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As numerous research studies have investigated the effect of the built environment on human contentment, building regulations have advanced as a direct impact on indoor environmental quality (IEQ) to include thermal, lighting, air quality and acoustics systems. Yet, while IEQ and residents' satisfaction have been discussed thoroughly in previous research, only a few studies have researched the role of building regulations as motivating factors in the housing context, specifically in Jordan.

A mixed-method approach was adopted to address this issue involving genotype analysis for building morphology and simulation using Design Builder software. This helped to understand the impact of building regulations variables, including building setback, the height of an adjacent building, orientation and building geometry. Meanwhile, an online survey was conducted to include 410 residents spread out in various building categories (A, B, C and D).

The results of this study revealed that building regulation of setbacks, the height of adjacent buildings and orientation are significant parameters that directly affect IEQ and residents' satisfaction. In addition, based on this study, the matter was clear that the highest total satisfaction resulted based on the highest comfort level in terms of temperature and daylight obtained due to larger setback and lower building height. Yet, this finding undermined smart growth principles due to the limited scope of building regulation that focused only on spatial and physical dimensions, so improving to include environmental aspects such as passive design strategies that appreciate natural ventilation and lighting is necessary, which positively impact IEQ.

The concept of IEQ and residents' satisfaction have been discussed thoroughly, but only a few studies have researched the role of building regulations as motivating factors in the housing context specifically in Jordan.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

The purpose of this study is to successfully apply ultrasonic waves for the quick extraction of flax seed gum from flaxseed hull or whole seed and compare it to the standard technique of extraction.

The effect of the heating source, extracted time, temperature and pH of extracted solution on the extraction was studied. The obtained gum is subsequently used for silk screen printing on cotton, linen and viscous fabrics. Rheological properties and viscosity of the printing paste were scrutinized in the current study to get a better insight into this important polysaccharide. The output of this effort aimed to specify the parameters of the processes for printing textiles to serve in women’s fashion clothes by applying innovated handmade combinations of Islamic art motives using a quick and affordable method. Seven designs are executed, and inspiring from them, seven fashion designs of ladies’ clothes were designed virtually by Clo 3D software.

The result recorded that the new gum has excellent printing properties. In addition, they have better rheological properties, viscosity, chromatic strength and fastness qualities, all of which could help them in commercial production.

Flaxseed and three different fabric types (Cotton, Linen and Viscous) were used.

Synthesis of a new biodegradable thickener from a natural resource, namely, flaxseed, by applying new technology to save time, water and energy.

Synthesis of eco-friendly biodegradable thickener and used in textile printing alternative to the synthetic thickener.