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The present study introduces an innovative approach to multi-criteria decision making (MCDM) aimed at handling decision analysis involving p,qrung orthopair fuzzy (p,qROF) data, where the criteria weights are completely unknown. To achieve this objective, we formulate generalized operational rules referred to as Frank operational rules, tailored for p,qROF numbers (p,qROFNs) utilizing the Frank t-norm and t-conorm. With these newly devised operations as a foundation, we create a variety of p,qROF aggregation operators (AOs) to effectively aggregate p,qROF information. Furthermore, we examine specific instances of these operators and rigorously establish their desirable properties, including idempotency, monotonicity, boundedness, and symmetry. Subsequently, we adapt the SWARA technique to the realm of p,qROF fuzzy data and this adapted technique becomes instrumental in determining criteria weights within the proposed MCDM framework centered around proposed AOs. We furnish a descriptive example to exemplify the practicality of the developed approach. Lastly, the effectiveness and soundness of our approach are underscored through both parameter analysis and a comparative evaluation. [ABSTRACT FROM AUTHOR]

In this study, a metasurface-based reflectarray is designed for X-band applications. The unit cells are equipped with an H-shaped slotted patch for additional resonance and phase range. Linear phase variation by altering the length of the patch is realized with a range exceeding 480 ∘ . The reflectarray is designed and fabricated on a thin and high-quality Rogers 5880 substrate. The Finite Element Boundary Integral (FEBI) method is used to simulate a 23 × 23 element reflectarray and then fabricated to achieve the measured results using an anechoic chamber. The peak gain of the proposed reflectarray is 25.5 dBi recorded with an aperture efficiency of 63.7% at a center frequency of 10 GHz. The cross-polarization and side-lobe levels in the entire band are less than −33 dB and −21 dB, respectively. Moreover, the proposed reflectarray antenna achieves a 20% 1-dB gain bandwidth. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that comprises amyloid-beta protein (Aβ) as a main component of neuritic plaques. Its deposition is considered a trigger for AD pathogenesis, progression, and the clinical symptoms of cognitive impairment. Some distinct pathological features of AD include phosphorylation of tau protein, oxidative stress, and mitochondrial dysfunction. These pathological consequences tend to produce reactive oxygen species (ROS), resulting in the dysregulation of various signaling pathways of neuroinflammation and neurodegeneration. The relationship between the Aβ cascade and oxidative stress in AD pathogenesis is like a "chicken and egg" story, with the etiology of the disease regarding these two factors remaining a question of "which comes first." However, in this review, we have tried our best to clarify the interconnection between these two mechanisms and to show the precise cause-and-effect relationship. Based on the above hallmarks of AD, several therapeutic strategies using natural antioxidants, monoclonal antibodies, and vaccines are employed as anti-Aβ therapy to decrease ROS, Aβ burden, chronic neuroinflammation, and synaptic failure. These natural antioxidants and immunotherapeutics have demonstrated significant neuroprotective effects and symptomatic relief in various in vitro and in vivo models, as well as in clinical trials for AD. However, none of them have received final approval to enter the drug market for mitigating AD. In this review, we extensively elaborate on the pitfalls, assurances, and important crosstalk between oxidative stress and Aβ concerning current anti-Aβ therapy. Additionally, we discuss future strategies for the development of more Aβ-targeted approaches and the optimization of AD treatment and mitigation. [ABSTRACT FROM AUTHOR]

This study thoroughly compares multiple single bidirectional and multiport converters (MPCs), highlighting the significant role of MPCs in multi-input and multi-output (MIMO) systems. MPCs offer a more efficient and cost-effective solution than multiple single converters, especially in applications involving photovoltaic (PV), electric vehicles (EVs) with storage systems, and power grids. This research emphasizes the importance of multi-input converters (MICs) in integrating diverse voltage sources. It notes the rising popularity of multi-output DC-DC converters in portable electronics, owing to their reduced component count, lower costs, and compact design. This paper emphasizes comparisons based on diverse aspects and applications, shedding light on recent developments in basic bidirectional converters. Additionally, it delves into the advancements in MPC topologies, focusing on efficiency, reliability, and modularity improvements. These advancements are crucial for harnessing cost reduction, simplicity, and compactness. Furthermore, this paper introduces an innovative multiport DC-DC converter tailored for integrating and managing renewable sources. This new converter design enhances PV system and battery storage performance by reducing power conversion steps, using fewer components, and improving voltage-boosting capabilities. Its unique bidirectional buck-boost structure allows for versatile connections between sources and loads with varying voltage and power requirements. The performance of this novel converter is evaluated through MATLAB/Simulink simulations under different scenarios. Experimental studies further validate its effectiveness, marking a significant contribution to power conversion and management in integrating renewable sources such as DC microgrids. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) play a pivotal role in diverse applications such as environmental monitoring, industrial automation, healthcare, and smart cities. The motivation behind the development of WSNs stems from their impact in providing real-time data on various environmental parameters. The challenge for WSNs is to achieve strong security and efficient energy saving together. Traditional methods sought to find solutions either through security or energy. In response, this study proposed a secure and energy-efficient framework for enhancing security measures in WSNs while minimizing the impact on energy resources by using the Enhanced Consumed Energy Leach (ECP-LEACH) protocol and the Enhanced Random Forest Classifier for Low Execution Time (ERF-LET) algorithm for attack detection named Security-Enhanced Energy Conservation with ERF-LET (S-2EC-ERF). The integration of the detection algorithm at the node level played a pivotal role in fortifying the security posture of individual nodes by detecting and mitigating potential security threats. Leveraging a comprehensive dataset obtained from NS3 simulations, the ERF-LET algorithm demonstrated its proficiency in differentiating between normal and attack packets, thereby laying a strong foundation for subsequent evaluations, where it achieved an accuracy of 98.193%. The proposed methodology was further validated through real-time simulations conducted on the NS3. The results demonstrated the superiority of the proposed S-2EC-ERF in terms of the packet delivery ratio (PDR), average throughput, end-to-end delay, and mean energy consumption compared to the Security-Enhanced Energy Conservation with Logistic Regression (S-2EC-LR), Security-Enhanced Energy Conservation with Decision Tree (S-2EC-DT), and Security-Enhanced Energy Conservation with AdaBoost (S-2EC-Ada) algorithms. [ABSTRACT FROM AUTHOR]

Understanding the size distribution, variation patterns, and potential formation mechanisms of particulate organic nitrates (PONs) is crucial for assessing their influences on atmospheric chemistry, air quality, and the regional climate. This study investigates PONs in the coastal atmosphere of Qingdao, China by collecting size-resolved particulate matter samples and analyzing six types of organic nitrates, namely pinene keto nitrate (PKN229), monoterpene hydroxyl nitrate (MHN215), monoterpene dicarbonyl nitrate (MDCN247), oleic acid hydroxyl nitrate (OAHN361), oleic acid keto nitrate (OAKN359), and pinene sulfate organic nitrate (PSON295), using ultrahigh-performance liquid chromatography(mass spectrometry). The mean total concentration of organic nitrates in fine particles reaches 677 ng m−3. The predominant compound is MHN215, followed by PKN229 and MDCN247. All six organic nitrates exhibited distinct concentration peaks in the droplet mode, with MDCN247 and OAHN361 showing a minor peak in the condensation mode. In addition, an apparent concentration peak is observed in the coarse mode for OAKN359. Comparative analyses under various conditions highlight the significant influences of primary emissions and secondary formation processes on the abundance and size distribution of organic nitrates. For instance, both firework displays during festivals and high NOx emissions from fuel combustion significantly increase the concentrations of condensation-mode organic nitrates, whereas dust particles enhanced the heterogeneous formation of coarse-mode particles. Furthermore, the high humidity of the coastal area promotes aqueous formation in droplet-mode particles. [ABSTRACT FROM AUTHOR]

An interval-valued q-rung orthopair fuzzy set ( I V q r O F S ) is a robust and esteemed model in managing imprecise information, utilizing a controllable parameter q ≥ 1 . Expanding its applicability, we propose a refinement to it, termed the interval-valued p,q-rung orthopair fuzzy set, denoted I V p , q r O F S . This advancement enables the handling of scenarios where varied assessment levels for membership and non-membership grades are necessary, a challenge unaddressed by existing extensions of interval-valued intuitionistic fuzzy sets. We establish the fundamental mathematical operations for the I V p , q r O F S and explore their key properties. To compare interval-valued p,q-rung orthopair fuzzy ( I V p , q r O F ) numbers, a novel score function is put forward and compared to the known I V q r O F S -based score functions to determine its viability. Moreover, we present I V p , q r O F aggregation operators (AOs), accompanied by rigorous proof of their essential characteristics, including boundedness, monotonicity, and symmetry. This study introduces the interaction of I V p , q r O F criteria through the inter-criteria correlation (CRITIC) approach. This method determines criteria weights based on the proposed distance measurements and the score function. The CRITIC method is integrated with the exponential TODIM approach (exp-TODIM), resulting in an innovative decision-making framework that is less susceptible to parameter fluctuations and showcases a high stability. An illustrative example of selecting a suitable supplier is provided to demonstrate the practical application of the developed exp-TODIM approach. Finally, a sensitivity analysis is conducted to exhibit the method's stability, and a comparative analysis is performed to elucidate its strengths and advantages. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD), is a progressive neurodegenerative disorder that involves the deposition of β-amyloid plaques and the clinical symptoms of confusion, memory loss, and cognitive dysfunction. Despite enormous progress in the field, no curative treatment is available. Therefore, the current study was designed to determine the neuroprotective effects of N-methyl-(2S, 4R)-Trans-4-hydroxy-L-proline (NMP) obtained from Sideroxylon obtusifolium, a Brazilian folk medicine with anti-inflammatory and anti-oxidative properties. Here, for the first time, we explored the neuroprotective role of NMP in the Aβ1–42-injected mouse model of AD. After acclimatization, a single intracerebroventricular injection of Aβ1–42 (5 µL/5 min/mouse) in C57BL/6N mice induced significant amyloidogenesis, reactive gliosis, oxidative stress, neuroinflammation, and synaptic and memory deficits. However, an intraperitoneal injection of NMP at a dose of (50 mg/kg/day) for three consecutive weeks remarkably decreased beta secretase1 (BACE-1) and Aβ, activated the astrocyte and microglia expression level as well as downstream inflammatory mediators such as pNF-ĸB, TNF-α, and IL-1β. NPM also strongly attenuated oxidative stress, as evaluated by the expression level of NRF2/HO-1, and synaptic failure, by improving the level of both the presynaptic (SNAP-25 and SYN) and postsynaptic (PSD-95 and SNAP-23) regions of the synapses in the cortexes and hippocampi of the Aβ1–42-injected mice, contributing to cognitive improvement in AD and improving the behavioral deficits displayed in the Morris water maze and Y-maze. Overall, our data suggest that NMP provides potent multifactorial effects, including the inhibition of amyloid plaques, oxidative stress, neuroinflammation, and cognitive deficits. [ABSTRACT FROM AUTHOR]

In recent years, the combination of wireless body sensor networks (WBSNs) and the Internet ofc Medical Things (IoMT) marked a transformative era in healthcare technology. This combination allowed for the smooth communication between medical devices that enabled the real-time monitoring of patient's vital signs and health parameters. However, the increased connectivity also introduced security challenges, particularly as they related to the presence of attack nodes. This paper proposed a unique solution, an enhanced random forest classifier with a K-means clustering (ERF-KMC) algorithm, in response to these challenges. The proposed ERF-KMC algorithm combined the accuracy of the enhanced random forest classifier for achieving the best execution time (ERF-ABE) with the clustering capabilities of K-means. This model played a dual role. Initially, the security in IoMT networks was enhanced through the detection of attack messages using ERF-ABE, followed by the classification of attack types, specifically distinguishing between man-in-the-middle (MITM) and distributed denial of service (DDoS) using K-means. This approach facilitated the precise categorization of attacks, enabling the ERF-KMC algorithm to employ appropriate methods for blocking these attack messages effectively. Subsequently, this approach contributed to the improvement of network performance metrics that significantly deteriorated during the attack, including the packet loss rate (PLR), end-to-end delay (E2ED), and throughput. This was achieved through the detection of attack nodes and the subsequent prevention of their entry into the IoMT networks, thereby mitigating potential disruptions and enhancing the overall network efficiency. This study conducted simulations using the Python programming language to assess the performance of the ERF-KMC algorithm in the realm of IoMT, specifically focusing on network performance metrics. In comparison with other algorithms, the ERF-KMC algorithm demonstrated superior efficacy, showcasing its heightened capability in terms of optimizing IoMT network performance as compared to other common algorithms in network security, such as AdaBoost, CatBoost, and random forest. The importance of the ERF-KMC algorithm lies in its security for IoMT networks, as it provides a high-security approach for identifying and preventing MITM and DDoS attacks. Furthermore, improving the network performance metrics to ensure transmitted medical data are accurate and efficient is vital for real-time patient monitoring. This study takes the next step towards enhancing the reliability and security of IoMT systems and advancing the future of connected healthcare technologies. [ABSTRACT FROM AUTHOR]

Since COVID-19's emergence in 2020, all segments of life, including farming communities, have been impacted. The pandemic revealed both vulnerabilities and opportunities for resilience, particularly for those dwelling in the harsh mountainous terrains, which have already strained food ecosystems. Taking influence from an exhaustive literature review, this study proposes and tests a model for the transformations observed in the agriculture markets, particularly input, labor, and product markets, and elucidates the influence of these changes on cropping and consumption patterns. With data from two major mountainous terrains in north Pakistan spanning three years before and during the pandemic, a quantitative inquiry was carried out on the agriculture markets and farming patterns. A total of 5273 members of the farming communities were targeted for data collection. A two-step process was used for data analysis, including an evaluation of the outer or measurement model followed by the inner or structural model through partial least squares structural equation modeling (PLS-SEM). With a hitherto ignored focus on the already vulnerable mountainous communities, the findings confirm the direct influence of agriculture markets on changes in the farmers' cropping patterns as well as the moderating influence of the pandemic on these relationships. Consistent with previous literature, the results also affirm the influence of changes in cropping patterns and changes in consumption patterns. However, it was found that the agriculture input markets strongly predict the changes in cropping patterns, whereas the labor and product markets have comparatively lower prediction value. By investigating the various facets of food supply chains, this study offers valuable insights on market dynamics in times of a crisis, such as a pandemic. [ABSTRACT FROM AUTHOR]

This paper presents the design and optimization of a dual-band polarization-dependent metasurface capable of dynamically switching transmission and reflection characteristics. The metasurface is composed of three metallic patterns, with the bottom layer governing the reflection and transmission phase for both TE-polarization and TM-polarization states. The middle and top layers are strategically employed to ensure optimal transmission and reflection performance. The results confirm that the metasurface enables the transformation of the transmission band into a complete reflection band, and vice versa, through variations in the incident wave polarization. Remarkable transmission and reflection characteristics are achieved within the frequency ranges of 6.1–6.55 GHz and 8.9–9.3 GHz, respectively. The proposed metasurface offers promising applications in advanced communication systems and radar technology, enabling dynamic manipulation of electromagnetic waves. [ABSTRACT FROM AUTHOR]

The use of optical systems in medical imaging, computer electronics, large-scale industries, and space exploration is common. The performance of these devices is closely related to the compactness and fast responses of lenses that are used in these optical systems. Typical lenses suffer from several key issues, including limited efficiency, significant size, and the presence of diffraction-induced distortions that compromise their overall performance. Herein these limitations are addressed by designing and simulating an ultra-thin compact metalens also known as a flat lens using a dielectric metasurface. A 1D array of 31 nano-cylinders is placed on a glass substrate that is utilized for focusing the incident wave both on and off center in the focal plane using simulations. The nano-cylinders are comprised of amorphous silicon hydrogenated (a-Si:H), which has a varying radius in a 1D configuration. Amorphous silicon hydrogenated (a-Si:H) nano-cylinders are utilized for the manipulation of the phase of the incident beam working at a frequency of 474 THz. Three metalenses are introduced with focal lengths of 7.46 μ m, 10 μ m, and 12.99 μ m, each having a numerical aperture (NA) of 0.7, 0.6, and 0.5, respectively. The designed single-array metalens showed a transmission efficiency of 73%. The nano-cylinders obtained a full 0–360 phase control that is beneficial in focusing the beam at the center and beyond the center. Symmetric focusing is obtained in the case of off-center focusing on both sides of the optical axis. The design and simulations of the metalens are performed using finite difference time domain (FDTD) simulation tools. [ABSTRACT FROM AUTHOR]

Trolox is a potent antioxidant and a water-soluble analog of vitamin E. It has been used in scientific studies to examine oxidative stress and its impact on biological systems. Trolox has been shown to have a neuroprotective effect against ischemia and IL-1β-mediated neurodegeneration. In this study, we investigated the potential protective mechanisms of Trolox against a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinson's disease mouse model. Western blotting, immunofluorescence staining, and ROS/LPO assays were performed to investigate the role of trolox against neuroinflammation, the oxidative stress mediated by MPTP in the Parkinson's disease (PD) mouse model (wild-type mice (C57BL/6N), eight weeks old, average body weight 25–30 g). Our study showed that MPTP increased the expression of α-synuclein, decreased tyrosine hydroxylase (TH) and dopamine transporter (DAT) levels in the striatum and substantia nigra pars compacta (SNpc), and impaired motor function. However, Trolox treatment significantly reversed these PD-like pathologies. Furthermore, Trolox treatment reduced oxidative stress by increasing the expression of nuclear factor erythroid-2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). Lastly, Trolox treatment inhibited the activated astrocytes (GFAP) and microglia (Iba-1), also reducing phosphorylated nuclear factor-κB, (p-NF-κB) and tumor necrosis factor-alpha (TNF-α) in the PD mouse brain. Overall, our study demonstrated that Trolox may exert neuroprotection on dopaminergic neurons against MPTP-induced oxidative stress, neuroinflammation, motor dysfunction, and neurodegeneration. [ABSTRACT FROM AUTHOR]

Oxidative stress plays an important role in cognitive dysfunctions and is seen in neurodegeneration and Alzheimer's disease (AD). It has been reported that the polyphenolic compound caffeic acid possesses strong neuroprotective and antioxidant effects. The current study was conducted to investigate the therapeutic potential of caffeic acid against amyloid beta (Aβ1–42)-induced oxidative stress and memory impairments. Aβ1–42 (5 μL/5 min/mouse) was administered intracerebroventricularly (ICV) into wild-type adult mice to induce AD-like pathological changes. Caffeic acid was administered orally at 50 mg/kg/day for two weeks to AD mice. Y-maze and Morris water maze (MWM) behavior tests were conducted to assess memory and cognitive abilities. Western blot and immunofluorescence analyses were used for the biochemical analyses. The behavioral results indicated that caffeic acid administration improved spatial learning, memory, and cognitive abilities in AD mice. Reactive oxygen species (ROS) and lipid peroxidation (LPO) assays were performed and showed that the levels of ROS and LPO were markedly reduced in the caffeic acid-treated mice, as compared to Aβ-induced AD mice brains. Moreover, the expression of nuclear factor erythroid 2–related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) were regulated with the administration of caffeic acid, compared to the Aβ-injected mice. Next, we checked the expression of ionized calcium-binding adaptor molecule 1 (Iba-1), glial fibrillary acidic proteins (GFAP), and other inflammatory markers in the experimental mice, which suggested enhanced expression of these markers in AD mice brains, and were reduced with caffeic acid treatment. Furthermore, caffeic acid enhanced synaptic markers in the AD mice model. Additionally, caffeic acid treatment also decreased Aβ and BACE-1 expression in the Aβ-induced AD mice model. [ABSTRACT FROM AUTHOR]

The shift towards sustainable and digital practices in organizations is transforming employees' mindsets and work performance. The digital transformation in academia is leading to meaningful changes in the behaviors and responsibilities of non-academic employees within organizations toward sustainable and responsible practices. By expounding insights into these views through social exchange theory (SET), this study aims to examine the key predictors of employee engagement (EE); namely, knowledge sharing (KS), employee mobility (EM), training and development (TD), and psychological empowerment (PE) in a digital workplace scenario. A quantitative survey based on convenience sampling was conducted to validate the research framework through partial least squares structural equation modelling (PLS-SEM). Accordingly, 205 responses were collected from the non-academic staff of universities in Klang Valley, Malaysia. Data analysis results showed that all hypotheses were significantly accepted. The impact of the model variables on employee engagement in digital transformation was found to be 75%, with employee mobility and knowledge sharing being the most prominent factors. Multigroup analysis (MGA) and importance-performance map analysis (IPMA) were additional analytical tools applied to reinforce the survey findings further and provide more comprehensive insights into employee engagement across different departments within the organization. The findings also showed the robustness of social exchange theory in digital business practices. This research offers novel and innovative perspectives on the impact of various factors (KS, EM, TD, PE) on employee engagement during digital transformation and how they mold employee behavior toward driving productive and responsible outcomes. [ABSTRACT FROM AUTHOR]

Drought stress restricts the growth of okra (Abelmoschus esculentus L.) by disrupting its biochemical and physiological functions. The current study was conducted to evaluate the role of selenium (0, 1, 2, and 3 mg Se L−1 as a foliar application) in improving okra tolerance to drought (control (100% field capacity-FC), mild stress (70% FC), and severe stress (35% FC)) imposed 30 days after sowing (DAS). Drought (severe) markedly decreased chlorophyll (32.21%) and carotenoid (39.6%) contents but increased anthocyanin (40%), proline (46.8%), peroxidase (POD by 12.5%), ascorbate peroxidase (APX by 11.9%), and catalase (CAT by 14%) activities. Overall, Se application significantly alleviated drought stress-related biochemical disturbances in okra. Mainly, 3 mg Se L−1 significantly increased chlorophyll (21%) as well as anthocyanin (15.14%), proline (18.16%), and antioxidant activities both under drought and control conditions. Selenium played a beneficial role in reducing damage caused by oxidative stress, enhancing chlorophyll and antioxidants contents, and improved plant tolerance to drought stress. Therefore, crops including okra especially, must be supplemented with 3 mg L−1 foliar Se for obtaining optimum yield in arid and semiarid drought-affected areas. [ABSTRACT FROM AUTHOR]

By leveraging ubiquitous computing and the Internet of Things (IoT), smart cities gain potential to provide a wider range of services. Different homogeneous and heterogeneous networking schemes and applications have been proposed in the literature to date. In these networking schemes, human and computer are connected for social, economic, physiological, and technological growth. However, there is a dearth of recent literature that incorporates recently proposed and operating techniques and technologies capable of enhancing the productivity of human and machine in IoT technologies. The role of this research is to investigate the protocols, followed by the advance frameworks for IoT, the characteristics and services that are being governed using IoT for establishing information-rich smart cities. To this end, likewise, physical layer, media access control, networking and applications protocols, and encapsulation standards of IoT for smart cities applications are critically reviewed. Certain open issues are discussed based on the literature collected that would improve the autonomous behavior, process control, device handling, and the QoS in smart environments. [ABSTRACT FROM AUTHOR]

The dual hesitant fuzzy linguistic term set (DHFLTS) is defined by two functions that express the grade of membership and the grade of non-membership using a set of linguistic terms. In the present work, we first quote an example to point out that the existing complement operation of DHFLTS is on the wrong track. Meanwhile, we redefine this operation to fill the holes in the existing ones. Next, the notion of information energy under a dual hesitant fuzzy linguistic background is provided in order to build the criteria weight determination model. To further facilitate the theory of DHFLTS, we propose two vector similarity measures, i.e., Jaccard and Dice similarity measures, and their weighted forms for DHFLTS. In addition, we pioneer some generalized similarity measures of DHFLTSs and indicate that the Dice similarity measures are particular instances of the generalized similarity measures for some parameter values. Afterward, the similarity measures-based model with unknown weight information under the background of dual hesitant fuzzy linguistic environment is constructed. Lastly, an illustrated example is included to validate the method's application, along with sensitivity analysis and comparative analysis, demonstrating the practicality and validity of its results. [ABSTRACT FROM AUTHOR]

Three-dimensionally printed materials show great performance and reliable stability in the removal of refractory organic pollutants in Fenton-like reactions. In this work, hierarchically porous zero-valent copper (3DHP-ZVC) was designed and fabricated via 3D printing and applied as a catalyst for the degradation of tetracycline (TC) through heterogeneous Fenton-like processes. It was found that the 3DHP-ZVC/H2O2 system could decompose over 93.2% of TC within 60 min, which is much superior to the homogeneous Cu2+/H2O2 system under similar conditions. The leaching concentration of Cu2+ ions in the 3DHP-ZVC/H2O2 system is 2.14 times lower than that in the Cu powder/H2O2 system in a neutral environment, which could be ascribed to the unique hierarchically porous structure of 3DHP-ZVC. Furthermore, 3DHP-ZVC exhibited compelling stability in 20 consecutive cycles. The effects of co-existing inorganic anions, adaptability, and pH resistance on the degradation of TC were also investigated. A series of experiments and characterizations revealed that Cu0 and superoxide radicals as reducing agents could facilitate the cycling of Cu(II)/Cu(I), thus enhancing the generation of hydroxyl radicals to degrade TC. This study provides new insights into employing promising 3D printing technology to develop high-reactivity, stable, and recycling-friendly components for wastewater treatment. [ABSTRACT FROM AUTHOR]

For the successful discovery and development of tight sand gas reserves, it is necessary to locate sand with certain features. These features must largely include a significant accumulation of hydrocarbons, rock physics models, and mechanical properties. However, the effective representation of such reservoir properties using applicable parameters is challenging due to the complicated heterogeneous structural characteristics of hydrocarbon sand. Rock physics modeling of sandstone reservoirs from the Lower Goru Basin gas fields represents the link between reservoir parameters and seismic properties. Rock physics diagnostic models have been utilized to describe the reservoir sands of two wells inside this Middle Indus Basin, including contact cement, constant cement, and friable sand. The results showed that sorting the grain and coating cement on the grain's surface both affected the cementation process. According to the models, the cementation levels in the reservoir sands of the two wells ranged from 2% to more than 6%. The rock physics models established in the study would improve the understanding of characteristics for the relatively high Vp/Vs unconsolidated reservoir sands under study. Integrating rock physics models would improve the prediction of reservoir properties from the elastic properties estimated from seismic data. The velocity–porosity and elastic moduli-porosity patterns for the reservoir zones of the two wells are distinct. To generate a rock physics template (RPT) for the Lower Goru sand from the Early Cretaceous period, an approach based on fluid replacement modeling has been chosen. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and the P-impedance template can detect cap shale, brine sand, and gas-saturated sand with varying water saturation and porosity from wells in the Rehmat and Miano gas fields, both of which have the same shallow marine depositional characteristics. Conventional neutron-density cross-plot analysis matches up quite well with this RPT's expected detection of water and gas sands. [ABSTRACT FROM AUTHOR]

The complex t-spherical fuzzy set (Ct-SFS) is a potent tool for representing fuzziness and uncertainty compared to the picture fuzzy sets and spherical fuzzy sets. It plays a key role in modeling problems that require two-dimensional data. The present study purposes the aggregation technique of Ct-SFSs with the aid of Aczel–-Alsina (AA) operations. We first introduce certain novel AA operations of Ct-SFSs, such as the AA sum, AA product, AA scalar multiplication, and AA scalar power. Subsequently, we propound a series of complex t-spherical fuzzy averaging and geometric aggregation operators to efficiently aggregate complex t-spherical fuzzy data. In addition, we explore the different characteristics of these operators, discuss certain peculiar cases, and prove their fundamental results. Thereafter, we utilize these operators and propose entropy measures to frame a methodology for dealing with complex t-spherical fuzzy decision-making problems with unknown criteria weight data. Finally, we provide a case study about vehicle model selection to illustrate the presented method's applicability followed by a parameter analysis and comparative study. [ABSTRACT FROM AUTHOR]

Apart from being emission-free, electric vehicles enjoy benefits such as low maintenance and operating costs, noise-free, easy to drive, and the convenience of charging at home. All these benefits are directly dependent on the performance of the battery used in the vehicle. In this paper, one-dimensional modeling of Li-ion and NiMH batteries was developed, and their performances were studied. The performance characteristics of the batteries, such as the charging and discharging characteristics, the constituent losses of over-potential voltage, and the electrolyte concentration profile at various stages of charge and discharge cycles, were also studied. It is found that the electrolyte concentration profiles of Li-ion batteries show a drooping behavior at the start of the discharge cycle and a rising behavior at the end of discharge because of the concentration polarization due to the low diffusion coefficient. The electrolyte concentration profiles of NiMH batteries show rising behavior throughout the discharge cycle without any deviations. The reason behind this even behavior throughout the discharge cycle is attributed to the reduced concentration polarization due to electrolyte transport limitations. It is found that the losses associated with the NiMH battery are larger and almost constant throughout the battery's operation. Whereas for the Li-ion batteries, the losses are less variable. The electrolyte concentration directly affects the overpotential losses incurred during the charging and discharging phases. [ABSTRACT FROM AUTHOR]

Grid-connected hybrid energy systems (HESs) represent a very promising option for addressing the problem of power outages worldwide. The selection of a suitable optimization approach and operational strategy are important aspects of the optimal design and operation of these HESs. This study aimed to find the optimal grid-connected PV/battery system sizes to supply electricity for a residential house in Karbala, Iraq, using two control strategies, load following (LF) and cycle charging (CC). The optimization was performed using HOMER software with and without the multi-year effects. The comparison analysis was carried out by considering the techno-economic and environmental performance of the feasible systems. The simulation results indicate that optimal configuration is achieved by using the CC strategy. Furthermore, the multi-year module affects the optimal results dramatically. Under the CC strategy, the multi-year effects increase the required PV size from 6 kW to 7 kW and the required number of batteries from 18 to 20, leading to an increase in the net present cost from $26,750 to $33,102 and a decrease in CO2 emissions from 7581 kg/year to 7379 kg/year. The results also show that the optimization results are highly affected by the variations of some critical parameters, such as solar radiation, average load, and battery degradation limits. The achievements indicate the higher effectiveness of the multi-year effects and control strategy on the optimal design of HESs. [ABSTRACT FROM AUTHOR]

Unreliable networks often use excess bandwidth for data integration in smart cities. For this purpose, Messaging Queuing Telemetry Transport (MQTT) with a certain quality of service (QoS) is employed. Data integrity and data security are frequently compromised for reducing bandwidth usage while designing integrated applications. Thus, for a reliable and secure integrated Internet of Everything (IoE) service, a range of network parameters are conditioned to achieve the required quality of a deliverable service. In this work, a QoS-0-based MQTT is developed in such a manner that the transparent MQTT protocol uses Transmission Control Protocol (TCP)-based connectivity with various rules for the retransmission of contents if the requests are not entertained for a fixed duration. The work explores the ways to improve the overall content delivery probability. The parameters are examined over a transparent gateway-based TCP network after developing a mathematical model for the proposed retransmission-based mutant QoS-0. The probability model is then verified by an actual physical network where the repeated content delivery is explored at VM-based MQTT, local network-based broker and a remote server. The results show that the repeated transmission of contents from the sender improves the content delivery probability over the unreliable MQTT-based Internet of Things (IoT) for developing smart cities' applications. [ABSTRACT FROM AUTHOR]

Iodine loss is common in the soil of hilly regions due to higher precipitation rates and steeper slopes. Iodine deficiency in soil reduces iodine's bioavailability to fruits and vegetables and consequently may contribute to health complications. However, the iodine retention of soils after the addition of selected organic and inorganic amendments has not been studied. Therefore, a study was carried out to investigate iodine loss during surface runoff. For this purpose, a soil amendment (namely, sawdust, charcoal, wood ash, lime or gypsum) was applied separately to pasture and agricultural soils under natural rainfall conditions. The soil was fertigated with iodine in the form of potassium iodide (KI) at the rate of 200 ppm. Surface runoff was related to soil properties. Results showed that iodine content in surface runoff was linearly related with soil pH (R2 = 0.89, p < 0.05) and inversely related with soil organic carbon (R2 = −0.76, p < 0.05). Soils amended with sawdust had significantly reduced iodine content in runoff. A higher amount of iodine was lost via surface runoff from soil after inorganic amendment. Soil amendments were varied for iodine retention in soil in the order of sawdust > charcoal > wood ash > lime > gypsum. The study results indicated that organic amendments, especially sawdust, improved soil properties and increased the iodine retention capacity of soils. [ABSTRACT FROM AUTHOR]

Solar stills are one of the low water production desalination systems, but its low yield makes it necessary to investigate different design and performance parameters to improve its productivity. This paper aims to perform a parametric analysis of a solar still desalination system and study the effect of different absorber materials on the performance of a single-slope solar desalination unit employing computational fluid dynamics (CFD) numerical simulation via COMSOL® Multiphysics software. To consider the absorptivity of water with different absorbing materials, simulation was conducted with the application of effective emissivity for the solar still walls. In addition, the economic, exergoeconomic, and CO2 mitigation of solar stills were studied. The results revealed that the hourly water output of the solar desalination unit, with different absorbing materials (black ink, black dye, and black toner), reached the maximum values at 1:00 PM. On comparing the simulation results of solar stills with and without absorbing materials, it has been observed that the solar still painted with black toner shows the highest improvement in hourly productivity, the exergy of evaporation, and evaporative heat transfer coefficient with a maximum increase in respective values by 10.52%, 13.68% and 5.37%. The CO2 mitigation and enviroeconomic parameter of the solar still using black toner were equal to 31.4 tons and 455.3 USD, respectively. Moreover, the lowest cost per liter (CPL) of the solar still was obtained using black toner, which was about 0.0066 USD/L. [ABSTRACT FROM AUTHOR]

Titanium has been one of the traditional metals used in the medical industry since 1940. This work modeled and simulated a hip-joint replacement implant using Creo 5.0 and DEFORM 3D (v11.0), respectively. Four titanium-based billets were modeled; out of four billets, three billets were coated with a specified thickness, and one was uncoated. Among the three coated billets, one billet was coated with a 500-micron and two billets coated with a 1000-micron thickness. At the end of the simulation, the coating materials formed patches on the surface of the forged parts. The coating material Ti-6Al-4V (high O2) produced excellent mechanical properties in contrast to the CP-Ti material, which displayed low mechanical properties and did not match the core property. Hence, it was suggested to provide a bulk coating of Ti-6Al-4V (high O2) on the billet to improve the physio-mechanical properties and biocompatibility. Four points were selected on the surface of the forged parts at different locations for identifying the property variations concerning forging time. Results found that coating thickness required more on the side surface of the billet material than on the upper and lower surfaces to enhance its properties. [ABSTRACT FROM AUTHOR]

Solar desalination is a sustainable approach to producing fresh water from saline water. Researchers have tried modifications to solar desalination systems to enhance the distillate output. This survey aims to recognize the characteristics of research work for investigating solar desalination systems. The essential terms to be focused on are computational fluid dynamics (CFD) and solar radiation consideration for the investigation. The data for this bibliometric study was taken from Scopus, with 1932 publications. The characteristics of the research work were analyzed by identifying the research publications, research subject areas, journals, most contributed countries, and data from the authors. The research trend was investigated utilizing yearly research growth, geographical contributions, source quality of publications, and participation of various institutions. VOSviewer software was used for network analysis of essential keywords used in relevant research works and to understand collaborations between the authors and co-authors. About 76% of the total publications belong to the document type articles. It illuminates research tendencies related to the topic under consideration. Results show that desalination research work concerned with CFD or solar radiation was mainly investigated in Engineering and Environmental Science, with their share of more than 50% of the total publications. Further study of relevant research works was assessed using network analysis that helped to link different keywords and authors' collaborations. This survey helps to spot the increasing research trends and the necessity of further research. [ABSTRACT FROM AUTHOR]

Hybrid energy systems (HESs) consisting of both conventional and renewable energy sources can help to drastically reduce fossil fuel utilization and greenhouse gas emissions. The optimal design of HESs requires a suitable control strategy to realize the design, technical, economic, and environmental objectives. The aim of this study is to investigate the optimum design of a grid-connected PV/battery HES that can address the load requirements of a residential house in Iraq. The MATLAB Link in the HOMER software was used to develop a new dispatch strategy that predicts the upcoming solar production and electricity demand. A comparison of the modified strategy with the default strategies, including load following and cycle charging in HOMER, is carried out by considering the techno-economic and environmental perspectives. According to optimization studies, the modified strategy results in the best performance with the least net present cost (USD 33,747), unmet load (87 kWh/year), grid purchases (6188 kWh/year), and CO2 emission (3913 kg/year). Finally, the sensitivity analysis was performed on various critical parameters, which are found to affect the optimum results on different scales. Taking into consideration the recent advocacy efforts aimed at achieving the sustainable development targets, the models proposed in this paper can be used for a similar system design and operation planning that allow a shift to more efficient dispatch strategies of HESs. [ABSTRACT FROM AUTHOR]

The present study aimed to assess the relationship of soil properties in salt-affected soils. The soil samples were collected from 14 districts of Pakistan. Soil salinity and sodicity are the common features of the arid and semiarid regions. The effects of the salt's interactions with soil micronutrients have not been well studied. Therefore, saline and non-saline soil samples were collected from different locations. The microelements (Fe, Cu, Mn, and Zn) were fractionated into water-soluble, exchangeable, carbonate, Fe + Mn oxide, organic, and residual fractions. Univariate and multivariate analysis (PCA) was carried out to determine the linear relationship between soil properties and micronutrients fractions. Results showed that the magnitude of micronutrients appeared to be affected by the salinity in soils. In saline soil, the Fe fractions differed in the order of residual > organic bound > Fe + Mn bound > carbonate bound > exchangeable > water soluble. Iron fractions varied in the non-saline soils as residual > Fe + Mn bound > organic bound > exchangeable > carbonate bound > water soluble. Copper concentration was higher in the residual and carbonate forms, and the amount was lower in the exchangeable and water-soluble forms under both saline and non-saline conditions. The water-soluble Mn fraction was lower, and the residual Mn fraction was proportionately higher than other forms of Mn in soils. Zinc was found mostly in the residual fraction in both saline and non-saline soils. The mobility factor of micronutrients in non-saline soil was greater than in saline soil. PCA revealed that organic matter (OM) and pH directly affected the fractionation of Cu, Mn, Zn, and Fe in soil. Thus, it could be inferred that salts can bring changes to the composition of micronutrients depending on the nature of the soil and the magnitude of salts. [ABSTRACT FROM AUTHOR]

Drought stress restricts the growth of okra (Abelmoschus esculentus L.) primarily by disrupting its physiological and biochemical functions. This study evaluated the role of Ascophyllum nodosum extract (ANE) in improving the drought tolerance of okra. Drought stress (3 days (control), 6 days (mild stress), and 9 days (severe stress)) and 4 doses of ANE (0, 0.1%, 0.2%, and 0.3%) were imposed after 30 days of cultivation. The results indicate that drought stress decreases the chlorophyll content (total chlorophyll, chlorophyll a, chlorophyll b, and carotenoid) but increases the activity of anthocyanin, proline, and antioxidant enzymes such as ascorbate peroxidase (APX), peroxidase (POD), and catalase (CAT). Physiological and biochemical plant disturbances and visible growth reduction in okra under drought stress were significantly decreased by the application of ANE foliar spray. ANE spray (0.3%) significantly increased the chlorophyll abundance and activity of anthocyanin, proline, and antioxidants (APX, POD, and CAT). ANE regulated and improved biochemical and physiological functions in okra under both drought and control conditions. The results of the current study show that ANE foliar spray may improve the growth performance of okra and result in the development of drought tolerance in okra. [ABSTRACT FROM AUTHOR]

Making decisions are very common in the modern socio-economic environments. However, with the increasing complexity of the social, today's decision makers (DMs) face such problems in which they hesitate and irresolute to provide their views. To cope with these uncertainties, many generalizations of fuzzy sets are designed, among them dual hesitant fuzzy set (DHFS) is quite resourceful and efficient in solving problems of a more vague nature. In this article, a novel concept called proportional dual hesitant fuzzy set (PDHFS) is proposed to further improve DHFS. The PDHFS is a flexible tool composed of some possible membership values and some possible non-membership values along with their associated proportions. In the theme of PDHFS, the proportions of membership values and non-membership values are considered to be independent. Some basic operations, properties, distance measure and comparison method are studied for the proposed set. Thereafter, a novel approach based on PDHFSs is developed to solve problems for multi-attribute group decision-making (MAGDM) in a fuzzy situation. It is totally different from the traditional approach. Finally, a practical example is given in order to elaborate the proposed method for the selection of the best alternative and detailed comparative analysis is given in order to validate the practicality. [ABSTRACT FROM AUTHOR]

Electric cars (EVs) are getting more and more popular across the globe. While comparing traditional utility grid-based EV charging, photovoltaic (PV) powered EV charging may significantly lessen carbon footprints. However, there are not enough charging stations, which limits the global adoption of EVs. More public places are adding EV charging stations as EV use increases. However, using the current utility grid, which is powered by the fossil fuel basing generating system, to charge EVs has an impact on the distribution system and could not be ecologically beneficial. The current electric vehicle (EV) market, technical requirements including recent studies on various topologies of electric vehicle/photovoltaic systems, charging infrastructure as well as control strategies for Power management of electric vehicle/photovoltaic system., and grid implications including electric vehicle and Plug-in hybrid electric vehicles charging systems, are all examined in depth in this paper. The report gives overview of present EV situation as well as a thorough analysis of significant global EV charging and grid connectivity standards. Finally, the challenges and suggestions for future expansion of the infrastructure of EV charging, grid integration, are evaluated and summarized. It has been determined that PV-grid charging has the ability to create a profit. However, due to the limited capacity of the PV as well as the batteries, the Power system may not be cost effective. Furthermore, since PV is intermittent, it is probable that it will not be able to generate enough electricity to meet consumer demand. [ABSTRACT FROM AUTHOR]

The classical matrix theory is deficient to express the vagueness of the real life. The fuzzy set theory has been successfully applied to bridge this gap. Much work has already been done on a two-person zero sum matrix game with fuzzy goals. In continuation, this paper is dedicated to define and study a multi-criteria two-person zero sum game with intuitionistic fuzzy goals. It is shown that solving such games is equivalent to solving two crisp multi object linear programming problems. Our work generalizes the previous study on a multi-criteria game with fuzzy goals by adopting the approach of linear programming with intuitionistic fuzzy sets. Finally, an illustrative numerical example is provided to elaborate the proposed approach. [ABSTRACT FROM AUTHOR]

This study investigated the ability of a HYDRUS 1D model for predicting the vertical distribution of potassium iodine (200 ppm) in soil columns after amendment with five different common remediation materials (gypsum, lime, fly ash, charcoal, and sawdust) at a rate of 2.5% (w/w), relative to an unamended control soil. Results showed that relative to the unamended soil, iodine leaching was decreased by all amendments but that the magnitude of the decreases varied with the soil amendment applied. Iodine content was highest in the upper layer of the soil columns and decreased progressively with soil depth. The model was evaluated via comparison of the model simulated values with measured values from the soil column studies. The results showed that the HYDRUS 1D model efficiency was near to 1, indicating the stimulated results near to the measured values. Therefore, this study showed that iodine leaching through a soil could be ascertained well using a HYDRUS 1D model. The model over predicted iodine leaching, results in a weak correspondence between the simulated and the measured results for iodine leaching. This suggests that the HYDRUS-1D model does not explain accurately different organic and inorganic amended soil and the preferential flow that occurs in these columns. This may be due to the fact that Freundlich isotherm, which is part of the transport equations, does not sufficiently describe the mechanism of iodine adsorption onto the soil particles. This study would help to select an amendment for an effective management strategy to reduce exogenous iodine losses from agro-ecosystems. This would also improve scientific understanding of iodine transport in soil profile. [ABSTRACT FROM AUTHOR]

Decision making is the key component of people's daily life, from choosing a mobile phone to engaging in a war. To model the real world more accurately, probabilistic linguistic term sets (PLTSs) were proposed to manage a situation in which several possible linguistic terms along their corresponding probabilities are considered at the same time. Previously, in linguistic term sets, the probabilities of all linguistic term sets are considered to be equal which is unrealistic. In the process of decision making, due to the vagueness and complexity of real life, an expert usually hesitates and unable to express its opinion in a single term, thus making it difficult to reach a final agreement. To handle real life scenarios of a more complex nature, only membership linguistic decision making is unfruitful; thus, some mechanism is needed to express non-membership linguistic term set to deal with imprecise and uncertain information in more efficient manner. In this article, a novel notion called probabilistic hesitant intuitionistic linguistic term set (PHILTS) is designed, which is composed of membership PLTSs and non-membership PLTSs describing the opinions of decision makers (DMs). In the theme of PHILTS, the probabilities of membership linguistic terms and non-membership linguistic terms are considered to be independent. Then, basic operations, some governing operational laws, the aggregation operators, normalization process and comparison method are studied for PHILTSs. Thereafter, two practical decision making models: aggregation based model and the extended TOPSIS model for PHILTS are designed to classify the alternatives from the best to worst, as an application of PHILTS to multi-attribute group decision making. In the end, a practical problem of real life about the selection of the best alternative is solved to illustrate the applicability and effectiveness of our proposed set and models. [ABSTRACT FROM AUTHOR]