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Strength enhancement of non-seismic concrete beam–column joints (NSCBCJs) via carbon fiber-reinforced polymer composites (CFRPCs) integration has become a viable strategy. However, the implementation of these NSCBCJs without transverse reinforcement shows poor performance during earthquakes in seismic locations. Thus, strengthening the anti-seismic performance of NSCBCJs to meet the acceptance criteria of ACI 374.1-05 is fundamentally significant. Yet, in addition to limited experimental results, only a few numerical studies based on the finite element model have been performed to determine the anti-seismic behavior of NSCBCJs. Consequently, the stress contribution of CFRPCs to NSCBCJs is not clearly understood. Therefore, we used a finite element model to examine the strength contribution of CFRPCs to NSCBCJs. The performance of the proposed finite element model was validated using the experimental results, demonstrating a good agreement between them. It was shown that the strength of NSCBCJs was improved due to CFRPC incorporation, thereby achieving compliance with the seismic requirements of ACI 374.1-05. In addition, CFRPCs presence could enhance the confinement, reduce the deformation of the NSCBCJs and, thus, decrease their stiffness and strength degradation, while simultaneously improving the energy dissipation.

As the demand for renewable energy sources continues to increase, solar energy is becoming an increasingly popular option. Therefore, effective training in solar energy systems design and operation is crucial to ensure the successful implementation of solar energy technology. To make this training accessible to a wide range of people from different backgrounds, it is important to develop effective and engaging training methods. Immersive virtual reality (VR) has emerged as a promising tool for enhancing solar energy training and education. In this paper, a unique method is presented to evaluate the effectiveness of an immersive VR experience for solar energy systems design using a multi-modal approach that includes a detailed analysis of user engagement. To gain a detailed analysis of user engagement, the VR experience was segmented into multiple scenes. Moreover, an eye-tracker and wireless wearable sensors were used to accurately measure user engagement and performance in each scene. The results demonstrate that the immersive VR experience was effective in improving users’ understanding of solar energy systems design and their ability to perform complex tasks. Moreover, by using sensors to measure user engagement, specific areas that required improvement were identified and insights for enhancing the design of future VR training experiences for solar energy systems design were provided. This research not only advances VR applications in solar energy education but also offers valuable insights for designing effective and engaging training modules using multi-modal sensory input and real-time user engagement analytics.

Background: Breast cancer (BC) is frequently diagnosed among Canadian women. While targeted therapies are available for most BC patients; treatment resistance is common and novel therapeutic targets are of interest. Thyroid hormones (TH) bound to thyroid hormone receptors (THR) influence cell proliferation and differentiation; they are also involved in the growth and development of normal breast tissue. Evidence suggests that THRβ is a tumor suppressor in various solid tumors. Purpose: This narrative review discusses retrospective studies regarding the clinical relevance of THRβ as a potential prognostic biomarker and therapeutic target in BC. Methods: We consulted with an information specialist to develop a search strategy to find all literature related to THRα expression as a potential prognostic and therapeutic biomarker in breast cancer. The primary search was developed for Medline and translated to Embase. The searches were conducted on the Ovid platform on 18 August 2023. Results: Across seven retrospective studies identified, several have shown an association between higher THRβ1 expression with a lower risk of BC recurrence and with longer overall survival. Conclusions: Some evidence suggests that THRβ expression is associated with a lower risk of BC recurrence and death. Validation of THRβ as an independent prognostic biomarker and possible predictive biomarker of response to endocrine therapy and/or chemotherapy is of interest. Given that THRβ is upstream of the AKT/PI3K pathway, its potential as a predictive biomarker of response to AKT inhibitors and/or PI3K inhibitors may also be of value. Finally, the potential re-purposing of THRβ agonists as anti-cancer agents warrants investigation.

This paper presents a comprehensive and systematic review of virtual reality (VR) as an innovative educational tool specifically for solar photovoltaic energy systems. VR technology, with its immersive and interactive capabilities, offers a unique platform for in-depth learning and practical training in the field of solar energy. The use of VR in this context not only enhances the understanding of solar photovoltaic (PV) systems but also provides a hands-on experience that is crucial for developing the necessary skills in this rapidly evolving field. Among the 6814 articles initially identified, this systematic review specifically examined 15 articles that focused on the application of VR in PV education. These selected articles demonstrate VR’s ability to accurately simulate real-world environments and scenarios related to solar energy, providing an in-depth exploration of its practical applications in this field. By offering a realistic and detailed exploration of PV systems, VR enables learners to gain a deeper understanding of harnessing, managing and using such a vast energy resource. The paper further discusses the implications of employing VR in educational settings, highlighting its potential to change the way solar energy professionals are trained, thereby contributing significantly to the acceleration of photovoltaic technology adoption and its integration into sustainable energy solutions.

Overuse and misuse of antibiotics have led to the emergence of antibiotic-resistant bacteria and pose a significant threat due to adverse drug reactions, increased healthcare costs, and poor patient outcomes. Antibiotic stewardship programs, including antibiotic de-escalation, aim to optimize antibiotic use and to reduce the development of antibiotic resistance. This systematic review and meta-analysis aim to fill the gap by analyzing the current literature on the implications of antibiotic de-escalation in patients on antibiotic use, duration of hospital stay, mortality, and cost; to update clinical practice recommendations for the proper use of antibiotics; and to offer insightful information about the efficacy of antibiotic de-escalation. Based on the PRISMA 2020 recommendations, a comprehensive literature search was conducted using electronic databases and reference lists of identified studies. Eligible studies were published in English, conducted in humans, and evaluated the impact of antibiotic de-escalation on antibiotic consumption, length of hospitalization, mortality, or cost in hospitalized adult patients. Data were extracted using a standardized form, and the quality of included studies was assessed using the Newcastle–Ottawa Scale. The data from 25 studies were pooled and analyzed using the Revman-5 software, and statistical heterogeneity was evaluated using a chi-square test and I2 statistics. Among the total studies, seven studies were conducted in pediatric patients and the remaining studies were conducted in adults. The studies showed a wide range of de-escalation rates, with most studies reporting a rate above 50%. In some studies, de-escalation was associated with a decrease in antimicrobial utilization and mean length of stay, but the impact on overall cost was mixed. Our pooled analysis for mortality reported that a significant difference was observed between the de-escalation group and the non-de-escalation group in a random effect model (RR = 0.67, 95% CI 0.52–0.86, p = 0.001). The results suggest that de-escalation therapy can be applied in different healthcare settings and patient populations. However, the de-escalation rate varied depending on the study population and definition of de-escalation. Despite this variation, the results of this systematic review support the importance of de-escalation as a strategy to optimize antibiotic therapy and to reduce the development of subsequent antibiotic resistance. Further studies are needed to evaluate the impact of de-escalation on patient outcomes and to standardize the definition of de-escalation to allow for better comparison of studies.

Background/Objectives: Nutritional status significantly influences cardiac surgery outcomes, with malnutrition contributing to poorer results and increased complications. This study addresses the critical gap in understanding by exploring the relationship between pre-operative nutritional status and post-operative cognitive dysfunction (POCD) in adult cardiac patients. Methods: A comprehensive search across key databases investigates the prevalence of malnutrition in pre-operative cardiac surgery patients, its effects, and its association with POCD. Factors exacerbating malnutrition, such as chronic illnesses and reduced functionality, are considered. The study also examines the incidence of POCD, its primary association with CABG procedures, and the impact of malnutrition on complications like inflammation, pulmonary and cardiac failure, and renal injury. Discussions: Findings reveal that 46.4% of pre-operative cardiac surgery patients experience malnutrition, linked to chronic illnesses and reduced functionality. Malnutrition significantly contributes to inflammation and complications, including POCD, with an incidence ranging from 15 to 50%. CABG procedures are particularly associated with POCD, and malnutrition prolongs intensive care stays while increasing vulnerability to surgical stress. Conclusions: The review underscores the crucial role of nutrition in recovery and advocates for a universally recognized nutrition assessment tool tailored to diverse cardiac surgery patients. Emphasizing pre-operative enhanced nutrition as a potential strategy to mitigate inflammation and improve cognitive function, the review highlights the need for integrating nutrition screening into clinical practice to optimize outcomes for high-risk cardiac surgery patients. However, to date, most data came from observational studies; hence, there is a need for future interventional studies to test the hypothesis that pre-operative enhanced nutrition can mitigate inflammation and improve cognitive function in this patient population.

Backgrounds: Sleep disturbances are prevalent among elderly individuals. While polysomnography (PSG) serves as the gold standard for sleep monitoring, its extensive setup and data analysis procedures impose significant costs and time constraints, thereby restricting the long-term application within the general public. Our laboratory introduced an innovative biomarker, utilizing artificial intelligence algorithms applied to PSG data to estimate brain age (BA), a metric validated in cohorts with cognitive impairments. Nevertheless, the potential of exercise, which has been a recognized means of enhancing sleep quality in middle-aged and older adults to reduce BA, remains undetermined. Methods: We conducted an exploratory study to evaluate whether 12 weeks of moderate-intensity exercise can improve cognitive function, sleep quality, and the brain age index (BAI), a biomarker computed from overnight sleep electroencephalogram (EEG), in physically inactive middle-aged and older adults. Home wearable devices were used to monitor heart rate and overnight sleep EEG over this period. The NIH Toolbox Cognition Battery, in-lab overnight polysomnography, cardiopulmonary exercise testing, and a multiplex cytokines assay were employed to compare pre- and post-exercise brain health, exercise capacity, and plasma proteins. Results: In total, 26 participants completed the initial assessment and exercise program, and 24 completed all procedures. Data are presented as mean [lower 95% CI of mean, upper 95% CI of mean]. Participants significantly increased maximal oxygen consumption (Pre: 21.11 [18.98, 23.23], Post 22.39 [20.09, 24.68], mL/kg/min; effect size: −0.33) and decreased resting heart rate (Pre: 66.66 [63.62, 67.38], Post: 65.13 [64.25, 66.93], bpm; effect size: −0.02) and sleeping heart rate (Pre: 64.55 [61.87, 667.23], Post: 62.93 [60.78, 65.09], bpm; effect size: −0.15). Total cognitive performance (Pre: 111.1 [107.6, 114.6], Post: 115.2 [111.9, 118.5]; effect size: 0.49) was significantly improved. No significant differences were seen in BAI or measures of sleep macro- and micro-architecture. Plasma IL-4 (Pre: 0.24 [0.18, 0.3], Post: 0.33 [0.24, 0.42], pg/mL; effect size: 0.49) was elevated, while IL-8 (Pre: 5.5 [4.45, 6.55], Post: 4.3 [3.66, 5], pg/mL; effect size: −0.57) was reduced. Conclusions: Cognitive function was improved by a 12-week moderate-intensity exercise program in physically inactive middle-aged and older adults, as were aerobic fitness (VO2max) and plasma cytokine profiles. However, we found no measurable effects on sleep architecture or BAI. It remains to be seen whether a study with a larger sample size and more intensive or more prolonged exercise exposure can demonstrate a beneficial effect on sleep quality and brain age.

Chemoresistance is a major obstacle in cancer treatment, often leading to disease progression and poor outcomes. It arises through various mechanisms such as genetic mutations, drug efflux pumps, enhanced DNA repair, and changes in the tumor microenvironment. These processes allow cancer cells to survive despite chemotherapy, underscoring the need for new strategies to overcome resistance and improve treatment efficacy. Crizotinib, a first-generation multi-target kinase inhibitor, is approved by the FDA for the treatment of ALK-positive or ROS1-positive non-small cell lung cancer (NSCLC), refractory inflammatory (ALK)-positive myofibroblastic tumors (IMTs) and relapsed/refractory ALK-positive anaplastic large cell lymphoma (ALCL). Crizotinib exists in two enantiomeric forms: (R)-crizotinib and its mirror image, (S)-crizotinib. It is assumed that the R-isomer is responsible for the carrying out various processes reviewed here The S-isomer, on the other hand, shows a strong inhibition of MTH1, an enzyme important for DNA repair mechanisms. Studies have shown that crizotinib is an effective multi-kinase inhibitor targeting various kinases such as c-Met, native/T315I Bcr/Abl, and JAK2. Its mechanism of action involves the competitive inhibition of ATP binding and allosteric inhibition, particularly at Bcr/Abl. Crizotinib showed synergistic effects when combined with the poly ADP ribose polymerase inhibitor (PARP), especially in ovarian cancer harboring BRCA gene mutations. In addition, crizotinib targets a critical vulnerability in many p53-mutated cancers. Unlike its wild-type counterpart, the p53 mutant promotes cancer cell survival. Crizotinib can cause the degradation of the p53 mutant, sensitizing these cancer cells to DNA-damaging substances and triggering apoptosis. Interestingly, other reports demonstrated that crizotinib exhibits anti-bacterial activity, targeting Gram-positive bacteria. Also, it is active against drug-resistant strains. In summary, crizotinib exerts anti-tumor effects through several mechanisms, including the inhibition of kinases and the restoration of drug sensitivity. The potential of crizotinib in combination therapies is emphasized, particularly in cancers with a high prevalence of the p53 mutant, such as triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSOC).

Muscle-enriched A-type lamin-interacting protein (MLIP) is an emerging protein involved in cellular homeostasis and stress adaptation. Eukaryotic cells regulate various cellular processes, including metabolism, DNA repair, and cell cycle progression, to maintain cellular homeostasis. Disruptions in this homeostasis can lead to diseases such as cancer, characterized by uncontrolled cell growth and division. This review aims to explore for the first time the unique role MLIP may play in cancer development and progression, given its interactions with the PI3K/Akt/mTOR pathway, p53, MAPK9, and FOXO transcription factors, all critical regulators of cellular homeostasis and tumor suppression. We discuss the current understanding of MLIP’s involvement in pro-survival pathways and its potential implications in cancer cells’ metabolic remodeling and dysregulated homeostasis. Additionally, we examine the potential of MLIP as a novel therapeutic target for cancer treatment. This review aims to shed light on MLIP’s potential impact on cancer biology and contribute to developing innovative therapeutic strategies.

This research aims to introduce and examine a new type of polynomial called the Δh Legendre–Appell polynomials. We use the monomiality principle and operational rules to define the Δh Legendre–Appell polynomials and explore their properties. We derive the generating function and recurrence relations for these polynomials and their explicit formulas, recurrence relations, and summation formulas. We also verify the monomiality principle for these polynomials and express them in determinant form. Additionally, we establish similar results for the Δh Legendre–Bernoulli, Euler, and Genocchi polynomials.

Background: Alzheimer’s disease (AD) presents a significant global health concern, characterized by neurodegeneration and cognitive decline. Neuroinflammation is a crucial factor in AD development and progression, yet effective pharmacotherapy remains elusive. Sulforaphane (SFN), derived from cruciferous vegetables and mainly from broccoli, has shown a promising effect via in vitro and in vivo studies as a potential treatment for AD. This study aims to investigate the possible prophylactic mechanisms of SFN against prefrontal cortex (PFC)-related recognition memory impairment induced by lipopolysaccharide (LPS) administration. Methodology: Thirty-six Swiss (SWR/J) mice weighing 18–25 g were divided into three groups (n = 12 per group): a control group (vehicle), an LPS group (0.75 mg/kg of LPS), and an LPS + SFN group (25 mg/kg of SFN). The total duration of the study was 3 weeks, during which mice underwent treatments for the initial 2 weeks, with daily monitoring of body weight and temperature. Behavioral assessments via novel object recognition (NOR) and temporal order recognition (TOR) tasks were conducted in the final week of the study. Inflammatory markers (IL-6 and TNF), antioxidant enzymes (SOD, GSH, and CAT), and pro-oxidant (MDA) level, in addition to acetylcholine esterase (AChE) activity and active (caspase-3) and phosphorylated (AMPK) levels, were evaluated. Further, PFC neuronal degeneration, Aβ content, and microglial activation were also examined using H&E, Congo red staining, and Iba1 immunohistochemistry, respectively. Results: SFN pretreatment significantly improved recognition memory performance during the NOR and TOR tests. Moreover, SFN was protected from neuroinflammation and oxidative stress as well as neurodegeneration, Aβ accumulation, and microglial hyperactivity. Conclusion: The obtained results suggested that SFN has a potential protective property to mitigate the behavioral and biochemical impairments induced by chronic LPS administration and suggested to be via an AMPK/caspase-3-dependent manner.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism, within which examining social sustainability becomes imperative. While the prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases, including Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana), are discussed through multi-layered investigations which involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people–place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people–place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

Deepfakes are digital audio, video, or images manipulated using machine learning algorithms. These manipulated media files can convincingly depict individuals doing or saying things they never actually did. Deepfakes pose significant risks to our lives, including national security, financial markets, and personal privacy. The ability to create convincing deep fakes can also harm individuals’ reputations and can be used to spread disinformation and fake news. As such, there is a growing need for reliable and accurate methods to detect deep fakes and prevent their harmful effects. In this paper, a hybrid convolutional neural network (CNN) and recurrent neural network (RNN) with a particle swarm optimization (PSO) algorithm is utilized to demonstrate a deep learning strategy for detecting deepfake videos. High accuracy, sensitivity, specificity, and F1 score were attained by the proposed approach when tested on two publicly available datasets: Celeb-DF and the Deepfake Detection Challenge Dataset (DFDC). Specifically, the proposed method achieved an average accuracy of 97.26% on Celeb-DF and an average accuracy of 94.2% on DFDC. The results were compared to other state-of-the-art methods and showed that the proposed method outperformed many. The proposed method can effectively detect deepfake videos, which is essential for identifying and preventing the spread of manipulated content online.

Despite Malaysia’s year-round sunny climate, vitamin D deficiency is surprisingly common among Malaysians. However, we hypothesise that vitamin D levels among coastal populations are above average. Thus, we aim to investigate vitamin D levels and correlate them with the potential contributing factors from three selected coastal villages in Johor, Melaka, and Negeri Sembilan. Convenient sampling was employed to recruit 120 Malay male and female participants, and dried blood spots (DBS) were obtained to measure 25 (OH) vitamin D3 levels via immunoassay. Participants also completed two questionnaires: the Sun Exposure and Protection Index (SEPI) and a validated food frequency questionnaire for Malaysians. The participant pool comprised 35.20% males and 64.80% females who completed all questionnaires and underwent DBS sampling. Our analysis revealed a significant difference (p < 0.05) based on skin tones, impacting various facets of the SEPI, including sunscreen usage, protective clothing utilisation, and the adoption of protective headwear. Furthermore, gender emerged as another pivotal factor, demonstrating significant distinctions in these SEPI components. Nevertheless, there is a weak correlation between SEPI scores and vitamin D levels. Subsequent regression analysis did produce statistically significant results (p = 0.018), yet the associated low R2 value indicated a weak correlation between dietary vitamin D intake that impacts vitamin D levels. In conclusion, our preliminary findings indicate that sun exposure and dietary factors are not the sole determinants of 25-OH vitamin D3 levels. However, we require more samples from various coastal locations for a definitive justification.

Increased pressure and shear stress distributions at the limb–socket interface are hypothesised to result from changes in the residual limb shape and volume, which can cause socket fit difficulties. Accurate residual limb volume measurements may aid clinicians in developing strategies to accommodate volume fluctuations. This review primarily aims to analyse the techniques available for measuring the residual lower limb volume that may be used in clinical settings, as documented in the works published over the previous four decades. A comprehensive search of articles in PubMed, ScienceDirect, Web of Science, and Google Scholar identified 904 articles, and further analysis resulted in only 39 articles being chosen to be analysed. Based on the findings, there are nine techniques available to measure the residual limb volume: water displacement, anthropometric measurement, contact probes, optical scanning, spiral X-ray computed tomography (SXCT), magnetic resonance imaging (MRI), ultrasound, laser scanning, and bioimpedance. Considering the variety of techniques for determining residual limb volume, it is critical to choose the ones that best suit clinicians’ objectives, and each technique has potential sources of error that should be avoided by taking precautionary action. A comprehensive study of the measurement techniques is needed since researchers have developed and extensively utilised many new measuring devices, especially handheld 3D laser scanners.

Polycystic ovary syndrome (PCOS) is the most common endocrine-metabolic disease in females of reproductive age, affecting 4–20% of pre-menopausal women worldwide. MicroRNAs (miRNAs) are endogenous, single-stranded, non-coding, regulatory ribonucleic acid molecules found in eukaryotic cells. Abnormal miRNA expression has been associated with several diseases and could possibly explain their underlying pathophysiology. MiRNAs have been extensively studied for their potential diagnostic, prognostic, and therapeutic uses in many diseases, such as type 2 diabetes, obesity, cardiovascular disease, PCOS, and endometriosis. In women with PCOS, miRNAs were found to be abnormally expressed in theca cells, follicular fluid, granulosa cells, peripheral blood leukocytes, serum, and adipose tissue when compared to those without PCOS, making miRNAs a useful potential biomarker for the disease. Key pathways involved in PCOS, such as folliculogenesis, steroidogenesis, and cellular adhesion, are regulated by miRNA. This also highlights their importance as potential prognostic markers. In addition, recent evidence suggests a role for miRNAs in regulating the circadian rhythm (CR). CR is crucial for regulating reproduction through the various functions of the hypothalamic-pituitary-gonadal (HPG) axis and the ovaries. A disordered CR affects reproductive outcomes by inducing insulin resistance, oxidative stress, and systemic inflammation. Moreover, miRNAs were demonstrated to interact with lncRNA and circRNAs, which are thought to play a role in the pathogenesis of PCOS. This review discusses what is currently understood about miRNAs in PCOS, the cellular pathways involved, and their potential role as biomarkers and therapeutic targets.

Coronavirus 2019 (COVID-19) disease management is highly dependent on the immune status of the infected individual. An increase in the incidence of depression has been observed during the ongoing COVID-19 pandemic. Autoantibodies against in vitro reactive oxygen species (ROS) modified BSA and Lys as well as antibodies against receptor binding domain subunit S1 (S1-RBD) (S1-RBD-Abs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were estimated using direct binding and competition ELISA. Serum samples were also tested for fasting blood glucose (FBG), malondialdehyde (MDA), carbonyl content (CC), interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α). Significant structural changes were observed in ROS modified BSA and Lys. Female depressed subjects who were also smokers (F-D-S) showed the highest levels of oxidative stress (MDA and CC levels). Similarly, increased levels of autoantibodies against ROS modified proteins were detected in F-D-S subjects, in males who were depressed and in smokers (M-D-S) compared to the other subjects from the rest of the groups. However, contrary to this observation, levels of S1-RBD-Abs were found to be lowest in the F-D-S and M-D-S groups. During the pandemic, large numbers of individuals have experienced depression, which may induce excessive oxidative stress, causing modifications in circulatory proteins. Thus, the formation of neo-antigens is induced, which lead to the generation of autoantibodies. The concomitant effect of increased autoantibodies with elevated levels of IFN-γ and TNF-α possibly tilt the immune balance toward autoantibody generation rather than the formation of S1-RBD-Abs. Thus, it is important to identify individuals who are at risk of depression to determine immune status and facilitate the better management of COVID-19.

The implementation of data mining has become very popular in many fields recently, including in the petroleum industry. It is widely used to help in decision-making processes in order to minimize oil losses during operations. One of the major causes of loss is oil flow blockages during transport to the gathering facility, known as the congeal phenomenon. To overcome this situation, real-time surveillance is used to monitor the oil flow condition inside pipes. However, this system is not able to forecast the pipeline pressure on the next several days. The objective of this study is to forecast the pressure several days in advance using real-time pressure data, as well as external factor data recorded by nearby weather stations, such as ambient temperature and precipitation. Three machine learning algorithms—multi-layer perceptron (MLP), long short-term memory (LSTM), and nonlinear autoregressive exogenous model (NARX)—are evaluated and compared with each other using standard regression evaluation metrics, including a steady-state model. As a result, with proper hyperparameters, in the proposed method of NARX with MLP as a regressor, the NARX algorithm showed the best performance among the evaluated algorithms, indicated by the highest values of R2 and lowest values of RMSE. This algorithm is capable of forecasting the pressure with high correlation to actual field data. By forecasting the pressure several days ahead, system owners may take pre-emptive actions to prevent congealing.

Postural stability may be affected during slope walking, as there are different body kinetics and kinematic responses compared with level walking. Understanding body adaptations toward different inclinations is essential to prevent the risk of injury from falls or slips. This study was conducted to determine the correlations between stability parameters and loading response in terms of joint reaction force at the lower-extremity joints during inclined and declined walking. Twenty male subjects walked in the level, incline, and decline directions on a custom-built platform at three different slope angles (i.e., 5°, 7.5°, and 10°). To determine the ground reaction force (GRF), joint reaction force (JRF), center of pressure (COP), and center of mass (COM), a motion capture system was used to read the data of the ten reflective markers and transfer them to visual three-dimensional (3D) software. Pearson’s correlation test was performed with statistical significance set at p < 0.05 to evaluate the correlation of the required coefficient of friction (RCOF), postural stability index (PSI), and COP-COM distance with the JRF. This study has identified that the JRF changes in opposition to the changes in the RCOF during the initial strike during incline and decline walking, as JRF increases, the RCOF decreases with different strengths of correlation. There is also a strong positive correlation between the PSI and JRF in the proximal–distal direction, where the JRFs change in accordance with the change in the PSI, and the JRF increases with the increment of PSI. In addition, the JRF of the lower extremity also changed in a manner similar to the COP-COM distance in the medial–lateral direction. Overall, each stability parameter was correlated with the JRF of the lower-extremity joints in different directions and strengths. This study demonstrated that slope walking is particularly affected by surface inclination in terms of stability and loading. Therefore, this research can serve as a basis for future studies on slopes, as there is no specific basis for a maximum degree of inclination that is safe and suitable for all applications.

Most diabetes patients develop a condition known as diabetic retinopathy after having diabetes for a prolonged period. Due to this ailment, damaged blood vessels may occur behind the retina, which can even progress to a stage of losing vision. Hence, doctors advise diabetes patients to screen their retinas regularly. Examining the fundus for this requires a long time and there are few ophthalmologists available to check the ever-increasing number of diabetes patients. To address this issue, several computer-aided automated systems are being developed with the help of many techniques like deep learning. Extracting the retinal vasculature is a significant step that aids in developing such systems. This paper presents a GAN-based model to perform retinal vasculature segmentation. The model achieves good results on the ARIA, DRIVE, and HRF datasets.

Neuromuscular disorders, characterized by progressive muscle degeneration and weakness, present substantial challenges to both affected individuals and their families. Genetic testing assumes a pivotal role in facilitating early diagnosis, intervention, treatment, and informed family planning for these conditions. The objective of this qualitative study is to delve into the knowledge, awareness, and perceptions surrounding genetic testing within the cohort of parents caring for individuals with neuromuscular disorders in Malaysia. A semi-structured interview approach was employed to elicit data from parents of individuals diagnosed with neuromuscular disorders, encompassing those with clinical diagnoses and those diagnosed through genetic testing. Examination of the interview responses yielded nine overarching themes, which furnish invaluable insights into the perspectives of Malaysian parents concerning genetic testing. The study discerned several challenges associated with genetic testing, notably encompassing the limited awareness among parents, the financial constraints associated with genetic testing, and the perceived significance of genetic testing in the context of neuromuscular disorders. The findings suggest that the level of knowledge and awareness pertaining to genetic testing for neuromuscular disorders among parents in Malaysia varies, with initial levels of awareness ranging from relatively low to reasonably sufficient prior to and following the birth of an affected child. However, the investigation revealed that parents tended to cultivate more favorable perceptions regarding genetic testing subsequent to their experience with genetic counseling. This underscores the potential for heightened awareness and comprehension as a consequence of the personal experience of parenting an affected child confirmed through genetic testing and genetic counseling, ultimately influencing parental awareness.

The aim of this phantom study was to assess the detectability and volumetric accuracy of pulmonary nodules on photon-counting detector CT (PCD-CT) at different low-dose levels compared to conventional energy-integrating detector CT (EID-CT). In-house fabricated artificial nodules of different shapes (spherical, lobulated, spiculated), sizes (2.5–10 mm and 5–1222 mm3), and densities (−330 HU and 100 HU) were randomly inserted into an anthropomorphic thorax phantom. The phantom was scanned with a low-dose chest protocol with PCD-CT and EID-CT, in which the dose with PCD-CT was lowered from 100% to 10% with respect to the EID-CT reference dose. Two blinded observers independently assessed the CT examinations of the nodules. A third observer measured the nodule volumes using commercial software. The influence of the scanner type, dose, observer, physical nodule volume, shape, and density on the detectability and volumetric accuracy was assessed by a multivariable regression analysis. In 120 CT examinations, 642 nodules were present. Observer 1 and 2 detected 367 (57%) and 289 nodules (45%), respectively. With PCD-CT and EID-CT, the nodule detectability was similar. The physical nodule volumes were underestimated by 20% (range 8–52%) with PCD-CT and 24% (range 9–52%) with EID-CT. With PCD-CT, no significant decrease in the detectability and volumetric accuracy was found at dose reductions down to 10% of the reference dose (p > 0.05). The detectability and volumetric accuracy were significantly influenced by the observer, nodule volume, and a spiculated nodule shape (p < 0.05), but not by dose, CT scanner type, and nodule density (p > 0.05). Low-dose PCD-CT demonstrates potential to detect and assess the volumes of pulmonary nodules, even with a radiation dose reduction of up to 90%.

In the current study, whey protein-based nanofibers were fabricated to encapsulate Lactobacillus rhamnosus. Purposely, different ratios of PVA (polyvinyl alcohol) and WPI (whey protein isolate) were blended to fabricate nanofibers. Nanofiber mats were characterized in terms of particle size, diameter, tensile strength, elongation at break, and loading efficiency. Morphological and molecular characterizations were carried out using scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). Moreover, in vitro viability under simulated gastrointestinal (GI) conditions and thermal stability were also assessed. The results reveal that by increasing the PVA concentration, the conductivity increased while the viscosity decreased. SEM micrographs showed that probiotics were successfully loaded within the nanofiber. The FTIR spectra show strong bonding between the encapsulating materials with the addition of probiotics. In vitro and thermal analyses revealed that the survival of encapsulated probiotics significantly (p < 0.05) improved. In a nutshell, PVA–WPI composite nanofibers have promising potential when used to enhance the viability and stability of probiotics under adverse conditions.

Worldwide, colon cancer is the third most frequent malignancy and the second most common cause of death. Although it can strike anybody at any age, colon cancer mostly affects the elderly. Small, non-cancerous cell clusters inside the colon, commonly known as polyps, are typically where colon cancer growth starts. But over time, if left untreated, these benign polyps may develop into malignant tissues and develop into colon cancer. For the diagnosis of colon cancer, with routine inspection of the colon region for polyps, several techniques, including colonoscopy and cancer scanning, are used. In the case identifying the polyps in the colon area, efforts are being taken to surgically remove the polyps as quickly as possible before they become malignant. If the polyps become malignant, then colon cancer treatment strategies, such as surgery, chemotherapy, targeted therapy, and immunotherapy, are applied to the patients. Despite the recent improvements in diagnosis and prognosis, the treatment of colorectal cancer (CRC) remains a challenging task. The objective of this review was to discuss how CRC is initiated, and its various developmental stages, pathophysiology, and risk factors, and also to explore the current state of colorectal cancer diagnosis and treatment, as well as recent advancements in the field, such as new screening methods and targeted therapies. We examined the limitations of current methods and discussed the ongoing need for research and development in this area. While this topic may be serious and complex, we hope to engage and inform our audience on this important issue.

Background: Despite the availability of a highly efficacious vaccine, varicella outbreaks are still being reported globally. In this study, we evaluated the real-world effectiveness of varicella vaccination among children between the ages of 1 and 18 years old during the period 2017 to 2019 in Qatar. Methods: A matched case–control study was conducted that included all reported varicella-infected children who visited the primary healthcare system in Qatar from January 2017 to December 2019. The cases were children under the age of 18 years who were clinically diagnosed with varicella. The controls were of the same age, who visited the Primary Health Care Corporation (PHCC) during 2017–2019 with a skin rash where varicella infection was ruled out. The data on varicella vaccination for each participant were obtained from the electronic database in the PHCC during the study period. Results: We included 862 cases of varicella and 5454 matched controls, with a median age of 8 years (IQR 3–12); 47.4% were female and almost 50% were of Qatari nationality. The year 2019 had the highest varicella infection count with a total of 416 cases. The cases were less likely to be vaccinated against varicella, with approximately a quarter (25.6%) of cases and 36.7% of the controls having either one or two doses of the vaccine (p < 0.001). Compared to not being vaccinated, a single dose vaccination showed a 56% reduction in the odds of varicella infection [OR 0.44, 95% CI: 0.34–0.55; p < 0.000], and a two-dose vaccination showed an 86% reduction in the odds of varicella infection [OR 0.13, 95% CI: 0.06–0.29; p < 0.000]. Conclusion: In this multicultural setting, a two-dose varicella vaccination shows reasonable protection against varicella infection.

Per- and polyfluoroalkyl substances (PFAS) consist of a range of manufactured fluorinated chemicals that are used in a variety of household and waterproofing products, industrial processes, and firefighting foams. In the past few years, there has been increasing concern about PFAS in the environment, since they are difficult to break down through natural processes, are highly persistent in humans, animals, soils and waters, and can travel long distances in surface and groundwater. This has created an increased need for PFAS analysis. Most PFAS monitoring currently takes place using field sampling and chromatographic analytical methods, which are laboratory-based and are very costly when used to monitor PFAS in the environment. Using a semi-systematic literature review approach, a comparative study is conducted in this article on the available analytical methods and sensor technologies that can be used to monitor and detect PFAS in the environment, including chromatographic, instrumentation analysis, and sensor-based methods. This study considered four critical factors for effective and efficient monitoring methods, which include the type of PFAS detected, removing background levels, determining detection limits, and identifying samples. In general, other analytical instruments are used in conjunction with chromatographic techniques for detecting both target and non-target analytes at a lower level of detection (LOD). It is shown that even though some sensor types have a low LOD, they are only useful for detecting targeted PFAS in water samples. However, sensors are an emerging technology that could be developed to enable low-cost, portable methods for the remote detection of PFAS species on-site.

The ecological and children’s Health Risk Assessments (HRA) of Copper (Cu) in aquatic bodies ranging from rivers, mangrove, estuaries, and offshore areas were studied using the Cited Cu Data in The Sediments (CCDITS) from 125 randomly selected papers published from 1980 to 2022. The ecological and children’s HRA were assessed in all CCDITS. Generally, local point Cu sources (8%) and lithogenic sources were the main controlling factors of Cu concentrations. The present review revealed three interesting points. First, there were 11 papers (8%) documenting Cu levels of more than 500 mg/kg dw while China was the country with the highest number (26%) of papers published between 1980 and 2022, out of 37 countries. Second, with the Cu data cited from the literature not normally distributed, the maximum Cu level was higher than all the established guidelines. However, the median Cu concentration was lower than most of the established guidelines. The median values of the geoaccumulation index (Igeo) indicated a status of ‘unpolluted‘ and ‘moderate contamination’ for the contamination factor (CF), and ‘low potential ecological risk’ for the ecological risk (ER) of Cu. However, the Cu ER could be based at present on the above mentioned 8% of the literature in the present study. Third, the calculated hazard index (HI) values were found to be below 1, indicating no potential chance of Cu non–carcinogenic effects in both adults and children, except for children’s HI values from Lake Pamvotis of Greece, and Victoria Harbor in Hong Kong. Thus, regular monitoring (every 2 years), depending upon the available resources, is recommended to assess the ecological–health risk of Cu pollution in aquatic bodies to abate the risk of Cu exposure to children’s health and avoid injurious impacts on the biota. It can be concluded that there is always a need for the mitigation and management of a Cu exposure risk assessment that can be used successfully for screening purposes to detect important human health exposure routes. Consequently, any sediments contaminated with Cu require rapid sediment remediation techniques.

The intricate neuroinflammatory diseases multiple sclerosis (MS) and neuromyelitis optica (NMO) often present similar clinical symptoms, creating challenges in their precise detection via magnetic resonance imaging (MRI). This challenge is further compounded when detecting the active and inactive states of MS. To address this diagnostic problem, we introduce an innovative framework that incorporates state-of-the-art machine learning algorithms applied to features culled from MRI scans by pre-trained deep learning models, VGG-NET and InceptionV3. To develop and test this methodology, we utilized a robust dataset obtained from the King Abdullah University Hospital in Jordan, encompassing cases diagnosed with both MS and NMO. We benchmarked thirteen distinct machine learning algorithms and discovered that support vector machine (SVM) and K-nearest neighbor (KNN) algorithms performed superiorly in our context. Our results demonstrated KNN’s exceptional performance in differentiating between MS and NMO, with precision, recall, F1-score, and accuracy values of 0.98, 0.99, 0.99, and 0.99, respectively, using leveraging features extracted from VGG16. In contrast, SVM excelled in classifying active versus inactive states of MS, achieving precision, recall, F1-score, and accuracy values of 0.99, 0.97, 0.98, and 0.98, respectively, using leveraging features extracted from VGG16 and VGG19. Our advanced methodology outshines previous studies, providing clinicians with a highly accurate, efficient tool for diagnosing these diseases. The immediate implication of our research is the potential to streamline treatment processes, thereby delivering timely, appropriate care to patients suffering from these complex diseases.

Aquaporin (AQP) channels in endometrial cancer (EC) cells are of interest as pharmacological targets to reduce tumor progression. A panel of compounds, including AQP1 ion channel inhibitors (AqB011 and 5-(phenoxymethyl) furan-2-carbaldehyde, PMFC), were used to test the hypothesis that inhibition of key AQPs can limit the invasiveness of low- and high-grade EC cells. We evaluated the effects on transwell migration in EC cell lines (Ishikawa, MFE-280) and primary EC cells established from surgical tissues (n = 8). Quantitative PCR uncovered classes of AQPs not previously reported in EC that are differentially regulated by hormonal signaling. With estradiol, Ishikawa showed increased AQPs 5, 11, 12, and decreased AQPs 0 and 4; MFE-280 showed increased AQPs 0, 1, 3, 4, 8, and decreased AQP11. Protein expression was confirmed by Western blot and immunocytochemistry. AQPs 1, 4, and 11 were colocalized with plasma membrane marker; AQP8 was intracellular in Ishikawa and not detectable in MFE-280. AQP1 ion channel inhibitors (AqB011; PMFC) reduced invasiveness of EC cell lines in transwell chamber and spheroid dispersal assays. In Ishikawa cells, transwell invasiveness was reduced ~41% by 80 µM AqB011 and ~55% by 0.5 mM 5-PMFC. In MFE-280, 5-PMFC inhibited invasion by ~77%. In contrast, proposed inhibitors of AQP water pores (acetazolamide, ginsenoside, KeenMind, TGN-020, IMD-0354) were not effective. Treatments of cultured primary EC cells with AqB011 or PMFC significantly reduced the invasiveness of both low- and high-grade primary EC cells in transwell chambers. We confirmed the tumors expressed moderate to high levels of AQP1 detected by immunohistochemistry, whereas expression levels of AQP4, AQP8, and AQP11 were substantially lower. The anti-invasive potency of AqB011 treatment for EC tumor tissues showed a positive linear correlation with AQP1 expression levels. In summary, AQP1 ion channels are important for motility in both low- and high-grade EC subtypes. Inhibition of AQP1 is a promising strategy to inhibit EC invasiveness and improve patient outcomes.

Much research has been carried out to discover partnership critical success factors that influence public-private partnership success. Since most public-private partnership projects are long-term in nature and include contractual arrangements, there is still a lot to learn about contract governance’s role in public-private partnership performance. Therefore, this study examines the effect of contract governance on the relationship between partnership critical success factors and partnership performance in Malaysia. Stakeholder Theory serves as the underpinning theory for this study. This study employed a quantitative method based on the positivist paradigm to distribute questionnaires. The information was collected from 261 contracting parties’ officials in Malaysian public-private partnership projects regulated by the Malaysian Public-Private Partnership Unit, and a stratified random sampling method was employed. The structural equation model analysis found that eight out of ten hypotheses were supported. According to this study, it has been established that contract governance has a direct favorable influence on partnership performance. However, it is also found that contract governance does not moderate the relationship between partnership critical success factors and partnership performance. Due to time constraints and the emergence of the COVID-19 pandemic, this study was from a cross-sectional viewpoint and adopted a quantitative methodology. The findings of this study are important in the contract governance and partnership performance literature, providing policymakers and concessionaires with new information on the impact of contract governance on public-private partnership project performance. Managers of public-private partnership projects should also be able to enhance their projects’ performance by understanding how contract governance influences the performance of their projects.

Leaf sheath blight disease (SB) of rice caused by the soil-borne fungus Rhizoctonia solani results in 10–30% global yield loss annually and can reach 50% under severe outbreaks. Many disease resistance genes and receptor-like kinases (RLKs) are recruited early on by the host plant to respond to pathogens. Wall-associated receptor kinases (WAKs), a subfamily of receptor-like kinases, have been shown to play a role in fungal defense. The rice gene WAK91 (OsWAK91), co-located in the major SB resistance QTL region on chromosome 9, was identified by us as a candidate in defense against rice sheath blight. An SNP mutation T/C in the WAK91 gene was identified in the susceptible rice variety Cocodrie (CCDR) and the resistant line MCR010277 (MCR). The consequence of the resistant allele C is a stop codon loss, resulting in an open reading frame with extra 62 amino acid carrying a longer protein kinase domain and additional phosphorylation sites. Our genotype and phenotype analysis of the parents CCDR and MCR and the top 20 individuals of the double haploid SB population strongly correlate with the SNP. The susceptible allele T is present in the japonica subspecies and most tropical and temperate japonica lines. Multiple US commercial rice varieties with a japonica background carry the susceptible allele and are known for SB susceptibility. This discovery opens the possibility of introducing resistance alleles into high-yielding commercial varieties to reduce yield losses incurred by the sheath blight disease.

The fundamental aim of this paper is to introduce the concept of poly-Jindalrae and poly-Gaenari numbers and polynomials within the context of degenerate functions. Furthermore, we give explicit expressions for these polynomial sequences and establish combinatorial identities that incorporate these polynomials. This includes the derivation of Dobinski-like formulas, recurrence relations, and other related aspects. Additionally, we present novel explicit expressions and identities of unipoly polynomials that are closely linked to some special numbers and polynomials.

Microalgae are well known for their metal sorption capacities, but their potential in the remediation of hydrophobic organic compounds has received little attention in polar regions. We evaluated in the laboratory the ability of an Antarctic microalga to remediate diesel hydrocarbons and also investigated physiological changes consequent upon diesel exposure. Using a polyphasic taxonomic approach, the microalgal isolate, WCY_AQ5_1, originally sampled from Greenwich Island (South Shetland Islands, maritime Antarctica) was identified as Tritostichococcus sp. (OQ225631), a recently erected lineage within the redefined Stichococcus clade. Over a nine-day experimental incubation, 57.6% of diesel (~3.47 g/L) was removed via biosorption and biodegradation, demonstrating the strain’s potential for phytoremediation. Fourier transform infrared spectroscopy confirmed the adsorption of oil in accordance with its hydrophobic characteristics. Overall, degradation predominated over sorption of diesel. Chromatographic analysis confirmed that the strain efficiently metabolised medium-chain length n-alkanes (C-7 to C-21), particularly n-heneicosane. Mixotrophic cultivation using diesel as the organic carbon source under a constant light regime altered the car/chl-a ratio and triggered vacuolar activities. A small number of intracellular lipid droplets were observed on the seventh day of cultivation in transmission electron microscopic imaging. This is the first confirmation of diesel remediation ability in an Antarctic green microalga.

The apocarotenoid zaxinone is a recently discovered regulatory metabolite required for proper rice growth and development. In addition, zaxinone and its two mimics (MiZax3 and MiZax5) were shown to have a remarkable growth-promoting activity on crops and a capability to reduce infestation by the root parasitic plant Striga through decreasing strigolactone (SL) production, suggesting their potential for application in agriculture and horticulture. In the present study, we developed a new series of MiZax via structural modification of the two potent zaxinone mimics (MiZax3 and MiZax5) and evaluated their effect on plant growth and Striga infestation. In general, the structural modifications to MiZax3 and MiZax5 did not additionally improve their overall performance but caused an increase in certain activities. In conclusion, MiZax5 and especially MiZax3 remain the likely most efficient zaxinone mimics for controlling Striga infestation.

The construction industry is increasingly focused on sustainability, with a particular emphasis on reducing the environmental impact of cement production. One approach to this problem is to use recycled materials and explore eco-friendly raw materials, such as alumino-silicate by-products like fly ash, which can be used as raw materials for geopolymer concrete. To enhance the ductility, failure mode, and toughness of the geopolymer, researchers have added crumb rubber processed from scrap tires as partial replacement to fine aggregate of the geopolymer. Therefore, this study aims to develop rubberized geopolymer concrete (RGC) by partially replacing the fine aggregate with crumb rubber (CR). To optimize the mechanical properties of RGC, response surface methodology (RSM) has been used to develop 13 mixes with different levels and proportions of CR (10–30% partial replacement of fine aggregate by volume) and sodium hydroxide molarity (10–14 M) as input variables. The results showed that the strength properties increased as the molarity of NaOH increased, while the opposite trend was observed with CR. The maximum values for compressive strength, flexural strength, and uniaxial tensile strength were found to be 25 MPa, 3.1 MPa, and 0.41 MPa, respectively. Response surface models of the mechanical strengths, which were validated using ANOVA with high R2 values of 72–99%, have been developed. It has been found that using 10% CR with 14 M sodium hydroxide resulting in the best mechanical properties for RGC, which was validated with experimental tests. The result of the multi-objective optimization indicated that the optimum addition level for NaOH is 14 M, and the fine aggregate replacement level with CR is 10% in order to achieve a rubberized geopolymer suitable for structural applications.

Despite the excellent ductility and energy absorption properties of engineered cementitious composites (ECCs), a low modulus of elasticity and excessive drying shrinkage remain some of its major disadvantages. With the current trend in the application of nanotechnology in cementitious composites research, the effect of graphene oxide (GO) on the properties of ECCs is yet to be fully investigated, despite its promising results in ordinary cement paste, mortar, and concrete. ECCs need extensive material tailoring to provide the required mechanical characteristics and controlled fracture size with strain-hardening behavior. Striking a balance between these crucial hardened aspects of ECC without compromising any desired properties is a challenge. Hence, the main aim of the study reported in this paper is to use the response surface methodology (RSM) multi-objective optimization technique to identify an appropriate GO content via the weight of cement and also the volume fraction of polyvinyl alcohol (PVA) fiber as input variables that positively impact ECCs’ properties. Using RSM’s central composite design (CCD), 13 mixtures of various combinations of the variables (GO: 0.05%, 0.065%, 0.08%; PVA: 1%, 1.5%, 2%) were developed. Six responses were studied, including compressive strength, direct tensile strength, tensile capacity, flexural strength, modulus of elasticity, Poisson’s ratio, and drying shrinkage. Moreover, the microstructural properties of the composites were assessed using field-emission scanning electron microscopy (FESEM) and mercury intrusion porosimetry (MIP). The outcomes revealed that all the properties of ECCs were significantly enhanced by adding an optimum amount of 0.05% GO and 1–1.5% PVA fiber volume fractions. A maximum increase in 30%, 35%, 49%, and 33.9% in the compressive strength, direct tensile strength, flexural strength, and modulus of elasticity, respectively, of the mixes with 0.05% GO addition was recorded. It is demonstrated that the use of 0.05% GO as a nanoscale particle can provide good outputs for the construction industry.

Engineered Cementitious Composites (ECC) are widely used in various structures due to their high strength, durability, and ductility. However, they are still vulnerable to environmental factors such as sulphate and acid attack. These attacks damage the concrete matrix, which leads to cracking and corrosion of the reinforcing steel. To mitigate these issues, various techniques have been developed, including the addition of graphene oxide to the ECC mix. Graphene oxide has shown potential in improving the mechanical properties and durability of ECC. The purpose of this study was to use multi-objective optimization to identify an appropriate GO by the weight of the cement and polyvinyl alcohol (PVA) fiber volume fraction in an ECC mixture. Using RSM’s central composite design (CCD), thirteen mixtures of various possible combinations of variables (GO: 0.05 percent to 0.08 percent, PVA: 1–2 percent) were established, and eight response responses (compressive strength, change in length, weight loss, pH test, weight gain, expansion, rapid chloride permeability test and water absorption) were examined. However, analysis of variance was used to effectively design and evaluate eight (six quadratic and two linear) response models. All the models had extremely high R2 values, ranging from 84 percent to 99 percent. The multi-objective optimization produced ideal variable values (GO: 0.05 percent and PVA: 1%) and projected optimum response values. The predicted values were verified experimentally and found to correlate extremely well with the experimental data, with less than a 5% error. The outcome showed that the maximum increase of 30% in the compressive strength was recorded at 0.05% of GO as a nanomaterial in ECC. In addition, the expansion due to sulfate resistance and change in length due to acid attack were decreased by 0.0023% and 0.28%, respectively, when the use of 0.08% of GO as a nanomaterial in the ECC matrix was reinforced with 1% PVA fiber for 28 days. Moreover, the weight loss and weight gain of ECC combined with 1% of PVA fiber due to chemical attack decreased by 66.70% and 77.80%, respectively, at 0.08% of GO as a nanoscale particle than that of the reference mix for 28 days. In addition, the pH value due to acid attack, rapid chloride permeability test value, water absorption, and slump flow of the fresh mixture were decreased as the concentration of GO rose in ECC. The results indicated that the incorporation of 0.05% GO as a nanomaterial and 1 to 1.5% of PVA fiber will provide the best outcomes for the construction industry.

Chemical deterioration, including sulphate and acid attacks, is a major issue affecting the long-term durability of engineered cementitious composite (ECC) constructions that contact water from various sources, including groundwater, seawater, sewer water, and drinking water. This research enhances ECCs’ strength and resilience against chemical attack by combining cementitious composites with multiwalled carbon nanotubes (CNTs) and polyvinyl alcohol (PVA) fibre volume fractions using multiobjective optimization. The central composite design (CCD) of RSM was applied to generate thirteen mixes of different potential combinations of factors (multiwalled CNTs: 0.05% to 0.08%, PVA: 1–2%) and eight outcome responses were studied, although eight response models—six quadratic and two linear—were successfully designed and assessed using analysis of variance. The coefficients associated with R2 for all the models were exceptionally high, with values varying from 84 to 99 percent. The multiobjective optimization predicted the best outcomes and developed optimal values for both variables (CNTs: 0.05% and PVA: 1%). The results showed that, at 0.05% of CNTs in ECCs, an ultimate improvement of 23% in compressive strength was seen. Additionally, when CNTs are used to grow in the ECC matrix, the expansion owing to sulphate resistance and length change due to acid attack are both reduced. In addition, when the percentage of CNTs increases in ECCs, the weight loss and pH value owing to acid attack, as well as the rate of chloride permeability test results, are reduced. Furthermore, CNTs and PVA fibres with 0.05% and 1–1.5% concentrations offer optimal construction sector outcomes.

Non-invasive prenatal testing was first discovered in 1988; it was primarily thought to be able to detect common aneuploidies, such as Patau syndrome (T13), Edward Syndrome (T18), and Down syndrome (T21). It comprises a simple technique involving the analysis of cell-free foetal DNA (cffDNA) obtained through maternal serum, using advances in next-generation sequencing. NIPT has shown promise as a simple and low-risk screening test, leading various governments and private organizations worldwide to dedicate significant resources towards its integration into national healthcare initiatives as well as the formation of consortia and research studies aimed at standardizing its implementation. This article aims to review the reliability of NIPT while discussing the current challenges prevalent among different communities worldwide.

The slow growth rate of primer species has affected the supply available to accommodate the market demand. To overcome these problems, a study was carried out to fully utilise fast-growing timber as the primary resource to ensure the demand for timber logs continues. This paper aimed to determine mechanical strength properties, treatability retention, and hazard classification of 7-, 10- and 13-year-old small-clear samples of Acacia mangium superbulk collected from Daiken Plantation Sdn. Bhd. Bintulu, Sarawak, following treatment with 10% copper chrome arsenic. As a result of this study, the maximum strength was obtained from the 10-year-old age group, with the modulus of rupture (MOR), the modulus of elasticity (MOE), and compression parallel to the grain values of small-clear treated Acacia mangium superbulk reaching 118.76 N/mm2, 15,020 N/mm2, and 57.82 N/mm2, respectively. In addition, the treatability retentions obtained were 149.27 L/m3, 147.25 L/m3, and 141.09 L/m3, which were recorded from the 7-, 10-, and 13-year-old samples, respectively. Meanwhile, the dry-salt retentions obtained from the 7-, 10- and 13-year-old samples were 14.93 kg/m3, 14.73 kg/m3, and 14.11 kg/m3, respectively. Hence, this species is classified as moderately difficult to treat under CCA (treatability retention: 80–160 L/m3) and is categorised under the hazard class of H4 (dry salt retention: 12–16 kg/m3).

Structural health monitoring is a popular inspection method that utilizes acoustic emission (AE) signals for fault detection in engineering infrastructures. Diagnosis based on the propagation of AE signals along any surface material offers an attractive solution for fault identification. However, the classification of AE signals originating from failure events, especially coating failure (coating disbondment), is a challenging task given the AE signature of each material. Thus, different experimental settings and analyses of AE signals are required to classify the various types of coating failures, and they are time-consuming and expensive. Hence, to address these issues, we utilized machine learning (ML) classification models in this work to evaluate epoxy-based-protective-coating disbondment based on the AE principle. A coating disbondment experiment consisting of coated carbon steel test panels for the collection of AE signals was implemented. The obtained AE signals were then processed to construct the final dataset to train various state-of-the-art ML classification models to divide the failure severity of coating disbondment into three classes. Consequently, methods for the extraction of useful features, the handling of data imbalance, and a reduction in the bias of ML models were also effectively utilized in this study. Evaluations of state-of-the-art ML classification models on the AE signal dataset in terms of standard metrics revealed that the decision forest classification model outperformed the other state-of-the-art models, with accuracy, precision, recall, and F1 score values of 99.48%, 98.76%, 97.58%, and 98.17%, respectively. These results demonstrate the effectiveness of utilizing ML classification models for the failure severity prediction of protective-coating defects via AE signals.

Many properties of special polynomials, such as recurrence relations, sum formulas, and symmetric properties, have been studied in the literature with the help of generating functions and their functional equations. In this study, we define Frobenius–Euler–Genocchi polynomials and investigate some properties by giving many relations and implementations. We first obtain different relations and formulas covering addition formulas, recurrence rules, implicit summation formulas, and relations with the earlier polynomials in the literature. With the help of their generating function, we obtain some new relations, including the Stirling numbers of the first and second kinds. We also obtain some new identities and properties of this type of polynomial. Moreover, using the Faà di Bruno formula and some properties of the Bell polynomials of the second kind, we obtain an explicit formula for the Frobenius–Euler polynomials of order α. We provide determinantal representations for the ratio of two differentiable functions. We find a recursive relation for the Frobenius–Euler polynomials of order α. Using the Mathematica program, the computational formulae and graphical representation for the aforementioned polynomials are obtained.

Obstructive sleep apnea (OSA) is a prevalent sleep disorder that affects approximately 3–7% of males and 2–5% of females. In the United States alone, 50–70 million adults suffer from various sleep disorders. OSA is characterized by recurrent episodes of breathing cessation during sleep, thereby leading to adverse effects such as daytime sleepiness, cognitive impairment, and reduced concentration. It also contributes to an increased risk of cardiovascular conditions and adversely impacts patient overall quality of life. As a result, numerous researchers have focused on developing automated detection models to identify OSA and address these limitations effectively and accurately. This study explored the potential benefits of utilizing machine learning methods based on demographic information for diagnosing the OSA syndrome. We gathered a comprehensive dataset from the Torr Sleep Center in Corpus Christi, Texas, USA. The dataset comprises 31 features, including demographic characteristics such as race, age, sex, BMI, Epworth score, M. Friedman tongue position, snoring, and more. We devised a novel process encompassing pre-processing, data grouping, feature selection, and machine learning classification methods to achieve the research objectives. The classification methods employed in this study encompass decision tree (DT), naive Bayes (NB), k-nearest neighbor (kNN), support vector machine (SVM), linear discriminant analysis (LDA), logistic regression (LR), and subspace discriminant (Ensemble) classifiers. Through rigorous experimentation, the results indicated the superior performance of the optimized kNN and SVM classifiers for accurately classifying sleep apnea. Moreover, significant enhancements in model accuracy were observed when utilizing the selected demographic variables and employing data grouping techniques. For instance, the accuracy percentage demonstrated an approximate improvement of 4.5%, 5%, and 10% with the feature selection approach when applied to the grouped data of Caucasians, females, and individuals aged 50 or below, respectively. Furthermore, a comparison with prior studies confirmed that effective data grouping and proper feature selection yielded superior performance in OSA detection when combined with an appropriate classification method. Overall, the findings of this research highlight the importance of leveraging demographic information, employing proper feature selection techniques, and utilizing optimized classification models for accurate and efficient OSA diagnosis.

Research has confirmed that the utilisation of Antarctic microorganisms, such as bacteria, yeasts and fungi, in the bioremediation of diesel may provide practical alternative approaches. However, to date there has been very little attention towards Antarctic microalgae as potential hydrocarbon degraders. Therefore, this study focused on the utilisation of an Antarctic microalga in the bioremediation of diesel. The studied microalgal strain was originally obtained from a freshwater ecosystem in Paradise Bay, western Antarctic Peninsula. When analysed in systems with and without aeration, this microalgal strain achieved a higher growth rate under aeration. To maintain the growth of this microalga optimally, a conventional one-factor-at a-time (OFAT) analysis was also conducted. Based on the optimized parameters, algal growth and diesel degradation performance was highest at pH 7.5 with 0.5 mg/L NaCl concentration and 0.5 g/L of NaNO3 as a nitrogen source. This currently unidentified microalga flourished in the presence of diesel, with maximum algal cell numbers on day 7 of incubation in the presence of 1% v/v diesel. Chlorophyll a, b and carotenoid contents of the culture were greatest on day 9 of incubation. The diesel degradation achieved was 64.5% of the original concentration after 9 days. Gas chromatography analysis showed the complete mineralisation of C7–C13 hydrocarbon chains. Fourier transform infrared spectroscopy analysis confirmed that strain WCY_AQ5_3 fully degraded the hydrocarbon with bioabsorption of the products. Morphological and molecular analyses suggested that this spherical, single-celled green microalga was a member of the genus Micractinium. The data obtained confirm that this microalga is a suitable candidate for further research into the degradation of diesel in Antarctica.

Cadmium (Cd) is one of the highly toxic, non-essential heavy metals that inhibit plant growth and development by prompting chlorophyll loss and affecting photosynthetic activities. This study investigated the efficacy of Spirulina platensis and Sargassum polycystum extracts in alleviating Cd stress in Pak Choi at morpho-biochemical, anatomical, and molecular levels. Different concentrations (0, 25, 50, and 100 mL/L) of S. polycyctum (SAR), S. platensis (SPI), and a mixture of both extracts (SS) were exposed to 100 mg/kg Cd-contaminated Pak Choi seedlings. Non-Cd-treated Pak Choi and Cd-contaminated Pak Choi without algal extracts were assigned as positive and negative controls, respectively. The results showed that the application of algal extracts increased the plant height, fresh weight (FW), and dry weight (DW) as the extract level increased. This was greatest in 100SS with 37.51% (shoot length), 68.91% (root length), 110.8% (shoot DW), and 216.13% (root DW), while an increase of 176.7% (shoot FW) and 256.9% (root FW) was seen in the 100SPI treatment. Chlorophyll a, b, carotenoid, and chlorophyll fluorescence increased significantly after the treatment with 100SS. Antioxidant enzymes CAT, APX, POD, and protein were significantly increased in 100 mL/L extracts by 28.13% (100SS), 36.40% (100SAR), 46.92% (100SS), and 153.48% (100SS), respectively. The same treatment was also identified to dominate the development of root structures such as total length, surface area, projected area, diameter, volume, tips, and fork number. The highest reduction of Cd content in the root and shoot of Pak Choi was observed in 100SS with a 53.8% and 39.88% decrease, respectively. Increasing algal extract concentration also improved the leaf histological characteristics substantially, such as stomatal size and opening, mesophyll tissues, and vascular bundles. In addition, the fold change ratio of the Rubisco gene at 100SS treatment was noticeably greater than other algal extract treatments, with a 0.99 fold change when compared with the untreated sample. This present study illustrated that Sargassum polycyctum and Spirulina platensis extracts have the potential to effectively alleviate Cd stress in Pak Choi plants, especially with the application of 100 mL/L of an algal extract mixture. These findings contribute to the development of sustainable strategies for mitigating Cd toxicity in crops.

Lung cancer is the most commonly diagnosed of all cancers and one of the leading causes of cancer deaths among men and women worldwide, causing 1.5 million deaths every year. Despite developments in cancer treatment technologies and new pharmaceutical products, high mortality and morbidity remain major challenges for researchers. More than 75% of lung cancer patients are diagnosed in advanced stages, leading to poor prognosis. Lung cancer is a multistep process associated with genetic and epigenetic abnormalities. Rapid, accurate, precise, and reliable detection of lung cancer biomarkers in biological fluids is essential for risk assessment for a given individual and mortality reduction. Traditional diagnostic tools are not sensitive enough to detect and diagnose lung cancer in the early stages. Therefore, the development of novel bioanalytical methods for early-stage screening and diagnosis is extremely important. Recently, biosensors have gained tremendous attention as an alternative to conventional methods because of their robustness, high sensitivity, inexpensiveness, and easy handling and deployment in point-of-care testing. This review provides an overview of the conventional methods currently used for lung cancer screening, classification, diagnosis, and prognosis, providing updates on research and developments in biosensor technology for the detection of lung cancer biomarkers in biological samples. Finally, it comments on recent advances and potential future challenges in the field of biosensors in the context of lung cancer diagnosis and point-of-care applications.

Interstitial deletions in the long arm of chromosome 3, although relatively rare, have previously been reported to be associated with several congenital anomalies and developmental delays. Around 11 individuals with interstitial deletion spanning the region 3q21 were reported to have overlapping phenotypes, including craniofacial dysmorphism, global developmental delay, skeletal manifestations, hypotonia, ophthalmological abnormalities, brain anomalies (mainly agenesis of corpus callosum), genitourinary tract anomalies, failure to thrive and microcephaly. We present a male individual from Kuwait with a 5.438 Mb interstitial deletion of the long arm of chromosome 3 (3q21.1q21.3) detected on the chromosomal microarray with previously unreported features, including feeding difficulties, gastroesophageal reflux, hypospadias, abdomino-scrotal hydrocele, chronic kidney disease, transaminitis, hypercalcemia, hypoglycemia, recurrent infections, inguinal hernia and cutis marmorata. Our report expands the phenotype associated with 3q21.1q21.3 while summarizing the cytogenetics and clinical data of the previously reported individuals with interstitial deletions involving 3q21, thus providing a comprehensive phenotypic summary.

Antimicrobial resistance, with the production of extended-spectrum β-lactamases (ESBL) and carbapenemases, is common in the opportunistic pathogen, Klebsiella pneumoniae. This organism has a genome that can contain clustered regularly interspaced short palindromic repeats (CRISPRs), which operate as a defense mechanism against external invaders such as plasmids and viruses. This study aims to determine the association of the CRISPR/Cas systems with antibiotic resistance in K. pneumoniae isolates from Iraqi patients. A total of 100 K. pneumoniae isolates were collected and characterized according to their susceptibility to different antimicrobial agents. The CRISPR/Cas systems were detected via PCR. The phenotypic detection of ESBLs and carbapenemases was performed. The production of ESBL was detected in 71% of the isolates. Carbapenem-resistance was detected in 15% of the isolates, while only 14% were susceptible to all antimicrobial agents. Furthermore, the bacteria were classified into multidrug (77%), extensively drug-resistant (11.0%) and pandrug-resistant (4.0%). There was an inverse association between the presence of the CRISPR/Cas systems and antibiotic resistance, as resistance was higher in the absence of the CRISPR/Cas system. Multidrug resistance in ESBL-producing and carbapenem-resistant K. pneumoniae occurred more frequently in strains negative for the CRISPR/Cas system. Thus, we conclude that genes for exogenous antibiotic resistance can be acquired in the absence of the CRISPR/Cas modules that can protect the bacteria against acquiring foreign DNA.

Uveal melanoma is one of the most common primary intraocular malignancies that accounts for about 85% of all ocular melanomas. The pathophysiology of uveal melanoma is distinct from cutaneous melanoma and has separate tumor profiles. The management of uveal melanoma is largely dependent on the presence of metastases, which confers a poor prognosis with a one-year survival reaching only 15%. Although a better understanding of tumor biology has led to the development of novel pharmacologic agents, there is increasing demand for minimally invasive management of hepatic uveal melanoma metastases. Multiple studies have already summarized the systemic therapeutic options available for metastatic uveal melanoma. This review covers the current research for the most prevalent locoregional treatment options for metastatic uveal melanoma including percutaneous hepatic perfusion, immunoembolization, chemoembolization, thermal ablation, and radioembolization.

This work experimentally and numerically explored how varied steel-polypropylene fibre mixtures affected simply supported reinforced concrete deep beams. Due to their better mechanical qualities and durability, fibre-reinforced polymer composites are becoming more popular in construction, with hybrid polymer-reinforced concrete (HPRC) promising to increase the strength and ductility of reinforced concrete structures. The study evaluated how different combinations of steel fibres (SF) and polypropylene fibres (PPF) affected beam behaviour experimentally and numerically. The study’s focus on deep beams, research of fibre combinations and percentages, and integration of experimental and numerical analysis provide unique insights. The two experimental deep beams were the same size and were composed of hybrid polymer concrete or normal concrete without fibres. Fibres increased deep beam strength and ductility in experiments. The calibrated concrete damage plasticity model in ABAQUS was used to numerically calibrate HPRC deep beams with different fibre combinations at varied percentages. Based on six experimental concrete mixtures, calibrated numerical models of deep beams with different material combinations were investigated. The numerical analysis confirmed that fibres increased deep beam strength and ductility. HPRC deep beams with fibre performed better than those without fibres in numerical analysis. The study also determined the best fibre percentage to improve deep beam behaviour where a combination of 0.75% SF and 0.25% PPF was recommended to enhance load-bearing capacity and crack distribution, while a higher content of PPF was suggested for reducing deflection.