Assessment of Drinking Water Quality Served in Different Restaurants at Islam Nagor Road Adjacent to Khulna University Campus, Bangladesh

Potable water is a growing requirement for sound health as contaminated water and water-borne pathogens pose serious health risks to human beings. Considering this issue, the current study aimed to assess the drinking water quality served in different restaurants close to the Khulna University campus in Bangladesh. A total number of ten drinking water samples were collected from different restaurants. Afterward, the collected water samples were analyzed to examine the physico-chemical properties and microbiological contamination of the water samples. Besides, microbial properties such as Total Coliform (TC), Fecal Coliform (FC), and E. coli were analyzed by the Membrane Filtration (MF) technique. The findings suggest that all the physico-chemical attributes were within the permissible limits regarding recommended Bangladesh standards and WHO guidelines. But in case of EC, 40% of the samples exceeded the WHO permissible limits and for sodium, 10% of samples exceeded both the BD and WHO standards. In addition, the results disclosed that the drinking water served in different restaurants was contaminated by TC, FC, and E. coli. It is observed that 100% of the samples were contaminated by TC and FC whereas 70% of the samples were contaminated by E. coli. Consequently, it is clearly evident that the water is considered suitable with respect to physico-chemical analysis but this drinking water is unfit for consumption while taking into account its microbiological quality. The total coliform, fecal coliform, and E. coli count attests to the fact that anyone can become harmed at any moment by ingesting water from roadside restaurants. Finally, due to bacterial contamination, the served drinking water in these places doesn’t meet safe and suitable water excellence, therefore, consumption of this water is deleterious to public health.

Surface Morphology and Thermo-Electrical Energy Analysis of Polyaniline (PANI) Incorporated Cotton Fabric

With the exponential development in wearable electronics,a significant paradigm shift is observed from rigid electronics to flexible wearable devices.Polyaniline(PANI)is considered as a dominant material in this sector,as it is endowed with the optical properties of both metal and semiconductors.However,its widespread application got delineated because of its irregular rigid form,level of conductivity,and precise choice of solvents.Incorporating PANI in textile materials can generate promising functionality for wearable applications.This research work employed a straightforward in-situ chemical oxidative polymerization to synthesize PANI on Cotton fabric surfaces with varying dopant(HCl)concentrations.Pre-treatment using NaOH is implemented to improve the conductivity of the fabric surface by increasing the monomer absorption.This research explores the morphological and structural analysis employing SEM,FTIR and EDX.The surface resistivity was measured using a digital multimeter,and thermal stability is measured using TGA.Upon successful polymerization,a homogenous coating layer is observed.It is revealed that the simple pre-treatment technique significantly reduces the surface resistivity of Cotton fabric to 1.27 kΩ/cm with increasing acid concentration and thermal stability.The electro-thermal energy can also reach up to 38.2°C within 50 s with a deployed voltage of 15 V.The modified fabric is anticipated to be used in thermal regulation,supercapacitor,sensor,UV shielding,antimicrobial and other prospective functional applications.

Is the Sundarbans of Bangladesh in a State of Pollution?

The Sundarbans is the world’s most extensive natural mangrove forest and home to various natural resources. The population in the vicinity has increased, causing more dependency on the resources of the Sundarbans. The increasing industrialization, urbanization, aquaculture, intensive agricultural practices, seaports, tourism facilities, and so on in the peripheral areas of the Sundarbans have made significant changes in the surrounding and upstream land uses of the Sundarbans. This situation may have detrimental influences on the ecosystem components of the Sundarbans. Therefore, it is highly demanded to prepare a piece of baseline information or database of different sources of pollution and their present status in the various components of the Sundarbans. This effort helps to identify issues and concerns, determine the key elements of the ecosystem to monitor the level or overall quality of the Sundarbans ecosystem. The present study systematically collects the potential sources of pollution, types, and current levels in the ecosystem components of the Sundarbans using academic databases, libraries, and online resources. Discharge of industrial waste into water, soil and air, heavy metal pollution, use of agrochemicals, oil (refined and crude) pollution, plastic materials from urban areas, and tourism are the major issues and concerns related to the sustainability of the Sundarbans ecosystem. The air quality of the Sundarbans is in good condition with 0 - 50 AQI of Bangladesh. While BOD, COD, TDS, TSS varied from 2.0 to 3.8 mg/L, 21.6 to 416 mg/L, 146.9 to 24,100 mg/L and 54 to 155 mg/L, respectively. Soil EC, organic carbon, total nitrogen, and total phosphorus ranged from 3.01 - 5.82 mS/cm, 1.41% - 2.69%, 0.51 - 1.05 mg/g, and 0.32 - 0.51 mg/g respectively. The air, water and soil quality parameters varied with the sites and seasons and not much at the state of contamination. Indeed, we must pay much attention to the Sundarbans’ air, water and soil quality with the massive and progressive change of the nearby land use pattern.

Environmental Study on a Coastal River of Bangladesh with Reference to Irrigation Water Quality Assessment: A Case Study on Shailmari River, Khulna

Water quality is the critical environmental determinant that influences the agricultural production and therefore, the economy that solely depends on its agricultural productions. Batiaghata Upazilla is one of the major crop productive areas of Khulna region and the agricultural production here largely depends on the natural water of the Shailmari River system around it. The present study was conducted to assess the suitability of this coastal river water for irrigational use. 66 water samples were collected during this study in three consecutive agricultural seasons, viz., pre-monsoon (22), monsoon (22) and post-monsoon (22) from 11 sampling stations within the river system considering the high (11) and ebb (11) tides for each station. Standard methods were followed throughout the study period for the collection of the samples and analysis of major physicochemical parameters (pH, EC, TDS, salinity, Na, K, Ca, Mg, Cl, HCO3, SO4, NO3 and PO4). Hydrocehmical characterization using Piper trilinear diagram shows that the water of the river system is Na-Cl dominated saline water type in pre-monsoon, whilst most of the samples of the river and the connected channel are characterized as fresh water of Ca-Mg-Na-HCO3 and Ca-Na-Mg-HCO3 types in monsoon and post-monsoon respectively. The calculated values of chemical indices like SAR, %Na, KI, PI and MH using the results of the analysed parameters indicate that the river water is chemically unsuitable for use in irrigation during pre-monsoon, while in the monsoon and post-monsoon the river water is within good to permissible limit for the use in the agricultural fields. However, high %Na, KI and MH values with high salinity of the channel water limit its use in agricultural applications in monsoon and post-monsoon. The USSL (United States Salinity Laboratory) diagram depicts that the river water is C4-S4 type with very high salinity and sodium content in pre-monsoon, while in other seasons the water is mostly C1-S1, C2-S1 or C2-S2 types (low to moderate salinity and sodium) in the river. Wilcox diagram shows that the river water is “suitable” for irrigation during monsoon and post-monsoon as the most of the samples range within “Excellent to Good” and “Good to permissible” categories, while it is “unsuitable” for crop irrigation during pre-monsoon when SAR (Sodium Adsorption Ratio) and EC (Electrical Conductivity) values of the water reach to their peaks.

Assessment of Spatio-Temporal Variations in Water Quality of Shailmari River, Khulna (Bangladesh) Using Multivariate Statistical Techniques

Surface water has become one of the most vulnerable resources on the earth due to deterioration of its quality from diverse sources of pollution. Understanding of the spatiotemporal distribution of pollutants and identification of the sources in the river systems is a prerequisite for the protection and sustainable utilization of the water resources. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA) were applied in this study to investigate the temporal and spatial variations of water quality and appoint the major factors of pollution in the Shailmari River system. Water quality data for 14 physicochemical parameters from 11 monitoring sites over the year of 2014 in three sampling seasons were collected and analyzed for this study. Kruskal-Wallis test showed significant (p < 0.01) temporal and spatial variations in all of the water quality parameters of the river water. Principal component analysis (PCA) allowed extracting the contributing parameters affecting the seasonal water quality in the river system. Scatter plots of the PCs showed the tidal and spatial variation within river system and identified parameters controlling the behavior in each case. Factor analysis (FA) further reduced the data and extracted factors which are significantly responsible for water quality variation in the river. The results indicate that the parameters controlling the water quality in different seasons are related with salinity, anthropogenic pollution (sewage disposal, effluents) and agricultural runoff in pre-monsoon;precipitation induced surface runoff in monsoon;and erosion, oxidation or organic pollution (point and non-point sources) in post-monsoon. Therefore, the study reveals the applicability and usefulness of the multivariate statistical methods in assessing water quality of river by identifying the potential environmental factors controlling the water quality in different seasons which might help to better understand, monitor and manage the quality of the water resources.

Characterization and Laboratory-Scale Treatment of Municipal Drainage Wastewater of Khulna, Bangladesh

The study was conducted to characterize and perform laboratory-scale treatment of municipal drainage wastewater of Khulna, Bangladesh. Wastewater samples were collected from three different points of existing urban drain outlets into the Mayur River around Khulna. Laboratory testing shows the BOD5 and COD concentration of wastewater samples varied from 57 - 226 mg/l and 320 - 435 mg/l, respectively, and the total dissolved solids ranged from 1800 - 2525 mg/l. Therefore, a laboratory-scale treatment technology was developed to treat this wastewater. Treatment technologies adopted were primary sedimentation, followed by aeration, chemical precipitation and filtration. In treated wastewater, BOD5, COD and TDS were found to be in the range of 40 - 115 mg/l, 160 - 256 mg/l and 1356 - 1500 mg/l, respectively. These test results suggest that the performance of laboratory-scale treatment plant was not adequate to fulfil the acceptable limit (ECR’97) for safe disposal into surface water bodies. Due to poor quality of effluents, modification of laboratory-scale treatment plant was made by an activated sludge process followed by granular media filtration. The final BOD5, COD TDS and TSS concentration of effluents was found to be 1.38 - 9.8 mg/l, 32 - 192 mg/l, 590 - 1667 mg/l, and 35 - 95 mg/l respectively, which satisfy ECR’97 standard limits for safe disposal into inland water bodies.

Unmanned Aerial Vehicle Assisted Forest Fire Detection Using Deep Convolutional Neural Network

Disasters may occur at any time and place without little to no presage in advance.With the development of surveillance and forecasting systems,it is now possible to forebode the most life-threatening and formidable disasters.However,forestfires are among the ones that are still hard to anticipate beforehand,and the technologies to detect and plot their possible courses are still in development.Unmanned Aerial Vehicle(UAV)image-basedfire detection systems can be a viable solution to this problem.However,these automatic systems use advanced deep learning and image processing algorithms at their core and can be tuned to provide accurate outcomes.Therefore,this article proposed a forestfire detection method based on a Convolutional Neural Network(CNN)architecture using a newfire detection dataset.Notably,our method also uses separable convolution layers(requiring less computational resources)for immediatefire detection and typical convolution layers.Thus,making it suitable for real-time applications.Consequently,after being trained on the dataset,experimental results show that the method can identify forestfires within images with a 97.63%accuracy,98.00%F1 Score,and 80%Kappa.Hence,if deployed in practical circumstances,this identification method can be used as an assistive tool to detectfire outbreaks,allowing the authorities to respond quickly and deploy preventive measures to minimize damage.

Fabrication of graphene oxide-keratin-chitosan nanocomposite as an adsorbent to remove turbidity from tannery wastewater

Excessive turbidity in water is aesthetically unappealing and severely malfunctions the photosynthesis process of aquatic ecosystems. This study aimed to evaluate the effectiveness of a nanocomposite adsorbent made of graphene oxide-keratin-chitosan for removing turbidity from tannery influent. The nanocomposite was fabricated with simple solution casting methods. Material dispersibility, bonding between composite materials (amide linkage), and the surface morphology of the nanocomposite were analyzed with the ultraviolet-visible spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. At pH of 6, 2 g/L of adsorbent and a 25-min contact time resulted in about 88% of turbidity elimination. After the adsorption process, the total suspended solids, total dissolved solids, salinity, biochemical oxygen demand, and chemical oxygen demand of the tannery wastewater were reduced by 55%, 29%, 12%, 58%, and 75%, respectively. The optimum dosage of the nanocomposite with the maximum turbidity removal capacity was 12.62 mg/g. According the adsorption kinetic and isotherm models, the graphene oxide-keratin-chitosan nanocomposite played a key role in the turbidity removal process with chemisorption and electrostatic multilayer adsorption. This study provided methodological and mechanistic insights into the procedures of investigating the removal of turbidity from tannery wastewater with a novel composite material.

A Highly Accurate Dysphonia Detection System Using Linear Discriminant Analysis

The recognition of pathological voice is considered a difficult task for speech analysis.Moreover,otolaryngologists needed to rely on oral communication with patients to discover traces of voice pathologies like dysphonia that are caused by voice alteration of vocal folds and their accuracy is between 60%–70%.To enhance detection accuracy and reduce processing speed of dysphonia detection,a novel approach is proposed in this paper.We have leveraged Linear Discriminant Analysis(LDA)to train multiple Machine Learning(ML)models for dysphonia detection.Several ML models are utilized like Support Vector Machine(SVM),Logistic Regression,and K-nearest neighbor(K-NN)to predict the voice pathologies based on features like Mel-Frequency Cepstral Coefficients(MFCC),Fundamental Frequency(F0),Shimmer(%),Jitter(%),and Harmonic to Noise Ratio(HNR).The experiments were performed using Saarbrucken Voice Data-base(SVD)and a privately collected dataset.The K-fold cross-validation approach was incorporated to increase the robustness and stability of the ML models.According to the experimental results,our proposed approach has a 70%increase in processing speed over Principal Component Analysis(PCA)and performs remarkably well with a recognition accuracy of 95.24%on the SVD dataset surpassing the previous best accuracy of 82.37%.In the case of the private dataset,our proposed method achieved an accuracy rate of 93.37%.It can be an effective non-invasive method to detect dysphonia.

An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization

Colorization is the practice of adding appropriate chromatic values to monochrome photographs or videos.A real-valued luminance image can be mapped to a three-dimensional color image.However,it is a severely ill-defined problem and not has a single solution.In this paper,an encoder-decoder Convolutional Neural Network(CNN)model is used for colorizing gray images where the encoder is a Densely Connected Convolutional Network(DenseNet)and the decoder is a conventional CNN.The DenseNet extracts image features from gray images and the conventional CNN outputs a^(*)b^(*)color channels.Due to a large number of desaturated color components compared to saturated color components in the training images,the saturated color components have a strong tendency towards desaturated color components in the predicted a^(*)b^(*)channel.To solve the problems,we rebalance the predicted a^(*)b^(*)color channel by smoothing every subregion individually using the average filter.2 stage k-means clustering technique is applied to divide the subregions.Then we apply Gamma transformation in the entire a^(*)b^(*)channel to saturate the image.We compare our proposed method with several existing methods.From the experimental results,we see that our proposed method has made some notable improvements over the existing methods and color representation of gray-scale images by our proposed method is more plausible to visualize.Additionally,our suggested approach beats other approaches in terms of Peak Signal-to-Noise Ratio(PSNR),Structural Similarity Index Measure(SSIM)and Histogram.

Modification of the Convergence of GG-PPA for Solving Generalized Equations

A modified Gauss-type Proximal Point Algorithm (modified GG-PPA) is presented in this paper for solving the generalized equations like 0 &#8712;T(x), where T is a set-valued mapping acts between two different Banach spaces X and Y. By considering some necessary assumptions, we show the existence of any sequence generated by the modified GG-PPA and prove the semi-local and local convergence results by using metrically regular mapping. In addition, we give a numerical example to justify the result of semi-local convergence.

Minimization of Air Consumption and Potential Savings of Textile Denim Fabric Manufacturing Process

One of the most important aspects of Bangladesh’s textile industry is denim. Bangladesh now has a new opportunity thanks to the global demand for denim among fashion industry professionals. Entrepreneurs from Bangladesh provide denim products to well-known international merchants all over the world. The worldwide denim market is predicted to expand by roughly 8% through the year 2020. We must raise the standard of denim if we are to keep up with the expanding industry. In contrast to projectile and rapier systems, air-jet weaving machines nowadays can weave practically all types of yarns without any issues and at higher rates. Due to this, air-jet looms are an excellent substitute for other weft insertion techniques. This kind of device still has one significant flaw, though, and that is the enormous power consumption brought on by the creation of compressed air. Researchers and manufacturers of air-jet looms have therefore worked very hard to find a solution to this issue and achieve a huge reduction in air consumption without compromising loom performance or fabric quality. Therefore, the purpose of this project is to look into ways to decrease air consumption and reduce auxiliary selvedge waste without any decrease in loom performance and fabric quality on existing air-jet weaving looms which reduce the manufacturing costs with process improvement. Just updating the air pressure allowed a weaving mill to reduce air usage by 11 cfm. So, with just almost no cost, a company with 100 looms could save $0.15 M each year, on compressed air. Two new methods for decreasing process costs on air jet looms have also been developed by this project work.

A Numerical Simulation of Air Flow in the Human Respiratory System Based on Lung Model

The lung is an important organ that takes part in the gas exchange process. In the study of gas transport and exchange in the human respiratory system, the complicated process of advection and diffusion (AD) in airways of human lungs is considered. The basis of a lumped parameter model or a transport equation is modeled during the inspiration process, when oxygen enters into the human lung channel. The quantitative measurements of oxygen are detached and the model equation is solved numerically by explicit finite difference schemes. Numerical simulations were made for natural breathing conditions or normal breathing conditions. The respiratory flow results for the resting conditions are found strongly dependent on the AD effect with some contribution of the unsteadiness effect. The contour of the flow rate region is labeled and AD effects are compared with the variation of small intervals of time for a constant velocity when breathing is interrupted for a negligible moment.

Optimization of Finishing Process and Energy Savings in Denim Textile Facility

Denim is widely accepted among exported textile products due to its aesthetics, appearance, and fashion. Practitioners employed several physical or chemical treatments to improve denim qualities in denim finishing operations. So, several treatment processes, including enzymatic, bleaching, singeing, heat set, and ozone finish, are used, which made this processing more energy consumption and time-consuming. Therefore, it is significant to investigate how changing the chemicals and raw ingredients could improve the finishing process, which is environmentally and economically beneficial for sustainable production practices in the denim finishing process. This study’s research design comprises an experimental investigation in a denim plant in Bangladesh. Two different fabrics were chosen to analyze, determining the potential savings of finishing on the denim fabrics’ performance characteristics. By deducting singeing and heat-set processes, the researchers ran an experimental process by maintaining the same length of fabric. Then, the impacts of finishing process optimization on the mechanical, thermal, and comfort parameters of drape, stiffness, and tear strength were examined. The study’s findings demonstrated that this experiment increased productivity and reduced the finishing unit’s energy consumption without compromising the denim fabrics’ quality. This study significantly impacts environmental sustainability by preserving limited energy resources and manufacturing denim finishing processes.

Variation of Dynamical Parameters with Upper Tropospheric Potential Vorticity in Tropical Cyclone over the North Indian Ocean Using WRF Model

Meteorologists are experiencing many challenges in the reliable forecasting of the track and intensity of tropical cyclones(TC).Uses of the potential vorticity(PV)technique will enrich the current forecasting system.The use of PV analysis of TC intensification over the North Indian Ocean(NIO)is rare.In this study,the authors analyze the behaviour of upper-level PV with dynamic parameters of TCs over NIO.The authors used NCEP FNL reanalysis 1×1 degree data as input in WRF model version 4.0.3 with one-way nesting between the parent and child domains.The authors used a coupling of the Kain-Fritsch(new Eta)scheme and the WSM 6-class graupel scheme as cumulus and microphysics options to run the model.The authors found that at least one potential vorticity unit(PVU)(1 PVU=10^(-6) m^(2)s^(-1)KKg^(-1))upper PV is required to maintain the intensification of TC.Larger upper PV accelerates the fall of central pressure.The high value of upper PV yields the intensification of TC.The wind shear and upper PV exhibited almost identical temporal evolution.Upper PV cannot intensify the TCs at negative wind shear and shear above the threshold value of 12 ms^(-1).The upper PV and geopotential heights of 500 hPa change mutually in opposite trends.The upper PV calculated by the model is comparable to that of ECMWF results.Therefore,the findings of this study are admissible.

Evaluating the Influence of Sea Level Rise on Beel Kapalia’s Livelihood and Local Adaptation Strategies: Perspectives from the Local Community

Bangladesh is vulnerable to climate change-induced sea level rise due to its location and socioeconomic position. The study examines the Beel Kapalia region in polder no. 24 of the Monirampur upazila of Jessore district, Khulna division. To assess local attitudes on sea level rise-related permanent flooding, Kapalia, Monoharpur, Nehalpur, Balidaha, and Panchakori were polled. This flooding has disrupted residents’ lifestyles, making them vulnerable to increasing sea levels. Viability and adaptability were assessed using livelihood capitals. Participants’ thoughts and knowledge about their resilience in several livelihood factors were gathered using participatory rural appraisal (PRA) instruments and a questionnaire survey in the area. Major discoveries include the impact of permanent floods on Beel Kapalia’s livelihoods, vulnerability and resilience assessments in numerous villages, and community viewpoints on regional adaptation methods to mitigate these consequences. The study found that a sustained 30.5 cm inundation would reduce local human, natural, physical, financial, and social capital resilience to 69.6%, 30.7%, 69.1%, 68.9%, and 69.1%. A constant 61 cm inundation would lower resistance to 40.9%, 8.7%, 42.4%, 45.6%, and 43.8%. Residents believe they can weather a 30.5 cm inundation with local adaptation measures, but if the water level rises to 61 cm, they may be displaced.

Biomolecular basis of the role of diabetes mellitus in osteoporosis and bone fractures

Osteoporosis has become a serious health problem throughout the world which is associated with an increased risk of bone fractures and mortality among the people of middle to old ages.Diabetes is also a major health problem among the people of all age ranges and the sufferers due to this abnormality increasing day by day.The aim of this review is to summarize the possible mechanisms through which diabetes may induce osteoporosis.Diabetes mellitus generally exerts its effect on different parts of the body including bone cells specially the osteoblast and osteoclast,muscles,retina of the eyes,adipose tissue,endocrine system specially parathyroid hormone(PTH) and estrogen,cytokines,nervous system and digestive system.Diabetes negatively regulates osteoblast differentiation and function while positively regulates osteoclast differentiation and function through the regulation of different intermediate factors and thereby decreases bone formation while increases bone resorption.Some factors such as diabetic neuropathy,reactive oxygen species,Vitamin D,PTH have their effects on muscle cells.Diabetes decreases the muscle strength through regulating these factors in various ways and ultimately increases the risk of fall that may cause bone fractures.

TGF-β/BMP signaling and other molecular events: regulation of osteoblastogenesis and bone formation

Transforming growth factor-beta（TGF-β）/bone morphogenetic protein（BMP） plays a fundamental role in the regulation of bone organogenesis through the activation of receptor serine/threonine kinases. Perturbations of TGF-β/BMP activity are almost invariably linked to a wide variety of clinical outcomes, i.e., skeletal, extra skeletal anomalies, autoimmune, cancer, and cardiovascular diseases. Phosphorylation of TGF-β（I/II） or BMP receptors activates intracellular downstream Smads, the transducer of TGF-β/BMP signals. This signaling is modulated by various factors and pathways, including transcription factor Runx2. The signaling network in skeletal development and bone formation is overwhelmingly complex and highly time and space specific.Additive, positive, negative, or synergistic effects are observed when TGF-β/BMP interacts with the pathways of MAPK, Wnt, Hedgehog（Hh）, Notch, Akt/m TOR, and mi RNA to regulate the effects of BMP-induced signaling in bone dynamics. Accumulating evidence indicates that Runx2 is the key integrator, whereas Hh is a possible modulator, mi RNAs are regulators, and b-catenin is a mediator/regulator within the extensive intracellular network. This review focuses on the activation of BMP signaling and interaction with other regulatory components and pathways highlighting the molecular mechanisms regarding TGF-β/BMP function and regulation that could allow understanding the complexity of bone tissue dynamics.

Effect of different pre-sowing treatments on seed germination percentage and growth performance of Acacia auriculiformis

Seed morphology,germination and seedlings growth of Acacia auriculiformis were studied.The experiment was conducted in the nursery of Forestry and Wood Technology Discipline,Khulna University,Bangladesh.Matured seeds of the species were collected from healthy trees of road side plantation from different areas of Khulna District,Bangladesh and treated with five pre-sowing treatments（control,immersion in cold water,immersion in hot water,scarification with sand paper and immersion in concentrated H2SO4）.The average length,breadth and thickness were found to be（0.58±0.017） cm,（0.44±0.007） cm and（0.20±0.089） cm,respectively.Germination was conducted in polybags with a mixture of top soil,coconut husk,coarse sand,and fine sand in a ratio of 3：4：1：1.Results reveal that pre-sowing treatments influences the germination rates of seeds that significantly increase the percentage germination compared with those in control（43%） and cold water treatment（52%）.The highest germination success rate was found 83% in hot water treatment followed by 78% in scarification with sand paper,and 75% with immersion in H2SO4.Germination started from 7 to 12 days and completed between 28 and 35 days period in all treatments.ANOVA showed the significant difference（p0.05） among the treatments in seed germination,but no significant difference among treatment with regard to starting day,closing day and total germination period.In case of height and diameter growth,seedlings originated from the seeds with hot water treatment shows significantly higher in wet season（from May to July）.Hot water treatment can be recommended on seed germination of the species in rural Bangladesh.

Analgesic,anti-inflammatory and anti-diarrheal activities of ethanolic leaf extract of Typhonium trilobatum L.Schott

Objective:To explore the efficacy of ethanolic leaf extract of Typhonium trilobatum L.Schott in treating diarrhea,pain and inflammation using experimental models.Methods:In the present study,acetic acid-induced writhing,xylene-induced ear edema and castor oil-imluced diarrlieal model were used to evaluate the analgesic,anti-inflammatory and anti-diarrheal activities,respectively.Acute toxicity test was carried out to fix the safe doses of the plant extract.Results:The plant extract demonstrated a significant inhibition of writhing(P<0.01)compared with the control group in acetic acid-induced writhing test in mice.The extract also significantly inhibited the xylene induced ear edema formation(P<0.05).In anti-diarrheal test,the extract significantly decreased the frequency of defecation and increased the mean latent period(P<0.0l)in castor oil-induced diarrheal model mice at the doses of 250 and 500 mg/kg body weight.Conclusions:These results suggest that the extract possesses significant analgesic,anti-inflammatory and anti-diarrheal activities that support to the ethnopharmacologicl uses of this plant.