Bio-Inspired Design of Mechanical Band Pass Sensor with the Ability to Scavenge Energy

Primary objective of this work is to introduce the multi-scale computational model for the bio-inspired acousto-ultrasonic band pass sensor that are capable of mechanically sense and/or filter wide range user defined frequencies. Selecting a particular and/or a distinct band of frequencies is essential for many applications in science engineering and technologies. For example design of sensors in chemical, biomedical and biological applications; device application for acoustic modulation by breaking the acoustic reciprocity and the sensors used in precision manufacturing applications requires sensing and/or filtering of wide range of acousto-ultrasonic frequencies. Presently, electronic devices are widely employed in commercial applications for selecting the target frequencies. Concurrent to the electronics sensors mechanical sensors with smart materials are significantly contributing to the sensing technologies, especially where electronic sensors are not compatible. Mechanical sensors are traditionally made of cantilever beams and use the resonance phenomenon to select the target frequencies. Considering the required size of the sensors, the above physics limits the design of these sensors for only the high frequency (\u3e ~3 KHz) applications. Hence, to employ such sensors, it is apparent that for the low (sonic) frequency operations humungous geometrical size will be required. Thus, in order to sublime the wide applicability of the mechanical sensors, in this work, a physics bases mechanical band pass frequency selection mechanism is proposed that is universal can be adopted for selecting extremely wide range of frequencies with controlled geometric configurations. To model the envisioned band pass frequency sensors, in this work, principles and the mechanics of the human cochlea are studied. Human cochlea is the most advanced and sophisticated band pass frequency sensor in nature, where it selects the sonic frequency band (20 Hz – 20 KHz) and filters all the infrasonic and ultrasonic frequencies using a device length of only ~ 35 mm (sub-wave length scale device). Inside the cochlea, the Basilar Membrane (BM) is naturally designed based on the variable stiffness model, starting from the base to the apex of the cochlea. During selecting and filtering the desired frequencies, the BM performs four major operations; (a) it create local resonances; (b) it captures only the chosen frequencies and remain unresponsive to the other frequencies; (c) it senses the input frequencies with a sensory medium (called hair cells); and in turn (d) it spatially selects the frequencies. Inspired by the cochlear mechanics, mimicking the functionalities of the basilar membrane, in this PhD dissertation, a mechanical frequency selection mechanism is proposed exploring two diverse innovative designs (1) Acousto-Elastic MetaMaterial (AEMM) model and the (2) Basilar Membrane (BM) model. Two approaches are adopted in designing the AEMM based mechanical sensor; (a) stop band technique, (SBT) and the (b) band pass technique, (BPT). The proposed AEMM consists of a heavy core mass encapsulated in a matrix inside a stiff frame. AEMM’s are recently proposed for stopping the acoustic frequencies and create the acoustic band gaps. Using SBT method, several AEMM models are studied to create very large stop band, such that, all unwanted frequencies in the environment can be filtered and user defined frequencies can be passed through the device, automatically. However, it was found to be challenging. After several unsuccessful attempts using SBT, the new BPT method is adopted where local resonance is the key in selecting a specific frequency. Using BPT, by filtering the other possible frequencies, automatically, it is intended to develop a model which is only able to select the target frequency. Using BPT, it has been found that the proposed AEMM structure is able to mimic the functionalities of the basilar membrane and a distinct frequency can be selected by efficiently placing a smart material capable of electromechanical transduction (e.g. piezoelectric material) inside a unit cell AEMM. It has also been reported that a broadband frequency is possible to be sensed using a multi-cell structure with a systematic selection of model parameters. Comprehensive studies with analytical, numerical and experimental approaches are performed to establish the hypothesis. AEMM model uses geometric configuration and the physics of local resonance by mimicking the functionalities of the basilar membrane. However, the mechanical frequency sensor based on exact BM model is not available. Hence, in this dissertation a real geometric configuration of the basilar membrane is adopted to serve the central objective. Using BM model, two designs are proposed; the plate model and the beam model. The plate model is preferred over the beam model, where a continuous frequency band is necessary to select without losing the intermediate frequencies. Alternatively, beam model is preferable for the precise selection of the discrete frequencies within a target frequency band. In the plate model, a trapezoidal membrane is designed, whereas, in the beam model, a series of beams supported at the ends with linearly varying lengths are proposed to fit the trapezoidal basilar geometry. In recent years, notable attempts were made to fabricate the broadband frequency sensors. Although, few experimental studies have been reported to fabricate band pass sensors mimicking the mechanics of the basilar membrane, a true predictive model to design these sensors is missing. An ultra-fast and versatile model is necessary such that it could be used for the optimization of the model parameters. Non availability of such predictive model hinders the optimized design of the cochlea type sensors tailored to specific applications. Hence, in this research, two novel predictive models (plate type, beam type) for the band pass frequency sensors are proposed, mimicking the tapered geometry of the basilar membrane. It is aimed in this dissertation to develop the most flexible/versatile predictive models with all possible variable parameters that contribute to the frequency selection process. The models are developed in such a way that they can be employed for the optimized design of the sensors for wide varieties of scientific applications, respectively. Hence, the predictive models developed herein not only capable of handling the homogeneous model parameters but also capable of managing the functionally graded model parameters. This study reports that using the proposed predictive models, it is also possible to manipulate the attributes of the target frequency band using the functionally graded model parameters. The model flexibility based on the functionally graded parameters will allow the used to alter the geometric configuration of the envisioned sensor for a selected specific designed frequency band. Studies, using the finite element method (FEM) confirm the outcome of the proposed predictive models and prove that the innovative proposed model presented in this dissertation is even couple of orders (~ at least 3 times in a conventional personal computer) faster than its counter FEM model. In addition to the introduction of bio-inspired mechanical band pass sensor, in this research, few novel applications of the proposed sensors are identified and envisioned, discussed herein. Two major applications in Mechanical and Biomedical engineering are identified, respectively. Mechanical application is in the realm of energy harvesting using the AEMM model and the biomedical application using the BM model is identified in the realm of pathogen identification where it is possible to sense and detect the presence of mycotoxins, a carcinogenic metabolite excreted by the fungal pathogens. . In this work, very promising power densities were recorded using the AEMM energy scavengers. This motivates the harvesters to be employed for powering the low power electronic gadgets. On the other hand the characterization and the genus identification of the fungal pathogens can be achieved by classifying their secondary metabolites called mycotoxins. A BM based cantilever beam design is proposed to detect the presence of the type of the mycotoxins in the environment

Organic Farming in Bangladesh: To Pursue or not to Pursue? An Exploratory Study Based on Consumer Perception

The development of organic agriculture in Bangladesh has been slow. According to the Bangladesh Bureau of Statistics (2018), approximately 12,000 farmers in Bangladesh produce organic crops on around 7,000 hectares of land. The transition from conventional to organic farming has been an issue of debate, especially in the context of developing nations such as Bangladesh. The debate stresses the urgency for the transition to preserve environment and health and to ensure a safe, sustainable and environmentally friendly food production system, but also emphasizes the pressure of maintaining food production for a large growing population. We focus on the debate in the context of Bangladesh, and question whether it is the proper time and stage in the development process to attempt the transition from conventional to organic food production systems. We ask why the organic rice market is not expanding in Bangladesh and explain the slow market growth through the two main factors of income constraint and lack of awareness among people about the environmental and health detriments of non-organic farming. The exploratory study finds that it is not mainly the lack of awareness but the income constraint that can be principally attributed to the slow expansion of the organic rice market in Bangladesh. Through exploring consumers’ awareness about organic farming methods and their demand for organic products, this study shows how income as a major constraint, besides price, affects consumers demand for organic and non-organic rice in Bangladesh. Income being identified as the major barrier reveals the potential of the organic rice market to grow in the future, as Bangladesh continues its journey towards becoming a middle-income country

Impact of a global pandemic on surgical education and training- review, response, and reflection

The catastrophic effects of the coronavirus disease-2019 global pandemic have revolutionised human society. The unprecedented impact on surgical training needs to be analysed in detail to achieve an understanding of how to deal with similar situations arising in the foreseeable future. The challenges faced by the surgical community initiated with the suspension of clinical activities and elective practice, and included the lack of appropriate personal protective equipment, and the self-isolation of trainees and reassignment to coronavirus patient-care regions. Together, all these elements had deleterious effects on the psychological health of the professionals. Surgical training irrespective of specialty is equally affected globally by the pandemic. However, the global crisis inadvertently has led to a few constructive adaptations in healthcare systems, including the development of tele-clinics, virtual academic sessions and conferences, and increased usage of simulation. The current review article was planned to highlight the impact of corona virus disease on surgical training and institutions\u27 response to the situation in order to continue surgical training, and lessons learnt from the pandemic

Promoting physical activity and reducing sedentary behaviour can minimise the risk of suicidal behaviours among adolescents

Suicide is a leading cause of premature mortality and a major public health concern (1). It is more common in low‐ and middle‐income countries like Bangladesh, where the rate is 39.6 per 100,000 population, compared to the estimated global average of 11.4 (2). Adolescents represent more than one‐fifth of the Bangladeshi population (3), but there is limited information on how health behaviours like physical activity (PA) affect suicidal thoughts and behaviours in this vulnerable group. Identifying potentially modifiable risk behaviours is essential to reduce the country's adolescent suicide rate

In a digitally connected world through likes, hashtags and followers - advancing surgical research through a social media: A narrative review

In this era of modern information technology, the world is now digitally connected through various platforms on social media, which has changed the way medical professionals work, communicate and learn. The use of social media in surgery is expanding, and it is now becoming an essential tool for surgical training, research and networking. Articles, journal clubs and surgical conferences are within reach of everyone regardless of geographical location worldwide. Electronic publications have now resoundingly replaced printed editions of journals. Collaborative research through social media platforms helps collect diverse data, enhancing the research\u27s global generalisability. The current narrative review was planned to discuss the importance of social media in advancing surgical research and the use of different social media applications in the context of promoting and disseminating surgical research alongside its evolving ethical challenges

Physical education class participation is associated with physical activity among adolescents in 65 countries

In this study we examined the associations of physical education class participation with physical activity among adolescents. We analysed the Global School-based Student Health Survey data from 65 countries (N = 206,417; 11–17 years; 49% girls) collected between 2007 and 2016. We defined sufficient physical activity as achieving physical activities ≥ 60 min/day, and grouped physical education classes as ‘0 day/week’, ‘1–2 days/week’, and ‘ ≥ 3 days/week’ participation. We used multivariable logistic regression to obtain country-level estimates, and meta-analysis to obtain pooled estimates. Compared to those who did not take any physical education classes, those who took classes ≥ 3 days/week had double the odds of being sufficiently active (OR 2.05, 95% CI 1.84–2.28) with no apparent gender/age group differences. The association estimates decreased with higher levels of country’s income with OR 2.37 (1.51–3.73) for low-income and OR 1.85 (1.52–2.37) for high-income countries. Adolescents who participated in physical education classes 1–2 days/week had 26% higher odds of being sufficiently active with relatively higher odds for boys (30%) than girls (15%). Attending physical education classes was positively associated with physical activity among adolescents regardless of sex or age group. Quality physical education should be encouraged to promote physical activity of children and adolescents

Changing face of trauma and surgical training in a developing country: A literature review

Trauma continues to be the major cause of disability and death globally and surgeons are often involved in immediate care. However there has been an exponential decrease in the number of the trained trauma surgeons. The purpose of the current review article is to summarize the published literature pertaining to trauma education in postgraduate surgical training programmes internationally and in a developing country as Pakistan. Several electronic databases like MEDLINE, PubMed, Google scholar and PakMediNet were searched using the keywords \u27trauma education\u27 or \u27trauma training\u27 AND \u27postgraduate medical education\u27, \u27surgery residency training\u27, \u27surgery residents\u27 and \u27surgeons\u27. The current training in most surgical residency programmes, locally and globally, is suboptimal. Change in trauma management protocols, and decrease in volume of trauma cases results in variable and/ or inadequate exposure and hands-on experience of the surgical trainees in operative and non-operative management of trauma. This warrants collaborative measures for integration of innovative educational interventions at all levels of the surgical educational programmes

Multi-category Bangla News Classification using Machine Learning Classifiers and Multi-layer Dense Neural Network

Online and offline newspaper articles have become an integral phenomenon to our society. News articles have a significant impact on our personal and social activities but picking a piece of an appropriate news article is a challenging task for users from the ocean of sources. Recommending the appropriate news category helps find desired articles for the readers but categorizing news article manually is laborious, sluggish and expensive. Moreover, it gets more difficult when considering a resource-insufficient language like Bengali which is the fourth most spoken language of the world. However, very few approaches have been proposed for categorizing Bangla news articles where few machine learning algorithms were applied with limited resources. In this paper, we accentuate multiple machine learning approaches including a neural network to categorize Bangla news articles for two different datasets. News articles have been collected from the popular Bengali newspaper Prothom Alo to build Dataset I and dataset II has been gathered from the famous machine learning competition platform Kaggle. We develop a modified stop-word set and apply it in the preprocessing stage which leads to significant improvement in the performance. Our result shows that the Multi-layer Neural network, Naïve Bayes and support vector machine provide better performance. Accuracy of 94.99%, 94.60%, 95.50% has been achieved for SVM, Logistic regression and Multi-layer dense neural network, respectively

Prevalence and sociodemographic patterns of physical activity among Bangladeshi young adult

Background: Physical activity offers physical and psychosocial health benefits that are important during young adulthood and later in life. However, little is known about the physical activity of young adults in low- and middle-income countries. The purpose of this study was to estimate the participation of physical activity in Bangladeshi young adults and to assess differences by gender, age and family income. Methods: This cross-sectional study with a self-administered survey used a convenience sample of 573 young adults aged 18\u201324 years from six purposively selected universities in Dhaka City, Bangladesh. Data were collected during September\u2013November 2015. Medians and their interquartile ranges of weekly time spent in total physical activity, and in different domains of physical activity, were computed. Non-parametric equality of medians test was used to examine gender differences in the median values. Chi-square test and Fisher\u2019s exact test were used to examine gender differences in the prevalence of meeting physical activity recommendations and frequency of participation in different leisure-time physical activities, and differences in meeting the activity recommendations by age and family income. Results: Seventeen percent of the participants were meeting moderate-to-vigorous physical activity (MVPA) recommendations with a significantly higher proportion of males than females (27 vs. 6%, p < .0001). Median duration of MVPA was significantly higher (p < .0001) for males [120 min/week (80, 190)] than females [90 min/week (50, 120)]. Jogging/running was the most commonly reported leisure-time physical activity, with 20% of males and 12% of females doing this at least once a week. Age and family income were not significantly associated with meeting MVPA recommendations. Conclusions: Four out of five young adults in Dhaka City did not meet the physical activity recommendations. Additional population-based studies, including regional and metropolitan areas, and using objective measurement, are needed to understand the physical activity patterns of Bangladeshi young adults