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Recently, the number of Internet of Things (IoT)-connected devices has increased daily. Consequently, cybersecurity challenges have increased due to the natural diversity of the IoT, limited hardware resources, and limited security capabilities. Intrusion detection systems (IDSs) play a substantial role in securing IoT networks. Several researchers have focused on machine learning (ML) and deep learning (DL) to develop intrusion detection techniques. Although ML is good for classification, other methods perform better in feature transformation. However, at the level of accuracy, both learning techniques have their own certain compromises. Although IDSs based on ML and DL methods can achieve a high detection rate, the performance depends on the training dataset size. Incidentally, collecting a large amount of data is one of the main drawbacks that limits performance when training datasets are lacking, and such methods can fail to detect novel attacks. Few-shot learning (FSL) is an emerging approach that is employed in different domains because of its proven ability to learn from a few training samples. Although numerous studies have addressed the issues of IDSs and improved IDS performance, the literature on FSL-based IDSs is scarce. Therefore, an investigation is required to explore the performance of FSL in IoT IDSs. This work proposes an IoT intrusion detection model based on a convolutional neural network as a feature extractor and a prototypical network as an FSL classifier. The empirical results were analyzed and compared with those of recent intrusion detection approaches. The accuracy results reached 99.44%, which shows a promising direction for involving FSL in IoT IDSs. [ABSTRACT FROM AUTHOR]

The quality and marketing of horticultural crops is affected by the feeding of thrips on plant tissues. Thrips commonly feed upon the gladiolus and different vegetative and floral parts of gladioli are attacked by them. Application of chemical insecticides provides effective control of insect pest in short period of time. The present investigation was carried out on Jasminum sambac against flower thrips for efficacy of insecticides. To conduct this experiment, six insecticides viz., imidacloprid 20Sl, Spinosad 240SC, Spintoram 120SC, Chlophenapyre, Imidacloprid+fipronil and abamectin were applied. Thrips population was observed on jasmine flower before application of insecticides and thrips mortality data was noted after 24, 72 and 168 hours of insecticides spray. The maximum mortality of thrips was recorded in Imidacloprid+fipronil (68.45%) and Spinosad (65.45%) after 24 hours of insecticides spray. The lowest mortality of thrips was counted in abamectin and imidacloprid. Population of thrips was reduced after 72 and 168 hours as compared to 24 hours after insecticides spray. It is concluded from the findings of investigation that the insecticide (Imidacloprid+fipronil) was found effective against the population of thrips after 24, 72 and 168 hours in years, 2021 and 2022, respectively when compared to other insecticides. [ABSTRACT FROM AUTHOR]

Simple Summary: Dermacentor ticks have a wide geographic range with an uneven distribution in the globe. They are not scientifically well known because they survive in hard topographic and harsh climatic regions along with elevated mountains. Many mammals serve as a primary host for Dermacentor ticks, like many other tick species. The present study aimed to provide the first morphological and molecular confirmation of Dermacentor marginatus and its related pathogens like Anaplasma marginale and Rickettsia raoultii in Pakistan. In this study, a total of 26 specimens (19 males and 7 females) were collected from goats and morphologically identified. A subset of 18 specimens were subjected for the molecular characterization of ticks and associated pathogen detection. In the BLAST and phylogenetic analyses, D. marginatus and their associated pathogen sequences showed close resemblance with their corresponding species. In the present study, we reported the first genetic characterization of D. marginatus and associated A. marginale and R. raoultii in Pakistan. Due to the difficult access and harsh climate, it is important to investigate the ticks and related pathogens in the northern parts of Pakistan due to their zoonotic threats. Ticks of the genus Dermacentor Koch, 1844 (Acari: Ixodidae) are poorly known systematically due to their habitation in harsh topographic environments and high mountains. Dermacentor ticks are diversely distributed in the Palearctic, Nearctic, and Oriental regions. There is no available information on the occurrence of Dermacentor marginatus in Pakistan; thus, the current investigation aimed the first morphological and molecular confirmation of this species and associated Anaplasma marginale and Rickettsia raoultii. Ticks were collected from goats (Capra hircus) and morphologically identified. Genomic DNA was extracted from 18/26 (69.23%) tick specimens, including 11 males and 7 females (1 unfed and 6 fed females). Extracted DNA was subjected to PCR for the amplification of genetic markers like 16S rDNA and cox1 for ticks, 16S rDNA for Anaplasma spp., and gltA and ompB for Rickettsia spp. A total of 26 D. marginatus ticks composed of 19 males (73.07%) and 7 females (26.9%) [1 (3.84%) unfed and 6 (23.07%) fed females] were collected from goats. According to amplicons via BLAST analysis, the 16S rDNA sequence showed 97.28–98.85% identity and the cox1 sequence showed 95.82–98.03% identity with D. marginatus. Additionally, the 16S rDNA sequence for Anaplasma sp. was detected in D. marginatus that showed 100% identity with Anaplasma marginale. Rickettsial gltA and ompB sequences for Rickettsia sp. showed 100% identity with Rickettsia raoultii. In phylogenetic analysis, ticks' 16S rDNA and cox1 sequences clustered with the same species. In phylogenetic analysis, A. marginale based on 16 rDNA clustered with A. marginale, while gltA and ompB sequences clustered with R. raoultii. This is the first study on the genetic characterization of D. marginatus and associated A. marginale and R. raoultii in Pakistan. The northern areas of Pakistan, which need to be explored in terms of ticks and associated pathogens due to their zoonotic threats, have been neglected due to the inaccessible climatic conditions. [ABSTRACT FROM AUTHOR]

Corals are sessile invertebrates living underwater in colorful structures known as reefs. Unfortunately, coral's temperature sensitivity is causing color bleaching, which hosts organisms that are crucial and consequently affect marine pharmacognosy. To address this problem, many researchers are developing cures and treatment procedures to restore bleached corals. However, before the cure, the researchers need to precisely localize the bleached corals in the Great Barrier Reef. The researchers have developed various visual classification frameworks to localize bleached corals. However, the performance of those techniques degrades with variations in illumination, orientation, scale, and view angle. In this paper, we develop highly noise-robust and invariant robust localization using bag-of-hybrid visual features (RL-BoHVF) for bleached corals by employing the AlexNet DNN and ColorTexture handcrafted by raw features. It is observed that the overall dimension is reduced by using the bag-of-feature method while achieving a classification accuracy of 96.20% on the balanced dataset collected from the Great Barrier Reef of Australia. Furthermore, the localization performance of the proposed model was evaluated on 342 images, which include both train and test segments. The model achieved superior performance compared to other standalone and hybrid DNN and handcrafted models reported in the literature. [ABSTRACT FROM AUTHOR]

Detecting cyber intrusions in network traffic is a tough task for cybersecurity. Current methods struggle with the complexity of understanding patterns in network data. To solve this, we present the Hybrid Deep Learning Intrusion Detection Model (HD-IDM), a new way that combines GRU and LSTM classifiers. GRU is good at catching quick patterns, while LSTM handles long-term ones. HD-IDM blends these models using weighted averaging, boosting accuracy, especially with complex patterns. We tested HD-IDM on four datasets: CSE-CIC-IDS2017, CSE-CIC-IDS2018, NSL KDD, and CIC-DDoS2019. The HD-IDM classifier achieved remarkable performance metrics on all datasets. It attains an outstanding accuracy of 99.91%, showcasing its consistent precision across the dataset. With an impressive precision of 99.62%, it excels in accurately categorizing positive cases, crucial for minimizing false positives. Additionally, maintaining a high recall of 99.43%, it effectively identifies the majority of actual positive cases while minimizing false negatives. The F1-score of 99.52% emphasizes its robustness, making it the top choice for classification tasks requiring precision and reliability. It is particularly good at ROC and precision/recall curves, discriminating normal and harmful network activities. While HD-IDM is promising, it has limits. It needs labeled data and may struggle with new intrusion methods. Future work should find ways to handle unlabeled data and adapt to emerging threats. Also, making HD-IDM work faster for real-time use and dealing with scalability challenges is key for its broader use in changing network environments. [ABSTRACT FROM AUTHOR]

Plant performance is mainly estimated based on plant architecture, leaf features and internal microstructural changes. Olive (Olea europaea L.) is a drought tolerant, oil yielding, and medium sized woody tree that shows specific structural and functional modifications under changing environment. This study was aimed to know the microstructural alteration involving in growth and yield responses of different Olive cultivars. Eleven cultivars were collected all over the world and were planted at Olive germplasm unit, Barani Agricultural Research Institute, Chakwal (Punjab) Pakistan, during September to November 2017. Plant material was collected to correlate morpho-anatomical traits with yield contributing characteristics. Overall, the studied morphological characters, yield and yield parameters, and root, stem and leaf anatomical features varied highly significantly in all olive cultivars. The most promising cultivar regarding yield was Erlik, in which plant height seed weight and root anatomical characteristics, i.e., epidermal thickness and phloem thickness, stem features like collenchymatous thickness, phloem thickness and metaxylem vessel diameter, and leaf traits like midrib thickness, palisade cell thickness a phloem thickness were the maximum. The second best Hamdi showed the maximum plant height, fruit length, weight and diameter and seed length and weight. It also showed maximum stem phloem thickness, midrib and lamina thicknesses, palisade cell thickness. Fruit yield in the studied olive cultivars can be more closely linked to high proportion of storage parenchyma, broader xylem vessels and phloem proportion, dermal tissue, and high proportion of collenchyma. [ABSTRACT FROM AUTHOR]

Cancer development is associated with the deregulation of various cell signaling pathways brought on by certain genetic and epigenetic alterations. Therefore, novel therapeutic strategies have been developed to target those pathways. The phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) (PI3K/Akt/mTOR) pathway is one major deregulated pathway in various types of cancer. Several anticancer drug candidates are currently being investigated in preclinical and/or clinical studies to target this pathway. Natural bioactive compounds provide an excellent source for anticancer drug development. Curcumin and plumbagin are two potential anticancer compounds that have been shown to target the PI3K/Akt/mTOR pathway individually. However, their combinatorial effect on cancer cells is still unknown. This study aims to investigate the synergistic effect of these two compounds on the PI3K/Akt/mTOR pathway by employing a sequential molecular docking and molecular dynamics (MD) analysis. An increase in binding affinity and a decrease in inhibition constant have been observed when curcumin and plumbagin were subjected to sequential docking against the key proteins PI3K, Akt, and mTOR. The MD simulations and molecular mechanics combined with generalized Born surface area (MM-GBSA) analyses validated the target proteins' more stable conformation when interacting with the curcumin and plumbagin combination. This indicates the synergistic role of curcumin and plumbagin against cancer cells and the possible dose advantage when used in combination. The findings of this study pave the way for further investigation of their combinatorial effect on cancer cells in vitro and in vivo models. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has provided significant help in many fields of life. This study proposed a framework that helped in understanding customers' attitudes about the adoption of Robo-advisors. The role of the Technology Readiness Index moderated as one of the primary relationships. A total of 208 potential users of Robo-advisor services provided the data that confirmed the validity of the model. This model provided the input for structural equation modeling and analysis of the study hypotheses. The results indicated that consumers showed positive attitudes about Robo-advisor services, with the moderating effect of Technology Readiness Index dimensions, namely, contributors and inhibitors. Perceived ease of use, perceived usefulness, and perceived convenience influenced consumers in developing positive attitudes about this service. Financial businesses can design better AI Robo-advisor services to fulfill the requirements of a wide range of consumers. This proposed framework contributes to the consumers' understanding of behavioral intentions for the use of Robo-advisors in FinTech. [ABSTRACT FROM AUTHOR]

The aim of this paper is to determine analytic solutions to the steady/unsteady 2-D flows of a Newtonian fluid passing through a porous media. Using the stream function, the analytical general solutions of the non-linear equations corresponding to boundary-layer flows are determined by employing the extended approach of variable separation. Some specific flow problems, described by given initial and boundary conditions, are investigated using the obtained general analytic solutions. [ABSTRACT FROM AUTHOR]

Objective: To find the magnitude of clinically overt hypocalcaemia post-total thyroidectomy and its relation with the age of the patient. Study Design: Cross-sectional study. Place and Duration of Study: Combined Military Hospital, Bahawalpur Pakistan, from Jan 2017 to Dec 2019. Methodology: Sixty patients who were to undergo total thyroidectomy were included in the study in strict compliance with the inclusion and exclusion criteria. Patients were divided into two groups according to their ages. In Group-A, patients younger than 50 and Group-B, patients older than 50 years were included. All the patients were followed up by clinical examination for the development of clinically overt hypocalcaemia and confirmed by measurement of serum calcium. Results: Mean age of the patients was 42.75±13.05 years, with an age range of 20 to 68 years. Of all the patients, 14(23.3%) were male, and 46(76.7%) were females. Seven patients in Group-A developed post-thyroidectomy hypocalcaemia clinically, whereas, in Group-B, only one developed this condition. Clinical post-thyroidectomy hypocalcaemia developed more often in the younger age group and these results were statistically significant (p= 0.023). Conclusion: Clinically overt hypocalcaemia develops more often in younger patients after total thyroidectomy. [ABSTRACT FROM AUTHOR]

To improve yield and shelf life of stock can enhance economic value to flowers growers globally. A study was conducted to evaluate the efficacy of various bio-stimulants on yield and quality of stock. Three cultivars of stock, viz. 'Cheerful White', 'Iron Rose' and 'Iron White' foliarly sprayed by bio-stimulants (Isabion and Tecamin Max) with three different concentrations (1 ppm, 3 ppm, and 5 ppm) with the different number of sprays (1, 2, or 3 sprays). The first spray was applied after one month of transplanting, while the other two were applied at fortnight intervals after the first spray. Fisher's Analysis of variance revealed that Isabion at 1 ppm as 1 spray, 3 ppm as 3 sprays, and 5 ppm as 3 sprays produced the highest plant height for three cultivars of stock. 'Cheerful White' had the highest stem length when plants were sprayed once at 1 ppm Isabion. Among cultivars, 'Iron Rose', produced highest leaf area (42.8 cm2) with 3 ppm Isabion application, when sprayed only one time. Among the number of sprays, plants sprayed three times with Isabion produced the thickest stem diameter followed by 2 and 1 sprays. 'Cheerful White' had maximum leaf total chlorophyll contents, followed by 'Iron White' and 'Iron Rose' (69.1 SPAD and 68.8 SPAD, respectively). Among the number of sprays, plants sprayed three times had the longest vase life. Cheerful White proved early cultivar of stock while Iron White were late cultivars when grown in agro-climatic conditions of Faisalabad. Tecamoin Mix is recommended biostimulant for quality production of Mathiola incoma L. rather than isabion. [ABSTRACT FROM AUTHOR]

An intrusion detection system is one of the main defense lines used to provide security to data, information, and computer networks. The problems of this security system are the increased processing time, high false alarm rate, and low detection rate that occur due to the large amount of data containing various irrelevant and redundant features. Therefore, feature selection can solve this problem by reducing the number of features. Choosing appropriate feature selection methods that can reduce the number of features without a negative effect on the classification accuracy is a major challenge. This challenge motivated us to investigate the application of different wrapper feature selection techniques in intrusion detection. The performance of the selected techniques, such as the genetic algorithm (GA), sequential forward selection (SFS), and sequential backward selection (SBS), were analyzed, addressed, and compared to the existing techniques. The efficiency of the three feature selection techniques with two classification methods, including support vector machine (SVM) and multi perceptron (MLP), was compared. The CICIDS2017, CSE-CIC-IDS218, and NSL-KDD datasets were considered for the experiments. The efficiency of the proposed models was proved in the experimental results, which indicated that it had highest accuracy in the selected datasets. [ABSTRACT FROM AUTHOR]

To improve yield and shelf life of stock can enhance economic value to flowers growers globally. A study was conducted to evaluate the efficacy of various bio-stimulants on yield and quality of stock. Three cultivars of stock, viz. ‘Cheerful White’, ‘Iron Rose’ and ‘Iron White’ foliarly sprayed by bio-stimulants (Isabion and Tecamin Max) with three different concentrations (1 ppm, 3 ppm, and 5 ppm) with the different number of sprays (1, 2, or 3 sprays). The first spray was applied after one month of transplanting, while the other two were applied at fortnight intervals after the first spray. Fisher’s Analysis of variance revealed that Isabion at 1 ppm as 1 spray, 3 ppm as 3 sprays, and 5 ppm as 3 sprays produced the highest plant height for three cultivars of stock. ‘Cheerful White’ had the highest stem length when plants were sprayed once at 1 ppm Isabion. Among cultivars, ‘Iron Rose’, produced highest leaf area (42.8 cm² ) with 3 ppm Isabion application, when sprayed only one time. Among the number of sprays, plants sprayed three times with Isabion produced the thickest stem diameter followed by 2 and 1 sprays. ‘Cheerful White’ had maximum leaf total chlorophyll contents, followed by ‘Iron White’ and ‘Iron Rose’ (69.1 SPAD and 68.8 SPAD, respectively). Among the number of sprays, plants sprayed three times had the longest vase life. Cheerful White proved early cultivar of stock while Iron White were late cultivars when grown in agro-climatic conditions of Faisalabad. Tecamoin Mix is recommended biostimulant for quality production of Mathiola incoma L. rather than isabion. [ABSTRACT FROM AUTHOR]

A formidable challenge in suburban agriculture is the sustainability of soil health following the use of wastewater for irrigation. The wastewater irrigation likely toxifies the crop plants making them unconsumable. We used a multivariate, completely randomized design in a greenhouse, comparing the phytoextraction capacities of Brassica juncea, Eruca sativa, Brassica rapa, and Brassica napus—all grown on silt loam soil irrigated with industrial wastewater, canal water, and a 1:1 mixture, during 2018. The studied Brassica plants were generally closely efficient in remediating toxic metals found in wastewater irrigated soil. Substantial differences between Brassica and Eruca plants/parts were recorded. For example, B. napus had significantly higher metal extraction or accumulation compared to E. sativa for Zn (71%), Cu (69%), Fe (78%), Mn (79%), Cd (101%), Cr (57%), Ni (92%). and Pb (49%). While the water and plant were the main predictors of metal extraction or accumulation, an interaction between the main effects substantially contributed to Cu, Mn, and Fe extractions from soil and accumulations in plants. Significant correlations between biological accumulation coefficient and biological transfer coefficient for many metals further supported the metal extraction or accumulation efficiencies as: B. napus > B. juncea > B. rapa > E. sativa. Root-stem mobility index correlation with stem-leaf mobility index indicated the metal translocation along the root-stem-leaf continuum. Therefore, we suggest that these crops may not be used for human or animal consumption when grown with industrial wastewater of toxic metal concentrations ≥ permissible limits. Rather these plants may serve as effective remediators of toxic metal-polluted soil. [ABSTRACT FROM AUTHOR]

Cybersecurity has been widely used in various applications, such as intelligent industrial systems, homes, personal devices, and cars, and has led to innovative developments that continue to face challenges in solving problems related to security methods for IoT devices. Effective security methods, such as deep learning for intrusion detection, have been introduced. Recent research has focused on improving deep learning algorithms for improved security in IoT. This research explores intrusion detection methods implemented using deep learning, compares the performance of different deep learning methods, and identifies the best method for implementing intrusion detection in IoT. This research is conducted using deep learning models based on convolutional neural networks (CNNs), long short-term memory (LSTM), and gated recurrent units (GRUs). A standard dataset for intrusion detection in IoT is considered to evaluate the proposed model. Finally, the empirical results are analyzed and compared with the existing approaches for intrusion detection in IoT. The proposed method seemed to have the highest accuracy compared to the existing methods. [ABSTRACT FROM AUTHOR]

The present mathematical model discloses the effects of Boussinesq and Rosseland approximations on unsteady 3D dynamics of water-driven hybridized nanomaterial with the movements of nanoplatelets (molybdenum disulfide, MoS 2 and graphene oxide, GO). Variable thermal conditions, namely, VST (variable surface temperature) and VHF (variable heat flux), are opted to provide temperature to the surface. MHD effects have also been used additionally to make the study more versatile. In order to transmute the transportation equations into nondimensionlized forms, similarity transformations have been adopted. The Keller-Box technique has been applied to obtain a numerical simulation of the modeled problem. The convergence of the solution for both VST and VHF cases is presented via the grid independence tactic. Thermal setup against escalating choices of power indices and nonlinear thermal radiation parameter is discussed via graphical illustrations. The rate of heat transaction has been discussed with the growing choices of mixed convection, thermal radiation, and unsteady parameters through various tabular arrangements. It is observed through the present analysis that mixed convection parameter, radiation parameter, temperature maintaining indices r , s , and unsteady parameter magnify the rate of heat transference under the control of platelet-shaped nanoparticles. [ABSTRACT FROM AUTHOR]

Wire coating is a commercial method to insulate wires for mechanical intensity and environmental protection. In this experimental study, the technique of computational intelligence is used for nonlinear wire coating analysis by soaking the wires in Oldroyd 8-constant fluid under a constant pressure gradient with the help of feed forward artificial neural networks (ANNs). The system of partial differential equations generated for the process of wire coating is transformed into a nonlinear dimensionless ordinary differential equation. One of the salient features of ANNs is the mathematical modeling of transformed equations by exploring the unsupervised error. A new scheme based on inverse multiquadric neural networks (IMQNNs) is used with a hybridization process of well-known genetic algorithms (GAs) and sequential quadratic programming (SQP) to obtain expeditious convergence, i.e., IMQNNs-GA-SQP. The applicability of the problem is investigated by altering the values of the dilatant constant, pressure gradient, shear stress, and pseudo-plastic constant, the outcome of which is in the form of varying polymer coating thickness. Comparison of highly accurate results in the shape of error analysis based on absolute errors of obtained results with those of the reference solution, calculated using the Adams numerical technique using MATHEMATICA software, statistical analysis such as root-mean-square error, Theil's coefficient for inequality, E-R2 (error function based on the coefficient of determination), E-VAF (variance accounted for), E-NSE (Nash–Sutcliffe efficiency), mean absolute error, box plot analyses, and the cumulative distributive function through histogram analyses, is also carried out in this research, which guarantees the effectiveness of the used scheme. [ABSTRACT FROM AUTHOR]

Application of wastewater to agricultural soils not only enhances economic benefits but is also considered as a safe disposal option by the administrators. Worldwide, peri-urban horticulture is a common practice for growing vegetables. When agricultural soils are irrigated with wastewater, numerous potentially toxic elements (PTEs) contained therein are bioaccumulated and pose health risks. The presented study aimed to reveal the PTEs, i.e., copper (Cu), cadmium (Cd), nickel (Ni) and lead (Pb) concentration in the agricultural soils irrigated with wastewater for longer times. Zeolite, a natural mineral was used to immobilize these in contaminated soils to reduce its availability to brinjal (Solanum melongena L.). During a pot study, zeolite was applied at four different levels, i.e., 0.25, 0.50, 1.00 and 2.00% in contaminated soil, keeping one control. The results revealed that growth as well as biochemical and physiological characters were found best with treatment receiving zeolite at 2.00%. In edible parts (fruit), PTE contents were found lowest in the same treatment. Relative to the control, ~121, 87, 120 and 140% less DTPA-extracted Cu, Cd, Ni and Pb in soil was found with this treatment. Based on the results, it was revealed that zeolite effectively immobilized Cu, Cd, Ni and Pb in the soil. Although all the applied levels of zeolite had positive potential to immobilize PTEs in wastewater-contaminated soil, zeolite applied at 2.00% proved most effective. [ABSTRACT FROM AUTHOR]

Tetralogy of Fallot is one of the frequently encountered cyanotic heart diseases. We describe how we handled anesthesia for a pregnant woman with uncorrected Tetralogy of Fallot during a cesarean section. Less than 10% of patients with Congenital Heart Disease survive for more than 10 years. Among the survivors, very few of them reach adulthood in countries like Pakistan with no previous surgical interventions. The occurrence of such case is quite rare. [ABSTRACT FROM AUTHOR]

In this exploration, we decided to investigate the significance of prescribed thermal conditions on unsteady 3D dynamics of water-based radiative hybrid nanofluid with the impact of cylindrical-shaped nanosized particles (alumina ( Al 2 O 3 ) and titania (Ti O 2 )). For physical relevancy, the impact of the Lorentz force is also included. The combination of suitable variables has been used to transform the transport equations into the system of ordinary differential equations and then numerically solved via the Keller-Box approach. Graphical illustrations have been used to predict the impact of the involved parameters on the thermal setup. Convergence analysis is presented via the grid independence approach. Skin frictions and local Nusselt numbers against various choices of involved parameters are plotted and arranged in tabular forms. It is observed through the present investigation that temperature distribution is increased with the higher choices of radiation parameter 0.0 ≤ R d ≤ 2.0 and decreased with the improvement in the choices of temperature maintaining indices (i.e., − 2.0 ≤ r , s ≤ 2.0). Moreover, the thermophysical properties except specific heat for hybrid nanofluid are improved with the involvement of cylindrical-shaped nanoparticles. The temperature of the hybrid nanofluid is observed to be higher for variable thermal conditions as compared to uniform thermal conditions. Outfalls for a limited version of the report have been compared with a previous published paper. [ABSTRACT FROM AUTHOR]

An investigation of the thermal performance of water-conveying nanospheres (magnetite ( Fe 3 O 4 ) and silver (Ag)) subject to variable thermal controls, namely, variable surface temperature and variable surface normal heat flux, has been made. A bidirectionally elongating surface is used to generate an unsteady flow mechanism with the action of the Lorentz force. Derived equations of basic laws are firstly nondimensionalized and then numerically solved by applying the Keller-Box method. The local Nusselt number for both the thermal cases is calculated and discussed. Percent-wise enhancement in the rate of heat transport has also been included in the analysis. It was concluded through the present exploration that at lower volume fractions of magnetite and silver, the rate of heat transport is observed to be dominant. The rate of heat transference has attained identical values for both the provided thermal conditions at the surface. Moreover, intensities of velocity and thermal profiles diminish with the appreciation of the choice of unsteadiness. The temperature-controlling indices also affect the thermal profile, and it is reduced with the intensification in the considerations of these indices. The values of thermal conductivity, density, and electrical conductivity have been improved with the inclusion of nanospheres (magnetite ( Fe 3 O 4 ) and silver (Ag)), whereas the value of specific heat is reduced with the mixture of these nanospheres. The Nusselt number is increased up to 5% with the involvement of magnetite nanospheres, and it is enhanced up to 4% with the involvement of silver nanospheres. [ABSTRACT FROM AUTHOR]

Little is known in the literature about the concept of nonuniform heat source/sink and higher-order chemical reaction for the dynamics of Oldroyd-B nanoparticles. Therefore, the present article addresses the nonuniform heat source/sink and higher-order chemical reaction features in nonlinear mixed convection bidirectional MHD dynamics of Oldroyd-B nanoparticles with thermal radiation aspects through porous space. Stratification effects for both the temperature and concentration setups are also used in the mathematical model with the significance of random movement and thermodiffusion of nanoparticles. Shape-preserving transformations have been employed to convert the transport equations into solvable forms. An innovative analytical tactic, namely, homotopy analysis method, has been adopted to find the solution of the modeled problem. Behaviors of pertinent parameters on thermal and concentration profiles have been discussed through various graphs. Inspection of heat/mass transport against appropriate varieties of pertinent parameters has been made and explained physically. Thermal profile is augmented with the higher estimations of space and temperature-dependent heat source/sink links. Concentration profile is diminished with the augmentation of higher-order chemical reaction parameter. Sherwood number is improved with the estimation of 0 ≤ β t ≤ 100 and is reduced with the growth of 0 ≤ β c ≤ 100. Nusselt number is declined with the upgraded amounts of 0 ≤ N b ≤ 3 and 0 ≤ N t ≤ 5. [ABSTRACT FROM AUTHOR]

The application of graph theory in the study of molecular physical and chemical properties involves theoretical mathematical chemistry. Atoms, represented by vertices, and edges, represented by bonds between them, are detailed in simple graphs called chemical graphs. The mathematical derivation of the numerical value of a graph is called the molecular descriptor of the graph. Any connected graph wherein no edge is contained in exclusive of a single cycle is called a cactus graph. In the research in this article, expressions for various molecular descriptors of line graph of the graph obtained by the rooted product of the cycle and path graphs are constructed. This article obtained the calculation of molecular descriptors for line graphs of chain ortho cactus and chain para cactus graphs. To predict the biological activity of a compound, the generalized Zagreb index, the first Zagreb index M 1 G , the second Zagreb index M 2 G , the F-index, the general Randic index, the symmetric division, the atom bond connectivity (ABC), and the geometric arithmetic (GA) descriptors are created. [ABSTRACT FROM AUTHOR]

In view of the successful applications of graph theory, relationships between the biological activity and chemical structure have been developed. One of the popular topics in graph theory is problems relating to topological indices. Degree-based topological indices, distance-based topological indices, and counting-related topological indices are various types of topological indices. Physiochemical properties such as boiling point and stability of chemical compounds are correlated by these topological indices. A topological index of a graph is a numerical quantity obtained from the graph mathematically. A cactus graph is a connected graph in which no edge lies in more than one cycle. In this study, we have derived certain degree-based topological indices for some families of graphs consisting of graph obtained by the rooted product of paths and cycles and two types of cactus graph (paracactus and orthocactus) with the help of the generalized Zagreb index. [ABSTRACT FROM AUTHOR]

The contribution of amino acids (AAs) to soil nitrogen (N) fluxes is higher than previously thought. The fact that AA uptake is pivotal for N nutrition in boreal ecosystems highlights plant AA transporters as key components of the N cycle. At the same time, very little is known about AA transport and respective transporters in trees. Tree genomes may contain 13 or more genes encoding the lysine histidine transporter (LHT) family proteins, and this complicates the study of their significance for tree N-use efficiency. With the strategy of obtaining a tool to study N-use efficiency, our aim was to identify and characterize a relevant AA transporter in hybrid aspen (Populus tremula L. x tremuloides Michx.). We identified PtrLHT1.2, the closest homolog of Arabidopsis thaliana (L.) Heynh AtLHT1, which is expressed in leaves, stems and roots. Complementation of a yeast AA uptake mutant verified the function of PtrLHT1.2 as an AA transporter. Furthermore, PtrLHT1.2 was able to fully complement the phenotypes of the Arabidopsis AA uptake mutant lht1 aap5 , including early leaf senescence-like phenotype, reduced growth, decreased plant N levels and reduced root AA uptake. Amino acid uptake studies finally showed that PtrLHT1.2 is a high affinity transporter for neutral and acidic AAs. Thus, we identified a functional AtLHT1 homolog in hybrid aspen, which harbors the potential to enhance overall plant N levels and hence increase biomass production. This finding provides a valuable tool for N nutrition studies in trees and opens new avenues to optimizing tree N-use efficiency. [ABSTRACT FROM AUTHOR]

The objective of the current investigation is to examine the influence of variable viscosity and transverse magnetic field on mixed convection fluid model through stretching sheet based on copper and silver nanoparticles by exploiting the strength of numerical computing via Lobatto IIIA solver. The nonlinear partial differential equations are changed into ordinary differential equations by means of similarity transformations procedure. A renewed finite difference based Lobatto IIIA method is incorporated to solve the fluidic system numerically. Vogel's model is considered to observe the influence of variable viscosity and applied oblique magnetic field with mixed convection along with temperature dependent viscosity. Graphical and numerical illustrations are presented to visualize the behavior of different sundry parameters of interest on velocity and temperature. Outcomes reflect that volumetric fraction of nanoparticles causes to increase the thermal conductivity of the fluid and the temperature enhances due to blade type copper nanoparticles. The convergence analysis on the accuracy to solve the problem is investigated viably though the residual errors with different tolerances to prove the worth of the solver. The temperature of the fluid accelerates due the blade type nanoparticles of copper and skin friction coefficient is reduced due to enhancement of Grashof Number. [ABSTRACT FROM AUTHOR]

Internet of Vehicles (IoV) is a complex system that consists of resource types such as vehicles, humans, and sensors. Although the Internet of Vehicles is complex, it improvises communication among vehicles on the roads. Quality of service (QoS) enabled the cooperative driving system (CDS) based on 5G technology, enabling vehicles to communicate and cooperate to improve road traffic efficiency. Due to the high vehicle density and limited resources (bandwidth) of current network infrastructure, sometimes a better channel that meets the requirements of cooperative driving is not available that causes network congestion, which directly influences the overall QoS of the CDS. To overcome this, we proposed a 5G network-based architecture for CDS that incorporates a D2D technology-based resource allocation scheme. The proposed network architecture and cooperative behavior-based scheme helps in improving QoS for CDS. We implemented our proposed scheme by incorporating the density-based scattered clustering algorithm with noise for vehicular clustering. The proposed scheme's performance shows significant improvement in terms of throughput compared with existing D2D approaches. [ABSTRACT FROM AUTHOR]

Researchers working in the field of unmanned aerial vehicles are observing rapid developments in the field, such as the use of quadrotors to grasp, manipulate, and transport objects. These advancements are made possible through sophisticated control systems, new types of actuation and sensing technologies, and a greater understanding of the aerodynamic effects and gyroscopic moment generated by the rotating blades of the quadrotor involved. Therefore, this research work proposes four novel optimized control laws, i.e., conditioned adaptive barrier-based double integral super twisting sliding mode controller (CABDIST-SMC), BF double integral SMC (BF-DISMC), BF integral SMC, and barrier function-based SMC control laws, for attitude, heading, position, and altitude trajectory tracking of the quadcopter. The non-linear model of the quadcopter is developed using the Lagrange formalism in MATLAB ODE-45 environment, including the gyroscopic moments and aerodynamic effects, and a Lyapunov stability analysis is performed to ensure the asymptotic stability of the system. A 3D-helical complex trajectory is employed to analyze the performance and consistency of the proposed optimized controllers. For performance comparison, the proposed four variants of the SMC are compared with three traditional control strategies, i.e., backstepping SMC, optimized adaptive SMC via particle swarm optimization algorithm, and improved adaptive SMC. These traditional control strategies have also been developed and tested in MATLAB-Simulink. All the controllers are optimized using the improved grey wolf optimization algorithm, and to determine the best control law, six performance indexes, i.e., mean absolute percentage error (MAPE), root mean square error (RMSE), integral square error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and integral time square error (ITSE) are used. A hardware-in-loop (HIL) test is also performed to validate the performance of the designed novel control law. The C2000 Delfino MCU F28379D launchpad is used for performing the HIL validation test. The simulated results showed that the performance of optimized CABDIST-SMC surpassed all other control laws for altitude, heading, position, and attitude trajectory tracking. It has achieved MAPE of 0.02%, RMSE of 3.9912e−5, ISE of 3.1859e−8, IAE of 7.9823e−4, ITAE of 0.0080, and ITSE of 3.1849e−7 in case of yaw angle control. The proposed control laws have successfully passed the HIL validation test, and real-time implementation of the proposed control laws indicates no significant variations compared to the simulated results. [ABSTRACT FROM AUTHOR]

This study is based on gray-box modeling for the prediction of optimum mass flow rates of inlet streams of a Plate and Fin Heat Exchanger under uncertainty. A first principle model of the Plate and Fin Heat Exchanger was developed in Aspen Exchanger Design and Rating. Genetic algorithm was integrated with the first principle model to achieve the highest possible exit temperature of the cold process stream under uncertainty. A dataset of uncertain process conditions and their corresponding optimum inlet flow rates derived through the first principle-genetic algorithm integration was used to develop an artificial neural networks model. The artificial neural networks model was then integrated with the first principle model by replacing the genetic algorithm to form a novel gray-box framework. The proposed gray box model, i.e., artificial neural networks and first principle integration, achieved a higher effectiveness and higher outlet temperature than those derived through the straight run first principle model. The performance of the gray box framework was also comparable to the first principle integrated genetic algorithm approach and significantly minimized the computation time needed for estimating the optimum process conditions. First principle integrated genetic algorithm approach enhanced the effectiveness of the straight run model by 3.05%. Performance of the proposed gray-box model was comparable to the integrated framework of the genetic algorithm with the first principle model but was significantly faster. The developed artificial neural networks model was employed as a surrogate in Sobol and FAST sensitivity analysis framework to identify the impact of input variables on output variables. The proposed gray box based method enhanced the capability of the plate and fin heat exchanger to recover energy from the process stream and its robustness to cope with uncertainty. The proposed approach is suitable for real-time application and would contribute to laying a foundation for petroleum refinery 4.0. • A Gray-box (GB) modeling framework was developed for the optimization of process conditions of a plate and fin heat exchanger of a tile industry under uncertainty. • The GB framework was based on the integration of first principle (FP) model and Artificial Neural Networks (ANN) model. • The proposed GB approach attained the optimum conditions in a significantly less period of time than the conventional FP-GA framework. [ABSTRACT FROM AUTHOR]

Various seed conditioning techniques were assessed for uniform germination, seedling vigor, and flower production in zinnia (Zinnia elegans Jacq.). Two initial laboratory experiments evaluated the timing and frequency of seed magnetic stimulation to select the most promising treatments for field production testing and flowering. In the first experiment, a 3% moringa leaf extract (MLE) showed the earliest (2.8 d) and the highest germination rate (90%) with an average root length of 4.2 cm. Hydro-priming resulted in the largest seedling fresh weight (0.8 g), seedling shoot length (5.8 cm), and seedling vigor index (980). The seedling vigor index was determined by multiplying the percent germination with the seedling length (cm). In the second experiment, seeds treated at 25 mT for 5 min. showed the highest (65%) and earliest (3.2 d) germination (T50) although not significantly different from treatments with 50 mT for 5 or 10 min. or 75 mT for 5 min. In field trials, seeds primed with MLE alone or in combination with magnetically treated water (MTW) produced the tallest plants (104 cm) with longer internodes and the largest canopy diameter (42.4 cm). Using MLE along with MTW produced greater plant fresh weight (137 g), more flowers (27.5), and larger flower diameter (9.7 cm) similar to the results of using MTW alone. In summary, seeds primed with MLE in combination with untreated water or MTW resulted in improved plant growth and yield characteristics and may be recommended to commercial growers of zinnia or other annual flowers. [ABSTRACT FROM AUTHOR]

The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches. [ABSTRACT FROM AUTHOR]

Topological indices(TIs) are important numerical number associate with the molecular graph of a chemical structure/compound because due to these parameters, one can guess almost all properties of concerned structure/compound with our performing experiments. In recent years, huge amount work has been done for calculating degreedependent indices for different structures/compouds. In order to compute TIs, one need to do many calculations. Our aim of this paper is to present a simple method to compute degree-dependent TIs. We computed M-polynomials for Block Shift Networks and with the help of this simple algebraic polynomials, we recovered nine important TIs for Block Shift Networks. Our work is important for chemists, physicians and pharmaceutical industry. [ABSTRACT FROM AUTHOR]

Network theory as an important role in the field of electronic and electrical engineering, for example, in signal processing, networking, communication theory, etc. The branch of mathematics known as Graph theory found remarkable applications in this area of study. A topological index (TI) is a real number attached with graph networks and correlates the chemical networks with many physical and chemical properties and chemical reactivity. The Optical Transpose Interconnection System (OTIS) network has received considerable attention in recent years and has a special place among real world architectures for parallel and distributed systems. In this report, we compute redefined first, second and third Zagreb indices of OTIS swapped and OTIS biswapped networks. We also compute some Zagreb polynomials of understudy Networks. [ABSTRACT FROM AUTHOR]

A study was conducted to develop indigenous soilless substrate compositions for improved growth, flower yield, stem quality and vase life of cut antirrhinum. Two experiments comprised of seven substrate compositions with variable ratios of saw dust (SD), peanut hulls (PH) and sugarcane pressmud (a by-product of sugar industry, which is rich in nutrients) or coco-coir (CC), rice hulls (RH) and sugarcane pressmud (PM) were used. Seeds were sown in plastic plug trays containing CC, silt (soil extracted from canal) and PM (1:1:1; v/v/v) substrate for seedling development and transplanted at the two to four leaf stage into lily crates with the treatment substrates. Plants grown in substrates containing SD + PH + PM (experiment I) indicated that plants grown in these soilless compositions died before flowering, while those grown in silt (control) performed best. While in experiment II, the highest quality plants were grown in 50% CC + 40% RH +10% PM. Quality was defined as plants with shortest production time (days), tallest plant height (cm), optimal leaf chlorophyll content (SPAD), highest leaf area (cm²), fresh and dry weight (g), longest vase life (days). Substrates containing CC, RH and PM (50% + 40% + 10%; v/v/v) were superior to substrates of SD, PH and PM. For commercial cut ant [ABSTRACT FROM AUTHOR]

A survey-based study was conducted to analyze the current scenario of substrate usage in local ornamental plants nurseries of Punjab, Pakistan, during 2017, using stratified random sampling technique. Ornamental nurseries of Faisalabad, Lahore, Islamabad, Kasur and Multan were surveyed on a detailed questionnaire, which consisted of comprehensive personal and business information of nurserymen, substrate usage for ornamental plant production and major issues of nursery production business in Punjab, Pakistan. Collected data were coded, decoded and arranged statistically in tabular form, and were analyzed through SPSS (Statistical Package for Social Science) IBM (International Business Machines) version 19. Results demonstrated that majority of local nurserymen were using soil or silt for raising ornamentals. Moreover, major obstacle in nursery production was the unawareness of the nurserymen regarding modern nursery raising techniques and majority (56%) even had no idea about use or significance of soilless substrates. However, a large number (62%) of nurserymen were interested to produce export quality plants, using cheaper local soilless substrates, if available at affordable prices. Only a few nurserymen, who were using modern imported substrates, demanded the tax exemption facility (35%) and reduction of import export barriers (21%), training of labor about modern substrates and nursery raising techniques (21%) and awareness about modern technologies (16%). Ignorance about modern soilless substrates (53%) and high costs of imported soilless substrates (25%) were reported to be the major issues in limited use of soilless substrates. Nurserymen also complained that they were using personal resources only to cope with their nursery issues and no support was available from public or private sector. Nurserymen were purchasing the traditional substrates, viz. silt from other nurserymen (48%), and get some guidance from university experts, floriculture websites or through floriculture department extension agents. Use of garden soil or silt traditionally and unawareness of the modern soilless substrates were reported as major reasons of low quality nursery production and nurserymen were looking for affordable locally developed soilless substrates for better quality ornamental nursery production. [ABSTRACT FROM AUTHOR]

Bibliometrics is a quantitative tool for the analysis of literature published in a scientific field. Using Scopus as the data source, we perform a thorough analysis of scholarly works published in the field of big data from 2008 to 2017. The objective of the work is to find the most cited articles in the given time frame, the citation trends, the authorship trends as well as the trends of research work in the related area. The analysis shows that over 50% of publications do not receive any citations, and the average number of citations per publication is 3.17. It is also observed that single authorship of research publications has declined over the time. The analysis reveals the pioneering role played by the USA in advancing the research in big data, which has lately been taken over by China, and the large-scale usage of big data analytics in various domains of science. [ABSTRACT FROM AUTHOR]

In this study, a stochastic numerical technique is used to investigate the numerical solution of heat transfer temperature distribution system using feed forward artificial neural networks. Mathematical model of fin equation is formulated with the help of artificial neural networks. The effect of the heat on a rectangular fin with thermal conductivity and temperature de-pendent internal heat generation is calculated through neural networks optimization with optimizers like active set technique, interior point technique, pattern search, genetic algorithm and a hybrid approach of pattern search - interior point technique, genetic algorithm - active set technique, genetic algorithm - interior point technique, and genetic algorithm - sequential quadratic programming with different selections of weights. The governing fin equation is transformed into an equivalent non-linear second order ODE. For this transformed ODE model we have performed several simulations to provide the justification of better convergence of results. Moreover, the effectiveness of the designed models is validated through a complete statistical analysis. This study reveals the importance of rectangular fins during the heat transformation through the system. [ABSTRACT FROM AUTHOR]

A study was conducted to develop indigenous soilless substrate compositions for improved growth, flower yield, stem quality and vase life of cut antirrhinum. Two experiments comprised of seven substrate compositions with variable ratios of saw dust (SD), peanut hulls (PH) and sugarcane pressmud (a by-product of sugar industry, which is rich in nutrients) or coco-coir (CC), rice hulls (RH) and sugarcane pressmud (PM) were used. Seeds were sown in plastic plug trays containing CC, silt (soil extracted from canal) and PM (1:1:1; v/v/v) substrate for seedling development and transplanted at the two to four leaf stage into lily crates with the treatment substrates. Plants grown in substrates containing SD + PH + PM (experiment I) indicated that plants grown in these soilless compositions died before flowering, while those grown in silt (control) performed best. While in experiment II, the highest quality plants were grown in 50% CC + 40% RH +10% PM. Quality was defined as plants with shortest production time (days), tallest plant height (cm), optimal leaf chlorophyll content (SPAD), highest leaf area (cm2 ), fresh and dry weight (g), longest vase life (days). Substrates containing CC, RH and PM (50% + 40% + 10%; v/v/v) were superior to substrates of SD, PH and PM. For commercial cut antirrhinum production, substrates with locally available components of CC, RH and RM can be recommended. [ABSTRACT FROM AUTHOR]

Objectives: To find out the frequency of retinopathy in low birth weight infant presenting at tertiary care hospital, Bahawalpur. Study Design: Cross sectional study. Setting: Department of Ophthalmology, Bahawal Victoria Hospital, Bahawalpur. Period: July 2018 to December 2018. Material & Methods: Neonatal eye examination was performed for ROP. Results: Total 78 neonates were recruited for present study and ROP was assessed. Mean gestational age of neonates was 32.54 ± 3.79 weeks. Mean weight was 1445.51 ± 517.373 grams. Out of 78 neonates, ROP was observed in 28 (36%) neonates. ROP was found in 27 (42.19%) neonates of premature group and in 1 (7.14%) neonates of at term group. ROP was found in 1 (3.23%), 5 (29.41%) and 22 (73.33%) neonates respectively in weight group 1500-2500 g, 1000-1500 g and <1000 g group. Male neonates were 35 (44.87%) and female neonates were 43 (55.13%). Development of ROP was not significantly (P = 0.248) associated with gender of the neonates. Statistically significant association between ROP and oxygen supplementation was observed with p value 0.021. Conclusion: Results showed higher association of development of ROP with gestational age. Oxygen supplementation and oxygen concentration was also associated with development of ROP. Findings also showed no effect of gender and duration of hospital stay on ROP. [ABSTRACT FROM AUTHOR]

Real world complex networks are indirect representation of complex systems. They grow over time. These networks are fragmented and raucous in practice. An important concern about complex network is link prediction. Link prediction aims to determine the possibility of probable edges. The link prediction demand is often spotted in social networks for recommending new friends, and, in recommender systems for recommending new items (movies, gadgets etc) based on earlier shopping history. In this work, we propose a new link prediction algorithm namely "Common Neighbor and Centrality based Parameterized Algorithm" (CCPA) to suggest the formation of new links in complex networks. Using AUC (Area Under the receiver operating characteristic Curve) as evaluation criterion, we perform an extensive experimental evaluation of our proposed algorithm on eight real world data sets, and against eight benchmark algorithms. The results validate the improved performance of our proposed algorithm. [ABSTRACT FROM AUTHOR]

The study examined association between perceived parent adolescent conflict and social competence and whether gender of the adolescents moderated impact of parent-adolescent conflicts on their social competence. The sample of 120 college students (60 boys and 60 girls) who were living with both biological parents was recruited from the public colleges of Lahore. The Conflict Behavior Questionnaire and Social Competence Scale for Adolescents were administered to the participants. Results revealed that there was statistically significant difference between the mean scores of adolescent boys and girls on their perceived adolescent conflict with father (t = 9.41, p <.001) and with mother (t = 2.66, p <.012) however boys' conflict with their parents was stronger than that of girls. Interestingly, both boys and girls perceived their relationship with the parent of the opposite sex as more conflicting. Parent-adolescent conflicts negatively predicted social competence and gender moderated the relationship between motheradolescent conflict and social competence of adolescents after statistically controlling for demographic variables i.e., age of adolescents, class and family system, unlike the case of father-adolescents conflict. Furthermore, adolescent girls scored significantly higher on social competence than boys (t =2.45, p < .016). The findings have been discussed in regard to gender roles in the cultural environment/settings of Pakistan where a huge gender disparity exists between the sexes. As a developing country, changing family life-style due to urbanization and spread of education in Pakistan appears to bode well in negotiating gender discrepancies and viewpoints for adaptive parent-adolescent relationship. It can, in turn, boost social competence as well, among adolescents. [ABSTRACT FROM AUTHOR]

Background: Global Health Estimates 2015 has shown IHD as second leading global cause of death and 3rd leading global cause for DALYs for 2015. The objectives of this study were to determine frequency, distribution and determinants of DM in adult acute coronary syndrome (ACS) population of D.I.Khan Division, Pakistan. Materials & Methods: This cross-sectional study was conducted in Departments of Ophthalmology & Community Medicine, Gomal Medical College, D.I.Khan, from February 1, 2017 to April 30, 2017. 331 cases were selected with margin of error 4.511%, 90%CL and 25% prevalence of DM in 73,438 adults assumed to have IHD. All indoor adult patients of ACS were eligible. Sex, age groups, and residence and presence of DM were variables. Frequency and distribution were analyzed by count and percentage. Hypotheses for distribution were substantiated by chisquare goodness-of-fit and of association by chi-square test of association. Results: Out of 331 patients with ACS, 225 (68.0%) were men and 106 (32.0%) women, 221 (66.8%) =60 years and 110 (33.2%) >60 years, and 210 (63.4%) urban and 121 (35.6%) rural. Frequency of DM was 79/331 (23.87%). Out of 79 patients with DM, men were 44 (13.29%), women 35 (10.57%), age group =60 years 57 (17.22%), >60 years 22 (6.65%), urban 53 (16.01%) and rural 60 (7.85%). Our prevalence of DM was lower than expected (p=.00214), our distribution by sex was similar to expected (p=.4993) while our distribution for age groups (p=.01209) and residence (p=.00005) were not similar to expected. Presence of DM was associated to sex (p=.011) but not to age groups (p=.0304) and residence (p=.5241). Conclusion: Prevalence of DM in adult ACS population of D.I.Khan Division, Pakistan was found lower than expected. The prevalence was more in men than women, more in younger age group (=60 years) than older age group (>60 years) and more in urban than rural population. Our prevalence of DM was lower than expected, our distribution by sex was similar to expected while our distribution for age groups and residence were not similar to expected. The presence of DM was associated to sex but not to age groups and residence. [ABSTRACT FROM AUTHOR]

Background: Pediatric cataracts cause significant visual disability worldwide. The objectives of this study were to determine the distribution of pediatric cataracts by sex, age groups, laterality, type and presentation in population of D.I.Khan District, Pakistan. Materials & Methods: This descriptive study was carried out at Department of Ophthalmology, Gomal Medical College, D.I.Khan, Pakistan from January 2015 to December 2015. Sample was collected from Eye unit, DHQ Teaching Hospital, D.I.Khan. Pediatric cataract patients under 14 years of age were included in the study. Demographic variables were sex and age groups. Research variables were laterality, type and presentation. All variables being nominal were analyzed through frequency and percentages. The observed and expected distribution of pediatric cataract by sex, age groups, laterality, type and presentation were respectively tested by chi-square goodness of fit test. Results: Out of a sample of 47 patients, 29 (61.7%) were boys and 18 (38.3%) girls, 22 (46.81%) were <5 years and 25 (53.19%) 5-14 years of age. Thirty three (70.21%) had unilateral and 14 (29.79%) bilateral cataracts. Type was congenital/developmental in 27 (57.45%) patients and traumatic in 20 (42.55%). Presentation was by defective vision in 23 (48.94%), leukocoria 14 (29.79%), strabismus 7 (14.89%) and screening in 3 (6.38%) cases. The observed distribution of pediatric cataract by sex (p=.0158), age groups (p=.00002), laterally (p=<.00001) and type (p=.00001) was similar to expected, while for presentation, it was different than expected (p=.1033). Conclusion: The prevalence of pediatric cataract was higher for boys than girls and higher for older children (5-14 years) than younger (<5 years) children. Unilateral were more common than bilateral cataracts and the congenital/developmental were more common than traumatic cataracts. Defective vision was the most common presentation of pediatric cataracts. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the interfacial bonding, interfacial nanostructure and reinforcing ability of 4 vol% multi-walled carbon nanotubes (mw CNT) and 6 vol% silicon carbide nanoparticles (SiC NP) in inductively sintered alumina ceramic hybrid nanocomposites. Homogenously dispersed reinforcing inclusions led hybrid nanocomposites to three-fold finer microstructure and respective 81% and 25% higher fracture toughness and microhardness over the monolithic alumina. Better mechanical properties were correlated with distinctive toughening mechanisms of crack-deflection as well as crack-bridging induced by reinforcing phases upon establishing sturdy interfaces with the alumina matrix. Moreover, the bonding mechanisms and nanostructural development at the mw CNT/alumina and SiC NP /alumina interfacial regions were probed by means of both qualitative and quantitative approaches. The results show strong interfacial bonding of alumina with mw CNT and SiC NP through an intermediate interfacial layer in the former case and direct physical sticking in the latter one. The bonding chemistry and nanostructural features at the interfaces are meticulously discussed. We also discuss the high temperature stability of the hybrid nanocomposites under air and argon atmospheres. Highlights • Hybrid alumina nanocomposites containing SiC/CNT were inductively sintered. • Dense nanocomposite showed higher 81% toughness and 25% hardness over alumina. • Interfacial bonding was appraised by qualitative and quantitative methods. • Bonding chemistry and nanostructures at interface are scrupulously discussed. • Hybrid nanocomposite manifested high thermal stability under inert atmosphere. [ABSTRACT FROM AUTHOR]

Abstract Hybrid alumina (Al 2 O 3) ceramic nanocomposites containing 3 wt% silicon carbide nanoparticles (SiCnp) and 0.5 wt% multilayer graphene (MLG) were consolidated to near theoretical density (99%) by an inductive hot-pressing (IHP) technology. The enhanced fracture toughness and hardness by 97% and 15% respectively, for the hybrid nanocomposites over the reference Al 2 O 3 were attributed to the higher densification, uniformly dispersed reinforcing constituents within the base matrix, toughening mechanisms of crack-deflection by the 0D-SiCnp and grain-anchoring as well as crack-bridging induced by the 2D-MLG. Thermal investigations of the hybrid nanocomposite verified the occurrence of a chemical reaction at the MLG/Al 2 O 3 interface and thermal diffusion at SiCnp/Al 2 O 3 interface during inductive hot-pressing. The bonding characteristics and interfacial microstructure were appraised by infra-red spectroscopy and high-resolution TEM microscope. Furthermore, the thermal stability in different gaseous environments and the ballistic performance of the hybrid nanocomposites were characterized and discussed. The produced hybrid nanocomposites may be suitable for high-temperature aerospace structural parts and may have applications in high-velocity impact technology. Highlights • Dense hybrid nanocomposites were prepared by inductive hot pressing method. • The hybrid nanocomposites demonstrated 97% higher fracture toughness over Al 2 O 3. • Hybrid nanocomposites manifested high thermal stability and ballistic performance. • Reinforcing phases (SiC and MLG) formed sturdy interface with Al 2 O 3 matrix. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the attitude estimation problem for rigid bodies moving in 3D-space with not negligible and time varying acceleration. For this case, we propose a simple and efficient globally asymptotic attitude estimation by using measurements from low-cost IMU and GPS. It consists of an observer based on proportional-integral (PI) term with discontinuous switching function to estimate the linear acceleration in the inertial frame for which we obtain global exponential convergence, along with a complementary filter for raw vectors from IMU to remove noise and bias. For this one, we get global asymptotic convergence of the observer taking into account gyro bias. Thereafter the filtered data is processed with an algebraic algorithm (e.g. TRIAD) for the attitude estimation. Note that when no gyro bias is considered, we obtain global exponential convergence for the overall system. To show the importance of filtering these raw vectors and the convergence behaviour of the proposed observers, simulation results are also given. [ABSTRACT FROM AUTHOR]

Introduction: Radiochemical purity (RCP) is a routine quality control test carried out at nuclear medicine to determine the concentration of various chemical species present in the radiopharmaceuticals (RPs). The present work describes three years of experience in a single institute for the measurement of these impurities in the RPs preparations. Methods: The RCP of different cold kit preparations were performed by chromatographic methods. Specifically, a small drop of the aliquot was spotted on the specific paper acting as the stationary phase and then developed in different solvents as mobile phases. The developed chromatograms were then quantified for various chemical species by Mini TLC scanner or well type counter. Results: The retention factor (Rf) values for the different chemical species in the labeling of RP were measured by using single, double or triple solvent systems. It was observed that 2.70% of the kits had RCP less than the acceptable limit whereas 97.30% kits were found within the permissible levels. Conclusion: Chromatographic techniques used for the assessment of RCP offer sufficiently good results for identification and separation of different chemical impurities. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) system generates energy that varies with the variation in environmental conditions such as temperature and solar radiation. To cope up with the ever increasing demand of energy, the PV system must operate at maximum power point (MPP), which changes with load as well as weather conditions. This paper proposes a nonlinear backstepping controller to harvest maximum power from a PV array using DC-DC buck converter. A regression plane is formulated after collecting the data of the PV array from its characteristic curves to provide the reference voltage to track MPP. Asymptotic stability of the system is proved using Lyapunov stability criteria. The simulation results validate the rapid tracking and efficient performance of the controller. For further validation of the results, it also provides a comparison of the proposed controller with conventional perturb and observe (P&O) and fuzzy logic-based controller (FLBC) under abrupt changes in environmental conditions. [ABSTRACT FROM AUTHOR]

Myocardial infarction (MI), a cause of significant morbidity and mortality, is typically followed by microstructural alterations where the necrotic myocardium is steadily replaced with a collagen scar. Engineered remodeling of the fibrotic scar via stem cell regeneration has been shown to improve/restore the myocardium function after MI. Nevertheless, the heterogeneous nature of the scar patch may impair the myocardial electrical integrity, leading to the formation of arrhythmogenesis. Radiofrequency ablation (RFA) offers an effective treatment for focal arrhythmias where local heating generated via electric current at specific spots in the myocardium ablate the arrhythmogenic foci. Characterization of these myocardial pathologies (i.e., infarcted, stem cell regenerated, and RFA-ablated myocardial tissues) is of potential clinical importance. Optical polarimetry, the use of light to map and characterize the polarization signatures of a sample, has emerged as a powerful imaging tool for structural characterization of myocardial tissues, exploiting the underlying highly fibrous tissue nature. This study aims to review the recent progress in optical polarimetry pertaining to the characterization of myocardial pathologies while describing the underlying biological rationales that give rise to the optical imaging contrast in various pathologies of the myocardium. Future possibilities of and challenges to optical polarimetry in cardiac imaging clinics are also discussed. [ABSTRACT FROM AUTHOR]

Objectives: To determine the outcome of trabeculotomy in patients presenting with primary congenital glaucoma at a tertiary care hospital in Pakistan. Design: It was a descriptive case series. Place and Duration of Study: This study was conducted at the Department of Ophthalmology, Allied Hospital Faisalabad over 3 years from January 2014 to December 2016. Material and Methods: 45 consecutive children presenting with primary congenital glaucoma were included after written informed consent. These children underwent trabeculotomy. Outcome variable was frequency of successful treatment which was defined as persistent intraocular pressure below 20 mmHg without medication for at least six months and reduction or stabilization of cupping of the optic disc. A predesigned proforma was used to record patient's demographic details along with outcome variables. Results: The mean age of the patients was 17.47±5.77 months. There were 28 (62.2%) male and 17 (37.8%) female children with a male to female ratio of 1.6:1. It was bilateral in 37 (82.2%) patients. There was significant improvement in the mean intraocular pressure (12.69±2.12 vs. 25.09±4.52 mmHg; p<0.00001), horizontal corneal diameter (11.96±1.49 vs. 14.87±2.03mm; p<0.00001), axial length (20.16±2.51 vs. 20.69±2.37mm; p=0.0002) and cup-disc ratio (0.30±0.15 vs. 0.51±0.19; p<0.00001) from baseline at 6 months follow-up after trabeculotomy. Treatment was successful in 39 (86.7%) patients. There was no significant difference in the frequency of successful treatment across age and gender groups. Conclusion: Trabeculotomy is an easy to perform procedure with high success rate of 86.7% in children with primary congenital glaucoma. The complications observed in the present series were related to surgical skill and technique and were successfully managed. [ABSTRACT FROM AUTHOR]