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A region’s transforming care partnership identified that autistic adults without an intellectual disability (ID) may be falling through gaps in services when presenting with a significant emotional and/or behavioural need in the absence of a mental health diagnosis. The region’s intensive support teams (ISTs) for adults with ID therefore piloted a short-term “behavioural support service” for this population. The purpose of this paper is to evaluate this pilot.

This study represents a mixed-methods service evaluation over a four year pilot period. The quantitative component examined referral rates and demographic data of accepted and declined referrals; and length of referral episodes and Health of The Nation Outcomes Scores (HoNOS) for accepted referrals. The qualitative component used thematic analysis to identify key themes relating to reasons for referral, clinical/therapeutic needs, and the models of support that most informed assessments and interventions at individual and systems levels.

The ISTs accepted 30 referrals and declined 53. Most accepted referrals were male (83%), and under 24 years old (57%). Average HoNOS scores were above the thresholds generally associated with hospital admission. Key qualitative themes were: transitional support; sexual risks/vulnerabilities; physical aggression; domestic violence; and attachment, trauma and personality difficulties. Support mostly followed psychotherapeutic modalities couched in trauma, attachment and second- and third-wave cognitive behavioural therapies. Positive Behaviour Support (PBS) did not emerge as a model of preference for service users or professionals.

This project represents one of the first of this type for autistic adults without an ID in the UK. It provides recommendations for future service development and research, with implications for Transforming Care policy and guidance.

Patients having ventricular arrhythmias and atrial fibrillation, that are early markers of stroke and sudden cardiac death, as well as benign subjects are all studied using the electrocardiogram (ECG). In order to identify cardiac anomalies, ECG signals analyse the heart's electrical activity and show output in the form of waveforms. Patients with these disorders must be identified as soon as possible. ECG signals can be difficult, time-consuming and subject to inter-observer variability when inspected manually.

There are various forms of arrhythmias that are difficult to distinguish in complicated non-linear ECG data. It may be beneficial to use computer-aided decision support systems (CAD). It is possible to classify arrhythmias in a rapid, accurate, repeatable and objective manner using the CAD, which use machine learning algorithms to identify the tiny changes in cardiac rhythms. Cardiac infractions can be classified and detected using this method. The authors want to categorize the arrhythmia with better accurate findings in even less computational time as the primary objective. Using signal and axis characteristics and their association n-grams as features, this paper makes a significant addition to the field. Using a benchmark dataset as input to multi-label multi-fold cross-validation, an experimental investigation was conducted.

This dataset was used as input for cross-validation on contemporary models and the resulting cross-validation metrics have been weighed against the performance metrics of other contemporary models. There have been few false alarms with the suggested model's high sensitivity and specificity.

The results of cross validation are significant. In terms of specificity, sensitivity, and decision accuracy, the proposed model outperforms other contemporary models.

Sleep arousal detection is an important factor to monitor the sleep disorder.

Thus, a unique nth layer one-dimensional (1D) convolutional neural network-based U-Net model for automatic sleep arousal identification has been proposed.

The proposed method has achieved area under the precision–recall curve performance score of 0.498 and area under the receiver operating characteristics performance score of 0.946.

No other researchers have suggested U-Net-based detection of sleep arousal.

From the experimental results, it has been found that U-Net performs better accuracy as compared to the state-of-the-art methods.

Sleep arousal detection is an important factor to monitor the sleep disorder. Objective of the work is to detect the sleep arousal using different physiological channels of human body.

It will help in improving mental health by monitoring a person's sleep.

Retrofitting and rehabilitation are part of the conservation approach in Heritage Building Conservation Guideline 2016 in Malaysia. Heritage buildings can be retrofitted to preserve their culture and history while being given a new lease. Rehabilitation is a preservation requirement that is more flexible since it assumes that the structure has already deteriorated to the point where repairs are required to prevent further deterioration. Although the strategies of these two approaches are different, their combination resulted in sustainable heritage building maintenance. This long-term maintenance strategy is necessary, especially for Malaysia's numerous heritage schools, which have serious maintenance problems as a result of infrequent maintenance, repairs, and funding shortages.

This study involved secondary data from an intensive literature review along with a comparative study from articles review and context analysis. A comparative study was conducted to determine the typical issue with heritage school buildings and the best maintenance practice for these structures. Finally, it involved a SWOT analysis study of retrofitting and rehabilitating heritage school buildings will be discussed in this study as well.

The findings of this study will focus on developing a strategic planning framework and maintenance for heritage school buildings in Malaysia to achieve sustainable maintenance. It will also highlight sustainable maintenance best practices for heritage school buildings in Malaysia. Finally, SWOT analysis will go over the pros and cons of retrofitting and rehabilitation for these buildings.

This paper put forward the requirements of strategic planning in heritage school buildings and outlines the significance of sustainable maintenance for educational buildings. It is an alternative for cost savings that has not been extensively investigated in previous studies.