Leaf epidermal micromorphology and its implications in systematics of certain taxa of the fern family Pteridaceae from Northern Pakistan

The present study is insights into foliar epidermal anatomy for characterizing clades, and their utility in taxonomic segregation of certain species of Pteridaceae from Northern Pakistan. The leaf epidermal anatomy of 10 species of Pteridaceae representing four genera were examined using light and scanning electron microscope. A micromorphological matrix was constructed for eight qualitative and 12 quantitative characters. unweighted pair group method with arithmetic means and principal components analysis statistical analysis were performed to test the validity of foliar epidermal anatomical features as method of separating species and genera, and phylogenetic clusters among species are constructed using qualitative and quantitative traits. The qualitative characters described here are shape of epidermal cells, stomata, guard cell and subsidiary cells, anticlinal wall pattern, and trichomes types which is helpful in defining groups within Pteridaceae. In addition, the size of stomata, guard cells, subsidiary cells, stomatal pore epidermal cells, and trichomes are quantitatively analyzed. All species have hypostomatic leaves. Two types of stomata were observed in studied species, anomocytic and polocytic. Anomocytic stomata were observed in three genera namely: Adiantum, Onychium, and Chielanthes whereas Pteris can be discriminated from other genera by its polocytic stomata. On the basis of multivariate analysis present study does provides sufficient information on the taxonomic importance of foliar anatomy which validate its efficacy in species and genera discrimination. From result obtained here it is further possible to use leaf micromorphologic data in ferns phylogeny and providing basis for future taxonomic delimitation in other taxa.     

Significance of leaf morphoanatomical markers for the authentication of adultered drugs sold in herbal markets of district Lahore,Pakistan

A number of herbal plants sold in herbal markets of Lahore are under adulteration threat which can pose harmful health effects to end‐user. This adulteration problem of medicinal plants can be resolved by the implication of some valuable taxonomic parameter such as leaf epidermal anatomical characteristics. Hence, this research was aimed to provide viable anatomical markers in order to resolve this adulteration issue persisted in some common marketed medicinal plants of district Lahore, that is, Cinnamomum verum Presl., Cinnamomum tamala (Buuch.‐Ham.) T.Nees&Eberm., Gymnema sylvestre (Retz.) R.Br.ex Sm., Sphaeranthus indicus Linn., Artemisia maritima Linn., Achillea millifolim L., Adhatoda vasica Nees, Butea monosperma (Lam.) Taub, and Morus nigra L. Overall multiple anatomical variations (epidermal cell shape, their length and width, type of stomata, length and width of guard cells along with presence or absence of trichomes) had been reported in the study that could be worthwhile for the correct identification of medicinal plants. Irregular shapes of epidermal cells were observed in Cinnamomum verum and Achillea millifolium while pentagonal and polygonal cells were found in their adultaerants, that is, Canella winterana and Adhatoda vasica, respectively. Types of stomata were also strikingly varied among genuine plant and its adulterant, for example, anisocytic stomata were observed in Artemisia maritima while in its adulterant (Artemisia absinthium) anomocytic stomata were found. Similarly, paracytic stomata were observed in Butea monosperma, whereas its adulterant plant (Averrhoa carambola) characteristically possessed anisocytic stomata. Hence, anatomical characteristics were proved to be a valuable taxonomic tool in resolving the adulteration issue of medicinal plants.     

Translucent Photodetector with Blended Nanowires–Metal Oxide Transparent Selective Electrode Utilizing Photovoltaic and Pyro‐Phototronic Coupling Effect

ZnO is a potential candidate for photodetection utilizing the pyroelectric effect. Here, a self‐biased and translucent photodetector with the configuration of Cu₄O₃/ZnO/FTO/Glass is designed and fabricated. In addition, the pyroelectric effect is effectively harvested using indium tin oxide (ITO), silver nanowires (AgNWs), and a blend of AgNWs‐coated ITO as the transparent selective contact electrode. The improved rise times are observed from 1400 µs (bare condition; without the selective electrode) to 69, 60, 7 µs, and fall times from 720 µs (bare condition) to 80, 70, 10 µs for corresponding ITO, AgNWs, and AgNWs‐coated ITO contact electrodes, respectively. Similarly, the responsivity and detectivity are enhanced by about 4.39 × 10⁷ and 5.27 × 10⁵%, respectively. An energy band diagram is proposed to explain the underlying working mechanism based on the workfunction of the ITO (4.7 eV) and AgNWs (4.57 eV) as measured by Kelvin probe force microscopy, which confirms the formation of type‐II band alignment resulting in the efficient transport of photogenerated charge carriers. The functional use of the transparent selective contact electrode can effectively harness the pyro‐phototronic effect for next‐generation transparent and flexible optoelectronic applications.     

Green synthesis of biodegradable terpolymer modified starch nanocomposite with carbon nanoparticles for food packaging application

As to control the increased rate of environmental pollution there is an urgent need to develop improved biodegradable materials regarding the old polymeric packaging materials. It has been done by the incorporation of carbon nanomaterials to the biodegradable starch terpolymers of acrylic acid, methyl methacrylate (MMA), acrylonitrile (AN), 2-Ethylhexyl acrylate (2-EHA), and Ethyl acrylate (EA). The starch-terpolymers were prepared through the free radical polymerization technique using AA, MMA, AN, 2-EHA, EA as monomers. Two different starch-terpolymers were further mixed with carbon nanoparticles (NPs) to form a biodegradable nanocomposite. The biodegradable starch-grafted terpolymers-carbon nanocomposites (STPC NCs) were characterized through scanning electron microscopy, Fourier-transform infrared spectroscopy, thermogravimetric analysis, differential scanning calorimeter, and UV–Visible spectrophotometry. Further, resistivity, electrical conductivity, and biodegradability tests were performed to check its properties for packing materials. The biodegradation of SGCP-composites recorded using the soil burial method was up to 78%. Starch-terpolymers were prepared via free-radical polymerization The biodegradation capability of starch-grafted terpolymers was found to be 78% The decrease in water vapor permeability and solubility proves their utilization as food packaging material     

A Quantum Spatial Graph Convolutional Network for Text Classification

The data generated from non-Euclidean domains and its graphical representation (with complex-relationship object interdependence) applications has observed an exponential growth. The sophistication of graph data has posed consequential obstacles to the existing machine learning algorithms. In this study, we have considered a revamped version of a semi-supervised learning algorithm for graph-structured data to address the issue of expanding deep learning approaches to represent the graph data. Additionally, the quantum information theory has been applied through Graph Neural Networks (GNNs) to generate Riemannian metrics in closed-form of several graph layers. In further, to pre-process the adjacency matrix of graphs, a new formulation is established to incorporate high order proximities. The proposed scheme has shown outstanding improvements to overcome the deficiencies in Graph Convolutional Network (GCN), particularly, the information loss and imprecise information representation with acceptable computational overhead. Moreover, the proposed Quantum Graph Convolutional Network (QGCN) has significantly strengthened the GCN on semi-supervised node classification tasks. In parallel, it expands the generalization process with a significant difference by making small random perturbations of the graph during the training process. The evaluation results are provided on three benchmark datasets, including Citeseer, Cora, and PubMed, that distinctly delineate the superiority of the proposed model in terms of computational accuracy against state-of-the-art GCN and three other methods based on the same algorithms in the existing literature.     

Identity management based on PCA and SVM

A new approach for face recognition, based on kernel principal component analysis (KPCA) and support vector machines (SVMs), is presented to improve the recognition performance of the method based on principal component analysis (PCA). This method can simultaneously be applied to solve both the over-fitting problem and the small sample problem. The KPCA method is performed on every facial image of the training set to get the core facial features of the training samples. To ensure that the loss of the image information will be as less as possible, the facial data of high-dimensional feature space is projected into low-dimensional space, and then the SVM face recognition model is established to identify the low-dimensional space facial data. Our experimental results demonstrate that the approach proposed in this paper is efficient, and the recognition accuracy of the proposed method reaches 95.4 %.     

Safety first: a two-stage algorithm for the synthesis of reactive systems

In the game-theoretic approach to the synthesis of reactive systems, specifications are often expressed as ω-regular languages. Computing a winning strategy to an infinite game whose winning condition is an ω-regular language is then the main step in obtaining an implementation. Conjoining all the properties of a specification to obtain a monolithic game suffers from the doubly exponential determinization that is required. Despite the success of symbolic algorithms, the monolithic approach is not practical. Existing techniques achieve efficiency by imposing restrictions on the ω-regular languages they deal with. In contrast, we present an approach that achieves improvement in performance through the decomposition of the problem while still accepting the full set of ω-regular languages. Each property is translated into a deterministic ω-regular automaton explicitly while the two-player game defined by the collection of automata is played symbolically. Safety and persistence properties usually make up the majority of a specification. We take advantage of this by solving the game incrementally. Each safety and persistence property is used to gradually construct the parity game. Optimizations are applied after each refinement of the graph. This process produces a compact symbolic encoding of the parity game. We then compose the remaining properties and solve one final game after possibly solving smaller games to further optimize the graph. An implementation is finally derived from the winning strategies computed. We compare the results of our tool to those of the synthesis tool Anzu.     

Service-oriented intelligent group decision support system: Application in transportation management

In today’s ever changing consumer driven market economy, it is imperative for providers to respond expeditiously to the changes demanded by the customer. This phenomenon is no different in the transportation sector in which a service-oriented Group Decision Support System (GDSS) provides an important role in transportation enterprise to effectively manage and rapidly respond to the varying needs of the customer. In this paper, we explore the integration problem of service-oriented system and intelligence technology through the use of a GDSS. Initially, we analyze a service-oriented architecture and then, propose the design architecture of a service-oriented GDSS. Next, we put forward a general framework that integrates the intelligent techniques as a component into the architecture of service oriented GDSS. In addition, we illustrate how Artificial Intelligence techniques can resolve the conflicts of distributed group decisions. The paper is concluded by providing a number of applications in the railway management system that demonstrates the benefits of the utilization of a service oriented intelligent GDSS.