Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan

Peer reviewedPublisher PD

Crop-based irrigation operations in the North West Frontier Province of Pakistan. Vol.II: Research approach and interpretation. Final Report

Irrigation management / Crop-based irrigation / Research / Irrigation canals / Water demand / Performance evaluation / Agricultural production / Pakistan / North West Frontier Province

Compact relativistic geometries in f(R,G)f(R,G) gravity

One of the possible potential candidates for describing the universe's rapid expansion is modified gravity. In the framework of the modified theory of gravity $f(R,G)$, the present work features the materialization of anisotropic matter, such as compact stars. Specifically, to learn more about the physical behavior of compact stars, the radial, and tangential pressures as well as the energy density of six stars namely $Her X-1$, $SAXJ1808.4-3658$, $4U1820-30$, $PSR J 1614 2230$, $VELA X-1$, and $Cen X-3$ are calculated. Herein, the modified theory of gravity $f(R,G)$ is disintegrated into two parts i.e. the $\tanh$ hyperbolic $f(R)$ model and the three different $f(G)$ model. The study focuses on graphical analysis of compact stars wherein the stability aspects, energy conditions, and anisotropic measurements are mainly addressed. Our calculation revealed that, for the positive value of parameter n of the model $f(G)$, all the six stars behave normally.Comment: Some changes have been made. " To appear in International Journal of Geometric Methods in Modern Physics

Chitosan biopolymer improves the fruit quality of litchi (Litchi chinensis Sonn.)

Chitosan (CHT) is a natural compound that has been used to control postharvest pathogenic diseases due to its capability of eliciting natural defense responses in plants. The aim of this study was to investigate the effect of foliar CHT application on yield and quality of the litchi fruit. Chitosan was applied by spraying on to fruit and foliage just after fruit set four times at 7-day intervals with four varying doses viz. 100, 250, 500, and 1,000 µg L−1 and a control (0 µg L−1). Although the application of CHT had no significant effect on the size of the fruits (length and width), the total contents of phenolics, flavonoids, and ascorbic acid and the antioxidant activity of litchi fruit arils were significantly increased in CHT-treated fruit compared with the untreated control. The highest phenolic, flavonoid, and ascorbic acid contents were 334 µg gallic acid g−1, 881 μg quercetin g−1, and 178 µg g−1, respectively, in fruits treated with 500 µg L−1 CHT. However, the highest antioxidant activity (622 μg butylated hydroxytoluene g−1) was recorded in 250 µg L−1 CHT-treated fruits. Our findings revealed that the application of low doses of CHT in a litchi orchard might improve fruit quality by increasing the content of antioxidants and antioxidant activities

Recognition of Radar-Based Deaf Sign Language Using Convolution Neural Network

The difficulties in the communication between the deaf and normal people through sign language can be overcome by implementing deep learning in the gestures signal recognition. The use of the Convolution Neural Network (CNN) in distinguishing radar-based gesture signals of deaf sign language has not been investigated. This paper describes the recognition of gestures of deaf sign language using radar and CNN. Six gestures of deaf sign language were acquired from normal subjects using a radar system and processed. Short-time Fourier Transform was performed to extract the gestures features and the classification was performed using CNN. The performance of CNN was examined using two types of inputs; segmented and non-segmented spectrograms. The accuracy of recognising the gestures is higher (92.31%) using the non-segmented spectrograms compared to the segmented spectrogram. The radar-based deaf sign language could be recognised accurately using CNN without segmentation

Recognition of Radar-Based Deaf Sign Language Using Convolution Neural Network

The difficulties in the communication between the deaf and normal people through sign language can be overcome by implementing deep learning in the gestures signal recognition. The use of the Convolution Neural Network (CNN) in distinguishing radar-based gesture signals of deaf sign language has not been investigated. This paper describes the recognition of gestures of deaf sign language using radar and CNN. Six gestures of deaf sign language were acquired from normal subjects using a radar system and processed. Short-time Fourier Transform was performed to extract the gestures features and the classification was performed using CNN. The performance of CNN was examined using two types of inputs; segmented and non-segmented spectrograms. The accuracy of recognising the gestures is higher (92.31%) using the non-segmented spectrograms compared to the segmented spectrogram. The radar-based deaf sign language could be recognised accurately using CNN without segmentation

Fractional transformation-based decentralized robust control of a coupled-tank system for industrial applications

Petrochemical and dairy industries, waste management, and paper manufacturing fall under the category of process industries where flow and liquid control are essential. Even when liquids are mixed or chemically treated in interconnected tanks, the fluid and flow should constantly be observed and controlled, especially when dealing with nonlinearity and imperfect plant models. In this study, we propose a nonlinear dynamic multiple-input multiple-output (MIMO) plant model. This model is then transformed through linearization, a technique frequently utilized in the analysis and modeling of fractional processes, and decoupling for decentralized fixed-structure H-infinity robust control design. Simulation tests based on MATLAB and SIMULINK are subsequently executed. Numerous assessments are conducted to evaluate tracking performance, external disturbance re jection, and plant parameter fluctuations to gauge the effectiveness of the proposed model. The objective of this work is to provide a framework that anticipates potential outcomes, paving the way for implementing a reliable controller synthesis for MIMO-connected tanks in real-world scenarios.This research was partially funded by FONDECYT grant number 1200525 (V.L.) from the National Agency for Research and Development (ANID) of the Chilean government under the Ministry of Science, Technology, Knowledge, and Innovation; and by Portuguese funds through the CMAT—Research Centre of Mathematics of University of Minho—within projects UIDB/00013/2020 and UIDP/00013/2020 (C.C.)

Synthesis of Multiwall Carbon Nanotubes by Inductive Heating CCVD

The CCVD syntheses of MWCNTs from acetylene on Fe:Co:CaCO 3 and Fe:Co:CaO were performed using two different methods of heating: outer furnace and inductive heating. The comparative analysis of the MWCNTs obtained by the two methods show that the tubes grown in inductive heating have smaller diameters (5-25 nm), with fewer walls and aspect ratio of the order of hundreds. The ratio of outer to inner diameter (od/id) is ranging between 2 and 2.5. Inductively assisted CCVD is a very attractive method because of the major advantages that it presents, like low energetic consumption, thinner, well crystallized and more uniform tubes

Serological evidence of hepatitis E virus infection in pigs and jaundice among pig handlers in Bangladesh

Hepatitis E virus (HEV) is the most common cause of viral hepatitis in humans. Pigs may act as a reservoir of HEV, and pig handlers were frequently identified with a higher prevalence of antibodies to HEV. The objectives of this study were to identify evidence of HEV infection in pigs and compare the history of jaundice between pig handlers and people not exposed to pigs and pork. Blood and faecal samples were collected from 100 pigs derived from three slaughterhouses in the Gazipur district of Bangladesh from January to June, 2011. We also interviewed 200 pig handlers and 250 non-exposed people who did not eat pork or handled pigs in the past 2 years. We tested the pig sera for HEV-specific antibodies using a competitive ELISA and pig faecal samples for HEV RNA using real-time RT-PCR. Of 100 pig sera, 82% (n = 82) had detectable antibody against HEV. Of the 200 pig handlers, 28% (56/200) demonstrated jaundice within the past 2 years, whereas only 17% (43/250) of controls had a history of jaundice (p < .05). Compared to non-exposed people, those who slaughtered pigs (31% versus 15%, p < .001), reared pigs (37% versus 20%, p < .001), butchered pigs (35% versus 19%, p < .001) or involved in pork transportation (28% versus 13%, p < .001) were more likely to be affected with jaundice in the preceding 2 years. In multivariate logistic regression analysis, exposure to pigs (odds ratio [OR]: 2.2, 95% CI: 1.2–3.9) and age (OR: 0.97, 95% CI: 0.95–0.99) was significantly associated with jaundice in the past 2 years. Pigs in Bangladesh demonstrated evidence of HEV infection, and a history of jaundice was significantly more frequent in pig handlers. Identifying and genotyping HEV in pigs and pig handlers may provide further evidence of the pig's role in zoonotic HEV transmission in Bangladesh