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An overview of remote monitoring methods in biodiversity conservation

Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the...

Fusing compressed deep ConvNets with a self-normalizing residual block and alpha dropout for a cost-efficient classification and diagnosis of gastrointestinal tract diseases

The challenging task of diagnosing gastrointestinal (GI) tracts recently became a popular research topic, where most researchers performed extraordinary feats using numerous deep learning (DL) and computer vision techniques to achieve state-of-the-art (SOTA) diagnostic performance based on accuracy. However, most proposed methods relied on combining complex computational methods and algorithms, causing a significant increase in...

eS2MART Teaching and learning material in chemistry: Enhancing spatial skills thru augmented reality technology

This study developed a teaching and learning material (TLM) in chemistry entitled eS2MART TLM with integrated augmented reality (AR) technology and assessed its effect on students’ learning gains in terms of spatial skills and students’ learning experience on the use of augmented reality as a tool in understanding atomic theory, chemical bonding and molecular structure....

Truncating a densely connected convolutional neural network with partial layer freezing and feature fusion for diagnosing COVID-19 from chest X-rays

Deep learning and computer vision revolutionized a new method to automate medical image diagnosis. However, to achieve reliable and state-of-the-art performance, vision-based models require high computing costs and robust datasets. Moreover, even with the conventional training methods, large vision-based models still involve lengthy epochs and costly disk consumptions that can entail difficulty during deployment due...

A pivotal restructuring of modelling the control of COVID-19 during and after massive vaccination for the next few years

This paper presents a new mathematical feedback model to demonstrate how direct observations of the epidemiological compartments of population could be mapped to inputs, such that the social spread of the disease is asymptotically subdued. Details of the stabilization and robustness are included. This is a pivotal restructuring of modelling the control of corona virus...

Kinetics and Isotherm Studies on Adsorption of Hexavalent Chromium Using Activated Carbon from Water Hyacinth

The present study is focused on the use of activated carbon derived from water hyacinth (WH-AC) as adsorbent for the removal of Cr(VI) from aqueous solution. The optimized WH-AC was found to be mesoporous and considered as granular. The surface area of 11.564 m2/g was found to have a good adsorption capacity. The adsorption data...

On the Use of Surfactant-Complexed Chitosan for Toughening 3D Printed Polymethacrylate Composites

This work reports a simple approach to prepare toughened 3D-printed polymethacrylate (PMA) composites using surfactant-modified chitosan (SMCS) particles at loadings between 2–10 wt%. Chitosan (CS) is modified with anionic surfactant, sodium dodecyl sulfate, via ionic complexation to facilitate compatibility and dispersion of CS to PMA matrix by non-covalent interactions between the components. The study successfully...

Empirical Analysis of a Fine-Tuned Deep Convolutional Model in Classifying and Detecting Malaria Parasites from Blood Smears

In this work, we empirically evaluated the efficiency of the recent EfficientNetB0 model to identify and diagnose malaria parasite infections in blood smears. The dataset used was collected and classified by relevant experts from the Lister Hill National Centre for Biomedical Communications (LHNCBC). We prepared our samples with minimal image transformations as opposed to others,...

Diagnosing Covid-19 chest x-rays with a lightweight truncated DenseNet with partial layer freezing and feature fusion

Due to the unforeseen turn of events, our world has undergone another global pandemic from a highly contagious novel coronavirus named COVID-19. The novel virus inflames the lungs similarly to Pneumonia, making it challenging to diagnose. Currently, the common standard to diagnose the virus’s presence from an individual is using a molecular real-time Reverse-Transcription Polymerase...

A Computational Approach to Multistationarity in Poly-PL Kinetic Systems

One important question that interests those who work in chemical reaction network theory (CRNT) is this: Does the system obtained from a reaction network admit a positive equilibrium and if it does, can there be more than one within a stoichiometric class? The higher deficiency algorithm (HDA) of Ji and Feinberg provided a method of...

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