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Tissue regeneration in many skin defects is progressing with new treatments in recent years. Tissue engineering with the use of scaffolds offers more versatile and faster solutions in treatment. Extracellular matrix (ECM) and its three-dimensional (3D) network structure as a biological bond by imitating the tissue microstructure has been used for tissue repair, which can answer many existing challenges. Vitamin A, which comes in several forms such as retinols, retinals, and retinoic acids, is a necessary vitamin that is crucial for wound healing. In this research, sheep kidney capsule tissue decellularized with sodium dodecyl sulfate (SDS) containing different doses of vitamin A has been used as an ECM in skin tissue engineering. The above scaffold was evaluated in terms of properties such as biocompatibility, analysis of mechanical properties, attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), hydrophilicity, antibacterial, and cell adhesion. The findings reported suitable properties for wound dressing, especially at a dose of 15,000 U/ml vitamin A for this scaffold. Then, the above scaffold was evaluated on the full-thickness wound model in rat, which showed good wound contraction, and increased VEGF factor. It showed a decrease in IL-1β level. Therefore, the use of the above-mentioned decellularized scaffold in combination with medicinal agents effective in wound healing can be introduced for further pre-clinical studies.

Mental illness is a common disease that at its extremes leads to personal and societal suffering. A complicated multi-factorial disease, mental illness is influenced by a number of socioeconomic and clinical factors, including individual risk factors. Traditionally, approaches relying on personal interviews and filling out questionnaires have been employed to diagnose mental illness; however, these manual procedures have been found to be frequently prone to errors and unable to reliably identify individuals with mental illness. Fortunately, people with mental illnesses frequently express their ailments on social media, making it possible to more precisely identify mental disease by harvesting their social media posts. This study offers a thorough analysis of how to identify mental illnesses (more specifically, depression) from users’ social media data. Along with the explanation of data acquisition, preprocessing, feature extraction, and classification techniques, the most recent published literature is presented to give the readers a thorough understanding of the subject. Since, in the recent past, the majority of the relevant scientific community has focused on using machine learning (ML) and deep learning (DL) models to identify mental illness, so the review also focuses on these techniques and along with their detail, their critical analysis is presented. More than 100 DL, ML, and natural language processing (NLP) based models developed for mental illness in the recent past have been reviewed, and their technical contributions and strengths are discussed. There exist multiple review studies, however, discussing extensive recent literature along with the complete road map on how to design a mental illness detection system using social media data and ML and DL classification methods is limited. The review also includes detail on how a dataset may be acquired from social media platforms, how it is preprocessed, and features are extracted from it to employ for mental illness detection. Hence, we anticipate that this review will help readers learn more and give them a comprehensive road map for identifying mental illnesses using users’ social media data.

Purpose: This systematic review examines extant literature to understand the relationship between e-governance initiatives and citizen participation. Design/Methodology/Approach: We conducted a systematic review of 72 articles published in interdisciplinary journals indexed in the Web of Science database between 1900 and 2024. This review examined various forms of e-governance, including digital platforms, official websites, mobile apps, social media, and open data portals Findings: This review revealed the evolution of e-governance from basic online services to sophisticated digital governance utilizing AI and data science. While e-governance initiatives hold promise for increased citizen participation, transparency, and accountability in policymaking, several factors influence their success, including technological infrastructure, digital literacy, trust in government, and legal frameworks. This study identified gaps in the current knowledge base, particularly regarding the long-term sustainability and impact of these initiatives. Implications/Originality/Value: These findings highlight the need for interdisciplinary research to better understand and evaluate the effectiveness of citizen-empowering e-governance initiatives. This study provides a structured overview of existing knowledge, pinpoints open research questions, and suggests a unified model for future research in this area.

In this article, we implemented the idea of a fuzzy interval-valued function with the well-known generalized fuzzy fractional operators, associated with different types of convexities and preinvexities. We developed the Prabhakar fuzzy fractional operators using the fuzzy interval-valued function. We presented the novel extensions of Hermite-Hadamard fuzzy-type and trapezoidal fuzzy-type inequalities, based on the $ h $-Godunova-Levin convex and $ h $-Godunova preinvex fuzzy interval-valued functions.

This study presents a sustainable method for producing iron oxide nanoparticles (FeO NPs) using aqueous extracts from coffee seeds. Characterization through X-ray diffraction (XRD), scanning electron microscopy, and transmission electron microscopy (TEM) revealed non-spherical NPs ranging from 30 to 50 nm. The XRD analysis confirmed that the face-centred cubic structure and the Debye–Scherrer’s crystalline size support the FeO particle size confirmed from TEM. The synthesized NPs demonstrated significant antimicrobial activity against Escherichia coli and Staphylococcus aureus, as well as antifungal activity against Aspergillus niger. Additionally, they exhibited potent antioxidant properties, effectively inhibiting DPPH, α-amylase, and α-glucosidase compared to acarbose and coffee extract. The findings suggest that these FeO NPs hold promise as antimicrobial, antioxidant, antifungal, and potentially antidiabetic agents.

Objective: To compare peri and early post-operative complications in long versus short proximal femoral nails for unstable proximal femoral fractures. Study Design: Quasi-experimental study. Place and Duration of Study: Orthopaedic Department, Combined Military Hospital, Lahore Pakistan, Jan to Sep 2021. Methodology: We included all the patients who suffered from unstable proximal femur fractures diagnosed by a consultant orthopedic surgeon based on clinical and radiological findings. They were randomly divided into two groups. Group-A was managed by a long proximal femoral nail, while Group-B was managed by a short proximal femoral nail. Both groups were compared for peri- and early post-operative complications. Results: The final analysis included 110 patients. The mean age of the study participants was 63.66±8.553 years. 79(71.8%) were male, while 31(28.2%) were female. Peri- and early post-operative complications were not statistically different in both groups except for the duration of surgery. Patients undergoing long proximal femoral nail fixation had more chances of having surgery lasting more than 40 minutes than patients undergoing short femoral nail fixation (p-value-0.004). Conclusion: The peri- and early post-operative complications rate was almost similar in both groups. Patients undergoing long proximal femoral nail fixation had more chances of having prolonged surgery than patients undergoing short femoral nail fixation.

Objective: The aim of our study was to investigate the relationship between clinical indicators and gene dysregulation in different types of epilepsy, while also seeking to identify a diagnostic model capable of distinguishing between focal and generalized seizures. This highlights the critical importance of understanding clinical indicators and gene dysregulation for targeted therapeutic interventions to effectively address the specific seizure types effectively. Materials and methods: In this study, we conducted a comprehensive analysis of the peripheral blood of epilepsy patients (n = 100) and a control group (n = 51) to determine the differential gene expression. Our analysis involved a range of statistical approaches, including correlation analysis to establish the association between clinical indicators and gene dysregulation, and principal component analysis to highlight distinct disease group from control group. Furthermore, we developed diagnostic models using logistic regression to aid in the accurate diagnosis of epilepsy. Results: Among several selected genes in this study such as AVP (AUC = 0.832, p

Reconfigurable intelligent surfaces (RIS) have been developed to exploit the stochastic characteristics of the propagation environment for next generation wireless systems. On the other hand, the integration of wireless physical network coding (PNC) and multiple antennas yields notable enhancements in system performance. This paper presents a multiuser system, employing RIS enabled PNC alongside multiple antennas to minimize both delay and error probability. Our aim is to establish reliable communication between the user pairs, which communicate through a base station (BS) via RIS. Therefore, the reflecting coefficients including both phases and amplitudes of the RIS are optimized by using the alternating direction method of multipliers (ADMM) algorithm for both single and multiple RIS cases. Extensive results are presented to compare the proposed algorithm with random phase shift, network coding (NC) and the search algorithm to illustrate its superiority.

The fifth generation of wireless communication is anticipated to provide improved quality of service and enhanced data rates to the end users. One such technology that stands out as a potential transmission scheme for 5G systems is Filter Bank Multicarrier using Offset Quadrature Amplitude Modulation (FBMC/OQAM) with an effective channel estimation technique for improved performance. However, due to the inherent imaginary interference, channel estimation methods relying on preamble structures in FBMC/OQAM systems exhibit sub-optimal performance, particularly within Multiple-Input Multiple-Output (MIMO) setups. For channel estimation schemes based on compressed sensing, the inherent sparsity of wireless channels can be exploited for accurate channel reconstruction and overall performance improvement.We propose a novel compressed sensing based algorithm namely, Adaptive Refined Random Orthogonal Matching Pursuit (ARROMP), for MIMO-FBMC system with Coordinated MultiPoint (CoMP) scheduling. This algorithm adaptively selects a support set by utilizing a double threshold for the minimization of mean squared error and for accurate channel reconstruction. The proposed algorithm's performance is compared with existing Orthogonal Matching Pursuit (OMP) schemes such as random OMP, refined random OMP, and least square-based estimation. The numerical simulations suggest that the proposed adaptive algorithm provides performance improvement in terms of reduced Mean Squared Error (MSE) of channel reconstruction and Bit Error Rate (BER). Moreover, the proposed ARROMP algorithm for MIMO-FBMC is rigorously tested with CoMP scheduling for a cellular network using frequency division duplex mode. The proposed system presents significant improvements in throughput and spectral efficiency for all types of cell users, including cell-edge users. The simulation results validate the improved performance of the proposed algorithm with CoMP scheduling over the existing single-cell system with no coordination.

This empirical study investigates the effect of financial innovation and infrastructure on inbound tourism in Central Asia, along with trade openness as a control variable. This study developed an infrastructure index for Central Asia comprised of different parameters of infrastructure. The data has been assessed for cross-sectional dependence, unit root and coefficients of parameters were obtained by pooled mean group autoregressive distributed lagged model and simultaneous quantile regression. Results show that financial innovation and trade openness have a significant and positive effect on inbound tourism in the long run whereas infrastructure has an insignificant effect. Dynamic stability analysis confirms that the model of the study is stable and will adjust itself from any imbalance within three years of span. The results of quantile regression highlight that financial innovation is positively associated with tourism development in Central Asia irrespective of quantile (Q25, Q50, Q75). Policy implications are provided based on research findings.

Bassia indica (Wight) A.J. Scott is an Indian origin plant with documented medicinal and nutritional value, but has not been fully characterized yet. The present study was designed to establish pharmacognostic standards for the proper identification of the B. indica plant and its chemical characterization. The plant was standardized with World Health Organization (WHO) standardization tools and chemically characterized by Fourier transform infrared spectroscopy (FTIR) and gas chromatography-mass spectroscopy (GC-MS) analysis. Antibacterial potential was assessed by the zone of inhibition and minimum inhibitory concentration (MIC), and molecular docking studies were also performed. Pharmacognostic evaluation established the macroscopic and microscopic parameters for the identification of whole plant and its powder. Physicochemical parameters were also set forth while quantitative phytochemical analysis showed that the ethyl acetate fraction had the highest quantity of phenols, flavonoids, and tannins. FTIR analysis showed several functional groups such as phenols, alkanes, and alcohols while 55 phytochemicals were identified in the GC-MS analysis of the crude fraction. The crude extract and other fractions showed marked antibacterial activity, while the ethyl acetate fraction showed the least MIC (1.95–31.25 mg/mL). Phytochemicals identified in the GC-MS showed good molecular docking interactions against the DNA gyrase subunit B of bacteria with binding energies ranging from −4.2 to −9.4 kcal/mol. The current study describes the pharmacognostic characterization and phytochemical profiling of B. indica and provides scientific evidence to support its use in infections.

In the present work, the disk-shaped zinc oxide (ZnO) nanoparticles were synthesized and functionalized with β-cyclodextrin (β-CD) and nicotinic acid (vitamin B3) using the wet co-precipitation method. The functionalized ZnO/β-CD/nicotinic acid nanocomposite materials were characterized using UV-visible spectroscopy (UV-Vis), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), field emission electron microscopy (FESEM), and band-gap energy analysis. The band gap value (E g) was 4.3 eV. The average XRD crystallite size was determined using the Scherrer formula and was found to be 50 nm. The ZnO/β-CD/nicotinic acid nanocomposite material showed a photocatalytic effect for dye-polluted wastewater. It also showed an antibacterial effect against the Gram-positive bacterial strain Streptococcus aureus (S. aureus) but did not show any antibacterial activity with Gram-negative Escherichia coli (E. coli). The ZnO/β-CD/nicotinic acid nanocomposite also showed antifungal activity with Aspergillus niger (A. niger). It was noticed that ZnO/β-CD/nicotinic acid nanocomposite showed efficient anticancer activity with IC50 = 14.95 µg·mL−1 in MCF-7 cell lines. Because of the formation of singlet oxygen (O2˙−) and hydrogen oxide radical (–OH˙), the composite material showed a photodegradation reaction against aq. solution of methylene blue dye. After 190 min, the blue colour of aq. solution methylene blue was decolourized at 6 pH at a constant time interval.

The extension of interval-valued and real-valued functions known as fuzzy interval-valued function (FIVF) has made substantial contributions to the theory of interval analysis. In this article, we explore the importance of h-Godunova-Levin fuzzy convex and preinvex functions and also develop the new generation of the Hermite-Hadamard and trapezoid-type fuzzy fractional integral by the implementation of generalized fuzzy fractional operators having modified version of the Bessel-Maitland E1vBMF function as its kernel. Moreover, we extract some well-known inequalities from our main results.

Objective: To evaluate the functional outcome of unilateral peroneus longus autograft in arthroscopic anterior cruciate ligament reconstruction Study Design: Cross-sectional study. Place and Duration of Study: Orthopedic Department, Combined Military Hospital, Lahore Pakistan, from Jul 2020 to Jun 2021. Methodology: We included all the patients who underwent ipsilateral peroneus longus autograft for anterior cruciate ligament reconstruction. Fixation was achieved with a bio-absorbable screw on the tibial side and an endobutton on the femoral side. Lateral or medial menisectomy was performed according to the requirement. Post-op X-rays were done to assess the position of the endobutton and tibial tunnel. Eight millimetres tunnels were drilled, and the tendon was tailored accordingly. Results were assessed for pain, infection, range of motion and instability after three months of surgical procedure. Results: A total of 52 patients were included in the final analysis. The mean age of the study participants was 33.36±6.353 years. At the end of three months, pain 6(11.5%) and restricted range of motion 6(11.5%) were the common untoward outcomes reported by the patients. High body mass index and lack of engagement in physiotherapy had a statistically significant relationship with the presence of untoward outcomes in our study (p-value

Background: Leptadenia pyrotechnica Forssk. Decne is a member of family Apocynaceae and locally known as ‘Khipp’. It is found in dry, sandy habitat of Pakistan and in several other regions around the world including Asia, Tropical Africa, Western Gulf and Mediterranean countries. It has nutritional value, containing 4 % lipids, 23 % proteins, 28 % carbohydrates, 4 % fibers, vitamin E and several minerals. Traditionally, this plant has been used by several communities for pain, different inflammatory and kidney disorders. Ethno-botanical studies have reported the use of L. pyrotechnica in nephrolithiasis, kidney disorders and induction of diuresis, which requires a detailed pharmacological study to validate the folkloric use of L. pyrotechnica as diuretic. Methods: The 70 % methanolic L. pyrotechnica (Lp.Cr) extract was prepared and qualitatively checked for the presence of various phytochemicals. Phenolic, flavonoid, tannin and saponin contents were quantified. GC-MS analysis of Lp.Cr was also performed. Antioxidant potential of Lp.Cr was evaluated by DPPH, ABTS and nitrite radical scavenging assays. CUPRAC and FRAP assay described the reducing potential of Lp.Cr. Diuretic activity was performed in both acute and prolonged models at different doses followed by the estimation of electrolytes, urea and creatinine levels. The mechanism of diuresis was described by pre-treatment with atropine, l-NAME, indomethacin and carbonic anhydrase inhibition. Results: Lp.Cr. indicated high phenolic and flavonoid contents which correlated with good antioxidant activity. GC-MS analysis showed the presence of 104 compounds from different phytochemical classes. Diuretic activity was performed at 10–300 mg/kg concentrations where the dose of 100 and 300 mg/kg showed good diuretic and saluretic activity comparable to furosemide. Lp.Cr exhibited diuresis both in acute and prolonged study protocols which can be attributed to carbonic anhydrase inhibition, effect on prostaglandins and cholinergic pathways. Conclusion: L. pyrotechnica contained several phytochemicals and exhibited good antioxidant activity. It induced diuresis and saluretic activity which was comparable to furosemide at higher doses. Diuretic activity can be attributed to carbonic anhydrase inhibition, prostaglandin synthesis and cholinergic pathways.

Abstract The developments on next generation IoT sensing devices, with the advances on their low power computational capabilities and high speed networking has led to the introduction of the edge computing paradigm. Within an edge cloud environment, services may generate and consume data locally, without involving cloud computing infrastructures. Aiming to tackle the low computational resources of the IoT nodes, Virtual-Function-Chain has been proposed as an intelligent distribution model for exploiting the maximum of the computational power at the edge, thus enabling the support of demanding services. An intelligent migration model with the capacity to support Virtual-Function-Chains is introduced in this work. According to this model, migration at the edge can support individual features of a Virtual-Function-Chain. First, auto-healing can be implemented with cold migrations, if a Virtual Function fails unexpectedly. Second, a Quality of Service monitoring model can trigger live migrations, aiming to avoid edge devices overload. The evaluation studies of the proposed model revealed that it has the capacity to increase the robustness of an edge-based service on low-powered IoT devices. Finally, comparison with similar frameworks, like Kubernetes, showed that the migration model can effectively react on edge network fluctuations.

Abstract This paper aims the development of a new reduced-cost algorithm for a multi-objective robust transmitter placement under uncertainty. Toward this end, we propose a new hybrid Kriging/Grey Wolf Optimizer (GWO) approach combined with robust design optimization to estimate the set of Pareto frontier by searching robustness as well as accuracy (lower objective function) in a design space. We consider minimization of the energy power consumption for transmitting as well as maximization of signal coverage in a multi-objective robust optimization model. The reliability of the model to control signal overlap for multiple transmitting antennas is also provided. To smooth computational cost, the proposed method instead of evaluating all receiver test points in each optimization iteration approximates signal coverages using Kriging interpolation to obtain optimal transmitter positions. The results demonstrate the utility and the efficiency of the proposed method in rendering the robust optimal design and analyzing the sensitivity of the transmitter placement problem under practically less-expensive computational efforts (350% and 320% less than computational time elapsed using standalone GWO and NSGAII respectively).

Abstract The green internet of things with heterogeneous communication technologies can provide data transmission and computing services for low‐carbon operation of smart buildings. However, latency‐sensitive task offloading in smart buildings for multi‐mode green internet of things still faces several challenges such as coupling between multi‐mode channel and multiple gateway selection, diversified quality of service requirement guarantee, and contradiction of long‐term performance guarantee and short‐term optimisation objectives. To address these challenges, a three‐dimensional quota matching‐based latency‐sensitive task offloading algorithm is proposed to minimise the weighted difference between energy consumption and throughput under the long‐term queuing delay constraints. Specifically, the minimisation problem is decoupled by Lyapunov optimisation. The three‐dimensional quota matching among devices, gateways, and channels is employed to solve the conflicts between gateway selection and channel selection. Finally, the three‐dimensional quota matching is converted to a two‐side quota matching to further reduce complexity and solved iteratively. Numerical results demonstrate that compared with H3CG and MMCS, the proposed algorithm improves the weighted difference between energy consumption and throughput by 21.85% and 27.91%, respectively, and reduces the sensor‐side average queuing delay by 30.82% and 16.83%, and gateway‐side average queuing delay by 16.57% and 26.71%, respectively.

Context-awareness is a pervasive computing enabling technology that allows context-aware applications to respond to multiple contexts such as activity, location, temperature, and so on. When many users attempt to access the same context-aware application, user conflicts may emerge. This issue is emphasized, and a conflict resolution approach is presented to address it. Although there are other conflict resolution approaches in the literature, the one presented here is unique in that it considers the users’ special cases such as their sickness, examinations, and so on when resolving conflicts. The proposed approach is helpful when several users with different special cases try to access the same context-aware application. To demonstrate the usefulness of the proposed approach, a conflict manager is integrated with the UbiREAL simulated context-aware home environment. The integrated conflict manager resolves conflicts by taking users special cases into account and employing either automated, mediated, or hybrid conflict resolution approaches. The evaluation of the proposed approach demonstrates that users are satisfied with it and that it is critical and essential to employ users’ special cases in detecting and resolving users conflicts.

In recent years, integral inequalities are investigated due to their extensive applications in several domains. The aim of the paper is to investigate certain new fractional integral inequalities which include Hermite-Hadamard inequality and different forms of trapezoid type inequalities related to Hermite-Hadamard inequality for h-Godunova-Levin preinvex function. Moreover, we compare our obtained results with the existing work in the literature and are represented by corollaries.

The Ostrowski inequality expresses bounds on the deviation of a function from its integral mean. The Ostrowski’s type inequality is frequently used to investigate errors in numerical quadrature rules and computations. In this work, Ostrowski-type inequality is demonstrated using the generalized fractional integral operators. From an application perspective, we present the bounds of the fractional Hadamard inequalities. The results that are being presented involve a number of fractional inequalities that are already known and have been published.

In this paper, we describe generalized fractional integral operator and its inverse with generalized Bessel-Maitland function (BMF-Ⅴ) as its kernel. We discuss its convergence, boundedness, its relation with other well known fractional operators (Saigo fractional integral operator, Riemann-Liouville fractional operator), and establish its integral transform. Moreover, we have given the relationship of BMF-Ⅴ with Mittag-Leffler functions.

The main goal of this paper is to describe the new version of extended Bessel–Maitland function and discuss its special cases. Then, using the aforementioned function as their kernels, we develop the generalized fractional integral and differential operators. The convergence and boundedness of the newly operators and compare them with the existing operators such as the Saigo and Riemann–Liouville fractional operators are explored. The integral transforms of newly defined and generalized fractional operators in terms of the generalized Fox–Wright function are presented. Additionally, we discuss a few exceptional cases of the main result.

Pakistan’s is relentlessly affected by climate change and is looking for foreign assistant to deal with climate change challenges. Also, Pakistan is trying to tackle with climate change domestically. Environmental degradation consequently leads to climate change domestically as well as globally. Environmental degradation is extensively studied in empirical literature. Efficient use of resources only can ensure to lessen environmental degradation and its effects in terms of climate change. Henceforth, the current empirical study is analyzing the impact of energy intensity and financial institutions efficiency on environmental degradation in Pakistan. The energy intensity is considered as a factor of environmental degradation as it is one of the proxy for energy efficiency. Moreover, for overall economic activities impact on environmental degradation, this study considered GDP as a control variable. The time series techniques such as unit root and bounds cointegration techniques are applied for non-stationarity, cointegration and results estimates. The result of this study documented that energy intensity, financial institutions efficiency and GDP are factors of environmental degradation and energy intensity and GDP are aggravating environmental degradation whereas financial institutions efficiency has abstained it in Pakistan.

The analgesic efficacy of the gabapentin-tramadol combination was compared with meloxicam-tramadol and tramadol perioperative analgesic regimens in cats brought to the clinic for ovariohysterectomy. Thirty adult cats belonging to comparable demographics (age, body weight), were enrolled into a randomized, blinded study after due consent from their owners into four treatment groups. A Gabapentin-Tramadol group (GT-group, n = 10), Meloxicam-Tramadol group (MT-group, n = 10), and a Tramadol group (T-group, n = 10) were formed. Gabapentin capsules at 50 mg were administered orally 2 hours before surgery while the rest received a placebo dose. Tramadol (2 mg/kg, IM) and meloxicam at (0.2 mg/kg, SC) were injected immediately prior to anesthetic premedication. Anesthetic protocol involved premedication with ketamine and xylazine, while anesthesia was induced using propofol. Inhalant isoflurane anesthesia was used to maintain a surgical plane. GT group scored lower on IVAS as well as CPS than MT group, and T group for up to 8 hours after surgery. The mechanical nociceptive threshold remained higher (98±0) for up to 12 hours postoperatively a nd serum cortisol concentrations remained significantly lower during the 24hr period. The addition of gabapentin to the tramadol regimen significantly improved analgesia and mechanical nociceptive threshold than when used on its own.

Military sociology being a special discipline has resulted in establishment of a permanent study group with contributors in shape of academic scholars and military officers. Based on the works of military profession theorists, modern militaries have adopted a more flexible and technologically advanced outlook with emphasis on professionalism through training, education, mentoring and ethics in order to address and live upto the challenges of 21st century. In these changing and testing times one resounding constant has emerged in the shape of human being and his will to fight as a single most determining factor between winning and losing.

A gearbox is a critical rotating component that is used to transmit torque from one shaft to another. This paper presents a data-driven gearbox fault diagnosis system in which the issue of variable working conditions namely uneven speed and the load of the machinery is addressed. Moreover, a mechanism is suggested that how an improved feature extraction process and data from multiple tasks can contribute to the overall performance of a fault diagnosis model. The variable working conditions make a gearbox fault diagnosis a challenging task. The performance of the existing algorithms in the literature deteriorates under variable working conditions. In this paper, a refined feature extraction technique and multitask learning are adopted to address this variability issue. The feature extraction step helps to explore unique fault signatures which are helpful to perform gearbox fault diagnosis under uneven speed and load conditions. Later, these extracted features are provided to a convolutional neural network (CNN) based multitask learning (MTL) network to identify the faults in the provided gearbox dataset. A comparison of the experimental results of the proposed model with that of several already published state-of-the-art diagnostic techniques suggests the superiority of the proposed model under uneven speed and load conditions. Therefore, based on the results the proposed approach can be used for gearbox fault diagnosis under uneven speed and load conditions.

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its successful integration and scalability within 5G and beyond, massive MIMO has proven its merits and adaptability. Notably, a series of evolutionary advancements and revolutionary trends have begun to materialize in recent years, envisioned to redefine the landscape of future 6G wireless systems and networks. In particular, the capabilities and performance of future massive MIMO systems will be amplified through the incorporation of cutting-edge technologies, structures, and strategies. These include intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), Terahertz (THz) communications, and cell-free architectures. In addition, an array of diverse applications built on the foundation of massive MIMO will continue to proliferate and thrive. These encompass wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, and inter-planetary communications, among others.

In this paper, we investigate the relation of generalized Meijer G-functions with some other special functions. We prove the generalized form of Laguerre polynomials, product of Laguerre polynomials with exponential functions, logarithmic functions in terms of generalized Meijer G-functions. The generalized confluent hypergeometric functions and generalized tricomi confluent hypergeometric functions are also expressed in terms of the generalized Meijer G-functions.

The recent increase in the use of graphene and its derivatives is due to their exceptional physicochemical, electrical, mechanical, and thermal properties as the industrial materials developed by involving graphene structures can fulfill future needs. In that view, the potential use of these graphene-containing nanomaterials in electronics applications has encouraged in-depth exploration of the electronic, conducting, and other functional properties. The protecting undifferentiated form of graphene has similarly been proposed for various applications, for example, as supercapacitors, photovoltaic and transparent conductors, touch screen points, optical limiters, optical frequency converters, and terahertz devices. The hybrid composite nanomaterials that undergo stimulus-induced optical and electrical changes are important for many new technologies based on switchable devices. As a two-dimensional smart electronic material, graphene has received widespread attention, and with that view, we aim to cover the various types of graphene oxide (GO)-based composites, linking their optical and electrical properties with their structural and morphological ones. We believe that the topics covered in this review can shed light on the development of high-yield GO-containing electronic materials, which can be fabricated as the field moves forward and makes more significant advances in smart optoelectronic devices.

The main goal of this paper is to develop the significance of generalized fractional integral inequalities via convex functions. We obtain the new version of fractional integral inequalities with the extended Wright generalized Bessel function acting as a kernel for the convex function, which deals with the Hermite-Hadamard type and trapezoid type inequalities. Moreover, we establish new mid-point type and trapezoid type integral inequalities for (η1,η2)-convex function related to Hermite-Hadamard type inequality. We establish new version of integral inequality for (η1,η2)-convex function related to Fejér type. The results discussed in this paper are a generalized version of many inequalities in literature.

Polyester is a popular class of material used in material engineering. With its 0.4% moisture regain, polyethylene terephthalate (PET) is classified as highly hydrophobic, which originates from its lack of polar groups on its backbone. This study used a parallel-plate nonthermal plasma dielectric barrier discharge system operating at medium pressure in dry air and nitrogen (N2) to alter the surface properties of PET fabrics to increase their hydrophilic capabilities. Water contact angle, atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS) were utilized to analyze any effect from the plasma treatment. The wettability analysis revealed a reduction in the contact angle of more than 80% within 5 min for both discharges. Scanning electron microscopy analysis showed no microscopic damage to the fiber structure, guaranteeing that the fabrics’ structural integrity was preserved after treatment. AFM analysis showed an increase in the nanometer roughness, which was considered beneficial because it increased the total surface area, further increasing the hydrophilic capacity. XPS analysis revealed a sharp increase in the presence of polar functional groups, indicating that the induced surface changes are mostly chemical in nature. Comparing that of untreated fabrics to treated fabrics, a Increase in water absorption capacity was observed for air-treated and N2-treated fabrics, when these fabrics were used immediately after plasma exposure.

In this work, we apply generalized Saigo fractional differential and integral operators having k-hypergeometric function as a kernel, to extended Lommel-Wright function. The results are communicated in the form of the k-Wright function and are utilized to compute beta transform. The novelty and the generalization of the obtained results are shown by relating them with existing literature as special cases.

Abstract At present, voice biometrics are commonly used for identification and authentication of users through their voice. Voice based services such as mobile banking, access to personal devices, and logging into social networks are the common examples of authenticating users through voice biometrics. In Pakistan, voice-based services are very common in banking and mobile/cellular sector, however, these services do not use voice features to recognize customers. Therefore, the chance to use these services with false identity is always high. It is essential to design a voice-based recognition system to minimize the risk of false identity. In this paper, we developed regional voice datasets for voice biometrics, by collecting voice data in different local accents of Pakistan. Although, there is a global need for voice biometrics especially when voice-based services are common, however, this paper uses Pakistan as a use case to show how to build regional voice dataset for voice biometrics. To build voice dataset, voice samples were recorded from 180 male and female speakers with two languages English and Urdu in form of five regional accents. Mel Frequency Cepstral Coefficient (MFCC) features were extracted from the collected voice samples to train Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF) and K-nearest neighbor (KNN) classifiers. The results indicate that ANN outperformed SVM, RF and KNN by achieving 88.53% and 86.58% recognition accuracy on both datasets respectively.

In this article, we establish the inequalities of the Redheffer-type involving generalized Fox-Wright function. Furthermore, as a consequence, new Redheffer-type inequalities for generalized hypergeometric functions and the four-parametric generalized Mittag-Leffler functions are also discussed by using the suitable values of exponents in generalized inequalities.

Bessel function has a significant role in fractional calculus having immense applications in physical and theoretical approach. Present work aims to introduce fractional integral operators in which generalized multi-index Bessel function as a kernel, and develop some important special cases which are connected with fractional operators in fractional calculus. Here, we construct important links to familiar findings from some individual occurrence with our key outcomes.

Integral inequalities play a key role in applied and theoretical mathematics. The purpose of inequalities is to develop mathematical techniques in analysis. The goal of this paper is to develop a fractional integral operator having a non-singular function (generalized multi-index Bessel function) as a kernel and then to obtain some significant inequalities like Hermit Hadamard Mercer inequality, exponentially (s−m)-preinvex inequalities, Pólya-Szegö and Chebyshev type integral inequalities with the newly developed fractional operator. These results describe in general behave and provide the extension of fractional operator theory (FOT) in inequalities.

Objective: To evaluate the in-hospital outcome of moderate to severe COVID-19 patients admitted in High Dependency Unit (HDU) in relation to invasive vs. non-invasive mode of ventilation. Methods: In this study, the patients required either non-invasive [oxygen ≤10 L/min or >10 L/min through mask or nasal prongs, rebreather masks and bilevel positive airway pressure (BiPAP)] or invasive ventilation. For analysis of 30-day in hospital mortality in relation to use of different modes of oxygen, Kaplan Meier and log rank analyses were used. In the end, independent predictors of survival were determined by Cox regression analysis. Results: Invasive ventilation was required by 15.1% patients while 84.9% patients needed non-invasive ventilation. Patients with evidence of thromboembolism, high inflammatory markers and hypoxemia mainly required invasive ventilation. The 30-day in hospital mortality was 72.7% for the invasive group and 12.9% for the non-invasive group (1.8% oxygen 10 L/min, 3.6% rebreather mask and 4.5% BiPAP). The median time from hospital admission to outcome was 7 days for the invasive group and 18 days for the non-invasive group (P

In this paper, we discuss the extended generalized multi-index Bessel function by using the extended beta type function. Then we investigate its several properties including integral representation, derivatives, beta transform, Laplace transform, Mellin transforms, and some relations of extension of extended generalized multi-index Bessel function (E1GMBF) with the Laguerre polynomial and Whittaker functions. Further, we also discuss the composition of the generalized fractional integral operator having Appell function as a kernel with the extension of extended generalized multi-index Bessel function and establish these results in terms of Wright functions.

The principal aim of this paper is to introduce $\mathtt{k}$-fractional derivative operator by using the definition of $\mathtt{k}$-beta function. This paper establishes some results related to the newly defined fractional operator such as the Mellin transform and the relations to $\mathtt{k}$-hypergeometric and $\mathtt{k}$-Appell's functions. Also, we investigate the $\mathtt{k}$-fractional derivative of $\mathtt{k}$-Mittag-Leffler and the Wright hypergeometric functions.

In the present technological era, healthcare providers generate huge amounts of clinical data on a daily basis. Generated clinical data is stored digitally in the form of Electronic Health Record (EHR) as a central data repository of hospitals. Data contained in EHR is not only used for the patients' primary care but also for various secondary purposes such as clinical research, automated disease surveillance and clinical audits for quality enhancement. Using EHR data for secondary purposes without consent or in some cases even with consent creates privacy issues. Secondly, EHR data is also made accessible to various stakeholders including different government agencies at various geographical sites through wired or wireless networks. Sharing of EHR across multiple agencies makes it vulnerable to cyber attacks and also makes it difficult to implement strict privacy laws as in some cases data is shared with organization that is governed by specific regional law. Privacy of individuals could be severely affected when their sensitive private information contained in EHR is leaked or exposed to the public. Data leaks can cause financial losses or an individual may encounter social boycott if his / her medical condition is exposed in public. To protect patients personal data from such threats, there exists different privacy regulations such as General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA) and My Health Record (MHR). However, continually evolving state-of-the-art techniques in Machine Learning (ML), Data Analytics (DA) and hacking are making it even more difficult to completely protect an individual's/patient's privacy. In this article, we have systematically examined various secondary uses of EHR with the aim to highlight how these secondary uses affect patients' privacy. Secondly, we have critically analyzed GDPR & HIPAA regulations and highlighted their possible areas of improvement, considering escalating use of technology and different secondary uses of EHR.

The present research is an effort to enhance the performance of voice processing systems, in our case the speaker identification system (SIS) by addressing the variability caused by the dialectical variations of a language. We present an effective solution to reduce dialect-related variability from voice processing systems. The proposed method minimizes the system’s complexity by reducing search space during the testing process of speaker identification. The speaker is searched from the set of speakers of the identified dialect instead of all the speakers present in system training. The study is conducted on the Pashto language, and the voice data samples are collected from native Pashto speakers of specific regions of Pakistan and Afghanistan where Pashto is spoken with different dialectal variations. The task of speaker identification is achieved with the help of a novel hierarchical framework that works in two steps. In the first step, the speaker’s dialect is identified. For automated dialect identification, the spectral and prosodic features have been used in conjunction with Gaussian mixture model (GMM). In the second step, the speaker is identified using a multilayer perceptron (MLP)-based speaker identification system, which gets aggregated input from the first step, i.e., dialect identification along with prosodic and spectral features. The robustness of the proposed SIS is compared with traditional state-of-the-art methods in the literature. The results show that the proposed framework is better in terms of average speaker recognition accuracy (84.5% identification accuracy) and consumes 39% less time for the identification of speaker.

The main objective of this article is to establish generalized fractional Hermite–Hadamard and related type integral inequalities for h-Godunova–Levin convexity and h-Godunova–Levin preinvexity with extended Wright generalized Bessel function acting as kernel. Moreover, Hermite–Hadamard-type and trapezoid-type inequalities for several known convexities including Godunova–Levin function, classical convex, s-Godunova–Levin function, P-function, and s-convex function are deduced as corollaries. These obtained results are analyzed in the form of generalization of fractional inequalities.

Flame retardancy is the property that is highly demanded when it comes to deal with plastics in different industries. In this research general purpose polystyrene (GPPS) and modified sepiolite clay are melt blended together to fabricate flame retardant nanocomposites. Structural analysis were performed with the help of Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) techniques. Morphological analysis of the fabricated nanocomposites were carried out using scanning electron microscope (SEM). As a result of better clay dispersion in polymer matrix and intermolecular interactions, mechanical properties are also improved. The standard procedure (ASTM D4986-20) was followed for observing the flame retardancy of the fabricated nanocomposites. Tangible decrease is noted upto 48% in burning rate of the optimum sample which reflects improvement in flame retardancy.

Abstract In this paper, our main aim is to deal with two integral transforms involving the Gauss hypergeometric functions as their kernels. We prove some composition formulas for such generalized fractional integrals with Mittag-Leffler k-function. The results are established in terms of the generalized Wright hypergeometric function. The Euler integral k-transformation for Mittag-Leffler k-functions has also been developed.