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Health disparities affecting lesbian, gay, bisexual, transgender and queer (LGBTQ) populations have been reported in many countries. For Singapore, no large quantitative studies on mental health and well-being in the local LGBTQ community have been published. The authors conducted a community-based survey (National LGBT Census Singapore, 2013; NLCS2013) that covered a comprehensive set of demographic, social and health indicators. Here, the authors investigated mental health status and its correlates in 2,350 LGBTQ individuals within the NLCS2013 sample.

The NLCS2013 was an anonymous online survey conducted amongst self-identified LGBTQ adults (aged ≥ 21 years) residing in Singapore. The survey included the World Health Organisation Well-being Index (WHO-5) as a measure of mental well-being, with low WHO 5 scores (<13/25) indicating poor mental well-being. The authors analysed relationships between low WHO-5 score and a range of respondent characteristics using multivariate logistic regression.

Strikingly, 40.9% of 2,350 respondents analysed had low WHO-5 scores, indicating poor mental well-being. Parental non-acceptance, experience of conflict at home and bullying/discrimination in the workplace or educational environments were all significantly associated with poor mental well-being. Conversely, community participation appeared protective for mental well-being, as respondents who participated in LGBTQ community organisations or events were less likely to have poor mental well-being than non-participants.

The NLCS2013 represents one of the first broad-based efforts to comprehensively and quantitatively capture the sociodemographic and health profile, including mental health status, within Singapore’s resident LGBTQ population. These findings affirm the need to address the mental health needs of LGBTQ individuals in Singapore and to foster safe spaces and allyship.

The electronics industries are relying increasingly on robotics for their production. Wafer handling robots are used to transfer wafers between wafer processing stations. A pick‐measure‐place method is typically utilized to transfer wafers accurately. The measurement step is performed using an aligner, which is time‐consuming. To increase wafer transfer efficiency, it is desirable to speed up the measurement process or place it in parallel with other operations. To solve the problem, optic sensors are installed at each station to estimate the wafer eccentricity on‐the‐fly. The eccentricity values are then applied to control the robot to place the wafer directly onto another station accurately without using the aligner. However, current methods face problems to achieve high accuracy requirements to meet the electronic manufacturing needs. The purpose of this paper is to develop a technique to improve the wafer handling performance in semiconductor manufacturing.

The kinematics model of the wafer handling robot is developed. Two sensor location calibration algorithms are proposed. Method I is based on the wafer handling path. Method II uses the offset paths from the wafer handling path. The results from these two methods are compared. To compute the wafer eccentricity on‐the‐fly, a wafer eccentricity estimation technique is developed.

The developed methods are implemented using a wafer handling robotic system in semiconductor manufacturing. The wafer eccentricity estimation errors are greatly reduced using the developed methods. The experimental results demonstrate that Method II achieves better results and can be used to improve the wafer handling accuracy and efficiency.

The proposed technique is implemented and tested many times on a wafer handing robotic system. The notch alignment in the wafer handling needs further research.

The developed method is validated using a system in semiconductor manufacturing. Hence the developed method can be directly implemented in production if the notch of a wafer can be identified.

This paper provides techniques to improve the wafer handling accuracy in semiconductor manufacturing. Compared with the results using other methods, Method II greatly increases the wafer handling accuracy to satisfy the semiconductor manufacturing needs.

The purpose of this paper is to construct a continuous time series model to study the thermal creep of rough surfaces in contact.

For normal loading, the contact between rough surfaces can often be modeled as the contact of an effective surface with a rigid fiat surface. A solution for the deformation of such equivalent surface, generated using fractal geometry, can be modified. However, in this study only the case of a single rough surface in contact with a rigid flat surface is considered. In the interface, the material is assumed to follow the idealized constitutive viscoelastic standard linear solid (SLS) model. Fractal geometry, through Cantor set theory, is utilized to model the roughness of the surface.

An asymptotic time series power law is obtained, which associates the creep load, the buck temperature and the creep of the fractal surface.

This law is only valid as long as the creep is of the size of the surface roughness. The modified model admits an analytical solution for the case when the behavior is linear viscoelastic. The proposed model shows a good agreement when compared with experimental results available in the literature.

The purpose of this paper is to design a low-power human physiological parameters monitoring system which can monitor six vital parameters simultaneously based on wearable body sensor network.

This paper presents a low-power multiple physiological parameters monitoring system (MPMS) which comprises four subsystems. These are: electrocardiogram (ECG)/respiration (RESP) parameters monitoring subsystem with embedded algorithms; blood oxygen (SpO₂)/pulse rate (PR)/body temperature (BT)/blood pressure (BP) parameters monitoring subsystem with embedded algorithms; main control subsystem which is in charge of system-level power management, communication and interaction design; and upper computer software subsystem which manipulates system function and analyzes data.

Results have successfully demonstrated monitoring human ECG, RESP, PR, SpO₂, BP and BT simultaneously using the MPMS device. In addition, the power reduction technique developed in this work at the physical/hardware level is effective. Reliability of algorithms developed for monitoring these parameters is assessed by Fluke Prosim8 Vital Signs Simulators (produced by Fluke Corp. USA).

The MPMS device provides long-term health monitoring without interference from normal personal activities, which potentially allows applications in real-time daily healthcare monitoring, chronic diseases monitoring, elderly monitoring, human emotions recognization and so on.

First, a power reduction technique at the physical/hardware level is designed to realize low power consumption. Second, the proposed MPMS device enables simultaneously monitoring six key parameters. Third, unlike most monitoring systems in bulk size, the proposed system is much smaller (118 × 58 × 18.5 mm3, 140 g total weight). In addition, a comfortable smart shirt is fabricated to accommodate the portable device, offering reliable measurements.

This paper aims to distinguish the relationship between the morphology characteristics of different scales and the contact performance of the mating surfaces. Also, an integrated method of the spectrum analysis and the wavelet transform is used to separate the morphology characteristics of the actual machined parts.

First, a three-dimensional (3D) surface profilometer is used to obtain the surface morphology data of the actual machined parts. Second, the morphology characteristics of different scales are realized by the wavelet analysis and the power spectral density. Third, the reverse modeling engineering is used to construct the 3D contact models for the macroscopic characteristics. Finally, the finite element method is used to analyze the contact stiffness and the contact area of the 3D contact model.

The contact area and the nominal contact pressure Pn have a nonlinear relationship in the whole compression process for the 3D contact model. The percentage of the total contact area of the macro-scale mating surface is about 70 per cent when the contact pressure Pn is in the range of 0-100 MPa, and the elastic contact area accounts for the vast majority. Meanwhile, when the contact pressure Pn is less than 10MPa, the influence factor (the relative error of contact stiffness) is larger than 50 per cent, so the surface macro-scale morphology has a weakening effect on the normal contact stiffness of the mating surfaces.

This paper provides an effective method for the multi-scale separation of the surface morphology and then lays a certain theoretical foundation for improving the surface quality of parts and the morphology design.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

The paper's aim is to predict numerically the contact temperatures between two rough sliding bodies and to compare with the experimental results.

An elastic contact algorithm is used to analyze the normal contact between two nominally smooth surfaces. The algorithm evaluates real contact area using digitized roughness data and the corresponding contact pressure distribution. Using finite element method a steady state 3D temperature distribution at the interface between the sliding bodies is obtained. Using infrared (IR) imaging technique, experiments were carried out to measure the contact temperature distribution between rough rubbing bodies with a systematic variation of surface roughness and operating variables.

Contact temperature distributions over a wide range of normal load, sliding velocity and surface roughness have been obtained. It was seen that the maximum contact temperature expectedly increases with surface roughness (S_a values), normal load and sliding velocity. The results also indicate that the “hot spots” are located exactly at the positions where the contact pressures are extremely high. Temperatures can be seen to fall drastically at areas where no asperity contacts were established. The temperature contours at different depths were also plotted and it was observed that the temperatures fall away from the actual contact zone and relatively high temperatures persist at the “hot spot” zones much below the contact surface. Finally it is encouraging to find a good correlation between the numerical and experimental results and this indicates the strength of the present analysis.

Experimental accuracy can be improved by using a thermal imaging camera that measures emissivity in situ and uses it to find the contact temperature. The spatial resolution and the response time of the camera also need to be improved. This can improve the correlation between numerical and experimental results.

One of the major factors attributed to the failure of sliding components is the frictional heating and the resulting flash temperatures at the sliding interface. However, it is not easy to measure such temperatures owing to the inherent difficulties in accessing the contact zone. Besides, thermal imaging techniques can be applied only with such tribo‐pairs where at least one of the contacting materials is transparent to IR radiation. In practice, such cases are a rarity. However, the good correlation observed between the numerical and experimental results in this work would give the practicing engineer a confidence to apply the numerical model directly and calculate contact temperatures for any tribo‐material pairs that are generally seen around.

A good correlation between the numerical and experimental results gives credence to the fact that the numerical model can be used to predict contact temperatures between any sliding tribo‐pairs.

Dynamic spreading and wetting on the rough surfaces is complicated, which directly affects the fluxion and phrase transition properties of the fluid. This paper aims to enhance our knowledge of the mechanism of micro-texture lubrication from interface wettability and provide some guidance for the practical manufacturing of the surfaces with special wettability and better lubrication characteristics.

The effect of surface topography on the wetting behavior of both smooth and rough hydrophilic surfaces was investigated using a combination of experimental and simulation approaches. Four types of patterns with different topographies were designed and fabricated through laser surface texturing. The samples were measured with a non-contact three-Dimensional (3D) optical profiler and were parameterized based on ISO 25178. Quantitative research on the relevancy between the topography characteristic and wettability was conducted with several 3D topography parameters.

Results show that for the surfaces with isotropic textures, topography with a small skewness (S_sk) and a large kurtosis (S_ku) exhibits better wettability and spreading behavior. For the surfaces with anisotropic textures (smaller texture aspect ratio, S_tr), dominant textures (such as long groove, rectangle) play a significant guiding role in promoting spreading. In addition, the moving mechanism of the triple contact line and anisotropic spreading were also studied using a computational fluid dynamics simulation. The simulation results have a good adherence with the experimental results.

Most of the surface characterization methods at present remain at a level that is related to geometric description, and the topography parameters are limited to 2D roughness parameters. So in present study, the relevancy between wettability and 3D surface topography parameters is explored. The authors believe that the current work provides a new viewpoint to the relevancy between surface topography and wettability.

The paper aims to investigate the effect of Degussa P-25 Titanium Dioxide (TiO₂) nanoparticles on hydrophobicity and self-cleaning ability as a single organic coating on glass substrate.

Two methods have been used to enhance the hydrophobicity on glass substrates, namely, surface modification by using low surface energy isooctyltrimethoxysilane (ITMS) solution and construction of rough surface morphology using Degussa P-25 TiO₂ nanoparticles with simple bottom-up approach. The prepared sol was applied onto glass substrate using dip-coating technique and stoved in the vacuum furnace 350°C.

The ITMS coating with nano TiO₂ pigment has modified the glass substrate surface by achieving the water contact angle as high as 169° ± 2° and low sliding angle of 0° with simple and low-cost operation. The solid and air phase interface has created excellent anti-dirt and self-cleaning properties against dilute ketchup solution, mud and silicon powder.

Findings will be useful in the development of self-cleaning and anti-dirt coating for photovoltaic panels.

Sol method provides the suitable medium for the combination of organic–inorganic network to achieve high superhydrophobicity and optimum self-cleaning ability.

Application of blended organic–inorganic sol as self-cleaning and anti-dirt coating film.