Systematic significance of pollen morphology and foliar epidermal anatomy of medicinal plants using SEM and LM techniques

Alternative medicinal source is a hot issue within medicine community now a days due to various side effects of allotropic drugs; most importantly the multidrug resistance phenomena. Medicinal plants provide an attractive and effective alternative to modern synthetic drugs as they contain different types of bioactive compounds, having great potential in treatment of various diseases. The present study deals with identification of micromorphological characteristics of 10 ethnomedicinally important plants of Northern Pakistan, that is, Aster himalaicus C. B. Clarke, Artemisia maritima (Berg.) Wellkomm, Isodon rugosus (Wall. ex Benth.), Myricaria squamosal Desv, Pedicularis groenlandica Retz. Polygonum aviculare L, Salvia himmelbauer E. Peter, Swertia kingie Hook. f., Tanacetum dolichophyllum (Kitam) Kitam, Verbascum epixanthinum Boiss. & Heldr. as potential source for pharmaceutical industry. The characters studied were shape and size of pollen, polar diameter and equatorial diameter, epidermal cell shape and size, stomata width and length, trichome shapes, and type. Most of the species had tricolporate pollen type but hexacolporate pollen was also observed in Isodon rugosus, Polygonum aviculare, Salvia himmelbauer. Different types of exine sculpturing observed were foveolate, scabrate, lophate, regular, steriate, and alveolate. Minimum equatorial diameter was noted in Tanacetum dolichophyllum (12.4 μm) and maximum in Myricaria squamosal (20.9 μm). Shape of epidermis cell ranged from rectangular and irregular, polygonal and pentagonal. Different types of stomata like anisocytic, actinocytic, paracytic, and diacytic were noticed. Variations in microscopic characters observed in the current study have great potential to be used as identification tools by the taxonomists for further studies.     

Open architecture dynamic manipulator design philosophy (DMD)

This paper presents a generic and universal architecture design for robotic manipulators. A flexible approach is taken to develop the design philosophy throughout, resulting in a hardware architecture that is portable, can be integrated and enables the implementation of advanced control methods. A software kernel of management, supervision and control was developed in order to obtain an easy user interface to the robotic researcher. The application of many such controls has, traditionally, often been severely restricted in partial commercial robotic systems because of limitations associated with their controllers; rather than the arms themselves.     

Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

Multicarrier Waveform (MCW) has several advantages and plays a very important role in cellular systems. Fifth generation (5G) MCW such as Non-Orthogonal Multiple Access (NOMA) and Filter Bank Multicarrier (FBMC) are thought to be important in 5G implementation. High Peak to Average Power Ratio (PAPR) is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user devices. The paper presents a novel Divergence Selective Mapping (DSLM) and Divergence Partial Transmission Sequence (D-PTS) for 5G waveforms. It is seen that the proposed D-SLM and PTS lower PAPR with low computational complexity. The work highlighted a combination of multi-data block partial transmit schemes along with tone reservation. In this, an overlapping factor is used to determine the number of data blocks for every group. Here, considering only those data blocks that have minimum signal power, the use of DSLM and DPTS are required to eliminate the segment’s peaks. Simulation results reveal that the suggested hybrid technique proves to be better than the conventional PTS scheme. Furthermore, the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing (OFDM) waveform.     

Improved Archimedes Optimization Algorithm with Deep Learning Empowered Fall Detection System

Human fall detection (FD) acts as an important part in creating sensor based alarm system, enabling physical therapists to minimize the effect of fall events and save human lives. Generally, elderly people suffer from several diseases, and fall action is a common situation which can occur at any time. In this view, this paper presents an Improved Archimedes Optimization Algorithm with Deep Learning Empowered Fall Detection (IAOA-DLFD) model to identify the fall/non-fall events. The proposed IAOA-DLFD technique comprises different levels of pre-processing to improve the input image quality. Besides, the IAOA with Capsule Network based feature extractor is derived to produce an optimal set of feature vectors. In addition, the IAOA uses to significantly boost the overall FD performance by optimal choice of CapsNet hyperparameters. Lastly, radial basis function (RBF) network is applied for determining the proper class labels of the test images. To showcase the enhanced performance of the IAOA-DLFD technique, a wide range of experiments are executed and the outcomes stated the enhanced detection outcome of the IAOA-DLFD approach over the recent methods with the accuracy of 0.997.     

Malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. The presented AFSADL-MURLC model intends to differentiate the malicious URLs from genuine URLs. To attain this, AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding technique. In addition, the created vector model is then passed onto Gated Recurrent Unit (GRU) classification to recognize the malicious URLs. Finally, AFSA is applied to the proposed model to enhance the efficiency of GRU model. The proposed AFSADL-MURLC technique was experimentally validated using benchmark dataset sourced from Kaggle repository. The simulation results confirmed the supremacy of the proposed AFSADL-MURLC model over recent approaches under distinct measures.     

Noble metal nanoclusters and their <Emphasis Type="Italic">in situ</Emphasis> calcination to nanocrystals: Precise control of their size and interface with TiO<Subscript>2</Subscript> nanosheets and their versatile catalysis applications

In this work, we present a new versatile strategy to prepare noble metal (Au, Ag and Cu) nanoclusters on TiO₂ nanosheets in large scales with exposed (001) facets with controlled size, crystalline interface, and loading amount. By precise in situ calcination, the metal (M = Au, Ag, and Cu) nanocrystals with controllable size and better crystalline interface with the TiO₂ support have been prepared. The potential application of the as-prepared Au, Ag, and Cu nanoclusters on TiO₂ nanosheets as potential heterogeneous catalysts for organic synthesis, such as catalytic reduction of 4-nitrophenol to 4-aminophenol, has been demonstrated. After calcination, Au, Ag, and Cu nanocrystals were found to be proficient cocatalysts for photocatalytic H₂ evolution, particularly the Au cocatalyst. Based on precise high-resolution transmission electron microscopy (HRTEM) and inductively coupled plasma optical emission spectrometry (ICP-OES) analyses, the flexible control of their size and loading amount as well as their intimate contact with the TiO₂ nanosheet enhanced the photocatalytic H₂ evolution activity and the sensitivity of the photocurrent response of the film. Furthermore, this aqueous-directed synthesis of metal nanoclusters on a support will generate further interest in the field of nanocatalysis.

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Reforming the Urban Water Supply and Sanitation (UWSS) Sector in Yemen

In the early 1990s, Yemen suffered from low service coverage and national tariffs that were too low to cover public expenditure, as well as an inadequate level of service provided by the centralized National Water and Sanitation Authority. In 1996, a reform study recommended that the UWSS sector should embrace a policy of decentralization, corporatization, commercialization, the separation of service delivery and regulatory functions, as well as public-private partnerships. The government approved this reform agenda as a Council of Ministers Decree in 1997. Awareness campaigns and consensus-building among stakeholders and political leaders and local demand supported the reform process. Currently, 95% of the total urban population related to utility towns is attended by independent utilities.     

A new method for aspherical surface fitting with large-volume datasets

In the framework of form characterization of aspherical surfaces, European National Metrology Institutes (NMIs) have been developing ultra-high precision machines having the ability to measure aspherical lenses with an uncertainty of few tens of nanometers. The fitting of the acquired aspherical datasets onto their corresponding theoretical model should be achieved at the same level of precision. In this article, three fitting algorithms are investigated: the Limited memory-Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), the Levenberg–Marquardt (LM) and one variant of the Iterative Closest Point (ICP). They are assessed based on their capacities to converge relatively fast to achieve a nanometric level of accuracy, to manage a large volume of data and to be robust to the position of the data with respect to the model. Nevertheless, the algorithms are first evaluated on simulated datasets and their performances are studied. The comparison of these algorithms is extended on measured datasets of an aspherical lens. The results validate the newly used method for the fitting of aspherical surfaces and reveal that it is well adapted, faster and less complex than the LM or ICP methods.     

Response of Semiconductor Medium of Variable Thermal Conductivity Due to Laser Pulses with Two-Temperature through Photothermal Process

Silicon - A novel model of variable thermal conductivity of semiconductor medium in two-temperature theory is studied. The Photothermal excitation due to laser pulses is investigated. The governing...