Search Results (244)

(1) Background: The occurrence, intensity, and characteristics of adverse drug reactions (ADRs) caused by anti-tuberculosis (TB) drugs have consistently been a subject of worry. There is a lack of published research from Pakistan regarding the negative effects of anti-TB treatment on children, specifically about ADRs. In this study, we aimed to investigate the ADR associated with anti-DR-TB treatment in children. (2) Methods: A prospective longitudinal study was conducted in the multicenter setting of Khyber Pakhtunkhwa, Pakistan. A total of 450 TB children in multicenter hospitals under ATT were assessed for ADRs. Naranjo Causality Assessment and Hartwig’s Severity Assessment Scale were used to evaluate the causality and severity. (3) Results: A total of 300 (66.66%) ADRs were reported in 450 people with DRTB. Anemia was the most frequently observed ADR (37.6%) followed by nausea and vomiting (18.6%). On multivariate analysis, the independent variables that had a statistically significant positive association with ADRs were participants aged, 5–14 years (AOR, 0.3 (0.1–0.5), p ≤ 0.001), normal weight (1.1 (2.0–1.9), p < 0.001), and children having comorbidities (AOR, 0.5 (0.1–0.8), p ≤ 0.001). (4) Conclusions: Our findings advocate for personalized treatment approaches, incorporating nutritional support, comprehensive comorbidity management, and vigilant monitoring to mitigate ADRs and improve treatment outcomes. Full article

A nanoliposome-integrated polymeric hydrogel was developed for the controlled release of essential oils (Argania spinosa, Passiflora edulis). A deep eutectic solvent (DES) composed of betaine and phytic acid enhanced the solubility and stability of essential oils, facilitating uniform encapsulation within nanoliposomes. The hydrogel exhibited a swelling capacity of 100% and retained 51.7% of water after 7 h, ensuring prolonged hydration. Structural analysis confirmed a homogeneous dispersion of nanoliposomes, contributing to the gradual release of bioactive components. Additionally, the hydrogel demonstrated high mechanical strength (7.5 MPa), ensuring flexibility and durability. The polymeric network, formed by acrylamide, sodium alginate, and bentonite, provided a stable and elastic matrix, optimizing water retention and mechanical performance. The controlled diffusion mechanism of the nanoliposomes was validated through in vitro release studies, indicating Fickian-controlled release behavior. These findings highlight the potential of this polymeric hydrogel system as a functional material for skincare formulations, offering enhanced hydration and sustained bioactive delivery. Full article

During the COVID-19 pandemic, vaccination hesitancy (VH) posed an equally unexpected and significant obstacle to the effectiveness of public health interventions. VH has not only the potential to stir up public unrest, but it may also impede the success of entire immunization programs and thus prevent the attainment of herd immunity. This cross-sectional, quantitative, and descriptive study examined VH and vaccination behavior (VB) among 3486 university students in Ghana, using a standardized self-administered questionnaire based on the 5Cs model among other relevant variables. The findings confirm a significant VH and a VB influenced by both sociodemographic factors, such as gender (OR: 1.45; [CI: 1.26–1.67]), study program (OR: 0.55; [CI: 0.47–0.64]), and ethnicity (OR: 1.31; [CI: 1.12–1.52]) and also four of the 5Cs, i.e., Confidence (OR:1.56; [CI: 1.45–1.68]), Constraints (OR: 0.83; [CI: 0.78–0.87]), Calculation (OR:0.85; [CI: 0.78–0.92]), and Collective Responsibility (OR:1.27; [CI: 1.16–1.38]), yet not Complacency, nor religion. Notably, VH was further shaped by previous vaccine experience, information sources, vaccine attributes, stance on vaccine passport, and conspiracy beliefs, with misinformation from unofficial sources playing a key role. The multiple regression models explained 11% to 34% of the variance in the 5Cs, indicating varying degrees of explanatory power for each factor influencing VB and eventually also VH. This study highlights the urgent need for targeted public health interventions, such as integrating vaccine education into university orientation programs, streamlining vaccination processes, and leveraging influencers for trust-building campaigns. Full article

With the increasing predominance of public cloud computing, managing the cost of usage for end users has become vital in importance. Task scheduling has emerged as an important target of research in this area. The present work considers the problem of assigning tasks with different priorities to clouds, with the main requirement being to ensure the meeting of deadlines for high-priority tasks at all costs. The idea is to use as many public cloud resources as needed to satisfy this constraint, even if it means incurring more cost. To solve this problem, the present work proposes a two-stage approach that uses a fuzzy logic controller and heuristic-based task rearrangement. The proposed approach is compared with the FCFS-EDF, SJF-EDF, and Random-EDF approaches using synthetic and GoCJ datasets, and it demonstrates the ability to meet all the primary constraints. The experiments also demonstrate that the required constraints do not necessarily require a higher cost expenditure. It is also shown that if a higher expenditure does occur for a particular task set, the proposed approach is able to keep the rise in cost minimal. Full article

Regenerative medicine is gaining interest in the medical field due to the limitations of conventional treatments, which often fail to address the underlying cause of disease. In recent years, stem cell-based therapies have evolved as a promising alternative approach to treat those diseases that cannot be cured using conventional medicine. Adult stem cells, particularly the mesenchymal stem cells (MSCs), have attracted a lot of attention due to their ability to regenerate and repair human tissues and organs. MSCs isolated from adult tissues are well characterized and are currently the most common type of cells for use in regenerative medicine. However, their low number in adult donor tissues, donor-age and cell-source related heterogeneity, limited proliferative and differentiation potential, and early senescence in in vitro cultures, negatively affect MSC regenerative potential. These factors restrict MSC use for research as well as for clinical applications. To overcome these problems, MSCs with superior regenerative potential are required. Induced MSCs (iMSCs) are obtained from induced pluripotent stem cells (iPSCs). These cells are patient-specific, readily available, and have relatively superior regenerative potential and, therefore, can overcome the problems associated with the use of primary MSCs. In this review, the authors aim to discuss the characteristics, regenerative potential, and limitations of MSCs for regenerative medicine applications. The main methods to generate iMSCs from iPSCs have been discussed in detail. In addition, the proposed criteria for their molecular characterization, applications of iMSCs for disease modeling and drug discovery, as well as potential use in regenerative medicine have been explored in detail. Full article

Hospital buildings require special attention to protect patients and healthcare workers from hospital-acquired infections and sick building illnesses. This is the first study to assess the prevalence of fungus in indoor air, outdoor air, and their contamination on surfaces at selected locations in four highly contaminated hospitals (A, B, C, and D) in Peninsular Malaysia. A total of 294 indoor air samples, 106 scrapped and 169 swabbed, were collected from July 2019 to August 2020. Bioaerosol concentrations were calculated using the colony-forming unit (CFU)/m³. Molecular identification was performed on the cultures. The internal transcribed spacer (ITS) region in the rRNA gene of the isolates was amplified by PCR. Results showed that fungal burden was in the range between 18 and 2597 CFU/m³. Fungal load in selected locations at Hospital D were in the higher range between 106 and 2597 CFU/m³, with two locations exceeding the national guidelines. Fungal genera were highly identified in air samples (47) compared to swabbed (29) and scrapped (18) samples. The dominant species were C. halotolerans, C. tenuissimum, P. alfredii, P. brevicompactum, P. brocae, P. cataractarum, and A. aculeatus. Fungal loads were higher in the Orthopedic and Oral Surgeon Clinic, the On Call Emergency Room, wards, and pathways. Full article

In recent years, the integration of industrial robotics has emerged as a powerful tool in reshaping industries by enhancing production efficiency, reducing waste generation, and optimizing resource utilization. However, industrial robotics, particularly in manufacturing and production, require significant energy that can potentially impact on environmental quality. Despite the growing adoption of artificial intelligence (AI)-based industrial robotics, there is a paucity of literature on the impact of industrial robotics on the ecological footprint (EF), particularly in the context of advanced economies. In this context, this study aims to investigate the impact of industrial robotics, resource efficiency, energy transition, and geopolitical risk EF in G7 countries from 1993 to 2021. The study employed advanced econometric techniques, including Kernel-based Regularized Least Squares (KRLS) and Artificial Neural Network (ANN) machine learning methods. The results unveiled that industrial robotics significantly curtail environmental degradation by impeding the EF. Resource efficiency and energy transition posed a significant and negative impact on the EF. Geopolitical risks and economic growth exacerbate the EF. Based on the results, the study proposes important policy implications for achieving sustainable development. Full article

The study of bubble growth and collapse is of great significance in the context of sustainability due to its influence on numerous energy-related processes and technologies. Understanding the dynamics of bubble behavior is vital for optimising heat transfer efficiency, which has an energetic role in improving the performance of sustainable systems such as nuclear reactors, thermal inkjet printing, and nucleate boiling. Indeed, researchers can progress strategies to enhance the efficiency of these technologies by analysing the parameters influencing bubble growth and collapse, which can lead to reduced energy consumption and environmental impact. Although several theoretical models and experimental investigations have been achieved in the past to inspect bubble growth and collapse, a thorough review and critical assessment of the studies conducted have not yet been achieved. This review aims to provide a comprehensive understanding of the relationship between bubble dynamics and sustainability, highlighting the potential for further research and development in this area. Specifically, the scope and limitations of past research on bubble growth and collapse is conducted to fill this gap in the open literature. The review covers both numerical and experimental studies of bubble growth and collapse in a wide set of innovative industrial applications including nuclear reactors, thermal inkjet printing, nucleate boiling, hydrodynamic erosion, and ultrasonic and medicinal therapy. The current review also attempts to illustrate and evaluate the numerical methods used and underlines the most relevant results from the studies that were looked at in order to provide researchers with a clear picture of the growth and collapse of bubbles in different applications. The results give a precise understanding of the dynamics of bubble growth and collapse and the related temperature change and cumulative heat transmission from the thermal boundary layer. Additionally, it has been demonstrated that simulation-based models can effectively predict transport coefficients. However, the review observes a number of limitations of the past research on bubble growth and collapse. Due to numerical instability, very little work with respect to dynamic modelling has been carried out on the mechanisms of bubble collapse. Accordingly, a number of recommendations are made for the improvement of heat transmission during bubble growth and collapse. Specifically, future criteria for the highest heat transmission will demand more precise experimental and numerical approaches. Full article

As farming practices evolve and climate conditions shift, achieving sustainable food production for a growing global population requires innovative strategies to optimize environmentally friendly practices and minimize ecological impacts. Agroecosystems, which integrate agricultural practices with the surrounding environment, play a vital role in maintaining ecological balance and ensuring food security. Rhizosphere management has emerged as a pivotal approach to enhancing crop yields, reducing reliance on synthetic fertilizers, and supporting sustainable agriculture. The rhizosphere, a dynamic zone surrounding plant roots, hosts intense microbial activity fueled by root exudates. These exudates, along with practices such as green manure application and intercropping, significantly influence the soil’s microbial community structure. Beneficial plant-associated microbes, including Trichoderma spp., Penicillium spp., Aspergillus spp., and Bacillus spp., play a crucial role in improving nutrient cycling and promoting plant health, yet their interactions within the rhizosphere remain inadequately understood. This review explores how integrating beneficial microbes, green manures, and intercropping enhances rhizosphere processes to rebuild microbial communities, sequester carbon, and reduce greenhouse gas emissions. These practices not only contribute to maintaining soil health but also foster positive plant–microbe–rhizosphere interactions that benefit entire ecosystems. By implementing such strategies alongside sound policy measures, sustainable cropping systems can be developed to address predicted climate challenges. Strengthening agroecosystem resilience through improved rhizosphere processes is essential for ensuring food security and environmental sustainability in the future. In conclusion, using these rhizosphere-driven processes, we could develop more sustainable and resilient agricultural systems that ensure food security and environmental preservation amidst changing climate situations. Full article

A management idea known as corporate social responsibility encourages businesses to incorporate social and environmental considerations into their daily operations and relationships with stakeholders. The purpose of this research is to identify the aspects that influence customers’ perceptions of a brand’s commitment to social responsibility and their subsequent intentions to purchase. The theoretical model proposed draws on numerous theories of consumer behavior, including the perceived value theory, the corporate identity theory, and the theory of planned behavior. A survey was then given to 280 users in Pakistan afterwards. Later, structural equation modeling was used to evaluate the suggested model. It was discovered that customer satisfaction, brand loyalty, and brand admiration mediated the relationship between CSR and CSR-related purchase intent. In conjunction with service quality, CSR practices increase customer satisfaction. The effect of customer satisfaction on CSR purchasing intent is also mediated by brand loyalty and brand admiration. This study backs consumer behavior theories by elucidating the lagged and immediate indicators of CSR purchasing intent. CSR may result in customer satisfaction if implemented intelligently to meet its objectives. Customer satisfaction is a requirement for customers to be ready to pay for CSR. Full article

Underwater image restoration is a crucial task in various computer vision applications, including underwater target detection and recognition, autonomous underwater vehicles, underwater rescue, marine organism monitoring, and marine geological survey. Among other categories, the physics-based methods restore underwater images by improving the transmission map through optimization or regularization techniques. Conventional optimization-based methods often do not consider the effect of structural differences between guidance and transmission maps. To address this issue, in this paper, we present a regularization-based method for restoring underwater images that uses coherent structures between the guidance map and the transmission map. The proposed approach models the optimization of transmission maps through a nonconvex energy function comprising data and smoothness terms. The smoothness term includes static and dynamic structural priors, and the optimization problem is solved using a majorize-minimize algorithm. We evaluate the proposed method on benchmark datasets, and the results demonstrate the superiority of the proposed method over state-of-the-art techniques in terms of improving transmission maps and producing high-quality restored images. Full article

The high amount of starch in fruits is responsible for its post-processing cloudiness. In the current study, α-amylase from porcine pancreases was immobilized onto carboxymethyl cellulose/polyacrylamide (CMC/PAM) hydrogel. This in-house-built CMC/PAM-Amy hydrogel offers a more efficient and sustainable solution for apple juice clarification. To acquire the best immobilization efficiency, the concentration of glutaraldehyde crosslinker was optimized. Biocatalytic characterization studies were brought into consideration for free and immobilized α-amylase. The synthesized native and immobilized CMC/PAM-Amy hydrogels were also characterized using SEM, FTIR and XRD. Under ideal circumstances, the activity of CMC/PAM-Amy was up to 604 μmolmin⁻¹, and its immobilization efficiency was 96.29 ± 1.15%. A kinetic parameters study resulted in a conspicuously lowered Km value for immobilized amylase, signifying its higher affinity for its substrate. CMC/PAM-Amy showed a half-life (t_1/2) 3.5 times higher than free-Amy at 50, 55 and 60 °C. The higher values of the inactivation rate constant (k_d), free energy of inactivation (ΔG*), enthalpy of inactivation (ΔH*) and change in entropy (ΔS*) of CMC/PAM-Amy manifested the enhanced thermal stability of amylase after immobilization. A reusability study revealed that immobilized amylase retained roughly 70% of its initial catalytic activity after six successive repetitions of the process. CMC/PAM-Amy displayed improved recycling ability operational stability and biocatalytic activity, rendering it an auspicious tool in decreasing the starch content of crude apple juice to about 61% of its total starch content before treatment. Moreover, the values of Brix, viscosity, acidity and turbidity were also decreased in CMC/PAM-Amyclarified apple juice. Therefore, immobilized amylases with other industrial enzymes could be an efficient tool for potential industrial application. Full article

Students’ behavioral and emotional engagement in the classroom environment may reflect the students’ learning experience and subsequent educational outcomes. The existing research has overlooked the measurement of behavioral and emotional engagement in an offline classroom environment with more students, and it has not measured the student engagement level in an objective sense. This work aims to address the limitations of the existing research and presents an effective approach to measure students’ behavioral and emotional engagement and the student engagement level in an offline classroom environment during a lecture. More precisely, video data of 100 students during lectures in different offline classes were recorded and pre-processed to extract frames with individual students. For classification, convolutional-neural-network- and transfer-learning-based models including ResNet50, VGG16, and Inception V3 were trained, validated, and tested. First, behavioral engagement was computed using salient features, for which the self-trained CNN classifier outperformed with a 97%, 91%, and 83% training, validation, and testing accuracy, respectively. Subsequently, the emotional engagement of the behaviorally engaged students was computed, for which the ResNet50 model surpassed the others with a 95%, 90%, and 82% training, validation, and testing accuracy, respectively. Finally, a novel student engagement level metric is proposed that incorporates behavioral and emotional engagement. The proposed approach may provide support for improving students’ learning in an offline classroom environment and devising effective pedagogical policies. Full article

The advancement of artificial intelligence (AI) has become a crucial element in autonomous cars. A well-designed AI architecture will be necessary to attain the full potential of autonomous vehicles and will significantly accelerate the development and deployment of autonomous cars in the transportation sector. Promising autonomous cars for innovating modern transportation systems are anticipated to address many long-standing transporting challenges related to congestion, safety, parking, and energy conservation. Choosing the optimal AI architecture for autonomous vehicles is a multi-attribute decision-making (MADM) dilemma, as it requires making a complicated decision while considering a number of attributes, and these attributes can have two-dimensional uncertainty as well as indiscernibility. Thus, in this framework, we developed a novel mathematical framework “complex intuitionistic fuzzy rough set” for tackling both two-dimensional uncertainties and indiscernibility. We also developed the elementary operations of the deduced complex intuitionistic fuzzy rough set. Moreover, we developed complex intuitionistic fuzzy rough (weighted averaging, ordered weighted averaging, weighted geometric, and ordered weighted geometric) aggregation operators. Afterward, we developed a method of MADM by employing the devised operators and investigated the case study “Selection of optimal AI architecture for autonomous vehicles” to reveal the practicability of the devised method of MADM. Finally, to reveal the dominance and supremacy of our proposed work, a benchmark dilemma was used for comparison with various prevailing techniques. Full article

Cupronickel-based alloys are widely known for their excellent resistance against aqueous corrosion, however, they can be susceptible to corrosion at accelerated rates and premature failure when exposed to a polluted or brackish seawater medium, even for short-term exposure durations. This unfamiliar corrosion behavior may be a result of the formation of an unprotected corrosion film during the early exposure durations. The paper investigates the corrosion phenomenon in cupronickel 90/10 alloy, by exposing the coupons in two different seawater compositions in the Arabian Sea region. Corrosion losses were investigated on the experimental coupons in a submerged position, for a maximum exposure duration of 150 days, using the conventional weight loss method and a new dimensional metrology-based measurement technique. Additionally, in this research the tubes of a marine heat exchanger having similar material that failed prematurely during operation in the Arabian Sea were also investigated for corrosion losses, followed by the characterization of the corrosion deposits using following analytical techniques: SEM, EDS, XRD and Raman Scattering. The experimental results showed significantly higher corrosion losses on coupons exposed to seawater site rich in pollutants and nutrients including dissolved inorganic nitrogenous compounds, compared to those subjected to a natural seawater solution in corrosion tanks maintained in a controlled environment. Full article