Objective Quality Research Articles

Effectivity and safety of trifocal intraocular lenses and capsular tension rings implantation for cataract patients with axial high myopia.

To assess effectivity and safety of trifocal intraocular lenses (IOLs) and capsular tension rings in treating cataract patients with axial high myopia. A prospective nonrandomized controlled clinical trial was conducted. Totally 98 eyes (74 patients) who underwent femtosecond laser-assisted cataract surgery (FLACS) with trifocal IOLs were enrolled in the study and followed up for 2y after surgery: 46 eyes (33 patients) with capsular tension ring implantation in the long axial lengths (AL) group (26<AL<29 mm) and 52 eyes (41 patients) in the normal AL group (22<AL<24.5 mm). Postoperative outcomes about effectivity and safety, including the subjective and objective visual quality, and postoperative complications were assessed. Uncorrected distance visual acuity at 5 m and uncorrected intermediate visual acuity at 60 and 80 cm in the long AL group were significantly worse than those in the normal AL group at 3mo postoperatively (P<0.05). The differences in reading speed, spectacle independence and potential visual complaints between the two groups were not statistically significant (P>0.05). The dysfunctional lens index and total modulation transfer function (MTF) average height were similar between the two groups. The postoperative internal coma aberrations in the axial high myopia eyes were significantly higher than that in the normal AL group (P<0.05). The total satisfaction score in the long AL group (91.32±2.76) was slightly higher than that in the normal AL group (90.36±3.47), but there was no difference (P=0.136). A statistically negative correlation was found between corrected distance visual acuity (CDVA) and dysfunctional lens index (r=-0.382, P=0.009), and between CDVA and the total MTF average height (r=-0.374, P=0.01). But there was no significant correlation between CDVA and total satisfaction score (r=0.059, P=0.696). Postoperative complications mainly presented as posterior capsular opacity (PCO), retinal detachment and cystoid macular edema. There was no difference in the incidence of fundus disease (6.5% vs 3.8%, P=0.663) or PCO (17.4% vs 7.7%, P=0.217) between the two groups at two years. The utilization of trifocal IOL and capsular tension ring implantation is beneficial for cataract patients with axial high myopia undergoing FLACS. This approach not only ensures excellent subjective feelings and objective visual quality, but also does not increase the incidence of postoperative complications.

Comparison of Early Vision Quality of SBL-2 and SBL-3 Segmented Refractive Lens.

To compare objective quality of vision in patients undergoing phacoemulsification with implantation of a bilateral segmented multifocal intraocular lens (SMIOL). A retro-prospective study included 110 eyes of 55 patients who underwent cataract surgery with bilateral SMIOL implantation. Patients were divided according to the type of implanted intraocular lens into group 1 (SBL-2, 62 eyes) and group 2 (SBL-3, 48 eyes). Postoperatively, monocular and binocular uncorrected distance visual acuity (UCDVA), corrected distance visual acuity (BCDVA), uncorrected intermediate visual acuity (UCIVA, at 66 cm), uncorrected near visual acuity (UCNVA, at 40 cm), corrected near visual acuity (BCNVA) and defocus curve were measured and evaluated. The follow-up period was 6 months. Mean UCDVA in group 1 (SBL-2) was 0.010 ±0.15 LogMAR monocularly, 0.01 ±0.10 LogMAR binocularly, and in group 2 (SBL-3) was 0.02 ±0.11 LogMAR monocularly and -0.07 ±0.09 LogMAR binocularly. Binocular defocus curves showed that the SBL-3 group performed better than the SBL-2 lens at a vergence of -1.50 D corresponding to 66 cm (center distance), averaging 0.03 ±0.11 LogMAR, while the SBL-2 group averaged 0.12 ±0.14 LogMAR (p = 0.01). The -2.50 D vergence characterizing near vision (40 cm) was achieved by the SBL-2 lens in our study at 0.33 ±0.15 LogMAR and by the SBL-3 lens at 0.00 ±0.11 LogMAR (p = 0.00). Both SMIOLs provided very good vision at all tested distances 6 months postoperatively. The SBL-2 lens performed better in UCIVA, while the SBL-3 lens excelled in UCDVA and UCNVA.

Improved overall image quality in low-dose dual-energy computed tomography enterography using deep-learning image reconstruction.

To demonstrate the clinical advantages of a deep-learning image reconstruction (DLIR) in low-dose dual-energy computed tomography enterography (DECTE) by comparing images with standard-dose adaptive iterative reconstruction-Veo (ASIR-V) images. In this Institutional review board approved prospective study, 86 participants who underwent DECTE were enrolled. The early-enteric phase scan was performed using standard-dose (noise index: 8) and images were reconstructed at 5mm and 1.25mm slice thickness with ASIR-V at a level of 40% (ASIR-V40%). The late-enteric phase scan used low-dose (noise index: 12) and images were reconstructed at 1.25mm slice thickness with ASIR-V40%, and DLIR at medium (DLIR-M) and high (DLIR-H). The 70keV monochromatic images were used for image comparison and analysis. For objective assessment, image noise, artifact index, SNR and CNR were measured. For subjective assessment, subjective noise, image contrast, bowel wall sharpness, mesenteric vessel clarity, and small structure visibility were scored by two radiologists blindly. Radiation dose was compared between the early- and late-enteric phases. Radiation dose was reduced by 50% in the late-enteric phase [(6.31 ± 1.67)mSv] compared with the early-enteric phase [(3.01 ± 1.09)mSv]. For the 1.25mm images, DLIR-M and DLIR-H significantly improved both objective and subjective image quality compared to those with ASIR-V40%. The low-dose 1.25mm DLIR-H images had similar image noise, SNR, CNR values as the standard-dose 5mm ASIR-V40% images, but significantly higher scores in image contrast [5(5-5), P < 0.05], bowel wall sharpness [5(5-5), P < 0.05], mesenteric vessel clarity [5(5-5), P < 0.05] and small structure visibility [5(5-5), P < 0.05]. DLIR significantly reduces image noise at the same slice thickness, but significantly improves spatial resolution and lesion conspicuity with thinner slice thickness in DECTE, compared to conventional ASIR-V40% 5mm images, all while providing 50% radiation dose reduction.

Assessing the Effect of Enzymatic Debridement on the Scar Quality in Partial-Thickness Burns to Deep Dermal Burns of the Hand: A Long-Term Evaluation.

Background and Objectives: Burn surgery on the hands is a difficult procedure due to the complex anatomy and fragility of the area. Enzymatic debridement has been shown to effectively remove burn eschar while minimizing damage to the surrounding tissue and has therefore become a standard procedure in many burn centers worldwide over the past decade. However, surprisingly, our recent literature review showed limited valid data on the long-term scarring after the enzymatic debridement of the hands. Therefore, we decided to present our study on this topic to fill this gap. Materials and Methods: This study analyzed partial-thickness to deep dermal burns on the hands that had undergone enzymatic debridement at least 12 months prior. Objective measures, like flexibility, trans-epidermal water loss, erythema, pigmentation, and microcirculation, were recorded and compared intraindividually to the uninjured skin in the same area of the other hand to assess the regenerative potential of the skin after EDNX. The subjective scar quality was evaluated using the patient and observer scar assessment scale (POSAS), the Vancouver Scar Scale (VSS), and the "Disabilities of the Arm, Shoulder, and Hand" (DASH) questionnaire and compared interindividually to a control group of 15 patients who had received traditional surgical debridement for hand burns of the same depth. Results: Between January 2014 and December 2015, 31 hand burns in 28 male and 3 female patients were treated with enzymatic debridement. After 12 months, the treated wounds showed no significant differences compared to the untreated skin in terms of flexibility, trans-epidermal water loss, pigmentation, and skin surface. However, the treated wounds still exhibited significantly increased blood circulation and erythema compared to the untreated areas. In comparison to the control group who received traditional surgical debridement, scarring was rated as significantly superior. Conclusions: In summary, it can be concluded that the objective skin quality following enzymatic debridement is comparable to that of healthy skin after 12 months and subjectively fares better than that after tangential excision. This confirms the superiority of enzymatic debridement in the treatment of deep dermal burns of the hand and solidifies its position as the gold standard.

Impact of AI-Based Post-Processing on Image Quality of Non-Contrast Computed Tomography of the Chest and Abdomen.

Non-contrast computed tomography (CT) is commonly used for the evaluation of various pathologies including pulmonary infections or urolithiasis but, especially in low-dose protocols, image quality is reduced. To improve this, deep learning-based post-processing approaches are being developed. Therefore, we aimed to compare the objective and subjective image quality of different reconstruction techniques and a deep learning-based software on non-contrast chest and low-dose abdominal CTs. In this retrospective study, non-contrast chest CTs of patients suspected of COVID-19 pneumonia and low-dose abdominal CTs suspected of urolithiasis were analysed. All images were reconstructed using filtered back-projection (FBP) and were post-processed using an artificial intelligence (AI)-based commercial software (PixelShine (PS)). Additional iterative reconstruction (IR) was performed for abdominal CTs. Objective and subjective image quality were evaluated. AI-based post-processing led to an overall significant noise reduction independent of the protocol (chest or abdomen) while maintaining image information (max. difference in SNR 2.59 ± 2.9 and CNR 15.92 ± 8.9, p < 0.001). Post-processing of FBP-reconstructed abdominal images was even superior to IR alone (max. difference in SNR 0.76 ± 0.5, p ≤ 0.001). Subjective assessments verified these results, partly suggesting benefits, especially in soft-tissue imaging (p < 0.001). All in all, the deep learning-based denoising-which was non-inferior to IR-offers an opportunity for image quality improvement especially in institutions using older scanners without IR availability. Further studies are necessary to evaluate potential effects on dose reduction benefits.

A multi-skilled staff scheduling and team configuration optimisation model for artificial intelligence project portfolio considering competence development and innovation-driven

This paper emphasises the pivotal role of enhancing research and development (R&D) staff competence and boosting team innovation efficiency in configuring R&D project teams for artificial intelligence (AI) product development. Diverging from traditional studies primarily focused on time, quality, and cost objectives, this study proposes prioritising the skill increments of staff and team diversity, aligning with the overarching goals of the R&D cycle. Targeting multi-skilled R&D personnel for scheduling and configuration, a three-objective tradeoff optimisation model is established. The nonlinear mixed-integer constrained programming model incorporates a learning effect for calculating employee skill value and employs a heterogeneity efficiency formula for assessing team diversity, particularly emphasising the diversity of R&D personnel research backgrounds. An algorithm based on Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is designed to obtain the approximate Pareto optimal solution. Furthermore, it compares the algorithm with the multi-objective particle swarm optimisation (MOPSO), explores practical decision-making methods for Pareto solutions, and conducts sensitivity analyses on the learning rate and diversity level. Our research is relevant to enterprises seeking to enhance R&D capabilities with a certain degree of homogeneity among R&D employees. This paper exemplifies and validates the proposed model and solution approach using a new AI product from a healthcare company.

3D Point Cloud Object Detection Method Based on Multi-Scale Dynamic Sparse Voxelization.

Perception plays a crucial role in ensuring the safety and reliability of autonomous driving systems. However, the recognition and localization of small objects in complex scenarios still pose challenges. In this paper, we propose a point cloud object detection method based on dynamic sparse voxelization to enhance the detection performance of small objects. This method employs a specialized point cloud encoding network to learn and generate pseudo-images from point cloud features. The feature extraction part uses sliding windows and transformer-based methods. Furthermore, multi-scale feature fusion is performed to enhance the granularity of small object information. In this experiment, the term "small object" refers to objects such as cyclists and pedestrians, which have fewer pixels compared to vehicles with more pixels, as well as objects of poorer quality in terms of detection. The experimental results demonstrate that, compared to the PointPillars algorithm and other related algorithms on the KITTI public dataset, the proposed algorithm exhibits improved detection accuracy for cyclist and pedestrian target objects. In particular, there is notable improvement in the detection accuracy of objects in the moderate and hard quality categories, with an overall average increase in accuracy of about 5%.

Objective sleep quality predicts subjective sleep ratings

In both clinical and observational studies, sleep quality is usually assessed by subjective self-report. The literature is mixed about how accurately these self-reports track objectively (e.g. via polysomnography) assessed sleep quality, with frequent reports of little to no association. However, previous research on this question focused on between-subject designs, which may be confounded by trait-level variables. In the current study, we used the novel Budapest Sleep, Experiences and Traits Study (BSETS) dataset to investigate if within-subject differences in subjectively reported sleep quality are related to sleep macrostructure and quantitative EEG variables assessed using a mobile EEG headband. We found clear evidence that self-reported sleep quality in the morning is influenced by within-subject variations in sleep onset latency, wake after sleep onset, total sleep time, and sleep efficiency. These effects were replicated if detailed sleep composition metrics (percentage and latency of specific vigilance states) or two alternative measures of subjective sleep quality were used instead. We found no effect of the number of awakenings or relative EEG delta and sigma power. Between-subject effects (relationships between individual mean values of sleep metrics and subjective sleep quality) were also found, highlighting that analyses focusing only on these may be erroneous. Our findings show that while previous investigations of this issue may have been confounded by between-subject effects, objective sleep quality is indeed reflected in subjective sleep ratings.

THE ROLE OF SPIRITUAL AND FORMAL EFFECTS IN THE PERCEPTION OF EMOTIONAL STATES CONSTITUTING A WORK OF ART

: The emotional states that constitute a work of art are formed through the effects of a series of rules and regularities that explain the organization of various systems and also form the foundation of a field of study. Emotions, formal pleasures, and spiritual approaches are among the phenomena that develop a theory defining the general definition of art, delineating its boundaries, and identifying the qualities that allow us to label something as a "work of art." Additionally, art is related with the aesthetics of nature and human subjective realities. The emotional sentiments, characterized as reality for the artist and manifested through seeing and understanding, are dependent on the subjects to be addressed in art. Art, an inherent human capability, is essentially a representation of existence. The tangible qualities of natural objects, considered reality for the artist, assist in perceiving and grasping these emotional feelings in art. Furthermore, individually arising emotional states give rise to aesthetic judgment based on both objective and subjective evaluations. The essential qualities inherent in the essence of the artwork are the foundation of artistic existence. The form that aids in the emergence of artistic presence appears as the perceptible reality of any object through our senses. For the artist, the material characteristics in nature bring forth perceptions. Artistic works produced for aesthetic purposes help bring forth the existing emotional states.&#x0D; The artist reflects their artistic expression through a perspective developed from their perception of the dynamics of art, attempting to create artistic forms based on the interaction between everyday objects and the senses. Objects that transport perceived forms into reality and everyday items, in interaction with the senses, aid in creating artworks as a synthesis of spiritual approaches. Cultural, sociopolitical, and economic factors influencing society are among the primary factors affecting the creation of artworks. Additionally, variables related to the artist's psychological state and societal structure play a role in this transformative process in the production of artworks. Thus, objects that inherently lack artistic meaning interact with each other in the journey of being transformed into artworks by artists.&#x0D; Our research is conducted by examining qualitative data related to the emotional states that constitute a work of art and their perceptual, spiritual, and formal effects. It is believed that this study will contribute to the field of art.

CALCULATION OF THE PROBABILITY OF TEST OBJECT COMPLIANCE WITH THE SPECIFIED REQUIREMENTS AND NON-BINARY DECISION-MAKING RULES

The probability of test object compliance with the specified requirements and non-binary decision is a measure of how likely the test object is to meet the criteria for acceptance or rejection based on multiple factors. It is necessary to calculate by using a valid mathematical model that takes into account the test object's characteristics, the test conditions, the test criteria, and the uncertainty of the measurements. The significance of the probability of test object compliance with the specified requirements and non-binary decision can help to evaluate the quality, reliability, and performance of the test object, as well as to support decision making in complex situations.

Effects of the catastrophic 2020 Yangtze River seasonal floods on microcystins and environmental conditions in Three Gorges Reservoir Area, China.

During July and August 2020, Three Gorges Reservoir Area (TGRA) suffered from catastrophic seasonal floods. Floods changed environmental conditions and caused increase in concentration of microcystins (MCs) which is a common and potent cyanotoxin. However, the effects and seasonal variations of MCs, cyanobacteria, and environmental conditions in TGRA after the 2020 Yangtze River extreme seasonal floods remain largely unclear, and relevant studies are lacking in the literature. A total of 12 representative sampling sites were selected to perform concentration measurement of relevant water quality objectives and MCs in the representative area of the TGRA. The sampling period was from July 2020 to October 2021, which included the flood period. Organic membrane filters were used to perform the DNA extraction and analyses of the 16S rRNA microbiome sequencing data. Results showed the seasonal floods result in significant increases in the mean values of microcystin-RR (MCRR), microcystin-YR (MCYR), and microcystin-LR (MCLR) concentration and some water quality objectives (i.e., turbidity) in the hinterland of TGRA compared with that in non-flood periods (p < 0.05). The mean values of some water quality objectives (i.e., total nitrogen (TN), total phosphorus (TP), total dissolved phosphorus (TDP), and turbidity), MC concentration (i.e., MCRR, MCYR, and MCLR), and cyanobacteria abundance (i.e., Cyanobium_PCC-6307 and Planktothrix_NIVA-CYA_15) displayed clear tendency of increasing in summer and autumn and decreasing in winter and spring in the hinterland of TGRA. The results suggest that seasonal floods lead to changes in MC concentration and environmental conditions in the hinterland of TGRA. Moreover, the increase in temperature leads to changes in water quality objectives, which may cause water eutrophication. In turn, water eutrophication results in the increase in cyanobacteria abundance and MC concentration. In particular, the increased MC concentration may further contribute to adverse effects on human health.

Don't judge a book or health app by its cover: User ratings and downloads are not linked to quality.

To analyse the relationship between health app quality with user ratings and the number of downloads of corresponding health apps. Utilising a dataset of 881 Android-based health apps, assessed via the 300-point objective Organisation for the Review of Care and Health Applications (ORCHA) assessment tool, we explored whether subjective user-level indicators of quality (user ratings and downloads) correlate with objective quality scores in the domains of user experience, data privacy and professional/clinical assurance. For this purpose, we applied spearman correlation and multiple linear regression models. For user experience, professional/clinical assurance and data privacy scores, all models had very low adjusted R squared values (< .02). Suggesting that there is no meaningful link between subjective user ratings or the number of health app downloads and objective quality measures. Spearman correlations suggested that prior downloads only had a very weak positive correlation with user experience scores (Spearman = .084, p = .012) and data privacy scores (Spearman = .088, p = .009). There was a very weak negative correlation between downloads and professional/clinical assurance score (Spearman = -.081, p = .016). Additionally, user ratings demonstrated a very weak correlation with no statistically significant correlations observed between user ratings and the scores (all p > 0.05). For ORCHA scores multiple linear regression had adjusted R-squared = -.002. This study highlights that widely available proxies which users may perceive to signify the quality of health apps, namely user ratings and downloads, are inaccurate predictors for estimating quality. This indicates the need for wider use of quality assurance methodologies which can accurately determine the quality, safety, and compliance of health apps. Findings suggest more should be done to enable users to recognise high-quality health apps, including digital health literacy training and the provision of nationally endorsed "libraries".

Risk-based imprecise post-remediation soil quality objectives

While risk-based contaminated land management is an essential component of sustainable remediation, uncertainty is an unavoidable aspect of risk assessment, since most of the parameters that influence risk are typically affected by uncertainty. Uncertainty may be of different origins; i.e., stochastic or epistemic. Stochastic (or aleatoric) uncertainty arises from random variability related to natural processes, while epistemic uncertainty arises from the incomplete/imprecise nature of available information. But the latter is rarely considered in risk assessments, with the result that risk-based soil quality objectives are almost invariably presented as precise (unique) threshold values. In this paper it is shown: (i) how the joint treatment of stochastic and epistemic uncertainty in risk assessment can lead to soil quality objectives presented as intervals rather than precise values and (ii) how this provides an upper risk-based safeguard for post-remediation monitoring values. The proposed method is illustrated by a real case of soils contaminated by arsenic located in the North-East of France. At this site steel manufacturers have gradually filled up a small valley with slag and dust, over more than a century. These materials are enriched in various metal(loid)s, including arsenic and lead. As the environmental authority has asked for a conversion of the site to other uses that may involve access by the general public, an investigation of human health risk was performed based on a sampling campaign and chemical characterizations including various types of extractions and an analysis of bioaccessibility. While further investigations are required to improve the bioaccessibility model, the human health risk presented herein shows how partial or imprecise information can be incorporated in the analysis while taking into account underlying uncertainties.

Role of Organisational Culture in Enabling Effective Communication and Total Quality Management Practices in Champion Breweries Plc, Uyo, Akwa Ibom State, Nigeria

Organisational culture shapes communication patterns and effectively implements Total Quality Management (TQM) practices. However, there is limited empirical research on how organisational culture influences these aspects, especially in developing countries like Nigeria. This study aimed to examine the role of organisational culture at Champion Breweries PLC in Akwa Ibom State, Nigeria, in enabling or hindering communication and TQM practices. A quantitative survey was conducted with a sample of 278 employees. The results revealed that while Champion Breweries' culture encourages openness and continuous improvement to some degree, enhancements are needed in organisational transparency, cross-departmental collaboration, employee involvement, and learning orientation to support communication and TQM fully. Key cultural aspects that facilitate effective practices include teamwork, shared goals and customer focus. However, empowerment and continuous improvement mindsets need reinforcement. Leadership is pivotal in championing culture evolution focused on greater openness, collaboration and empowerment. The study concludes that shaping a quality-focused culture is crucial for optimal TQM implementation and communication effectiveness. It provides insights into realigning organisational culture with quality objectives through initiatives targeted at assumptions, values, structures and leadership role modelling. It is recommended that, the leadership at champion breweries, needs to spearhead culture change through their communication and behaviours, consciously. Also should transparency, collaboration, learning and empowerment that are vital for commination and TQM effectiveness.

Do Objective and Peer-perceived Qualities Moderate the Effect of Narcissism on Social Outcomes?

Narcissistic individuals have a strong desire for attracting short-term mates, being influential in groups, and attaining prestige and material wealth. Past research suggests that narcissistic individuals are also quite successful in attaining these outcomes and these effects are due to narcissists’ grandiose self-image and admiration-seeking tendency (i.e., admiration component of narcissism). In the current research, we investigated whether the effects of narcissistic admiration are moderated by specific qualities that are helpful for attaining the respective outcomes. Specifically, we tested whether physical attractiveness moderates the effect of narcissistic admiration on short-term mate appeal, whether intelligence and socio-emotional abilities moderate the effect on social influence, and whether intelligence moderates the effects on occupational prestige and material wealth. Analyzing data from a speed-dating study (Study 1, N = 397), a round-robin laboratory study (Study 2, N = 256), and a panel study representative of the German population (Study 3, N = 1,477), we found that narcissistic admiration and the respective qualities predicted the outcomes, but in most cases, their interactions were non-significant. There was one exception: Narcissistic admiration interacted with verbal intelligence in the sense that the effects of narcissistic admiration on occupational prestige and material wealth were more positive, the higher verbal intelligence was.

Performance Comparison of VVC, AV1, HEVC, and AVC for High Resolutions

Over the years, there has been growing interest in multimedia services, especially in the video domain, where firms and subscribers require higher resolutions, framerates, and sampling precision. This results in a huge amount of data that needs to be processed, stored, and transmitted. As a result, researchers face the challenge of developing new compression standards that can reduce the amount of data while maintaining the same quality. In this paper, the compression performance of the latest and most commonly used video codecs, namely H.266/VVC, AV1, H265/HEVC, and H.264/AVC was examined. The test set included seven sequences of various content at 8K, Ultra HD (UHD), and Full HD (FHD) resolutions, encoded to bitrates ranging from 1 to 15 Mbps for FHD and UHD resolutions and from 5 to 50 Mbps for 8K resolution. Objective quality metrics, such as peak signal-to-noise ratio (PSNR), the structural similarity index (SSIM), and video multi-method assessment fusion (VMAF) were used to measure codec performance. The results showed that H.266/VVC outperformed all other codecs, namely H.264/AVC, H.265/HEVC, and AV1, in terms of the Bjøntegaard delta (BD) model. The average bitrate savings were approximately 78% for H.266/VVC, 63% for AV1, and 53% for H.265/HEVC relative to H.264/AVC, 59% for H.266/VVC and 22% for AV1 compared to H.264/AVC, and 46% for H.266/VVC relative to AV1 (all for 8K resolution). The results also showed that codec performance varied depending on resolution, with higher resolutions showing greater efficiency for newly developed codecs, such as H.266/VVC and AV1. This confirms the fact that the H.266/VVC and AV1 codecs were primarily developed for videos at high resolutions, such as 8K and/or UHD.

PCQD‐AR: Subjective quality assessment of compressed point clouds with head‐mounted augmented reality

AbstractThis letter fully studies the coloured point cloud quality assessment in augmented reality (AR) environment through subjective test. Firstly, a point cloud dataset, named point cloud quality dataset‐AR, including ten reference point clouds and their 90 distorted versions is presented, which were generated using the reference software of video‐based point cloud compression across various combinations of geometry and texture quantization parameters. Then, the impact of geometry and texture distortions on perceived quality of point clouds in AR environment was discussed in detail. Moreover, the performance of existing objective point cloud quality assessment metrics on the proposed dataset is evaluated. The subjective dataset including the values of mean opinion score were released to public.

Anomaly detection using deep learning based model with feature attention

&lt;span lang="EN-US"&gt;Anomaly detection is a difficult problem with numerous industrial applications, such as analyzing the quality of objects using images. Anomaly detection is the process of identifying outliers in a given dataset. Recently, machine learning approaches to computer vision problems have outperformed classical state-of-the-art approaches. Anomaly detection problems can be solved using supervised approaches. However, labelled datasets are hard to obtain. Thus, many researchers have taken an unsupervised approach to solving the problem of anomaly detection. In this study, we use an adversarial auto encoder model as a base model and create a custom model to detect anomalies in images and videos. The model was trained exclusively on normal data. The modified national institute of standards and technology database (MNIST) dataset achieved an area under curve (AUC) score of 0.872 for anomaly detection, while the University of California San Diego (UCSD) anomaly dataset (Video dataset) achieved an AUC score of 0.74 for Ped1 and 0.87 for Ped2. To calculate the anomaly score, the concept of attention weights is combined with the reconstruction loss, and the proposed method outperformed other similar methods designed for the same problem. However, the usefulness of the proposed model was demonstrated through the detection of anomalies, and the model is still being improved for use in real-world situations.&lt;/span&gt;

Technical assessment of resolution of handheld ultrasound devices and clinical implications.

Since handheld ultrasound devices are becoming increasingly ubiquitous, objective criteria to determine image quality are needed. We therefore conducted a comparison of objective quality measures and clinical performance. A comparison of handheld devices (Butterfly IQ+, Clarius HD, Clarius HD3, Philips Lumify, GE VScan Air) and workstations (GE Logiq E10, Toshiba Aplio 500) was performed using a phantom. As a comparison, clinical investigations were performed by two experienced ultrasonographers by measuring the resolution of anatomical structures in the liver, pancreas, and intestine in ten subjects. Axial full width at half maximum resolution (FWHM) of 100µm phantom pins at depths between one and twelve cm ranged from 0.6-1.9mm without correlation to pin depth. Lateral FWHM resolution ranged from 1.3-8.7mm and was positively correlated with depth (r=0.6). Axial and lateral resolution differed between devices (p<0.001) with the lowest median lateral resolution observed in the E10 (5.4mm) and the lowest axial resolution (1.6mm) for the IQ+ device. Although devices showed no significant differences in most clinical applications, ultrasonographers were able to differentiate a median of two additional layers in the wall of the sigmoid colon and one additional structure in segmental portal fields (p<0.05) using cartwheel devices. While handheld devices showed superior or similar performance in the phantom and routine measurements, workstations still provided superior clinical imaging and resolution of anatomical substructures, indicating a lack of objective measurements to evaluate clinical ultrasound devices.

Evaluation of the impact of coal mining on surface water in the Boesmanspruit, Mpumalanga, South Africa

Surface water quality has major environmental and socioeconomic consequences, notably in terms of the country’s long-term fresh water supply. This study aimed at assessing the current state of water quality and status of the Boesmanspruit in a coal mining environment. The study used historical water quality data for a period of five years from 2017 to 2021. Aluminum, calcium, iron, manganese, magnesium, sodium, sulfate, electrical conductivity, pH, and total dissolved solids were the water quality variables selected for the study; the chosen variables were chosen based on the available secondary data. The water quality was evaluated against South African resource quality objectives, the South African water quality guidelines, and the Canadian Council of Ministers of the Environment water quality index (CCME-WQI). The data were analyzed using such as the CCME-WQI, the comprehensive pollution index (CPI), and multivariate statistics. The following parameters were above the prescribed thresholds: pH, total dissolved solids, electrical conductivity, sulfate, manganese, and iron. The CCME-WQI results showed that monitoring locations GR S26 and GR S21 near mining activities had poor water quality (40–44), whereas comprehensive pollution index (CPI) also had similar category results for the monitoring points, indicating that they were heavily polluted (2.4–4.8). The WQI showed that if certain variables, such as aluminum, iron, magnesium, sulfate, electrical conductivity, and total dissolved solids, exceed the permissible range, the water quality would deteriorate in accordance with the CPI classification. Therefore, the CPI was the best way to categorize the water quality. The principal component analysis and cluster analysis identified two primary sources of pollution which are anthropogenic and natural. The utilization of statistical analysis proved to be effective in determining the ideal quantity of significant variables within the study area. The study recommends low-cost options for reducing the effects of acid mine drainage, which includes passive mine water treatment methods using artificial wetlands.