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Word completion and word prediction are two important phenomena in typing that benefit users who type using keyboard or other similar devices. They can have profound impact on the typing of disable people. Our work is based on word prediction on Bangla sentence by using stochastic, i.e. N-gram language model such as unigram, bigram, trigram, deleted Interpolation and backoff models for auto completing a sentence by predicting a correct word in a sentence which saves time and keystrokes of typing and also reduces misspelling. We use large data corpus of Bangla language of different word types to predict correct word with the accuracy as much as possible. We have found promising results. We hope that our work will impact on the baseline for automated Bangla typing., Comment: in International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.5, No.6, November 2015

Cities become mission-critical zones during pandemics and it is vital to develop a better understanding of the factors that are associated with infection levels. The COVID-19 pandemic has impacted many cities severely; however, there is significant variance in its impact across cities. Pandemic infection levels are associated with inherent features of cities (e.g., population size, density, mobility patterns, socioeconomic condition, and health environment), which need to be better understood. Intuitively, the infection levels are expected to be higher in big urban agglomerations, but the measurable influence of a specific urban feature is unclear. The present study examines 41 variables and their potential influence on COVID-19 cases and fatalities. The study uses a multi-method approach to study the influence of variables, classified as demographic, socioeconomic, mobility and connectivity, urban form and density, and health and environment dimensions. This study develops an index dubbed the PVI-CI for classifying the pandemic vulnerability levels of cities, grouping them into five vulnerability classes, from very high to very low. Furthermore, clustering and outlier analysis provides insights on the spatial clustering of cities with high and low vulnerability scores. This study provides strategic insights into levels of influence of key variables upon the spread of infections as well as fatalities, along with an objective ranking for the vulnerability of cities. Thus it provides critical wisdom needed for urban healthcare policy and resource management. The pandemic vulnerability index calculation method and the process present a blueprint for the development of similar indices for cities in other countries, leading to a better understanding and improved pandemic management for urban areas and post-pandemic urban planning across the world., Comment: 22 pages, 7 figures

Mango (Mangifera indica L.) is an important tropical fruit that is grown commercially in many countries of the world. Nowadays, fruit powder is a great alternative source of healthy nutrient and exceptional value-added products. An effective extraction condition can play an important role in minimizing the loss of nutrients, which depends on its perfect selection of effective parameter conditions. In this study, the effects of temperature, the concentration of ethanol, extraction time, and material ratio on the flavonoid contents in mango powder have been investigated. The Response Surface Methodology along with Central Composite Design, was used to get the optimum value of Total Flavonoid Content extracted from mango powder. We have observed from the model that the amount of secondary metabolites (flavonoids) has reached its maxima 501.08 mg QE/100 g extracted at 80oC for 4 h. by using 80% ethanol with a material ratio of 1:1. The accuracy of the developed model was validated by conducting the extraction process of flavonoids in the laboratory using the derived optimum conditions. The experimental value of the total flavonoid content is 498.96 ± 3.45 mg QE/100 g (N = 3), which was very close to the predicted score of the model. This indicates that the model is adequate to optimize the extraction of flavonoids from mango powder.

This study empirically investigates the causes of urban traffic congestion to bring into focus the variety of beliefs that provide support for policy interventions to mitigate traffic congestion in...

An attempt was made to evaluate the contamination status of surface water collected from the Balu river for irrigation. Twenty samples were collected to analyze pH, EC, TDS and ions. Samples were slightly alkaline in nature. Water samples were from low to medium salinity and low alkalinity hazards (C1S1-C2S1). As per TDS values, samples were classified as freshwater. Considering SAR and SSP values, samples were excellent and good to permissible classes, respectively. Most of the water samples were free from RSC and all the samples were under moderately hard. The status of Cr and Mn ions in samples surpassed FAO guideline values indicating contaminants for long-term irrigation. The levels of other metal ions in samples were within acceptable levels and did not pose a threat to irrigated soil. This finding revealed that Cr and Mn ions were considered as contaminants in river water for irrigation posing harmful impact on soils and crops. Environ. Sci. & Natural Resources, 12(1&2): 57-65, 2019

Recognizing an urgent need to understand the dynamics of the pandemic’s severity, this longitudinal study is conducted to explore the evolution of complex relationships between the COVID-19 pandemic, lockdown measures, and social distancing patterns in a diverse set of 86 countries. Collecting data from multiple sources, a structural equation modeling (SEM) technique is applied to understand the interdependencies between independent variables, mediators, and dependent variables. Results show that lockdown and confinement measures are very effective to reduce human mobility at retail and recreation facilities, transit stations, and workplaces and encourage people to stay home and thereby control COVID-19 transmission at critical times. The study also found that national contexts rooted in socioeconomic and institutional factors influence social distancing patterns and severity of the pandemic, particularly with regard to the vulnerability of people, treatment costs, level of globalization, employment distribution, and degree of independence in society. Additionally, this study portrayed a mutual relationship between the COVID-19 pandemic and human mobility. A higher number of COVID-19 confirmed cases and deaths reduces human mobility and the countries with reduced personal mobility have experienced a deepening of the severity of the pandemic. However, the effect of mobility on pandemic severity is stronger than the effect of pandemic situations on mobility. Overall, the study displays considerable temporal changes in the relationships between independent variables, mediators, and dependent variables considering pandemic situations and lockdown regimes, which provides a critical knowledge base for future handling of pandemics. It has also accommodated some policy guidelines for the authority to control the transmission of COVID-19.

This paper will explore child health care and treatment seeking behavior of villagers and presents factors that discourage them from using public health facilities. The perspective of human health is not only stay behind in the contact between the disease and the human body and the extermination of the demon by providing few medicines rather it is a complex web where multiple factors are affecting human to live a sound life. The environment has a diverse effect on human life: some indulge humans with it extravaganza while some impose serious theaters but one thing in common, every environment shares basic problems of acquiring and allocating space, food, energy and resources for health. Haor people have endless problems to meet, starting from food to basic human rights. Maintaining a healthy life does end up with some formality of going to some popular and folk treatment though going to professionals is rare. Government and non-Governmental organizations have a variety of scope to improve the situation by providing health infrastructure, awareness building measures, eradicating superstition and including health education in the school curriculum.

Arsenic (As) is an environmentally hazardous toxic metalloid. To evaluate As tolerance and assimilation capacity, seedlings of jute (Corchorus capsularis L. var. BJC-7370 and CVE-3), kenaf (Hibiscus cannabinus L. var. HC-95 and HC-3) and mesta (Hibiscus sabdariffa L. var. Samu-93) were grown for 25 days in hydroponic nutrient solution containing four levels of As viz 0, 5, 10 and 15 mg L-1 with four replications. Results were showed that the seedlings of jute, kenaf and mesta were highly potential to tolerate As toxicity. Arsenic had no significant effects on survibility of kenaf, mesta and jute seedlings (var.VE-3). Root and shoot length and dry biomass were decreased with the increasing levels of As. Values of bio-concentration factor indicated the varieties of kenaf, mesta and jute (var.VE-3) were As accumulator. Arsenic accumulation was higher in root than shoot and translocation factor indicated that As is slowly translocated from root to shoot. The rate of translocation is increased with the increasing concentration of As in solution. Highest As contents in shoot (3636.10 mg kg-1) and root (6350.38 mg kg-1) were detected from kenaf HC-3. The highest amount (16.05 mg As pot-1) of As accumulation was also calculated from the variety of kenaf HC-3 with the addition of 45 mg As pot-1. The order of As tolerance and absorption potentiality were kenaf HC-3>mesta Samu-93>jute CVE- 3>kenaf HC-95>jute BJC-7370. These varieties are good cultivar for cultivation and/or phytoremediation of As contaminated environment.

Al-Biruni's foremosteffort on astronomy is mainly a blend of observational diagram and mathematical context. In his astronomical work, the Qanun-i Masoodi (al-Qanun al-Masudi, fi al-Hai'a wa al-Nujum), he uses his observational facts to challenge Ptolemy's steady solar 'apogee'.. Al-Biruni's eclipse facts was used by Dunthorne to supportcontrol the 'acceleration of the moon' and his observational facts has entered the more astronomical accounts and is still used today. The present paper aims to explore the major contributions of Al-Biruni to geophysics and astronomy as well as to identify the impacts of his works on the modern astronomy. Major findings indicate that Al-Biruni's key concern in astronomy was for calculations. He paid devotion to theoretical problems that had and have still been contributing to the development and critical analysis of both applied (in the procedure of solving problems), and theoretical (in the process of thought formulations) astronomy. This paper concludes that Al-Biruni's contributions must be seen in the comprehensiveness of his work, and in his continual attempts to formulate astronomical thoughts.

We conducted a systematic review to evaluate the knowledge base for amphibian chytrid Batrachochytrium dendrobatidis (Bd) infection in the continent of Asia. Despite an indication of geographic bias in terms of studying chytrid fungus distribution in Asia, 167 amphibian species (145 spp. native to Asia) from 16 countries have been reported as infected with Bd. Our meta-analysis shows that overall prevalence is 8.19 % (out of 28,433 samples), and Bd-positive rate in amphibia significantly varies among sampling sources (χ2= 380.57, DF= 6, P< 0.001) and age categories (χ2= 22.09, DF= 2, P< 0.001). We used Kernel Density analysis to produce a hotspot map for chytrid infection, and Digital Elevation Model to understand the distribution of chytrid positive locations across different elevations. In our meta-analysis, most of the Bd-positive sites range between 4.45–27.49 °C, 167–4,353 mm rainfall, 10–40°N, and at lower elevations (

Graphite, with appealing features such as good stability, high electrical conductivity, and natural abundance, is still the main commercial anode material for lithium-ion batteries. The charge-discharge rate capability of graphite anodes is not significant for the development of mobile devices and electric vehicles. Therefore, the feasibility investigation of the rate capability enhancement of graphite by manipulating the structure is worthwhile and of interest. In this study, an effective ball-milling process has been set up by which graphite nanostructures with a high surface area are produced. An in-depth investigation into the effect of ball milling on graphite structure as well as electrochemical performance, particularly rate capability, is conducted. Here, we report that graphite nanoflakes with 350 m2 g−1 surface area deliver retained capacity of ~75 mAh g−1 at 10 C (1 C = 372 mA g−1). Finally, the Li+ surface-storage mechanism is recognised by associating the structural characteristics with electrochemical properties.

With the aim of evaluating the effect of Government Youth Development Training on the KSA of the incumbents, this research used structured interview schedule and accomplished face-to-face interview of 142 randomly selected trainees from four purposefully selected Youth Training Centers. A strong positive significant change of KSA occurred due to the training and major change happened in knowledge followed by skill and attitude. The regression analysis shows that the traits of the trainers, location of the training center, and regularity in class attendance had significant relationship with knowledge change of the incumbents, while the traits of the trainers, experience of other trainings, and location of the training centers were significant determinants of skill change. Continuous improvement of trainer’s traits as well as inclusion of more practical field works in training sessions, and frequent evaluation of each training program based on KSA( Knowledge Skill & Attitude) is crucial to improve the effect of government youth development training in the study area.

Water samples were collected from the Rupsha river of Khulna region to determine ionic contamination for irrigation purpose. The chemical analyses included pH, EC, TDS and ions. pH values of water samples were slightly alkaline in nature. Samples were rated as fresh water based on TDS values. Samples were high salinity and low alkalinity hazards expressing C3S1. Regarding SAR and SSP values, samples were excellent and good classes, respectively. Samples were free from RSC and were very hard class. Regarding PI values, samples were under class-II implying 75% maximum soil permeability. Ca, Mg, Na, Cu, Ni, Zn, HCO3, SO4 and PO4 levels in samples were within safe limit. Cd, Cr and Cl ions in water samples were above the permissible limit and were treated as water contaminants for irrigation. From the present findings, it is noted that the detected ions as water contaminants should be considered for irrigation usage toward food safety. J. Environ. Sci. & Natural Resources, 11(1-2): 145-151 2018

Congenital myasthenic syndromes (CMS) comprise a heterogeneous group of rare inherited diseases in which the neuromuscular transmission in the motor plate is compromised by one or more genetic pathophysiological specific mechanisms are characterized by fatigable weakness of skeletal muscle (e.g., ocular, bulbar, limb muscles) with onset at or shortly after birth or in early childhood; rarely, symptoms may not manifest until later in childhood. The diagnosis of CMS is based on clinical findings, a decremental EMG response of the compound muscle action potential (CMAP) on low-frequency (2- 3 Hz) stimulation, absence of anti-acetylcholine receptor (AChR) and anti-MuSK antibodies in the serum, a positive response to acetylcholinesterase (AchE) inhibitors and lack of improvement of clinical symptoms with immunosuppressive therapy. Pathogenic variants in one of multiple genes encoding proteins expressed at the neuromuscular junction are currently known to be associated with subtypes of CMS. The most commonly associated genes include: CHAT, CHRNE, COLQ, DOK7, GFPT1 and RAPSN. We studied on a sibling presented with progressive fatigability and fluctuating ptosis with frequent exacerbations of muscle weakness during infections since infancy. On both cases CT scan of chest were negative for thymoma, antibodies against the acetylcholine receptor (AChR) and the muscle specific kinase (MuSK) were negative and decremental response on electrophysiological study of Repetitive nerve stimulation (RNS) and EMG were consistent with disease of neuromuscular junction (post synaptic) and they were only on pyridostigmine for long time with marked improvement of symptoms and signs. Considering all scenario both of our cases mostly fits with the autosomal recessive, post synaptic CMS associated with Rapsyn deficiency. Objective : As in Bangladesh, there is inadequate data on the epidemiological profile of CMS, our aim is to describe these cases for their rarity and the difficulty encountered in diagnosis as they are easily confused with Juvenile Myasthenia Gravis (JMG) and familial myopathies. As both the cases are very rare, it should be an original article. Bangladesh Journal of Neuroscience 2019; Vol. 35 (2): 95-103

Hemidactylus is a taxonomically complex genus and little is known about its feeding and breeding behavior in Bangladesh. Most of the species of this genus have a preference to live within human habitations, and play an important role in ecosystem, controlling insect pest population. Their breeding strategy is almost similar with each other and associated with their body structure. Review of literature found that there is a relationship between life history pattern and their reproductive biology. They lay two eggs per clutch usually and the highest egg number (12) has been recorded for H. frenatus. Strong significant positive correlation (r = 0.91) was found for preclaocal-femoral pores and egg number. Besides, significant negative correlation was found for average female body size and egg number (r = 0.96). Previous work and observation records showed that feeding habit is almost similar among all species of Hemidactylus and dipteran insects were the mostly consumed food item. J. Biodivers. Conserv. Bioresour. Manag. 2019, 5(1): 77-84

Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle an epidemiological process that evolves rapidly and is spatially heterogeneous. On the other hand, machine learning methods are limited at the beginning of the pandemics due to small data size for training. We propose a deep learning approach to predict future COVID-19 infection cases and deaths 1 to 4 weeks ahead at the fine granularity of US counties. The multi-variate Long Short-term Memory (LSTM) recurrent neural network is trained on multiple time series samples at the same time, including a mobility series. Results show that adding mobility as a variable and using multiple samples to train the network improve predictive performance both in terms of bias and of variance of the forecasts. We also show that the predicted results have similar accuracy and spatial patterns with a standard ensemble model used as benchmark. The model is attractive in many respects, including the fine geographic granularity of predictions and great predictive performance several weeks ahead. Furthermore, data requirement and computational intensity are reduced by substituting a single model to multiple models folded in an ensemble model.

Transportation interventions influence land use patterns of the city and transport activities of the people. For example, construction and improvement of transportation infrastructure (e.g...

Global amphibian populations are facing a novel threat, chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd), which is responsible for the severe decline of a number of species across several continents. Chytridiomycosis in Asia is a relatively recent discovery yet there have been no reports on Bd-presence in Bangladeshi amphibians. We conducted a preliminary study on 133 wild frogs from seven sites in Bangladesh between April and July 2018. Nested PCR analysis showed 20 samples (15.04%) and 50% of the tested taxa (9 species from 6 genera and 4 families) as Bd-positive. Eight of the nine species are discovered as newly infected hosts. Analysis of Bd-positive samples shows prevalence does not significantly vary among different land cover categories, although the occurrence is higher in forested areas. The prevalence rate is similar in high and low disturbed areas, but the range of occurrence is statistically higher in low disturbance areas. Maximum entropy distribution modeling indicates high probabilities of Bd occurrence in hilly and forested areas in southeast and central-north Bangladesh. The Bd-specific ITS1-5.8S-ITS2 ribosomal gene sequence from the Bd-positive samples tested is completely identical. A neighbor-joining phylogenetic tree reveals that the identified strain shares a common ancestry with strains previously discovered in different Asian regions. Our results provide the first evidence of Bd-presence in Bangladeshi amphibians, inferring that diversity is at risk. The effects of environmental and climatic factors along with quantitative PCR analysis are required to determine the infection intensity and susceptibility of amphibians in the country.

There exists a compelling need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February of 2021 and late March of 2021 shows that in spite of overall strength of positive sentiment, and increasing numbers of Americans being fully vaccinated, negative sentiment about COVID-19 vaccines still persists among sections of people who are hesitant towards the vaccine. In this study, we performed sentiment analytics on vaccine tweets, studied changes in public sentiment over time, conducted vaccination sentiment validation using actual vaccination data from the US CDC and Household Pulse Survey (HPS), explored influence of maturity of Twitter user-accounts and generated geographic mapping of sentiments by location of Twitter users. Furthermore, we leverage the emotion polarity based Public Sentiment Scenarios (PSS) framework which was developed for COVID-19 sentiment analytics, to systematically analyze directions for public policy processes to potentially improve the administration of vaccines. Application of the PSS framework provides important time sensitive insights for state and federal government agencies and associated organizations to better implement public policy processes for healthcare management, communication, transparency, motivation and societal operational policies such as social distancing. These insights are expected to contribute to processes that can expedite the vaccination program and move closer to the cherished herd immunity goal.

Sugarcane is the only sugar yielding and economically important crop in Bangladesh. Although, it is a good source of sucrose, alcohol and organic matter waste, soil fertility is declining in sugarcane growing areas. Considering the facts, a field study was carried out during 2014-2015 cropping season to evaluate the impacts of integrated use of different organic and chemical nutrients on the quality of sugarcane. Seven treatments were comprised in this experiment (T1 = Control, T2 = 165:55:120:30:10:2.5:4 kg NPKSMgZnB ha-1, T3 = Poultry Litter (PL) @ 5 t ha-1 + 95:51:87:9:10:2.5:4 kg NPKSMgZnB ha-1, T4 = Cow Dung (CD) @ 15 t ha-1 + 36:52:60:17:10:2.5:4 kg NPKSMgZnB ha-1, T5 = Press Mud (PM) @ 15 t ha-1 + 10:50:43:0:10:2.5:4 kg NPKSMgZnB ha-1, T6 = Mustard Oil Cake (MOC) @ 0.5 t ha-1 + 140:54:115:25:10:2.5:4 kg NPKSMgZnB ha-1 and T7 = GM (Green Manure) @ 5 t ha-1 + 140:53:100:28:10:2.5:4 kg NPKSMgZnB ha-1). The experiment was carried out in a Randomized Complete Block Design (RCBD) with three replications. Results of cane quality parameters, the treatment T3 (PL @ 5 t ha-1 + 95:51:87:9:10:2.5:4 kg NPKSMgZnB ha-1) recorded the highest brix (20.9 %), pol in cane (14. 9%) and sugar yield (15 t ha-1). The goor quality parameters likes sucrose (80.1 %), colour transmittance (57.80%) and goor recovery (11.21%) were noticed highest in T3 treatment, which was similar to T4 treatment (CD @ 15 t ha-1 + 36:52:60:17:10:2.5:4 kg NPKSMgZnB ha-1). On the other hand the lowest reducing sugars (6.56%) and ash content (2.96%) were also observed in T3 treatment. The results from this experiment revealed that the treatment - PL @ 5 t ha-1 + 95:51:87:9:10:2.5:4 kg NPKSMgZnB ha-1 followed by CD @ 15 t ha-1 + 36:52:60:17:10:2.5:4 kg NPKSMgZnB ha-1 provided a scope to supply raw material with juice and goor quality of sugarcane grown in High Ganges River Floodplain soils to sugar industry and goor makers.

This study empirically investigates the complex interplay between the severity of the coronavirus pandemic, mobility changes in retail and recreation, transit stations, workplaces, and residential areas, and lockdown measures in 88 countries of the word. To conduct the study, data on mobility patterns, socioeconomic and demographic characteristics of people, lockdown measures, and coronavirus pandemic were collected from multiple sources (e.g., Google, UNDP, UN, BBC, Oxford University, Worldometer). A Structural Equation Modeling (SEM) technique is used to investigate the direct and indirect effects of independent variables on dependent variables considering the intervening effects of mediators. Results show that lockdown measures have significant effects to encourage people to maintain social distancing. However, pandemic severity and socioeconomic and institutional factors have limited effects to sustain social distancing practice. The results also explain that socioeconomic and institutional factors of urbanity and modernity have significant effects on pandemic severity. Countries with a higher number of elderly people, employment in the service sector, and higher globalization trend are the worst victims of the coronavirus pandemic (e.g., USA, UK, Italy, and Spain). Social distancing measures are reasonably effective at tempering the severity of the pandemic., Comment: 17 pages, 3 figures, 6 tables

Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric Association, is a neurodevelopmental disorder that includes deficits of social communication and social interaction with the presence of restricted and repetitive behaviors. Children with ASD have difficulties in joint attention and social reciprocity, using non-verbal and verbal behavior for communication. Due to these deficits, children with autism are often socially isolated. Researchers have emphasized the importance of early identification and early intervention to improve the level of functioning in language, communication, and well-being of children with autism. However, due to limited local assessment tools to diagnose these children, limited speech-language therapy services in rural areas, etc., these children do not get the rehabilitation they need until they get into compulsory schooling at the age of seven years old. Hence, efficient approaches towards early identification and intervention through speedy diagnostic procedures for ASD are required. In recent years, advanced technologies like machine learning have been used to analyze and investigate ASD to improve diagnostic accuracy, time, and quality without complexity. These machine learning methods include artificial neural networks, support vector machines, a priori algorithms, and decision trees, most of which have been applied to datasets connected with autism to construct predictive models. Meanwhile, the selection of features remains an essential task before developing a predictive model for ASD classification. This review mainly investigates and analyzes up-to-date studies on machine learning methods for feature selection and classification of ASD. We recommend methods to enhance machine learning’s speedy execution for processing complex data for conceptualization and implementation in ASD diagnostic research. This study can significantly benefit future research in autism using a machine learning approach for feature selection, classification, and processing imbalanced data.