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This paper aims to understand the experiences of disabled doctoral students at one Aotearoa New Zealand University, identifying barriers to accessibility and meaningful participation, and enabling practices.

This research was underpinned by the social model of disability and used an explanatory sequential mixed methods approach. A survey comprising closed and freeform questions was distributed to all doctoral students. From the 64 respondents, 12 also took part in an unstructured, narrative interview. Data were analysed using a combination of methods: descriptive statistics, thematic analysis and poetic inquiry.

Findings are presented mainly as data poetry. The poems centre on complexities faced by disabled doctoral students, and articulate challenges, enabling practices and possibilities for the future encountered by students in this study. Findings are additionally supported with quotes from narrative interviews, open-ended survey questions and descriptive data analysis.

The poetic inquiry approach gives voice to the collective experiences of disabled students. The poetic texts bear witness to the intersections of disability, impairment, chronic illness, neurodiversity and doctoral study, and the lives of students who navigate these intersections. These poems voice and seek to be lightning-rods for social change.

This study aims to improve the stability and obstacle surmounting ability of the traditional wall-climbing robot on the surface of the ship, a wheel-track composite magnetic adsorption wall-climbing robot is proposed in this paper.

The robot adopts a front and rear obstacle-crossing mechanism to achieve a smooth crossover. The robot is composed of two passive obstacle-crossing mechanisms and a frame, which is composed of two obstacle-crossing magnetic wheels and a set of tracks. The obstacle-crossing is realized by the telescopic expansion of the obstacle-crossing mechanism. Three static failure models are established to determine the minimum adsorption force for the robot to achieve stable motion. The Halbach array is used to construct the track magnetic circuit, and the influence of gap, contact area and magnet thickness on the adsorption force is analyzed by parameter simulation.

The prototype was designed and manufactured by the authors for static failure and obstacle crossing tests. The prototype test results show that the robot can cross the obstacle of 10 mm height under the condition of 20 kg load.

A new structure of wall-climbing robot is proposed and verified. According to the test results, the wall-climbing robot can stably climb over the obstacle of 10 mm height under the condition of 20 kg load, which provides a new idea for future robot design.

This article presents a history of the visual merchandising of American firearms from the mid-19th century until the present day. Although the scholarly literature has investigated visual representations of guns in advertising and popular media, it has paid far less attention to how sellers have displayed these objects at or near the point of purchase.

Primary sources include frescoes, engravings and photographs, plus papers, advertising and illustrations in popular newspapers and trade magazines. These and other period visual data are supplemented by secondary sources from a variety of fields, especially retailing and firearms history.

Evidence shows that American firearms were merchandised visually by Samuel Colt at three world expositions in the 1850s, by gunmakers and retailers in the latter 19th century, by Winchester and Remington dealers in the 1920s and 1930s, by high- and low-end retailers in New York in the first half of the 20th century and by gun stores, auctions and shows up to the present day.

The history of visual merchandising generally has focused upon major department stores, their alluring street-front windows and their fancy interior displays. This research explores past and present visual merchandising of firearms by manufacturers and smaller retailers. To the best of the author’s knowledge, it is the first such history of the subject.

This study aims to introduce a novel machine learning feature vector (MLFV) method to bring machine learning to overcome the time-consuming computational fluid dynamics (CFD) simulations for rapidly predicting turbulent flow characteristics with acceptable accuracy.

In this method, CFD snapshots are encoded in a tensor as the input training data. Then, the MLFV learns the relationship between data with a rod filter, which is named feature vector, to learn features by defining functions on it. To demonstrate the accuracy of the MLFV, this method is used to predict the velocity, temperature and turbulent kinetic energy fields of turbulent flow passing over an innovative nature-inspired Dolphin turbulator based on only ten CFD data.

The results indicate that MLFV and CFD contours alongside scatter plots have a good agreement between predicted and solved data with R² ≃ 1. Also, the error percentage contours and histograms reveal the high precisions of predictions with MAPE = 7.90E-02, 1.45E-02, 7.32E-02 and NRMSE = 1.30E-04, 1.61E-03, 4.54E-05 for prediction velocity, temperature, turbulent kinetic energy fields at Re = 20,000, respectively.

The method can have state-of-the-art applications in a wide range of CFD simulations with the ability to train based on small data, which is practical and logical regarding the number of required tests.

The paper introduces a novel, innovative and super-fast method named MLFV to address the time-consuming challenges associated with the traditional CFD approach to predict the physics of turbulent heat and fluid flow in real time with the superiority of training based on small data with acceptable accuracy.

This paper aims to view the tradition of the Prophet in zakat payment, especially the attributed measurements, and adapt these measures to current zakat measurement practices.

This study is designed with an exploratory sequential mixed method where qualitative data were collected from historical archives and also from the measurement of available ṣāʿ صاع and mud_ مد. These standard measures were collected from Malaysia and other Muslim countries and calibrated at the National Measurement Standards Laboratory (currently carried out by the National Metrology Institute of Malaysia). The volume of the ṣāʿ were tabulated, charted, analyzed and determined.

Prophet Muḥammad ordered for zakat al-fiṭr زكاة الفطر to measure the crops using ṣāʿ (gallon: volume measure), not raṭl رطل (pound: standard weight). This paper recommends a reference volume for the ṣāʿ, and from this value, the volume for the smaller measure mud and much larger measure wasq وسق were calculated. The agricultural niṣāb (5 wasq) is one of the key parameters in ṣāʿ volume analysis.

This study covers standard measures acquired from Malaysia, Saudi Arabia and the United Kingdom (traceable to India). Several empirical data are attained from previous studies from Saudi Arabia and North Africa. Also, some theoretical data are obtained from kitab tafsir, hadith and kitab turath (books and records written by early scholars). A concern in this study is the ratio of de-husked grains currently approximated at half of un-hulled grains. This might not necessarily be accurate and may differ by different types of grains.

After the introduction of the modern measurement system known as the International System of Units (SI) in 1971, ṣāʿ became obsolete, leaving each state in Malaysia to define and convert ṣāʿ to SI units variously. This paper contributes to standardizing the conversion to one value with an appropriate SI unit, that has traceability to the Prophet’s ṣāʿ. This national reference standard ṣāʿ is essential for zakat al-fiṭr measurement, important for zakat centers and impacting every Muslim in Malaysia. Often overlooked, ṣāʿ is more crucial as a basis in determining and standardizing the seasonal crops niṣāb, unfolding the reasons why the poor are paying the paddy zakat in Malaysia.

The Prophet’s tradition for ablution is to use water not more than one mud, this is aligned with the 12th Sustainable Development Goals by the United Nations which promoted the responsible consumption of water. Considering half (adults) of the 1.9 billion Muslims in the world, multiplied by 5 times of prayer, the Muslims will at least use 4.75 billion muds of water for ablution alone in 1 day. This is approximately 3.5 billion liters of water daily, and if they limit their water usage to 1 mud for each ablution, they collectively will save at least four times more water (about 14 billion liters) daily than performing ablution from a running tap. Though for ablution, accuracy is not an issue, the mud impact on all Muslims is vital on a daily basis, literally by volume.

Ṣāʿ is essential in measuring food for the annually obligated zakat al-fiṭr and more crucial as a basis in determining the seasonal crops niṣāb. This paper contributes to the development of a national reference standard ṣāʿ for Malaysia that has traceability to the Prophet’s ṣāʿ.

This study aims to address the limited understanding of the complex correlations among strut size, structural orientation and process parameters in selective laser melting (SLM)-fabricated lattice structures. By investigating the effects of crucial process parameters, strut diameter and angle on the microstructure and mechanical performance of AlSi10Mg struts, the research seeks to enhance the surface morphologies, microstructures and mechanical properties of AM lattice structures, enabling their application in various engineering fields, including medical science and space technologies.

This comprehensive study investigates SLM-fabricated AlSi10Mg strut structures, examining the effects of process parameters, strut diameter and angle on densification behavior and microstructural characteristics. By analyzing microstructure, geometrical properties, melt pool morphology and mechanical properties using optical microscopy, scanning electron microscope, energy dispersive X-ray spectroscopy and microhardness tests, the research addresses existing gaps in knowledge on fine lattice strut elements and their impact on surface morphology and microstructure.

The study revealed that laser energy, power density and strut inclination angle significantly impact the microstructure, geometrical properties and mechanical performance of SLM-produced AlSi10Mg struts. Findings insight enable the optimization of SLM process parameters to produce lattice structures with enhanced surface morphologies, microstructures and mechanical properties, paving the way for applications in medical science and space technologies.

This study uniquely investigates the effects of processing parameters, strut diameter and inclination angle on SLM-fabricated AlSi10Mg struts, focusing on fine lattice strut elements with diameters as small as 200 µm. Unlike existing literature, it delves into the complex correlations among strut size, structural orientation and process parameters to understand their impact on microstructure, geometrical imperfections and mechanical properties. The study provides novel insights that contribute to the optimization of SLM process parameters, moving beyond the typically recommended guidelines from powder or machine suppliers.

The purpose of this paper is to determine the relationship between employee empowerment (structural empowerment [SE] and psychological empowerment [PE]), employee commitment (EC) and organizational citizenship behavior (OCB) within the unique context of a learning organization in the Indian retail sector.

The investigation was conducted using a survey-based questionnaire approach. Data were gathered from 222 frontline employees working in different retail stores in India. The researcher used AMOS 22.0 version and SPSS 22.0 version for the data analysis.

This study concluded that SE and PE have a positive and significant influence on OCB and EC. In addition, EC is a mediator between employee empowerment (SE and PE) and OCB.

This research is built on cross-sectional data with a limited sample size, that is, 222 sample size. This study also offers some practical insights to managers of retail stores.

To the best of authors’ knowledge, this study is the first to empirically investigate the mediating role of EC between SE and OCB. By focusing on the interplay of these variables within a learning organization, this study sheds light on the mechanisms driving employee behavior and organizational dynamics in this rapidly evolving retail sector.

The Fourth Industrial Revolution is a prominent area of interest in the field of manufacturing that is bringing about revolutionary changes. In this study, the authors sought to determine whether professionals in academia or industry could have predicted the composition of advanced technologies associated with Industry 4.0 before Germany's Industrie 4.0 policy announcement. The purpose of this paper is to use the process for identifying technologies that can be included in industrial policy to improve national competitiveness in manufacturing.

Relevant documented research from 2000 to 2012 was identified and captured using a systematic literature review. The significant technological advancements during this period were analyzed to determine how technological innovations may have affected predictions about the future of manufacturing. The identified predictions were analyzed using an open-source natural language processing code that clustered relevant topics in the predictions that indicated common themes. The results were then compared to the ideas within “Industry 5.0”.

The results of this study showed that an aggregate analysis of manufacturing predictions would have preemptively revealed the Fourth Industrial Revolution and could have been used to inform industrial policy that could accelerate technology adoption. Also, contrary to popular belief, the popular Industry 5.0 is a sematic exemplification of a concept already embedded within the origins of the Fourth Industrial Revolution.

By examining the provenance of the Fourth Industrial Revolution, lessons are learned that bring light to Industry 4.0 and the measures that can be taken to enable the advancements that it brings. The results of this study show that is would be wise for government policymakers to enact programs that monitor the manufacturing predictions coming out of academia and to analyze them aggregately using natural language processing as a means to identify the next evolutions and revolutions and to mobilize policymakers to enhance outcomes of enacting policy.

Despite high hopes for the realization of Industry 4.0, there has been little discussion about the technological innovations and events that occurred to enable it. To the best of the authors’ knowledge, this is the first study that has determined that an aggregate analysis of manufacturing predictions would have preemptively revealed the Fourth Industrial Revolution. The success of the methodology used in this study has theoretical implications in support of natural language processing (NLP) being used to inform national policy.

Nanotechnology (NT) advancements in personal protective textiles (PPT) or personal protective equipment (PPE) have alleviated spread and transmission of this highly contagious viral disease, and enabled enhancement of PPE, thereby fortifying antiviral behavior.

Review of a series of state of the art research papers on the subject matter.

This paper expounds on novel nanotechnological advancements in polymeric textile composites, emerging applications and fight against COVID-19 pandemic.

As a panacea to “public droplet prevention,” textiles have proven to be potentially effective as environmental droplet barriers (EDBs).

PPT in form of healthcare materials including surgical face masks (SFMs), gloves, goggles, respirators, gowns, uniforms, scrub-suits and other apparels play critical role in hindering the spreading of COVID-19 and other “oral-respiratory droplet contamination” both within and outside hospitals.

When used as double-layers, textiles display effectiveness as SFMs or surgical-fabrics, which reduces droplet transmission to <10 cm, within circumference of ∼0.3%.

NT advancements in textiles through nanoparticles, and sensor integration within textile materials have enhanced versatile sensory capabilities, robotics, flame retardancy, self-cleaning, electrical conductivity, flexibility and comfort, thereby availing it for health, medical, sporting, advanced engineering, pharmaceuticals, aerospace, military, automobile, food and agricultural applications, and more. Therefore, this paper expounds on recently emerging trends in nanotechnological influence in textiles for engineering and fight against COVID-19 pandemic.