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Hantavirus is a member of the order Bunyavirales and an emerging global pathogen. Hantavirus infections have affected millions of people globally based on available epidemiological data and research studies. Hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS) are the two main human diseases associated with hantavirus infections. Hence, efforts are required to develop a potent vaccine against the pathogen. The only vaccine that is in use for hantavirus is an inactivated virus vaccine, “Hantavax”, but it failed to produce neutralizing antibodies. Vaccine development is of much importance in dealing with the surge of hantavirus globally. In this study, hantavirus five proteins (N protein, G1 and G2, L protein, and non-structural proteins) were used in NetCTL 1.2 program to predict T-cell epitopes. To predict major histocompatibility complex (MHC) binding alleles, an immune epitope database (IEDB) was used. All predicted epitopes were then investigated for different immunoinformatics analyses such as antigenicity and toxicity analyses. The good water-soluble, non-toxic, probable antigenic, and DRB*0101 binder was selected. A multi-epitopes-based vaccine designing was then done where linkers were used to connect the shortlisted epitopes. In addition, an adjuvant molecule was supplementary to the multi-epitopes peptide to improve the vaccine’s immunogenic potential. The final vaccine construct’s three-dimensional structure was modeled by ab initio method. The vaccine molecule was then evaluated for its binding potential with TLR-3 immune receptor, which is key for its recognition and processing by the host immune system. Docking studies were performed using HADDOCK software. The best-docked complex was selected and visualized for intermolecular binding and interactions using UCSF Chimera 1.16 software. The findings revealed that the designed vaccine might be a potential vaccine against hantavirus and can be used in experimental animal model testings. Communicated by Ramaswamy H. Sarma

Glioblastoma multiforme is a serious and life-threatening tumor of central nervous system, characterized by aggressive behavior, poor prognosis, and low survival rate. Despite of the availability of aggressive antitumor therapeutic regimen for glioblastoma (radiotherapy followed by chemotherapeutic dose), recovery rate, and patients’ survival ratio is attributed to the lack of selectivity of therapeutic drugs and less advancement in cancer therapeutics over last decade. Moreover, tools employed in conventional diagnosis of glioblastoma are more invasive and painful, making the process excruciating for the patients. These challenges urge for the need of novel biomarkers for diagnosis, prognosis, and prediction purpose with less invasiveness and more patient compliance. This article will explore the genetic biomarkers isocitrate dehydrogenase mutation, MGMT mutations, and EGFR that can be deployed as an analytical tool in diagnosis of disease and prognosis of a therapeutic course. The review also highlights the importance of employing novel microRNAs as prognostic biomarkers. Recent clinical advancements to treat GBM and to prevent relapse of the disease are also discussed in this article in the hope of finding a robust and effective method to treat GBM.

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Automatic Meter Reading (AMR) is tackled by leveraging the high capability of Region-Convolutional Neural Networks (RCNN). However, license plate recognition is quite popular, but AMR problem is still unexplored. Numerous investigations are still crucial due to some constraints: handcrafted features, low efficiency, blur, rotate digits, low reflection, and poor quality images. With the significance of robust AMR, we have achieved advances of AMR in computer vision and deep learning, but still, these methods lack of some errors. To address these problems, we proposed a method Mask-RCNN (AMR) based on mask region convolutional neural networks (Mask-RCNN) used for counter detection, digit segmentation, and recognition. Experiments demonstrated that our proposed method substantially outperforms the state-of-the-art methods in terms of counter detection and digit recognition on publically available UFPR-AMR dataset.

In this article we used picture linguistic fuzzy Choquet integral weighted averaging (PLFCIWA) operator for multi-attribute group decision making problem, where the attribute weight information are completely unknown. Firstly, we utilized the PLFCIWA operator to aggregate the total preference value of each alternative by decision makers. An optimization model are used to obtain the weighting vector of the criteria, using the basic ideal of traditional grey relational analysis (GRA) method. The degree of grey relation between every alternative and positive-ideal solution and negative-ideal solution is computed. Then, a relative relational degree is defined to find the ranking order of all alternatives by calculating the degree of grey relation to both the positive-ideal solution (PIS) and negative ideal solution (NIS) simultaneously. Finally, a descriptive example is solved to satisfy effectiveness and practicality of the proposed techniques.

Biotransformation of dydrogesterone (1) by using cell suspension cultures of Azadirachta indica yielded a metabolite 20R-hydroxy-9b ,10a-pregna-4,6-diene-3-one (2). The structure of this compound was deduced on the basis of various spectroscopic techniques.

Aircraft Ad Hoc Network is regarded as highly dynamic and sparse network because of high mobility, limited bandwidth and connection restrictions where nodes move in random fashion anywhere, which is different from terrestrial mobile ad hoc networks (MANETs), both in terms of network capability and underlying assumption. In such a highly dynamic environments the end-to-end communication between aircraft-to-aircraft is unique and serious challenge. To cope this problem we present a new geographical routing protocol for heterogeneous aircraft ad hoc networks (GHRAA), which is the extended version of Location Aided Routing (LAR) protocol. The main contribution of this geographic routing protocol is summarized as followings. 1) Primary path is established by using the known route information of the aircrafts, 2) Once the primary path is made, optimization path is reestablished by the aircrafts with arbitrary mobility pattern. Finally for simulation and analysis, we demonstrate high packet delivery ratio and short end-to-end delay in highly dynamic networks.

The study mainly concerns the potential of the tissue culture for mass propagation and to evaluate the trueness to type of regenerated plants from tissue culture using appropriate molecular markers. Three soft fruits species Ribes, Fragaria and Rubus were used in this study. The study has three main sections dealing with an evaluation of appropriate molecular marker systems to study the plants regenerated via micropropagation, callus culture and regeneration and tissue culture and regeneration. The first section evaluates the potential of SDS-PAGE protein electrophoresis and RAPD-PCR as markers to distinguish among clonally propagated cultivars of R. nigrum. SDS-PAGE was able to distinguish only four out of ten cultivars tested. RAPD-PCR was able to distinguish all the cultivars studied using only two primers. The data generated by RAPD-PCR and from pedigree information was used to examine the relatedness among the cultivars studied. RAPD-PCR was further used to examine the purity of the cultivar Baldwin collected at various locations in the UK. Polymorphism was detected and differences were found between the sub-samples of a single cultivar. The second section deals with the multiplication of Rubus, Ribes and Fragaria by micropropagation. The effect of culture cycle on the plants regenerated was evaluated using RAPD-PCR. Ribes did not show any variation until the 14th generation cycle but in the 15th and 16th cycles variation was detected from 6.2% and 13.4% respectively. Considerable variation was detected in Rubus starting with the 4th sub-culture and was at a maximum in the 7th sub-culture. In Fragaria. all plants at sub-culture 3 were evaluated and variation was detected between them. The relevance of such variation on the release of material of all three species is discussed in relation to certification scheme requirements. The third experimental section evaluates the potential of callus as explant source for the multiplication and regeneration of plants in Ribes and Fragaria species. The study also describes investigations in the optimum growth regulators concentrations for callus culture and subsequent plant regeneration. Both the explant type leaf disc and leaf petiole showed successful callus induction in Ribes cultivars. However, plant regeneration was not successful in the cultivars and explant sources studied. In Fragaria regeneration was easily achieved from leaf disc callus and the plants were evaluated for trueness to type using RAPD-PCR This indicated variation ranges from 0.68 to 22.80%. The final discussion reviews micropropagation, callus culture and regeneration and their application to mass propagation. The use of molecular marker systems to evaluate multiplication methodology is discussed both in terms of the needs of the soft fruits industry and as the general approach to the evaluation of progeny of clonally propagated species.

Background: The Root Knot Nematode (RKN) is a serious economic threat to various cultivated crops worldwide. It is a devastating pest of soybean and responsible to cause severe yield loss in Pakistan. The cultivation of resistant soybean varieties against this pest is the sustainable strategy to manage the heavy loss and increase yield. There is an utmost need to identify RKN resistant varieties of soybean against cultivated in Pakistan. The presented study is an attempt to identify and confirm the presence of resistant gene Rmi1 in soybean. Method: Molecular studies have been done using Simple Sequence Repeat (SSR) marker system to identify resistant soybean varieties against Root Knot Nematode (RKN) using fifteen (15) indigenous cultivars and four (4) US cultivars. DNA was isolated, purified, quantified and then used to employ various SSR markers. The amplified product is observed using gel documentation system after electrophoresis. Results: Diagnostic SSR markers Satt-358 and Satt-492 have shown the presence of Rmi1 gene in all resistance carrying genotypes. Satt-358 amplified the fragment of 200 bp and Satt-492 generated 232 bp bands in all resistant genotypes. This study confirmed the Rmi gene locus (G248A-1) in all internationally confirmed resistant including six (6) native varieties. Conclusion: These investigations have identified six (6) resistant cultivars revealing the effective and informative sources that can be utilized in breeding programs for the selection of RKN resistance soybean genotypes in Pakistan.

This paper introduces the realization and evaluation of multi input multi output (MIMO) wireless system and fiber based sigma delta Radio-over-Fiber (Δ-RoF)based optical link as a front haul using fifth generation (5G) new radio (NR) multiband signals. The proposed 5G NR signals comprise of 3 GHz flexible waveforms and 23 GHz-400 MHz bandwidth. The Δ-RoF has been demonstrated by using 2nd order Sigma-Delta Modulation (SDM) with 5 km of Standard Single Mode Fiber. The EVM performance for the system meets the 3GPP Release 16. Furthermore, EVM performance for received optical power is evaluated up to 400 MHz bandwidth. It can be concluded that Δ-RoF-MIMO system suits the required range of the 5G C-RAN fronthaul networks and can be a propitious candidate for future mobile haul applications.