Search Results (34)

Waste streams, leachates, and wastewater often contain high-strength ammonia, which can be challenging to manage. Microbial fuel cells (MFCs) offer a promising solution for treating such a nuisance of high-strength ammonia. However, optimizing MFC operating conditions, at lower technology readiness levels, is crucial to achieve a sustainable and economically viable application. This study investigates the factors affecting ammonia nitrogen removal in MFCs. MFCs with a cation exchange membrane (CEM) exhibit a higher diffusion rate of ammonium ions from the anode to the cathode compared to those with a proton exchange membrane (PEM). In close circuit mode (CCM), MFCs with a Pt-coated cathode electrode achieved an ammonium removal efficiency of 96% in the cathode chamber. Moreover, a plain carbon cathode electrode yielded an 87.1% removal efficiency. These results indicate that the combination of a catalyst (Pt) and oxygen in the cathode chamber can effectively remove or recover ammonia nitrogen from wastewater. Simultaneously, the removal of ammonia nitrogen in a microbial electrolysis cell (MEC) was studied. At an applied potential of 1.0 V, an ammonium removal efficiency of 87.5% was achieved. It was concluded that ammonium losses in MFCs can occur through electron migration, volatilization, and biological processes such as nitrification and denitrification. Full article

Symmetry in non-planar graphs is a fundamental concept that enhances understanding, simplifies analyses, and has practical implications in diverse fields such as science, engineering, and mathematics. A total $\kappa$-labeling for a graph $\check{G_{\nu }}$ is composed of two labeling: one is an edge labeling ${{\rm Y}}_e:E(\check{G_{\nu }})\to \{1,2,3,\dots ,{\kappa }_e\}$ and the other is a vertex labeling ${{\rm Y}}_v:V(\check{G_{\nu }})\to \{0,2,4,\dots ,2{\kappa }_v\}$, where $\kappa =max\{{\kappa }_e,2{\kappa }_v\}$. The weight of an edge under reflexive labeling is defined as $wt(pq)={{\rm Y}}_v(p)+{{\rm Y}}_e(pq)+{{\rm Y}}_v(q)\forall e=pq$. The total $\kappa -labeling$ is said to be an edge-irregular reflexive $\kappa -labeling$, if for every two edges $e_{\delta }$ and $e_j$, the weights are distinct. The lowest value of $\kappa$ for which the graph $\check{G_{\nu }}$ has an irregular reflexive edge $\kappa -labeling$ is called the reflexive edge strength of $\check{G_{\nu }}$, denoted as $res(\check{G_{\nu }})$. $res(\check{G_{\nu }})$ captures irregularity while preserving reflexivity by quantifying edge-weight variability in reflexive graphs. In this article, we are interested in determining the tight lower bound for non-planar prisms, cross prisms, cross-particle modified graphs, and cross-particle glowing graphs under reflexive labeling. Full article

Podophyllum hexandrum Royle, also known as Podophyllum emodi Wall, holds significant ecological, ornamental, and medicinal values. However, it has become endangered due to overexploitation, prolonged seed dormancy, slow natural regeneration, and climate change. This study developed an efficient in vitro protocol for callogenesis and micropropagation of P. hexandrum to conserve germplasm in in vitro conditions. Callus formation from various plant parts, including the leaf, stem, rhizome, radicle, and cotyledon, was induced using Murashige and Skoog (MS) medium supplemented with different plant growth regulators. The combination of benzyladenine at 1 mg L⁻¹ and 4-dichlorophenoxy acetic acid at 3 mg L⁻¹ was optimal for biomass production, yielding 215.88 ± 0.31 mg, with growth per gram at 8.32 ± 0.32 and a growth rate of 13.62 ± 0.25 mg/day on MS medium. For shoot proliferation, benzyladenine (3.5 mg L⁻¹) and naphthalene acetic acid (0.5 mg L⁻¹) combined with activated charcoal showed the highest shoot induction percentage per explant. For shoot regeneration from calluses, 6-benzylaminopurine (0.5 mg L⁻¹) and thidiazuron (2 mg L⁻¹) were most effective, producing superior shoot length, number of regenerations, and regeneration percentage. Root induction was successful with α-naphthalene acetic acid supplementation (0.5 to 1.5 mg L⁻¹) in MS medium, resulting in the highest number per explant (4.08 ± 0.08), length (5.45 ± 0.15 cm), and rooting rate (87.00 ± 1.66%) of roots in plantlets. Subculturing for callus culture was performed every 28 days for up to four subcultures to prevent nutrient depletion and toxic metabolite accumulation, ensuring tissue health and viability. Continuous subculturing of callus on MS medium maintained healthy P. hexandrum germplasm in vitro. Overall, this micropropagation protocol provides a rapid system for conserving P. hexandrum germplasm. Full article

Alzheimer’s disease (AD) is a degenerative neurological condition that severely affects the elderly and is clinically recognised by a decrease in cognition and memory. The treatment of this disease has drawn considerable attention and sparked increased interest among the researchers in this field as a result of a number of factors, including an increase in the population of patients over time, a significant decline in patient quality of life, and the high cost of treatment and care. The current work was carried out for the synthesis of benzimidazole-oxazole hybrid derivatives as efficient Alzheimer’s inhibitors and as a springboard for investigating novel anti-chemical Alzheimer’s prototypes. The inhibition profiles of each synthesised analogue against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) enzymes were assessed. All the synthesized benzimidazole-based oxazole analogues displayed a diverse spectrum of inhibitory potentials against targeted AChE and BuChE enzymes when compared to the reference drug donepezil (IC₅₀ = 2.16 ± 0.12 M and 4.50 ± 0.11 µM, respectively). The most active AChE and BuChE analogues were discovered to be analogues 9 and 14, with IC₅₀ values of 0.10 ± 0.050 and 0.20 ± 0.050 µM (against AChE) and 0.20 ± 0.050 and 0.30 ± 0.050 µM (against BuChE), respectively. The nature, number, position, and electron-donating and -withdrawing effects on the phenyl ring were taken into consideration when analysing the structure-activity relationship (SAR). Molecular docking studies were also carried out on the active analogues to find out how amino acids bind to the active sites of the AChE and BuChE enzymes that were being studied. Full article

The current study aimed to improve the nitrogen recovery efficiency (NRE) of maize under the application of balanced proportions of ammoniacal-nitrogen (NH₄⁺-N) and nitrate-nitrogen (NO₃⁻-N) (1:1), as well as to determine economic impacts of such fertilizers on maize productivity. A 3-year field study was carried out in Sahiwal, Punjab, Pakistan during the 2018–2020 growing seasons with autumn maize. In parallel, multi-location field experiments were conducted at farmer’s fields in Sahiwal during the same growing seasons with autumn maize. The trials compared the effects of different fertilizers like urea, calcium ammonium nitrate (CAN), Sarsabz nitrophos (NP), nitrphos plus (NP Plus), and di-ammonium phosphate (DAP) on maize growth and yield, as well their economic efficiency. The results revealed that the application of Sarsabz NP and CAN increased the maize grain yield by 30%, 13%, 15%, 19%, 15%, and 9% as compared to the control, NP + urea, NP Plus + CAN, NP Plus + urea, DAP + urea, and DAP + CAN, respectively. In addition, the combined application of NP and CAN increased the total N and NO₃⁻-N concentrations, whereas it decreased the NH₄⁺-N concentrations in the soils. By contrast, NP + CAN increased the NH₄⁺-N concentrations in maize leaves as compared to NO₃⁻-N concentrations. Overall, the NRE of maize plants and the net return were higher under combined application of NP and CAN. In conclusion, CAN fertilizer increased the soil NO₃⁻-N concentrations, which thus assimilated in the plants as NH₄⁺ and improved the NRE of maize. Improved NRE thus enhanced maize yield and resulted in the maximum net return as compared to all other fertilizer combinations. Full article

Neuroblastoma (NB) is one of the primary causes of death for pediatric malignancies. Given the high heterogeneity in NB’s mutation landscape, optimizing individualized therapies is still challenging. In the context of genomic alterations, MYCN amplification is the most correlated event with poor outcomes. MYCN is involved in the regulation of several cellular mechanisms, including cell cycle. Thus, studying the influence of MYCN overexpression in the G1/S transition checkpoint of the cell cycle may unveil novel druggable targets for the development of personalized therapeutical approaches. Here, we show that high expression of E2F3 and MYCN correlate with poor prognosis in NB despite the RB1 mRNA levels. Moreover, we demonstrate through luciferase reporter assays that MYCN bypasses RB function by incrementing E2F3-responsive promoter activity. We showed that MYCN overexpression leads to RB inactivation by inducing RB hyperphosphorylation during the G1 phase through cell cycle synchronization experiments. Moreover, we generated two MYCN-amplified NB cell lines conditionally knockdown (cKD) for the RB1 gene through a CRISPRi approach. Indeed, RB KD did not affect cell proliferation, whereas cell proliferation was strongly influenced when a non-phosphorylatable RB mutant was expressed. This finding revealed the dispensable role of RB in regulating MYCN-amplified NB’s cell cycle. The described genetic interaction between MYCN and RB1 provides the rationale for using cyclin/CDK complexes inhibitors in NBs carrying MYCN amplification and relatively high levels of RB1 expression. Full article

Code comments are considered an efficient way to document the functionality of a particular block of code. Code commenting is a common practice among developers to explain the purpose of the code in order to improve code comprehension and readability. Researchers investigated the effect of code comments on software development tasks and demonstrated the use of comments in several ways, including maintenance, reusability, bug detection, etc. Given the importance of code comments, it becomes vital for novice developers to brush up on their code commenting skills. In this study, we initially investigated what types of comments novice students document in their source code and further categorized those comments using a machine learning approach. The work involves the initial manual classification of code comments and then building a machine learning model to classify student code comments automatically. The findings of our study revealed that novice developers/students’ comments are mainly related to Literal (26.66%) and Insufficient (26.66%). Further, we proposed and extended the taxonomy of such source code comments by adding a few more categories, i.e., License (5.18%), Profile (4.80%), Irrelevant (4.80%), Commented Code (4.44%), Autogenerated (1.48%), and Improper (1.10%). Moreover, we assessed our approach with three different machine-learning classifiers. Our implementation of machine learning models found that Decision Tree resulted in the overall highest accuracy, i.e., 85%. This study helps in predicting the type of code comments for a novice developer using a machine learning approach that can be implemented to generate automated feedback for students, thus saving teachers time for manual one-on-one feedback, which is a time-consuming activity. Full article

This paper investigates the impact of life expectancy on carbon emission, in Saudi Arabia. Additionally, we examined the role of governance to achieve carbon neutrality status. We used the novel dynamic ARDL technique for estimations. This is one of the pioneer studies that analyze the role of life expectancy to control carbon emissions. The coefficients of life expectancy, education, and political stability are significantly negative. On contrary, governance effectiveness is an obstacle to achieving carbon neutrality. Empirical findings of life expectancy and governance effectiveness are quite surprising. In terms of Vision 2030 estimations, the coefficient of corruption control is significant and negative, indicating that the Saudi government has prioritized corruption control. While governance effectiveness remains positive, the Saudi government still requires governance reforms in order to achieve carbon neutrality goals. Full article

The Mobile Ad-Hoc Network (MANET) has received significant interest from researchers for several applications. In spite of developing and proposing numerous routing protocols for MANET, there are still routing protocols that are too inefficient in terms of sending data and energy consumption, which limits the lifetime of the network for forest fire monitoring. Therefore, this paper presents the development of a Location Aided Routing (LAR) protocol in forest fire detection. The new routing protocol is named the LAR-Based Reliable Routing Protocol (LARRR), which is used to detect a forest fire based on three criteria: the route length between nodes, the temperature sensing, and the number of packets within node buffers (i.e., route busyness). The performance of the LARRR protocol is evaluated by using widely known evaluation measurements, which are the Packet Delivery Ratio (PDR), Energy Consumption (EC), End-to-End Delay (E2E Delay), and Routing Overhead (RO). The simulation results show that the proposed LARRR protocol achieves 70% PDR, 403 joules of EC, 2.733 s of E2E delay, and 43.04 RO. In addition, the performance of the proposed LARRR protocol outperforms its competitors and is able to detect forest fires efficiently. Full article

This work offers an overview of the effective communication techniques for space exploration of ground, aerial, and underwater vehicles. We not only comprehensively summarize the trajectory planning, space exploration, optimization, and other challenges encountered but also present the possible directions for future work. Because a detailed study like this is uncommon in the literature, an attempt has been made to fill the gap for readers interested in path planning. This paper also includes optimization strategies that can be used to implement terrestrial, underwater, and airborne applications. This study addresses numerical, bio-inspired, and hybrid methodologies for each dimension described. Throughout this study, we endeavored to establish a centralized platform in which a wealth of research on autonomous vehicles (on the land and their trajectory optimizations), airborne vehicles, and underwater vehicles, is published. Full article

This exploratory study examines the effectiveness of social robots’ ability to deliver advertising messages using different “appeals” in a business environment. Specifically, it explores the use of three types of message appeals in a human-robot interaction scenario: guilt, humour and non-emotional. The study extends past research in advertising by exploring whether messages communicated by social robots can impact consumers’ behaviour. Using an experimental research design, the emotional-themed messages focus on the health-related properties of two fictitious energy drink brands. The findings show mixed results for humour and guilt messages. When the robot delivered a promotion message using humour, participants perceived it as being less manipulative. Participants who were exposed to humourous messages also demonstrated a significantly greater intent for future purchase decisions. However, guilt messages were more likely to persuade consumers to change their brand selection. This study contributes to the literature as it provides empirical evidence on the social robots’ ability to deliver different advertising messages. It has practical implications for businesses as a growing number seek to employ humanoids to promote their services. Full article

Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for resource allocation. This study proposes a reliable hybrid dynamic bandwidth slice forecasting framework that combines the long short-term memory (LSTM) neural network and local smoothing methods to improve the network forecasting model. Moreover, the proposed framework can dynamically react to all the changes occurring in the data series. Backbone traffic was used to validate the proposed method. As a result, the forecasting accuracy improved significantly with the proposed framework and with minimal data loss from the smoothing process. The results showed that the hybrid moving average LSTM (MLSTM) achieved the most remarkable improvement in the training and testing forecasts, with 28% and 24% for long-term evolution (LTE) time series and with 35% and 32% for the multiprotocol label switching (MPLS) time series, respectively, while robust locally weighted scatter plot smoothing and LSTM (RLWLSTM) achieved the most significant improvement for upstream traffic with 45%; moreover, the dynamic learning framework achieved improvement percentages that can reach up to 100%. Full article

This article presents the design of a uni-planar MIMO antenna system for sub-6 GHz 5G-enabled smartphones. The MIMO antenna designed comprises four loop-shaped radiators placed at each corner of the mobile phone board, which follows the principle of pattern diversity. The single-antenna element resonates at 3.5 GHz, its impedance bandwidth is noted to be 1.28 GHz (3–4.28 GHz) for S${}_{11}\le$ −6 dB, and it is equal to 720 MHz (3.18–3.9 GHz) for S${}_{11}\le$ −10 dB. For a single-antenna element, a peak gain of 3.64 dBi is observed with an antenna efficiency of >90%. The isolation of >10 dB between antenna elements is achieved for the MIMO configuration. Furthermore, the MIMO antenna designed provides enough radiation coverage to support different sides of the mobile phone board, which is an important feature for future 5G-enabled handsets. In addition, the impacts of human hands and heads on MIMO antenna performance are investigated, and acceptable performance in the data and conversation modes is observed. Full article

The present study was aimed at analyzing students’ perceptions toward mobile assisted language learning (MALL), their use patterns, and their usefulness in their academic outcomes. The results indicated that students use widely different MALL software for different applications. In a survey of 581 students from Indian colleges and universities, the research identified five antecedent factors (namely, individual desire and motives, perceived ease of use, technological factors, social influence, and perceived usefulness) which influenced students in the areas of adopting MALL software, students’ readiness, students’ motivation, and the subsequent effect on student performances. The research further indicated that students’ readiness and their motivation level mediated the relationship between factors of adoption of MALL and perceived outcome. The relevance of positive language learning outcomes, theoretical contribution and managerial implications of the study are discussed. Full article