Modeling on population growth and its adaptation: A comparative analysis between Bangladesh and India

The biggest challenge in the world is population growth and determining how society and the state adapt to it as it directly affects the fundamental human rights such as food, clothing, housing, education, medical care, etc. The population estimates of any country play an important role in making the right decision about socio-economic and population development projects. Unpredictable population growth can be a curse. The purpose of this research article is to compare the accuracy process and proximity of three mathematical model such as Malthusian or exponential growth model, Logistic growth model and Least Square model to make predictions about the population growth of Bangladesh and India at the end of 21st century. Based on the results, it has been observed that the population is expected to be 429.32(in million) in Bangladesh and 3768.53 (in million) in India by exponential model, 211.70(in million) in Bangladesh and 1712.94(in million) in India by logistic model and 309.28 (in million) in Bangladesh and 2686.30 (in million) in India by least square method at the end of 2100. It was found that the projection data from 2000 to 2020 using the Logistic Growth Model was very close to the actual data. From that point of view, it can be predicted that the population will be 212 million in Bangladesh and 1713 million in India at the end of the 21st century. Although transgender people are recognized as the third sex but their accurate statistics data is not available. The work also provides a comparative scenario of how the state has adapted to the growing population in the past and how they will adapt in the future

A new estimate of carbon for Bangladesh forest ecosystems with their spatial distribution and REDD+ implications

In tropical developing countries, reducing emissions from deforestation and forest degradation (REDD+) is becoming an important mechanism for conserving forests and protecting biodiversity. A key prerequisite for any successful REDD+ project, however, is obtaining baseline estimates of carbon in forest ecosystems. Using available published data, we provide here a new and more reliable estimate of carbon in Bangladesh forest ecosystems, along with their geo-spatial distribution. Our study reveals great variability in carbon density in different forests and higher carbon stock in the mangrove ecosystems, followed by in hill forests and in inland Sal (Shorea robusta) forests in the country. Due to its coverage, degraded nature, and diverse stakeholder engagement, the hill forests of Bangladesh can be used to obtain maximum REDD+ benefits. Further research on carbon and biodiversity in under-represented forest ecosystems using a commonly accepted protocol is essential for the establishment of successful REDD+ projects and for the protection of the country’s degraded forests and for addressing declining levels of biodiversity

Determining the optimum tilt angle and orientation for photovoltaic (PV) systems in Bangladesh

Tilt angle of a PV module is one of the most significant parameters for receiving maximum solar irradiation falling on the PV systems. This research article investigates the numerical aspects of selecting the optimal tilt angle for the PV modules used in Bangladesh and makes recommendations on how the collected power output of the module can be increased by altering the tilt angle. The results show that the optimum tilt angle of Cox’s Bazzar Chittagong, Dhaka, Jessore, Ishurdi, Bogra, Sylhet and Rangpur is 26o, 25o, 30o, 25o, 27o, 27o, 28o and 29o, respectively. The annual energy production of Cox’s Bazar and Sylhet has shown the highest and the lowest energy production, the month was March and July, respectively. The characteristics curves obtained by the simulation with the data provided by using simulated software SAM (System Advisor Model). Finally, the article measures the optimum tilt for PV applications in Bangladesh on Monthly and yearly bases

Citizens’ attitudes toward the protection of flying squirrels in urban areas

The Siberian flying squirrel ( Pteromys volans ) is included among the strictly protected species of the Habitats Directive (92/43/EC) of the European Union, which is one of the key instruments for biodiversity preservation in Europe. Strict protection of the species has a potential to cause conflicts in areas where forest management and urban development compete for the same space with the flying squirrel. This study examined attitudes of Finnish citizens toward the protection of flying squirrels in urban areas using survey data collected in three cities: Espoo, Jyväskylä, and Kuopio. Two samples (random and self-selection samples) were collected to investigate how the specific process of giving “voice” to citizens by polls in urban planning affects the results. The analysis was conducted by integrating factor and cluster analysis and multinomial logistic regression modeling. Four attitude groups of citizens were identified and named: “neutral on protection” (share of respondents: 33%), “strongly in favor of protection” (32%), “somewhat against protection” (26%), and “strongly against protection” (9%). Several individual-specific factors were found to be associated with the probability of belonging to different attitude groups. For example, female respondents had a higher probability of belonging to the group that was strongly in favor of protection, and older respondents had a higher probability of belonging to groups against protection. Respondents of the self-selection sample had a higher probability of belonging to the “strongly in favor of protection” group. They therefore had a more positive attitude toward the protection of flying squirrels than the other respondents. This finding indicates that cities may gain an overly positive view of citizens’ attitudes toward the protection of flying squirrels through current public participation methods based on self-selection procedures, such as public hearings used in land use planning

Grafting of Cellulose and Microcrystalline Cellulose with Oligo(L-lactic acid) by Polycondensation Reaction

Oligo(L-lactic acid) (OLLA) was synthesized by ring opening polymerization of L-lactides using stannous octoate (0.03 wt% of lactide). While this served as the initiator, L-lactic acids were the co-initiators at 140 °C for 10 h, wherein L-lactic acids were prepared by hydrolytic degradation of L-lactides at 100 °C for 1 h. The molecular weight or degree of polymerization was controlled with monomer/co-initiator ratio (mol/mol). α-cellulose and microcrystalline cellulose (MCC) were extracted from jute fiber by subsequent treatment with sodium chlorite (Na2ClO2), NaOH and H2SO4. Grafting of OLLA onto α-cellulose and MCC in toluene was carried out using para-toluene sulphonic acid as a catalyst and potassium persulphate (KPS) as an initiator at 130 °C under 380 mm (Hg) pressure for 3, 6, 9, 12, 15, and 18 h. New properties of α-cellulose and MCC were observed due to the successful grafting onto α-cellulose and MCC. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) were conducted in order to confirm grafting of OLLA onto cellulose and MCC. The FTIR analysis results showed there are some new characteristic absorption peaks appeared (1728 to 1732 cm−1) in the spectrum, which confirmed the grafting of OLLA onto α-cellulose and MCC was successful. SEM images of α-cellulose and MCC before and after grafting revealed significant changes in surface morphology. Grafting of MCC could be more effective for further application in comparison to α-cellulose

Design and numerical analysis of a graphene-coated spr biosensor for rapid detection of the novel coronavirus

In this paper, a highly sensitive graphene-based multiple-layer (BK7/Au/PtSe2/Graphene) coated surface plasmon resonance (SPR) biosensor is proposed for the rapid detection of the novel Coronavirus (COVID-19). The proposed sensor was modeled on the basis of the total internal reflection (TIR) technique for real-time detection of ligand-analyte immobilization in the sensing re-gion. The refractive index (RI) of the sensing region is changed due to the interaction of different concentrations of the ligand-analyte, thus impacting surface plasmon polaritons (SPPs) excitation of the multi-layer sensor interface. The performance of the proposed sensor was numerically investigated by using the transfer matrix method (TMM) and the finite-difference time-domain (FDTD) method. The proposed SPR biosensor provides fast and accurate early-stage diagnosis of the COVID-19 virus, which is crucial in limiting the spread of the pandemic. In addition, the performance of the proposed sensor was investigated numerically with different ligand-analytes: (i) the monoclonal antibodies (mAbs) as ligand and the COVID-19 virus spike receptor-binding domain (RBD) as analyte, (ii) the virus spike RBD as ligand and the virus anti-spike protein (IgM, IgG) as analyte and (iii) the specific probe as ligand and the COVID-19 virus single-standard ribonucleic acid (RNA) as analyte. After the investigation, the sensitivity of the proposed sensor was found to provide 183.33°/refractive index unit (RIU) in SPR angle (θSPR) and 833.33THz/RIU in SPR frequency (SPRF) for detection of the COVID-19 virus spike RBD; the sensitivity obtained 153.85°/RIU in SPR angle and 726.50THz/RIU in SPRF for detection of the anti-spike protein, and finally, the sensitivity obtained 140.35°/RIU in SPR angle and 500THz/RIU in SPRF for detection of viral RNA. It was observed that whole virus spike RBD detection sensitivity is higher than that of the other two detection processes. Highly sensitive two-dimensional (2D) materials were used to achieve significant enhancement in the Goos-Hänchen (GH) shift detection sensitivity and plasmonic properties of the conventional SPR sensor. The proposed sensor successfully senses the COVID-19 virus and offers additional (1 + 0.55) × L times sensitivity owing to the added graphene layers. Besides, the performance of the proposed sensor was analyzed based on detection accuracy (DA), the figure of merit (FOM), signal-noise ratio (SNR), and quality factor (QF). Based on its performance analysis, it is expected that the proposed sensor may reduce lengthy procedures, false positive results, and clinical costs, compared to traditional sensors. The performance of the proposed sensor model was checked using the TMM algorithm and validated by the FDTD technique

Economics and Employment Generation of Bamboo-Based Enterprises: A Case Study from Eastern Bangladesh

In the last decade non-timber forest products (NTFPs) and their associated goods have received much attention from researchers and development workers for their perceived socio-economic importance and potential, particularly in developing countries. It has been increasingly recognized that promoting the use, production and sustainable harvesting of such kinds of products could also contribute to forest conservation in the long run. However, since the development process has progressed in most regions, alternatives or substitutes of such products have become available on the markets, and it will be difficult for these nature-based products to exist without additional product values. A market survey was conducted in an urban fringe of north-eastern Bangladesh to investigate NTFP-based product diversity, and marketing patterns and challenges. Further information was collected from sellers and consumers to understand their views on probable future strategies to sustain the markets of these products. A total of 38 NTFP and NTFP-based secondary products were recorded from 25 NTFP shops, including 16 permanent, 7 temporary (or semi-permanent) and 2 mobile shops. The greatest demand was observed for bamboo and cane-based products, for which supply suffered due to the scarcity of raw materials. A decreasing trend in the consumption of NTFP-based articles for urban domestic use was also reported from the sellers. To cope with the competitive markets, sellers were found to place more emphasis on creative marketing, durability and appearance of their products. The study concluded that active government support is needed for the sustenance of this industry in a changing global perspective. This could be in the form of technical advancement in the production process, improvement of existing product supply chains and skill development of the workers which will not only secure the future of these products but also provide an essential means for the survival of this industry and for thousands of people living from it. © 2010 Steve Harrison, John Herbohn