176 research outputs found
In Silico Evaluation of Different Flavonoids from Medicinal Plants for Their Potency against SARS-CoV-2
No full textThe ongoing pandemic situation of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a global threat to both the world economy and public health. Therefore, there is an urgent need to discover effective vaccines or drugs to fight against this virus. The flavonoids and their medicinal plant sources have already exhibited various biological effects, including antiviral, anti-inflammatory, antioxidant, etc. This study was designed to evaluate different flavonoids from medicinal plants as potential inhibitors against the spike protein (Sp) and main protease (Mpro) of SARS-CoV-2 using various computational approaches such as molecular docking, molecular dynamics. The binding affinity and inhibitory effects of all studied flavonoids were discussed and compared with some antiviral drugs that are currently being used in COVID-19 treatment namely favipiravir, lopinavir, and hydroxychloroquine, respectively. Among all studies flavonoids and proposed antiviral drugs, luteolin and mundulinol exhibited the highest binding affinity toward Mpro and Sp. Drug-likeness and ADMET studies revealed that the chosen flavonoids are safe and non-toxic. One hundred ns-MD simulations were implemented for luteolin-Mpro, mundulinol-Mpro, luteolin-Sp, and mundulinol-Sp complexes and the results revealed strong stability of these flavonoid-protein complexes. Furthermore, MM/PBSA confirms the stability of luteolin and mundulinol interactions within the active sites of this protein. In conclusion, our findings reveal that the promising activity of luteolin and mundulinol as inhibitors against COVID-19 via inhibiting the spike protein and major protease of SARS CoV-2, and we urge further research to achieve the clinical significance of our proposed molecular-based efficacy
EFFECT OF MANURES AND INORGANIC FERTILIZERS ON GROWTH AND YIELD OF TWO SELECTED MUNGBEAN VARIETIES
Get PDFA Thesis
Submitted to the Faculty of Agriculture,
Sher-e-Bangla Agricultural University, Dhaka,
in partial fulfilment of the requirements
for the degree of
MASTER OF SCIENCE (MS)
IN
AGRONOMYThe experiment was conducted at the Agronomy Farm of Sher-e-Bangla
Agricultural University, Dhaka during the period from March to June 2015
(kharif-I season) to find out the effect of different manures and inorganic
fertilizers on growth and yield of two selected mungbean varieties. The
experiment consisted of two factors: factor A: five levels of manures and
inorganic fertilizers;[ T
0
= Control (no fertilizer or manure) T
= Recommended
dose of fertilizer (45 kg urea ha
-1
+ 100 kg TSP ha
ii
-1
1
+ 58 kg MoP ha
=
Recommended dose of fertilizer + cowdung (3 t ha
-1
), T
= Recommended dose
of fertilizer + poultry manure (2 t ha
-1
), T
4
3
= Recommended dose of fertilizer +
vermicompost (2.5 t ha
-1
)] and factor B: two mungbean varieties; (V
= BARI
Mung 5 and V
= BARI Mung 6). The experiment was laid out in split plot
design with three replications. In case of manures and fertilizers, the maximum
grain yield (1.53 t ha
2
-1
) and maximum stover yield (1.88 t ha
-1
) was recorded
from T
treatment and minimum was from control treatment. In case of variety
the maximum grain yield (1.58 t ha
4
-1
) and minimum stover yield (1.45 t ha
)
was obtained from V
(BARI Mung 6) variety on the other hand the minimum
grain yield (1.29 t ha
2
-1
) and maximum stover yield (1.91 t ha
-1
) was obtained
from V
(BARI Mung 5) variety. In case of combined effect the maximum
grain yield (2.01 t ha
1
-1
) and maximum stover yield (2.61t ha
-1
) was recorded
from T
4
V
2
and minimum from T
0
V
. So, BARI Mung 6 performed the best
result with the application of vermicompost @ 2.5 t ha
1
-1
with recommended
dose of fertilizer
Bangladesh-India Diplomatic Relations (1975-1996): Transitions, Bilateral Disputes and Legacies
No full textBangladesh, born in 1971, endured her very first setback in 1975 when a bloody military coup took place, which killed the father of the nation, and subsequently, the army seized power. From then to 1990, two military dictators ruled the country for a short time as a military dictator and the rest of the time under the veil of the democratically elected President. With the fall of the Mujib government, a new diplomatic stance had taken up; from a socialist, liberal, secular, and democratic state, Bangladesh crawled down to a capitalist, conservative, Islamist and authoritarian form of state. It appears from the policy of the dictators that they had tried to satiate the people through the amendments in the constitution to shape it as an Islamist country and to satisfy the capitalist class, they replaced the moderate socialist economy into a capitalist one. An identical procedure that was implemented by the Pakistani military ruler in the pre-independence era, had been ensued by the military dictators in independent Bangladesh.
The two military dictators and an elected government of the time discussed in this study tried to draw the attention of world leaders who were holding the same ideologies and interests that ran here by them. Consequently, the friendly and warm diplomatic relations with India came to an end and the foreign dependency of Bangladesh became dependent on Pakistan and pro-Pakistan friendly nations for the protection and support of the military government. China and the USA, who vigorously opposed our liberation war, became the key friends of Bangladesh in the diplomatic arena and our largest neighbor country without her help; we couldn\u27t possibly have our independence, became an ultimate scapegoat of our newly adopted foreign policy. A new trait in politics had been intentionally indoctrinated that was the anti-Indian sentiment. From then to now, this trait has been nurtured by most of the political parties who are now out of mainstream politics. In this study, we will try to investigate the transitions, bilateral disputes, and legacies of Bangladesh\u27s diplomatic relations with India from 1975 to 1996
Micromachined Acoustic Transducers With Embedded Vertical Capacitive Arrays
No full textAcoustic transducers are the crucial interface between acoustic signals and electrical signals, playing a pivotal role in converting and manipulating sound waves for a wide range of applications across industries and healthcare, such as non-destructive evaluation, range finding, proximity sensing, ultrasonic actuation and sensors, medical imaging probes, therapeutic ultrasound, microphones, and micro speakers. Such applications require transducers operating at frequencies spanning from tens of hertz to hundreds of megahertz. For most of the applications, generating strong acoustical signal is the most important design parameter. Achieving strong acoustic signals and heightened sensitivity demands a high output pressure per transducer unit area. To generate high output pressure per transducer unit area, higher vibration amplitude is required. When a transducer vibrates with a large vibrational amplitude, it can generate high output pressure per surface area even at a lower frequency. For example, when an acoustic membrane generates high output pressure per surface area, it would enable the membrane to produce enough audible sound at low frequency and works as a low frequency speakers or hearing aid instruments. Over the past century, acoustic transducer technology has evolved from piezoelectric crystals to contemporary
capacitive micromachined ultrasonic transducer (CMUT) or piezoelectric micromachined ultrasonic transducer (PMUT). However, current piezoelectric or electrostatic micromachined transducer face design and fabrication limitations for generating substantial vibration amplitudes.
The main objective of this work is to demonstrate a novel approach that transforms the electrostatic transduction that is conventionally performed by a closely spaced electrode next to the vibrating membrane to an array of electrostatic cells embedded within the membrane. The air gap between the fixed electrode and moveable membrane of the conventional electrostatic acoustic transducers limits the vibration amplitude in the range of tens of nm to few microns. Expanding this gap further is restricted by concerns related to reliability, difficulties in fabrication, and the need for higher operating voltages. The array structures of this research can bypass all the above-mentioned issues and enable the realization of ultrasonic transducers and microspeakers with large out-of-plane displacement, resulting in high sound pressure output per unit area at moderate operating voltage. Extremely narrow air gaps can be made in the vertical electrostatic cells which allows the devices to be operated at low operating voltage while generating high electrostatic force and energy per unit area. Electrostatic cells embedded within the membrane also facilitate the membrane to vibrate with much larger vibration amplitude compared to the conventional devices.
Using this novel approach, an acoustic membrane operating in the audible range has shown almost 5 times higher output pressure per surface area per volt compared to the state-of-the-art. Smaller membrane with a resonance frequency in the ultrasonic range would have much higher output pressure per surface area compared to the conventional CMUT and PMUT. This approach can also be used to design a much stronger MEMS micropump for drug delivery, and other MEMS devices where vibrating membrane is the crucial part
Synergy of governance, finance, and technology for sustainable natural resource management
No full textThe complexity of global supply chains and the interconnected nature of resource systems present significant challenges in ensuring equitable resource access and management. Good governance and an effective financial system are vital for managing natural resources sustainably. This study investigates the roles of good governance and innovative financial systems—including digital financial inclusion, green finance, and FinTech—in influencing natural resource management. Additionally, it explores how good governance moderates the effects of these variables on natural resources. Using a panel dataset of 18 nations for 2013–2019 years, we employ a hybrid methodology that integrates Fuzzy-set Qualitative Comparative Analysis (fsQCA), Necessary Condition Analysis (NCA), and econometric modeling. fsQCA is employed to uncover and examine intricate combinations of causal conditions of the researched variables that together contribute to natural resource management. Our findings reveal that while green finance positively impacts natural resources, FinTech and digital financial inclusion initially have negative effects. However, these negative impacts are reversed under the moderating influence of good governance, resulting in positive outcomes. High levels of good governance consistently interact with varying levels of green finance, FinTech, and digital financial inclusion to foster natural resource management. Furthermore, good governance plays a critical role in shaping the necessary conditions for sustainable resource utilization. The study emphasizes the importance of governance reforms to achieve sustainable resource management. By identifying essential conditions for natural resource utilization, the research provides actionable insights for targeted policy interventions and strategic initiatives
Integrating green tax, green logistics, green climate finance, green technology, and sustainability for a green economy: SEM-ANN approaches
No full textThe transition towards a green economy is crucial for sustainable development, yet existing research often examines key elements such as green tax, green logistics, green climate finance, green technology, and environmental sustainability in isolation. This fragmented approach fails to capture the interconnectedness and comprehensive impact of these factors. Thus, this study aims to address this gap by developing an integrated model to explore the relationships between these green factors and their collective influence on the green economy. Additionally, it investigates the mediating roles of green technology and sustainability in the green economy. Data were randomly collected from 423 managerial-level individuals across various manufacturing industries in Bangladesh through independent online surveys. “Structural Equation Modeling (SEM) was used to test direct and mediating relationships, while Artificial Neural Network (ANN) was employed to rank the factors based on their impact on the green economy. The SEM analysis revealed that green tax, green logistics, green climate finance, green technology, and environmental sustainability all positively and significantly impact the green economy. Furthermore, environmental sustainability was found to mediate the relationship between green climate finance and the green economy. ANN analysis ranked green logistics as the most critical factor, followed by green tax, environmental sustainability, green technology, and green climate finance. The findings offer valuable insights for policymakers, managers, and practitioners by highlighting the importance of an integrated approach to fostering a green economy for sustainable development. Policymakers can leverage these insights to develop comprehensive strategies that optimize resource allocation and prioritize interventions based on the ranked importance of green factors
Green technology, policy and sustainable finance nexus with SDG-12: Moderating effects of stakeholder awareness
No full textThe world is currently grappling with unparalleled environmental and social challenges that threaten sustainable development. Among these challenges, the attainment of Sustainable Development Goal-12 (SDG-12), which focuses on responsible consumption and production, is especially crucial. Thus, this study aims to investigate the impact of key factors, including green technology, policy and governance, access to sustainable finance, and stakeholder awareness, on SDG-12 by collecting 359 responses from pharmaceutical companies in Bangladesh. Employing a multi-method approach that integrates Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN), the research investigates both direct effects and moderating influences of stakeholder awareness on the relationships among the variables. The results demonstrate significant direct effects of all predictor variables on SDG-12, with access to sustainable finance exhibiting the highest impact, followed closely by green technology, stakeholder awareness, and policy and governance. Furthermore, the moderating analysis reveals that stakeholder awareness significantly strengthens the relationships between the predictor variables and SDG-12, highlighting its crucial role in promoting sustainable practices. The ANN results rank sustainable finance as the most critical factor, affirming the consistent importance of these variables across different analytical frameworks. This research contributes to the literature by offering insights into the moderating effects of stakeholder awareness within the context of stakeholder theory, providing valuable theoretical and practical implications for policymakers and practitioners in advancing sustainability initiatives
Can Renewable Energy and Export Help in Reducing Ecological Footprint of India? Empirical Evidence from Augmented ARDL Co-Integration and Dynamic ARDL Simulations
No full textThe objective of this study is to investigate the impact of exports, renewable energy, and industrialization on the ecological footprint (EF) of India over the period spanning from 1970–2017 by employing the newly developed augmented ARDL (A-ARDL) co-integration approach and the novel dynamic ARDL (D-ARDL) technique. The empirical results demonstrate that exports and renewable energy consumption reduce the EF, while industrialization intensifies the EF. More precisely, a 1% increase in export (renewable energy consumption) reduces the EF by 0.05% (0.09%). In addition, the short-run elasticity of the GDP is found to be larger than the long-run elasticity indicating the possibility of the existence of the Environmental Kuznets Curve (EKC) of the EF for India. The study indicates that the income effect and increased policy focus on renewable energy usage can be expected to reduce India’s per capita EF in the long run. Moreover, India’s export sector has been traditionally less energy intensive, which reflects in our findings of export growth leading to a reduction in EF. Based on the empirical findings, this study recommends some policy insights that may assist India to effectively reduce its ecological footprint
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