Showing papers by "International Islamic University, Chittagong published in 2020"

A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models

Abstract: Load forecasting is a pivotal part of the power utility companies. To provide load-shedding free and uninterrupted power to the consumer, decision-makers in the utility sector must forecast the future demand for electricity with a minimum error percentage. Load prediction with less percentage of error can save millions of dollars to the utility companies. There are numerous Machine Learning (ML) techniques to amicably forecast electricity demand, among which the hybrid models show the best result. Two or more than two predictive models are amalgamated to design a hybrid model, each of which provides improved performances by the merit of individual algorithms. This paper reviews the current state-of-the-art of electric load forecasting technologies and presents recent works pertaining to the combination of different ML algorithms into two or more methods for the construction of hybrid models. A comprehensive study of each single and multiple load forecasting model is performed with an in-depth analysis of their advantages, disadvantages, and functions. A comparison between their performance in terms of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values are developed with pertinent literature of several models to aid the researchers with the selection of suitable models for load prediction.

SICE: an improved missing data imputation technique

Abstract: In data analytics, missing data is a factor that degrades performance. Incorrect imputation of missing values could lead to a wrong prediction. In this era of big data, when a massive volume of data is generated in every second, and utilization of these data is a major concern to the stakeholders, efficiently handling missing values becomes more important. In this paper, we have proposed a new technique for missing data imputation, which is a hybrid approach of single and multiple imputation techniques. We have proposed an extension of popular Multivariate Imputation by Chained Equation (MICE) algorithm in two variations to impute categorical and numeric data. We have also implemented twelve existing algorithms to impute binary, ordinal, and numeric missing values. We have collected sixty-five thousand real health records from different hospitals and diagnostic centers of Bangladesh, maintaining the privacy of data. We have also collected three public datasets from the UCI Machine Learning Repository, ETH Zurich, and Kaggle. We have compared the performance of our proposed algorithms with existing algorithms using these datasets. Experimental results show that our proposed algorithm achieves 20% higher F-measure for binary data imputation and 11% less error for numeric data imputations than its competitors with similar execution time.

Biochemical and Computational Approach of Selected Phytocompounds from Tinospora crispa in the Management of COVID-19.

Abstract: A pandemic caused by the novel coronavirus (SARS-CoV-2 or COVID-19) began in December 2019 in Wuhan, China, and the number of newly reported cases continues to increase. More than 19.7 million cases have been reported globally and about 728,000 have died as of this writing (10 August 2020). Recently, it has been confirmed that the SARS-CoV-2 main protease (Mpro) enzyme is responsible not only for viral reproduction but also impedes host immune responses. The Mpro provides a highly favorable pharmacological target for the discovery and design of inhibitors. Currently, no specific therapies are available, and investigations into the treatment of COVID-19 are lacking. Therefore, herein, we analyzed the bioactive phytocompounds isolated by gas chromatography-mass spectroscopy (GC-MS) from Tinospora crispa as potential COVID-19 Mpro inhibitors, using molecular docking study. Our analyses unveiled that the top nine hits might serve as potential anti-SARS-CoV-2 lead molecules, with three of them exerting biological activity and warranting further optimization and drug development to combat COVID-19.

Drug repurposing approach against novel coronavirus disease (COVID-19) through virtual screening targeting SARS-CoV-2 main protease

Abstract: Novel coronavirus disease (COVID-19) was identified from China in December 2019 and spread rapidly through human-to-human transmission, affecting so many people worldwide. Until now, there has been no specific treatment against the disease and repurposing of the drug. Our investigation aimed to screen potential inhibitors against coronavirus for the repurposing of drugs. Our study analyzed sequence comparison among SARS-CoV, SARS-CoV-2, and MERS-CoV to determine the identity matrix using discovery studio. SARS-CoV-2 Mpro was targeted to generate an E-pharmacophore hypothesis to screen drugs from the DrugBank database having similar features. Promising drugs were used for docking-based virtual screening at several precisions. Best hits from virtual screening were subjected to MM/GBSA analysis to evaluate binding free energy, followed by the analysis of binding interactions. Furthermore, the molecular dynamics simulation approaches were carried out to assess the docked complex's conformational stability. A total of 33 drug classes were found from virtual screening based on their docking scores. Among them, seven potential drugs with several anticancer, antibiotic, and immunometabolic categories were screened and showed promising MM/GBSA scores. During interaction analysis, these drugs exhibited different types of hydrogen and hydrophobic interactions with amino acid residue. Besides, 17 experimental drugs selected from virtual screening might be crucial for drug discovery against COVID-19. The RMSD, RMSF, SASA, Rg, and MM/PBSA descriptors from molecular dynamics simulation confirmed the complex's firm nature. Seven promising drugs for repurposing against SARS-CoV-2 main protease (Mpro), namely sapanisertib, ornidazole, napabucasin, lenalidomide, daniquidone, indoximod, and salicylamide, could be vital for the treatment of COVID-19. However, extensive in vivo and in vitro studies are required to evaluate the mentioned drug's activity.

Understanding the influences of Mg doping on the physical properties of SrMoO3 perovskite

Abstract: The structural, mechanical, and electronic properties of perovskite molybdates are a topic of frequent study in materials science. In this study, the influence of Mg doping on the physical metallurgy of perovskite molybdates is investigated using first-principles calculations based on density functional theory (DFT) and molecular dynamics (MD) simulation. Our calculated optimized lattice parameters (3.9945, 3.8964, 3.8634, 3.8440, and 3.7952 A [mentioned only DFT data, MD data listed in Table 2 ] for x = 0, 0.1, 0.2, 0.3, and 0.4 respectively) of SrMo1-xMgxO3 are highly consistent with other experimental results (3.9762, 3.9695, and 3.9649 A for x = 0, 0.1, and 0.2 respectively) and some available theoretical results (3.9720 A for x = 0, no previous data available for Mg-doped systems). The calculated elastic constants satisfied the Born stability criteria, indicating that our studied materials are mechanically stable at all doping concentrations, which was also confirmed by the calculated negative values of Cohesive energy. The mechanical behaviors of perovskite, including elastic constants, elastic moduli, ductility, and elastic anisotropy, were investigated and discussed. Our computed results suggest that Mg doping can increase elastic moduli. The calculated Pugh’s ratio increased from 0.42 to 0.71 [DFT] and from 0.47 to 0.75 [MD] as well as the Poisson’s ratio decreased from 0.31 to 0.21 [DFT] and from 0.30 to 0.21 [MD] which transformed the compound from ductile to brittle due to the addition of Mg at Mo-site. The band structures, density of states, and charge density redistributions of the undoped and Mg-doped materials were predicted. Our simulation outputs clearly illustrated the importance of accounting for Mg doping’s influence in theoretical simulations of the physical properties of the presently studied perovskite material.

Deciphering the Pharmacological Properties of Methanol Extract of Psychotria calocarpa Leaves by In Vivo, In Vitro and In Silico Approaches

Abstract: The present study explores the neuropharmacological, antinociceptive, antidiarrheal, antioxidant, thrombolytic and cytotoxic activity of methanol extract of Psychotria calocarpa leaves (MEPC). In anxiolytic activity testing of MEPC by elevated plus maze test, hole-board test and light-dark test, the extract exhibited a dose-dependent reduction of anxiety while the open field test observed a decreased locomotion. The administration of MEPC revealed a significant dose-dependent reduction of depressant behavior in forced swimming and tail suspension test. Additionally, the antinociceptive and antidiarrheal activity exposed a significant reduction of nociception and diarrheal behavior at the highest dose. In addition, a strong antioxidant activity was observed in DPPH-free radical-scavenging assay (IC50 = 461.05 μg/mL), total phenol content (118.31 ± 1.12 mg) and total flavonoid content (100.85 ± 0.97 mg). The significant clot-lysis activity was also observed with moderate toxicity (LC50 = 247.92 μg/mL) level in the lethality assay of brine shrimp. Moreover, in silico molecular docking study showed that the compound Psychotriasine could offer promising active site interactions for binding proteins. Furthermore, ADME/T and toxicological properties of the compound satisfied the Lipinski's rule of five and Veber rules for drug-like potential and toxicity level. Overall, MEPC had a potential neuropharmacological, antinociceptive, antidiarrheal and antioxidant activity that warranted further investigation.

Design and parametric analysis of a wide-angle polarization-insensitive metamaterial absorber with a star shape resonator for optical wavelength applications

Abstract: Optical wavelengths considered as the key source of electromagnetic waves from the sun, and metamaterial absorber (MMA) enables various applications for this region like real invisible cloaks, color imaging, magnetic resonance imaging, light trapping, plasmonic sensor, light detector, and thermal imaging applications. Contemplated those applications, a new wide-angle, polarization-insensitive MMA is presented in this study. The absorber was formatted with three layers that consisted of a sandwiched metal-dielectric-metal structure. This formation of metamaterial absorber showed a good impedance match with plasmonic resonance characteristics. The structure was simulated using the FIT and validated with the FEM. A variety of parametric studies were performed with the design to gain best physical dimension. The mechanism of absorption also explained immensely by various significant analysis. The design had average 96.77% absorption from wavelengths of 389.34 nm to 697.19 nm and a near-perfect absorption of 99.99% at a wavelength of 545.73 nm for TEM mode. For an ultra-wide bandwidth of 102 nm, the design exhibited above 99% absorbance. The proposed is wide-angle independent up to 60° for both TE and TM mode, which is useful for solar energy harvesting, solar cell, and solar thermophotovoltaics (STPV). This MMA can be used for an optical sensor or as a light detector. Moreover, this proposed design can be employed in some applications mentioned above.

Modulation of cell signaling pathways by Phyllanthus amarus and its major constituents: potential role in the prevention and treatment of inflammation and cancer.

Abstract: The causal and functional connection between inflammation and cancer has become a subject of much research interest. Modulation of cell signaling pathways, such as those involving mitogen activated protein kinases (MAPKs), nuclear factor kappa β (NF-κB), phosphatidylinositol 3-kinase and protein kinase B (PI3K/Akt), and Wnt, and their outcomes play a fundamental role in inflammation and cancer. Activation of these cell signaling pathways can lead to various aspects of cancer-related inflammation. Hence, compounds able to modulate inflammation-related molecular targets are sought after in anticancer drug development programs. In recent years, plant extracts and their metabolites have been documented with potential in the prevention and treatment of cancer and inflammatory ailments. Plants possessing anticancer and anti-inflammatory properties due to their bioactive constituents have been reported to modulate the molecular and cellular pathways which are related to inflammation and cancer. In this review we focus on the flavonoids (astragalin, kaempferol, quercetin, rutin), lignans (phyllanthin, hypophyllanthin, and niranthin), tannins (corilagin, geraniin, ellagic acid, gallic acid), and triterpenes (lupeol, oleanolic acid, ursolic acid) of Phyllanthus amarus, which exert various anticancer and anti-inflammatory activities via perturbation of the NF-κB, MAPKs, PI3K/Akt, and Wnt signaling networks. Understanding the underlying mechanisms involved may help future research to develop drug candidates for prevention and new treatment for cancer and inflammatory diseases.

GC-MS Phytochemical Profiling, Pharmacological Properties, and In Silico Studies of Chukrasia velutina Leaves: A Novel Source for Bioactive Agents.

Abstract: Chukrasia velutina is a local medicinal plant commonly known as chikrassy in Bangladesh, India, China, and other South Asian countries. The leaves, bark, and seeds are vastly used as herbal medicine for fever and diarrhea, and its leaves essential oils are used for antimicrobial purposes. In this study, we discuss the neuropsychiatric properties of C. velutina leaves through several animal models, quantitative and qualitative phytochemical analysis, and computational approaches. Neuropsychiatric effects were performed in rodents on the methanolic extract of C. velutina leaves (MECVL). Antidepressant, anxiolytic, and sedative effects experimented through these rodent models were used such as the force swimming test (FST), tail suspension test (TST), hole board test (HBT), elevated plus maze test (EPMT), light/dark box test (LDBT), open field test (OFT), and hole cross test (HCT). In these rodent models, 200 and 400 mg/kg doses were used which exhibited a significant result in the force swimming and tail suspension test (p < 0.001) for the antidepressant effect. In the anxiolytic study, the results were significant in the hole board, elevated plus maze, and light/dark box test (p < 0.001) for doses of 200 and 400 mg/kg. The result was also significant in the open field and hole cross test (p < 0.001) for sedative action in the sake of similar doses. Moreover, qualitative and quantitative studies were also performed through phytochemical screening and GC-MS analysis, and fifty-seven phytochemical compounds were found. These compounds were analyzed for pharmacokinetics properties using the SwissADME tool and from them, thirty-five compounds were considered for the molecular docking analysis. These phytoconstituents were docking against the human serotonin receptor, potassium channel receptor, and crystal structure of human beta-receptor, where eight of the compounds showed a good binding affinity towards the respective receptors considered to the reference standard drugs. After all of these analyses, it can be said that the secondary metabolite of C. velutina leaves (MECVL) could be a good source for inhibiting the neuropsychiatric disorders which were found on animal models as well as in computational studies.

Teaching English to the Test: Why Does Negative Washback Exist within Secondary Education in Bangladesh?

Abstract: This article reports on a study that was carried out to explore the factors that contribute to a negative washback effect on English language teaching (ELT) in secondary schools in Bangladesh. Twel...

Cornus officinalis Ethanolic Extract with Potential Anti-Allergic, Anti-Inflammatory, and Antioxidant Activities.

Abstract: Atopic dermatitis (AD) is an allergic and chronic inflammatory skin disease. The present study investigates the anti-allergic, antioxidant, and anti-inflammatory activities of the ethanolic extract of Cornus officinalis (COFE) for possible applications in the treatment of AD. COFE inhibits the release of β-hexosaminidase from RBL-2H3 cells sensitized with the dinitrophenyl-immunoglobulin E (IgE-DNP) antibody after stimulation with dinitrophenyl-human serum albumin (DNP-HSA) in a concentration-dependent manner (IC50 = 0.178 mg/mL). Antioxidant activity determined using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, ferric reducing antioxidant power assay, and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) scavenging activity, result in EC50 values of 1.82, 10.76, and 0.6 mg/mL, respectively. Moreover, the extract significantly inhibits lipopolysaccharide (LPS)-induced nitric oxide (NO) production and the mRNA expression of iNOS and pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α) through attenuation of NF-κB activation in RAW 264.7 cells. COFE significantly inhibits TNF-α-induced apoptosis in HaCaT cells without cytotoxic effects (p < 0.05). Furthermore, 2-furancarboxaldehyde and loganin are identified by gas chromatography/mass spectrometry (GC-MS) and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis, respectively, as the major compounds. Molecular docking analysis shows that loganin, cornuside, and naringenin 7-O-β-D-glucoside could potentially disrupt the binding of IgE to human high-affinity IgE receptors (FceRI). Our results suggest that COFE might possess potential inhibitory effects on allergic responses, oxidative stress, and inflammatory responses.

Corporate governance and banks’ productivity: evidence from the banking industry in Bangladesh

Abstract: Though remarkable literature exploring productivity and efficiency has emerged since the last half of the previous century, but dearth studies have been found in showing the impact of corporate governance on banks’ productivity. The study aims to investigate the banks’ productivity and its relationship with corporate governance. For this purpose, the study examines the productivity of 30 listed banks of Bangladesh deploying a Malmquist Productivity Index (an extension of Data Envelopment Analysis) with a panel data covering the period of five years from 2013 to 2017. The empirical results show that the average productivity of the banks is 1.03%. Finally, the ordinary least square (OLS), fixed effect (FE), and random effect (RE) regression were run separately. The research outcomes show that the productivity of the Bangladeshi banks is significantly influenced by financial performance, ownership structure, and board characteristics. The study provides the researchers, academicians, management of the banks, and regulatory body a new insight of how corporate governance influences the banks’ productivity so that they can formulate a better policy to generate more productivity.

Intervention in Neuropsychiatric Disorders by Suppressing Inflammatory and Oxidative Stress Signal and Exploration of In Silico Studies for Potential Lead Compounds from Holigarna caustica (Dennst.) Oken leaves.

Abstract: Holigarna caustica (Dennst.), a popular plant used in folk medicine in Bangladesh, is often used by the local folk practitioner to treat a variety of chronic diseases. The present research is an attempt to find out an innovative therapeutic prospect for the management of neuropsychiatric disorders. The methanol extract of H. caustica leaves (MEHC) were utilized on various behavioral tests for assessing anxiolytic, anti-depressant, and anti-inflammatory activities. The antioxidant potentials and quantitative phytochemicals were evaluated through spectrophotometric methods. Results revealed that treatment of MEHC (200 and 400 mg/kg) significantly reduced anxiety like behaviors in mice, particularly, 400 mg/kg efficiently improved % of entries and time spent (p < 0.05) in the open arms in elevated plus maze test, whereas, superior head dipping tendency (p < 0.05) was observed in hole-board test. In contrast, mice treated with 200 mg/kg revealed better anxiolytic effect in both open field and hole-cross tests. During antidepressant evaluation, mice administrated with MEHC exhibited active behaviors (swimming and struggling) in forced swimming and tail suspension tests. In parallel, MEHC manifested a noteworthy (p < 0.001) suppression of inflammatory response induced by histamine. The MEHC also showed strong antioxidant activities in 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) (IC50: 57.64 μg/mL) scavenging, H2O2 (IC50: 51.60 μg/mL) scavenging, and ferric reducing power assay. The levels of total phenol, flavonoid, flavonol, condensed tannin, and antioxidant were estimated as higher in MEHC. Moreover, 11 compounds were documented as bioactive, displayed good binding affinities to potassium channel receptor, human serotonin receptor, cyclooxygenase (COX-1 and 2), and xanthine oxidoreductase enzyme targets in molecular docking experiments. Furthermore, ADME/T and Prediction of Activity Spectra for Substances (PASS) analyses exposed their drug-likeness, nontoxic upon consumption, and likely pharmacological actions. Overall, the H. caustica is potentially bioactive as evident by in vivo, in vitro, and computational analysis. Our findings support the folkloric value of this plant, which may provide a potential source towards developing drug leads.

Pharmacological and computer-aided studies provide new insights into Millettia peguensis Ali (Fabaceae).

Abstract: Millettia peguensis, popular for its ethnopharmacological uses, was employed to evaluate its different pharmacological properties in this study. The analgesic studies of the plant have been performed by acetic acid-induced writhing and formalin-induced licking tests respectively, whereas the antidiarrheal experiment was done by castor oil-induced diarrheal test. Besides, antioxidant, cytotoxic, antimicrobial, thrombolytic evaluations were performed by DPPH scavenging with phenol content determination, brine shrimp lethality, disc diffusion and clot lysis methods respectively. Moreover, in silico study of the phytoconstituents was carried out by molecular docking and ADME/T analysis. The methanol extract of Millettia peguensis (MEMP) revealed significant biological activity in the analgesic and antidiarrheal test (p

Comprehensive first-principles calculations on physical properties of ScV2Ga4 and ZrV2Ga4 in comparison with superconducting HfV2Ga4

Abstract: We use first-principles method for a comprehensive investigation of structural, elastic, electronic, Mulliken atomic population based bonding, phonon, thermodynamic and optical properties of ScV2Ga4 and ZrV2Ga4 in comparison with the isostructural HfV2Ga4 superconductor. The single and polycrystalline elastic constants are all evaluated and discussed. Cell stability employing elastic constants criteria, formation enthalpy and phonon dispersion are verified. Brittleness and hardness features are also discussed. Elastic anisotropies are evaluated and discussed to unravel some of the macroscopic behaviors of the studied compounds. The significant overlapping between conduction and valence bands in the vicinity of Fermi level (EF) confirms the metallic characteristics for MV2Ga4 (M = Hf, Sc, Zr). It is predicted that the TDOS around the EF arises mostly from V–3d with a smaller contribution of Ga–4p states. The Fermi surfaces show multiband nature but that of ScV2Ga4 has different and complex shape in contrast to ZrV2Ga4 and superconducting HfV2Ga4. The bonding characteristics are analyzed using the energy band structure, charge density distribution and Mulliken atomic and bond overlap population. Such analysis exhibits directional electronic density-channel, highly populated 1D V leashed in (100) plane in the lattices. The formation of such V-chains which accumulate the highest electronic charge might generate Cooper pairs to exhibit superconducting behavior in the yet unobserved Sc and Zr containing compounds. The phonon dispersion curves, phonon density of states and optical phonon frequencies, Raman and infrared activities of the materials are discussed for the first time. The temperature dependent thermodynamic properties including heat capacity at constant pressure are calculated as a function of temperature and compared with the available data. Various optical properties are calculated and their features are analyzed. The potentials of the compounds for practical uses as coating materials to reduce solar heating and enhance radiative cooling are also mentioned.

A Wide Incident Angle, Ultrathin, Polarization-Insensitive Metamaterial Absorber for Optical Wavelength Applications

Abstract: Polarization-insensitive metamaterial absorbers (MMAs) are currently attracting a great deal of interest throughout the optical region. These kinds of MMAs can be used as energy harvesting, thermal imaging, plasmonic sensor, magnetic imaging, light trapping, optical modulator, and can help to decipher an inherence for the field. Here, a polarization-insensitive ultrathin MMA has been proposed with an extensive incident angular stability for the optical region with a sandwiched three-layer structure. Tungsten (W) and silicon dioxide (SiO2) have been chosen as materials for their various advantages in the optical spectrum with higher temperature stability. The design simulated with the finite integration technique (FIT), and validation of the simulated data is assured with the interference theory model (ITM). Underlying physics of the absorption characteristics and performance of the structure are immensely explained. The design acquired an average absorption of 96.7% from 380nm to 700nm and 96.61% for both transverse electric (TE) and transverse magnetic (TM) polarization. It has a peak absorption of 99.99% at 498.25nm, and over 99% from 460nm to 540nm, due to a very good impedance match with plasmonic resonance characteristics. For both TE and TM mode, it has wide angular independence up to 60°, which can be used for solar cell and solar thermo-photovoltaics (STPV). The various parametric sweep also analyzed for acquiring the geometric shape with a wide bandwidth to find resonance wavelength. As the MMA shifts its resonance wavelength with the change of its dielectric thickness, it can be used as an optical sensor. Changing dielectric in a Pyrex will enable the structure to be used as a light detector. Such outstanding absorption properties render the proposed MMA a successful candidate for the optical wavelength applications mentioned above.

The Genus Curcuma and Inflammation: Overview of the Pharmacological Perspectives.

Abstract: The Curcuma genus has been extensively used for therapeutic purposes in traditional or folk medicine worldwide, including for its anti-inflammatory activity. Curcuma spp.'s active constituents, such as alkaloids, flavonoids, and terpenoids, can act on various targets in the signaling pathway, restrain pro-inflammatory enzymes, lower the production of inflammatory cytokines and chemokines, and reduce oxidative stress, which subsequently suppresses inflammatory processes. Preclinical and clinical studies have reported the predominant anti-inflammatory activity of several Curcuma species. This review provides an overview of the anti-inflammatory effects of different extracts, preparations, and bioactive components in this genus. This analysis may provide a scientific basis for developing new and alternative methods for the isolation of a single entity from this genus to attenuate inflammatory conditions. The Curcuma genus is waiting for researchers interested in developing safe and efficient anti-inflammatory agents for further investigation.

Physical properties of a novel boron-based ternary compound Ti2InB2

Abstract: The present study aims to investigate the structural, mechanical, thermal, dynamic and optical properties of a new type and recently synthesized 212 MAX phase Ti2InB2 in comparison with other 211 MAX phases (Ti2InC, Ti2SnC and Ti2AlC). Our calculated lattice parameters show excellent agreement with the available data. The obtained elastic constants and phonon dispersion spectra confirm the mechanical and dynamical stability of the new compound. The studied MAX phases are found to be brittle in nature. In Ti2InB2, the B B bonds exist with the larger bond population, indicating its high covalent nature, makes it stiffer than the typical 211 MAX phases, particularly, Ti2InC. Consequently, Ti2InB2 possesses high C11, C33, B, G and Y compared with Ti2InC. The calculated hardness of the newly synthesized Ti2InB2 is the highest among all the MAX phases under consideration. Temperature and pressure dependent thermal properties are investigated through quasi-harmonic Debye model for the first time. The heat capacity of Ti2InB2 at room temperature with the inclusion of lattice and electronic contribution is higher than those of other studied 211 MAX phases. The optical reflectivity suggests that the studied MAX compounds can be promising candidates as protective coating of other materials against solar heating.

Traditional Herbal Medicines Against CNS Disorders from Bangladesh

Abstract: The majority of the population in Bangladesh uses traditional plant-based medicines to manage various ailments, including central nervous system (CNS) disorders. This review presents ethnobotanical information and relevant scientific studies on plants used in traditional healthcare for the management of various CNS disorders in Bangladesh. The information on the medicinal plants of Bangladesh effective against CNS disorders published in scientific journals, books, and reports was compiled from different electronic databases using specific key words. The present article provides comprehensive information on a total of 224 medicinal plant species belonging to 81 families used for the treatment of CNS disorders by the various peoples of Bangladesh. In total, we reviewed more than 290 relevant papers. In this study, leaves were found as the most often used plant organ, followed by roots, fruits, whole plants, barks, seeds, stems, rhizomes, and flowers. The Fabaceae family contributes the highest number of used species, followed by Rubiaceae, Lamiaceae, Cucurbitaceae, Vitaceae, Euphorbiaceae, Malvaceae, and Zingiberaceae. The most frequently used species (in decreasing order) are Asparagus racemosus, Centella asiatica, Stephania japonica, Aegle marmelos, Coccinia grandis, Tabernaemontana divaricata, Bacopa monnieri, Abroma augusta, and Scoparia dulcis. This review may serve as a starting point for a rational search for neuroactive natural products against CNS disorders within the Flora of Bangladesh.

Pharmacological studies on the antinociceptive, anxiolytic and antidepressant activity of Tinospora crispa

Abstract: Pharmacological studies were performed in mice on the methanol extract of Tinospora crispa (TC), and of its hexane (HF) and chloroform (CF) fractions. Significant antinociceptive activity was observed for TC, HF, and CF in the acetic acid-induced writhing and formalin-induced paw licking tests. Anxiolytic and antidepressant activity were assessed using the open field, hole board, and elevated plus maze (EPM) tests. TC, HF, and CF demonstrated a significant decrease in spontaneous locomotor activity. They also showed an increase in the number of head-dippings in the hole board test, suggesting decreased fearfulness. TC, and most of its fractions, showed a significant increase of the time spent in the opened arm of the EPM, indicating reduced anxiety. A computational study (PASS prediction, molecular docking and ADME/T analyses) was performed to identify the phytochemicals responsible for activity. Syringin and secoisolariciresinol, displayed a strong predictive binding affinity towards the cyclooxygenase COX-1 and COX-2 enzymes and the KcsA potassium channel while rumphioside B showed the highest predicted binding affinity towards the human serotonin receptor. This provided some support to explain the observed in-vivo antinociceptive, anxiolytic and antidepressant effects and the traditional use of T. crispa as a remedy for pain.

Newly synthesized A-site ordered cubic-perovskite superconductor (Ba0.54K0.46)4Bi4O12: A DFT investigation

Abstract: Theoretical investigation of the elastic, electronic, superconducting, and thermal properties of newly synthesized cubic perovskite superconductor (Ba0.54K0.46)4Bi4O12 (BKBO) is carried out by generalized gradient approximation (GGA) which is based on density functional theory (DFT). Comparisons are made with two recently discovered Bi-basedAA'3B4O12-typeperovskite superconductors (Na0.25K0.45)Ba3Bi4O12 and (K1.00)(Ba1.00)3(Bi0.89Na0.11)4O12 and with available experimental data of (Ba0.54K0.46)4Bi4O12 perovskite. The elastic constants, mechanical stability, machinability index, Poisson's ratio, Cauchy's pressure, elastic anisotropy, Vickers hardness and Peierls stress are all investigated. The electronic band structure, density ofstates, features of Fermi surface and distributions of charge density are studied as well. Hybridization involving Bi-6s and O-2p orbitals (dominant contribution) is observed at EF similar to that seen in the previously published Bi-based perovskite superconductors. Both electron and hole like Fermi surfaces are seen which exhibits multiband nature of the superconductor. The flatness of the Fermi surface promotes transport features in Bi-based perovskite superconductor. The distribution of charge density of BKBO is basically spherical around all ions which essentially reveal the ionic characteristics of the material. The thermal properties, namely, Debye temperature, specific heat capacities and volume thermal expansion coefficient as a function of temperature areanalyzed with the help of quasi-harmonic Debye model. The estimated electron-phonon (e-ph) coupling constant of (Ba0.54K0.46)4Bi4O12 indicates its typical nature of a strongly coupled superconductor similar to the previously studied isostructural perovskites superconductors.

An Integrated CNN-LSTM Model for Micro Hand Gesture Recognition

Abstract: Vision based micro gesture recognition systems enable the development of HCI (Human Computer Interaction) interfaces to mirror real-world experiences. It is unlikely that a gesture recognition method will be suitable for every application, as each gesture recognition system rely on the user cultural background and application domain. This research is an attempt to develop a micro gesture recognition system suitable for the asian culture. However, hands vary in shapes and sizes while gesture varies in orientation and motion. For accurate feature extraction, deep learning approaches are considered. Here, an integrated CNN-LSTM (Convolutional Neural Network- Long Short-Term Memory) model is proposed for building micro gesture recognition system. To demonstrate the applicability of the system two micro hand gesture-based datasets namely, standard and local dataset consisting of ten significant classes are used. Besides, the model is tested against both augmented and unaugmented datasets. The accuracy achieved for standard data with augmentation is 99.0%, while the accuracy achieved for local data with augmentation is 96.1% by applying CNN-LSTM model. In case of both the datasets, the proposed CNN-LSTM model appears to perform better than the other pre-trained CNN models including ResNet, MobileNet, VGG16 and VGG9 as well as CNN excluding LSTM.