning task of recognizing a “beautiful-weld” AM parts. The classification accuracy using the full image and the ensemble of model outputs is 100 per cent.

The purpose of this paper is to describe key policy and practice issues regarding a significant subgroup of people with intellectual disability – those with offending behaviour being treated in forensic hospitals.

The reasons why psychiatrists continue to be involved in the treatment of people with intellectual disability and mental health or behavioural problems and the factors that may lead to patients needing hospital admission are examined. Using two illustrative examples, three key questions – containment vs treatment, hospital care vs conditional discharge and hospital treatment vs using deprivation of liberty safeguards usage in the community are explored.

Patients with intellectual disability, mental health problems and offending behaviours who are treated within forensic inpatient units tend to have long lengths of stay. The key variable that mediates this length of stay is the risk that they pose to themselves or others. Clinicians work within the framework of mental health law and have to be mindful that pragmatic solutions to hasten discharge into the community may not fall within the law.

This paper makes practical suggestions for the future on how to best integrate hospital and community care for people with intellectual disability, mental health and offending behaviours.

The 11th revision of the International Classification of diseases which sets global standards for defining, reporting and managing health conditions is under way. The International Classification of Diseases (ICD) underpinning principle of clinical utility is currently poor for persons with Disorders of Intellectual Development (DID) and mental disorders. This impedes access to healthcare resources; services and social inclusion thereby further aggravating their vulnerability. The purpose of this paper is to present a critical overview and evidence informed recommendations within the context of an international collaborative programme, undertaken by the Faculty of Psychiatry of Intellectual Disability, Royal College of Psychiatrists, UK with support from the World Health Organisation (WHO).

The authors carried out: first, a systematic review (SR) of literature, using PRISMA guidelines regarding the reliability, validity and utility of the ICD-10/Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria in people with DID (PWDID); second, a national and international consultation exercise with partners, stakeholders and experts; third, a multicentric survey of problem behaviours in PWDID; and finally, information dissemination/dialogues including presentations and workshops at key scientific events, consultation networking, data gathering and consensus building.

The SR revealed a dearth of robust studies – most consisting of weak research methodologies. Significant difficulties were highlighted regarding the application of diagnostic criteria in the current classificatory systems – particularly in people with severe/moderate DID. Recommendations supported the introduction WHERE APPROPRIATE of modifications based on observed phenomena (signs) in PWDID in lieu of reported symptoms to facilitate DIAGNOSIS AND better access to healthcare and the community. Heterogeneity precluded quantitative pooling and meta-analysis. The consensus building exercise globally revealed that problem behaviours were the commonest reasons for referral to healthcare services with significant numbers without a diagnosed mental disorder being prescribed psychoactive medication.

The consensus gathering exercise WAS SELECTIVE AND did not cover all of the 194 member states of WHO due to resource and time constraints and this constitutes the main limitation of our study. Based on the SR and expert consensus, the authors submitted evidence informed pragmatic proposals to the WHO aimed at addressing the shortcomings of the ICD-10. The key recommendations focused on improving clinical utility within the context of epistemic iteration which would consolidate and strengthen the future evidence base. It was also recommended that self-injurious behaviour should form a standalone sub category in view of its relevance for healthcare services and resources which underpin clinical utility.

The ICD-11 is a global, multidisciplinary and multilingual development for public health benefit with 70 per cent of the world's health expenditures assigned using this system for resource allocation. Currently mental disorders in PWDID can be misinterpreted, unrecognised and under reported resulting in barriers to access to treatment and healthcare resources. Conversely disorders may be over diagnosed when the inherent discrepancies between the chronological age and the developmental level of functioning are not considered. Conclusions and recommendations from this study will result in better diagnosis of mental disorders and healthcare resources in this population.

PWDID are a vulnerable sector of the population with an increased prevalence of mental health problems who are marginalised and discriminated by society. Early detection, treatment and management of these conditions will prevent further decompensation and stigmatisation.

To the best of the authors knowledge this is the first comprehensive, large-scale study which evaluates the ICD classificatory system within the context of clinical utility for PWDID, including experts and stakeholders from both lower/middle- and high-income countries. The international consultation/consensus building process culminating in the formulation of evidence informed recommendations, aimed at improving the clinical utility of the ICD-11 for this population, has the potential to improve access to appropriate healthcare and treatment and consequent enhancement of their quality of life.

Milk cake is a well-renowned khoa-based dairy product in India, produced either from the buffalo milk or using a specific danedar variety of khoa. Under ambient conditions, shelf-life of milk cake is generally up to 3–4 days, whereas under refrigeration conditions, it can last up to 12–14 days. Therefore, the present study aims to evaluate the effect of modified atmosphere packaging (MAP) to enhance the shelf-life and keeping intact freshness of milk cake under refrigerated conditions (4 ± 2 °C).

Different gas concentrations of N₂ and CO₂ (70:30, 50:50 and 90:10) were used as a treatment, whereas control samples were kept under atmospheric air composition. The product was examined for sensory, physicochemical and microbiological parameters at weekly intervals.

The physicochemical and microbiological attributes displayed gradual elevation with progressive storage period in all the samples. However, the overall sensory profile of the product remained acceptable for a longer duration. Most of the quality parameters in control declined more rapidly with a shelf life of 14 days, in comparison to MAP packed samples, where gas flushing with the ratio 70:30 was found to be best suited for extending the shelf life of milk cake up to 28 days at refrigeration temperature.

To extend the shelf life of milk cake, modified atmosphere was provided with different gas ratios to reach a best-suited environment for sensory, storage life and proximate parameters.

In this paper, the authors introduce supply disruption ambiguity as the inability of a sourcing firm to attach probability point estimates to the occurrence of and to the magnitude of loss from supply disruptions. The authors drew on the “ambiguity in decision-making” literature to define this concept formally, connected it to relevant supply disruption information deficit, positioned it relative to supply chain risk assessment and hypothesized and tested its negative associations with both supply base ties and inventory turnover.

The authors analysed survey data from 171 North American manufacturers and archival data for a subset (88 publicly listed) of these manufacturers via Ordinary Least Squares (OLS) estimation after ensuring that methodological concerns with survey research have been addressed. They used appropriate controls and employed the heteroskedasticity-based instrumental variable (HBIV) approach to ensure that inferences from our results are not unduly influenced by endogeneity.

Strong supply base ties decrease supply disruption ambiguity, which, in turn, increases inventory turnover. Moreover, strong supply base ties and data integration with the supply base have indirect and positive effects on inventory turnover. As sourcing firms strengthen ties and integrate data exchange with their supply base, their inventory turnover improves from access to information relevant to detect and diagnose supply disruptions effectively.

Research on supply disruption management has paid more attention to the “disruption recovery” stage than to the “disruption discovery” stage. In this paper, the authors add novel insights regarding the recognition and diagnosis aspects of the “disruption discovery” stage. These novel insights reveal how and why sourcing firms reduce their overall ambiguity associated with detecting and assessing losses from supply disruptions through establishing strong ties with their supply base and how and why reducing such ambiguity improves inventory turnover performance.

The literature review of post-harvest supply chain (PHSC) losses is carried out and analyzed in this paper followed by bibliometric analysis of the literature.

The literature survey is performed across various dimensions such as PHSC losses, PHSC risks and PHSC sustainability (waste management and waste reduction). One hundred thirty research articles during the period of 1989–2020 were considered for the review.

The PHSC losses have been identified in this literature survey. The calculation and mitigation strategies stated by various researchers in the literature are addressed. The important loss mitigation dynamics are also presented to reduce the PHSC losses and to improve food availability.

The major focus is given on the PHSC of agriculture produces. However, research articles from fish and meat supply chain are excluded as they follow a different perishability curve.

The current work will add value to the agriculture supply chain literature, provide a platform for PHSC losses and provide assistance/guideline toward loss calculation, loss mitigation, improved rural employability, improved rural entrepreneurship and improved revenue generation.

The performed research will assist the researchers, entrepreneurs and farmers to understand the current scenario of food wastage at different stages of the supply chain better. It will provide the guidelines for calculation and mitigation of various stated PHSC losses. This study will be helpful to enhance food availability and food security in post-coronavirus crisis.

The paper explores and highlights PHSC loss calculations and mitigation strategies to identify the postharvest loss situation and better utilization of fresh produces.