ARTICLE | doi:10.20944/preprints202108.0314.v1
Subject: Social Sciences, Economics Keywords: energy poverty; economic growth; energy governance; multidimensional poverty
Online: 16 August 2021 (09:00:19 CEST)
During the last two decades, energy poverty has captured a growing attention of researchers and policymakers due to its strong association with economic poverty and poor economic performance. This study uses a broad set of macro level indicators and makes the first attempt to measure energy poverty and its impact on economic growth of Pakistan over the period 1990 to 2017. In particular, our energy poverty indicator considers four main dimensions of energy poverty, namely, energy services, clean energy, energy governance and energy affordability. Our main results show that though the overall energy poverty has reduced in Pakistan during the selected sample period, the country shows an increasing dependence on polluted energy supply in order to meet its growing demand of energy. In second stage of the investigation, we test the neoclassical growth theory where we incorporate energy poverty along with human capital as source of economic growth. Our cointegration results reveal a strong relationship between energy poverty and economic growth that is also dynamically stable in short run. These strong negative linkages between energy poverty with economic growth for the sample economy complement the previous literature on the subject.
REVIEW | doi:10.20944/preprints202010.0485.v1
Online: 23 October 2020 (10:42:55 CEST)
The multidisciplinary nature of the work required for research in the Covid-19 pandemic has created new challenges for health professionals in the battle against the virus. They need to be equipped with novel tools and resources ---that have emerged during the pandemic--- to gain access to breakthrough findings, know the latest developments, and to address their specific needs for rapid data acquisition, analysis, evaluation, and reporting. Because of the complex nature of the virus, the healthcare systems worldwide are severely impacted as the treatment and the vaccine for Covid-19 disease are not yet discovered. This leads to frequent changes in regulations and policies by governments and international organizations. Our analysis suggests that given the abundance of information sources, finding the most suitable tool for a given task is one of such challenges. But health professionals and policymakers need access to the most relevant, reliable, trusted, and latest information and tools that can be used in their day-to-day tasks of Covid-19 research and analysis. In this article, we present our analysis of various novel and important tools that have been specifically developed during the Covid-19 pandemic and that can be used by the health professionals community to help in advancing their analysis and research. These tools comprise of search engines, information repositories for literature and clinical trials, data sources, dashboards, and forecasting models. We present list of the minimally essential tools to serve a multitude of purposes, from hundreds of those developed since the beginning of the pandemic. A critical analysis is provided for the selected tools based on 17 parameters that can be useful for researchers and analysts for their evaluations. These parameters make up our evaluation framework and have not been used previously for analysis and evaluation. Hence, knowledge of the tools will not only increase the productivity but will also allow to explore new dimensions for using existing tools with more control, better management, and greater outcome of their research. In addition, the parameters used in our framework can be applied for future evaluations of similar tools and health professionals can adapt them for evaluation of other tools not covered in this analysis.
ARTICLE | doi:10.20944/preprints201910.0231.v1
Subject: Mathematics & Computer Science, Artificial Intelligence & Robotics Keywords: Android; arduino; bluetooth; grass cutter; sensors; speech recognition
Online: 20 October 2019 (02:03:44 CEST)
We present an Arduino-based automatic robotic system which is used for cutting grass or lawns, mostly healthy grass which needs to cut neatly like in a public park or a private garden. The purpose of this proposed project is to design a programmable automatic pattern design grass cutting robot with solar power which no longer requires time-consuming manual grass-cutting, and that can be operated wirelessly using an Android Smartphone via Bluetooth from a safe distance which is capable of cutting the grass in indeed required shapes and patterns; the cutting blade can also be adjusted to maintain the different length of the grass. The main focus was to design a prototype that can work with a little or no Physical user interaction. The proposed work is accomplished by using an Arduino microcontroller, DC geared Motors, IR obstacle detection sensor, motor shield, relay module, DC battery, solar panel, and Bluetooth module. The grass-cutting robot system can be moved to the location in the lawn remotely where the user wants to cut the grass directly or in desired patterns. The user can press the desired pattern button from the mobile application, and the system will start cutting grass in the similar design such as a circle, spiral, rectangle, and continue pattern. Also, with the assistance of sensors positioned at the front of the vehicle, an automatic barrier detection system is introduced to enhance safety measurements to prevent any risks. IR obstacle detector sensors are used to detect obstacles, if any obstacle is found in front of the robot while traveling; it avoids the barrier by taking a right/right turn or stop automatically appropriately, thereby preventing the collision. Also, the main aim of this project is the formation of a grass cutter that relieves the user from mowing their own grasses and reduces environmental and noise pollution. The proposed system is designed as a lab-scale prototype to experimentally validate the efﬁciency, accuracy, and affordability of the systems. The experimental results prove that the proposed work has all in one capability (Simple and Pattern based grass cutting with mobile-application, obstacle detection), is very easy to use, and can be easily assembled in a simple hardware circuit. We note that the systems proposed can be implemented on a large scale under real conditions in the future, which will be useful in robotics applications and cutting grass in playing grounds such as cricket, football, and hockey, etc.
ARTICLE | doi:10.20944/preprints202110.0246.v1
Subject: Biology, Plant Sciences Keywords: Chloroplast genome; Machilus leptophylla; Hanceola exserta; Rubus bambusarum; Rubus henryi; Simple sequence repeat; Phylogenetic analysis
Online: 18 October 2021 (14:30:50 CEST)
The chloroplast genome is conservative and stable, which can be employed to resolve genotypes. Currently, published nuclear sequences and molecular markers failed to differentiate the species from taxa robustly, including Machilus leptophylla, Hanceola exserta, Rubus bambusarum, and Rubus henryi. In this study, the four chloroplast genomes were characterized, and then their simple sequence repeats (SSRs) and phylogenetic positions were analyzed. The results demonstrated the four chloroplast genomes consisted of 152.624 kb, 153.296kb, 156.309 kb, and 158.953 kb in length, involving 124, 130, 129, and 131 genes, respectively. Moreover, the chloroplast genomes contained typical four regions. Six classes of SSR were identified from the four chloroplast genomes, in which mononucleotide was the class with the most members. The types of the repeats were various within individual classes of SSR. Phylogenetic trees indicated that M. leptophylla was clustered with M. yunnanensis, and H. exserta was confirmed under family Ocimeae. Additionally, R. bambusarum and R. henryi were clustered together, whereas they did not belong to the same species due to the differing SSR features. This research would provide evidence for resolving the species and contributed new genetic information for further study.
ARTICLE | doi:10.20944/preprints202011.0050.v1
Subject: Biology, Anatomy & Morphology Keywords: Nigella sativa; Curcuma longa; Pasteurella multocida; feed conversion ratio; gross pathological changes; histopathological changes
Online: 2 November 2020 (14:34:20 CET)
The antibiotic residues and pathogenic resistance against the drug are very common in poultry due to usage of antibiotics in their feed. It is the need of the time to use natural feed additives as effective alternatives instead of synthetic antibiotic. The aim of this study was to investigate the immune response of Nigella sativa and Curcuma longa in broilers under biological stress against Pasteurella multocida. The total 100, one-day old chicks were divided into 5 groups. The Groups 1 and 2 were served as control negative and control positive. Both control groups were receiving simple diet without any natural feed additives but infection was given in Group 2 at day 28 with the dose of 5.14×107 CFU by IV. Groups 3A & 3B were offered 2% seed powder of Nigella sativa, Groups 4A & 4B were offered Curcuma longa 1% in powdered form and Group 5A & 5B were offered both Curcuma longa 1% & Nigella sativa 2% in feed from day 1 and groups 3B, 4B and 5B were challenged with Pasteurella multocida. The Haemagglutination inhibition titter against Newcastle Disease Virus (NDV), feed conversion ratio, mortality, gross and histopathology were studied. The results of this study revealed that haemagglutination inhibition titers against NDV were highly significant (P< 0.05) in treated groups, highest titers (3A 6.8, 3B 6.4 and 5A 7.2) were obtained from treated Group. The feed conversion ratio (FCR) of Nigella sativa + Curcuma longa treated Groups (5A 1.57 and 3A 1.76) were higher as compared to other non-treated groups. The gross and histopathological changes were much severe in control positive, but less changes were seen in treated groups. Therefore, we recommend that natural feed additives; black cumin (Nigella sativa) and turmeric (Curcuma longa) act as immune enhancer in broilers against Pasteurella multocida.
ARTICLE | doi:10.20944/preprints202108.0128.v1
Subject: Materials Science, Biomaterials Keywords: Carbon foam; multi walled carbon nanotubes; Graphene oxide; electrical; mechanical and thermal properties
Online: 5 August 2021 (08:36:50 CEST)
Multi-walled carbon nanotubes (MWCNTs) and graphene oxide (GO) reinforced carbon foam (CF) composite were prepared by direct pyrolysis of MWCNTs, GO and mesophase coal tar pitch. The effect of additive amount of the mixture of MWCNTs and GO on the microstruture and properties of carbon foam was analzyed by transmission electron miscroscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), Four-probe resistance meter, universal testing machine, and laser thermal conductivity tester respectively. The result shows that MWCNTs and GO had significant impact on the microstructure of carbon foam. Futhermore, the electrical, mechanical and thermal properties of carbon foam composites were significantly enhanced by increasing the additive amount. Maximum compressive strenght of 19.2 MPa and Young’s modulus of 56.8 MPa of CF composite were observed. Similarly, Highest thermal conductivity of 30.91 W/m.K and electrical conductivity of 27.2 ×103 S/m were observed at 2 wt. % of MWCNTs-GO additive loading.