CURRENT APPLIED SCIENCE AND TECHNOLOGY

Protein Folding in the Presence of Osmolytes - a Complex Interplay of Multiple Forces

Vandhana Srinivasan — 2024-10-24

Living organisms employ various approaches to evade stressful environmental conditions such as high and low temperatures, salinity, and drought. The most adapted strategy to circumvent such stress conditions is the use of osmolytes, which are low molecular weight organic compounds. A large amount of evidence clearly demonstrates the role of osmolytes in conferring stability to proteins. Much is now known about the interaction mechanisms that exists between osmolytes and proteins. Osmolytes exert their effect on protein stability by acting on the thermodynamic equilibrium, ‘native conformation ↔ denatured conformation’ in the reverse direction. There are various forces that osmolytes interact with proteins to make such an effect on this equilibrium. The preferential hydration phenomenon is most accepted for the explanation of protein folding in the presence of osmolytes. The unfavorable interaction between the peptide backbone and osmolyte molecules has been understood to be the driving force for the preferential hydration effect. Contrary to this, the stabilization of proteins induced by polyols is solvophobic in nature. Numerous other models have been devised to explain the interactions between proteins and osmolytes at the atomic level. In this review, we systematically reviewed all major forces involved in osmolyte-protein interactions.

Pharmacophore-based SAR Analysis and Synthetic Route Review of Imidazole Core Analogues

Ravisekhar Mohana Priya — 2024-10-17

The five-membered nitrogen-containing heterocyclic moiety imidazole forms part of molecules that have been used to treat various diseases including life-threatening cancer. Moreover, the imidazole moiety is naturally present in various plants, marine, and microorganism-based metabolites and possesses various medicinal benefits. In this review, the pharmacophore-based substitution effect on the imidazole skeleton is primely compiled. A plethora of synthetic approaches have been adopted to develop imidazole hybrids, a number of which have been used as a basic skeleton for synthesizing other fused hybrids. Second, various recent synthetic methods, both in vitro and in vivo activities, are reviewed. Pharmacophoric examination showed that imidazole acts as a ring aromatic, or hydrophobic center depending on the type of substitution. While substitution with benzene ring, it acts only as a hydrogen bond donor and substitution with a hydrophobic ring and an aliphatic long chain on the imidazole ring leads to anticonvulsant and anti-inflammatory activity. The substitution of various electron-sharing features increases the antiulcerogenic property as well as anticancer activity. The results of this review work suggest that fabrication with specific pharmacophoric features aids in the synthesis of selective antagonist for various diseases.

Emotion Classification from Speech Waveform Using Machine Learning and Deep Learning Techniques

Smitha Narendra Pai — 2024-10-16

Emotions play a key role in determining the human mental state and indirectly express an individual’s well- being. A speech emotion recognition system can extract a person’s emotions from his/her speech inputs. There are some universal emotions such as anger, disgust, fear, happiness, pleasantness, sadness and neutral. These emotions are of significance especially in a situation like the Covid pandemic, when the aged or sick are vulnerable to depression. In the current paper, we examined various classification models with finite computational strength and resources in order to determine the emotion of a person from his/her speech. Speech prosodic features like pitch, loudness, and tone of speech, and work spectral features such as Mel Frequency Capstral Coefficients (MFCCs) of the voice were used to analyze the emotions of a person. Although sequence to sequence state of the art models for speech detection that offer high levels of accuracy and precision are currently in use, the computational needs of such approaches are high and inefficient. Therefore, in this work, we emphasised analysis and comparison of different classification algorithms such as multi layer perceptron, decision tree, support vector machine, and deep neural networks such as convolutional neural network and long short term memory. Given an audio file, the emotions that were exhibited by the speaker were recognized using machine learning and deep learning techniques. A comparative study was performed to identify the most appropriate algorithms that could be used to recognize emotions. Based on the experiment results, the MLP classifier and convolutional neural network model offered better accuracy with smaller variations when compared with other models used for the study.

An Effective Method for Quantitative Interpretation of Seawater Intrusion in Shallow Aquifers from Electrical Resistivity Data

Nur Islami — 2024-10-16

Groundwater in coastal areas is vulnerable to saltwater intrusion. Electrical resistivity is commonly used in order to detect saltwater intrusion due to its ability to distinguish the occurrence of saltwater in the pore water. In this research, a correlational approach was used to estimate percentage seawater content that was mixed with fresh water in a shallow aquifer. The study area was located in Dumai City, which was covered mainly by peat soil, but some areas were covered by sand and silt. A ground surface resistivity survey and direct soil resistivity measurements were used in the study. For both experiments, the Wenner configuration of electrical resistivity was employed. In order to determine the direct soil resistivity values, measurements of the soil's fluid content and character were made. The findings indicate that the resistivity value in the aquifer increased to 5–10 Wm at a 25% seawater content, from roughly 2–5 Wm at a 50% seawater content. The pore soil's rising salt content was the primary source of the sharp decline in resistivity values. By measuring the electrical resistivity on the surface, it is possible to accurately forecast the percentage of seawater mixture in the pore soil fluid.

Comparative Analysis of Deep Learning Models for Building Extraction from High-resolution Satellite Imagery

Tachasit Chueprasert — 2024-10-16

In this research, an approach to extract buildings from Google's satellite imagery was proposed. The performances of various deep learning models (U-Net, RIU-Net, U-Net++, Res-U-Net, and DeepLabV3+) on pre-processed datasets were compared. The models were trained using the similarity metrics of Intersection over Union (IoU) and Dice Similarity Coefficient (DSC). The best-performing models among the segmentation techniques were Res-U-Net and DeepLabV3+. Res-U-Net, an enhanced version of the traditional U-Net model that incorporates residual connections for improved feature propagation, achieved an F1 score of 85.43% when using the RGB dataset. Similarly, DeepLabV3+ also achieved high performance on the Enhanced RGB dataset, obtaining an F1 score of 85.18% after applying pre-processing techniques. This research highlights the significance of color as a dominant feature for accurate building extraction from satellite images. The findings contribute to improved methodologies for building identification, benefiting urban planning, and disaster management applications.

Phytotoxicity Stress Induced by Allelochemicals from Foliar Spray of Sida cordifolia Methanol Leaf Extract on Ageratum conyzoides and Oryza sativa

Hassan Ahmed — 2024-10-16

Allelochemicals are key inhibitors that induce chemical stress in plants. Their mechanisms as agents of oxidative stress are not well understood. A field study was conducted to evaluate herbicidal potential of Sida cordifolia methanol leaf extract (SCLE) on Ageratum conyzoides and Oryza sativa (weedy rice). SCLE concentrations of 0, 3, 6 and 9 g L^-1 were prepared and sprayed twice at 7 days interval. The results showed that the SCLE significantly (p<0.05) affected growth attributes, chlorophyll pigments, and proline, and catalase, superoxide dismutase and peroxidase enzyme activities in a concentration-dependent pattern. It was found that high concentrations of SCLE induced greater phytotoxicity against A. conyzoides compared to O. sativa. SCLE spraying stimulated production of reactive oxygen species, boosting their ability to cause damage and inhibit growth. The allelochemicals in the extract stimulated an increased in the level of proline, which is an indicator of oxidative stress. Understanding the physiological and biochemical responses to Sida extract can improve our knowledge on allelochemical target sites and help us to explicate the mechanisms of action of such compounds.

Gamma-oryzanol, Physicochemical and Antioxidant Properties of Stabilized Rice Bran Oil from Dough and Mature Grain Stages

Boonyabhorn Duangsa — 2024-10-17

Rice bran samples from dough and mature grain stages of rice were stabilized by heating in a hot air oven at 70ºC for 3h (or moisture <5.0%). Unstabilized and stabilized rice bran samples were subsequently pressed for oil extraction using a screw press machine. The γ-oryzanol, physicochemical, and antioxidant properties of both the unstabilized and stabilized rice bran oil (RBO) were determined. The fat content of fresh rice bran (unstabilized) from dough stage (19.19 %w.b.) was higher than that of the mature stage (13.22 %w.b.). Unstabilized RBO from mature stage (URBO-MS) had the lowest L* (35.70) and the highest a* (4.28) values. The γ-oryzanol content detected by UV-Vis spectophotometer was not significantly different among URBO-MS, stabilized RBO from the dough stage (SRBO-DS), and crude commercial RBO (CRBO). While the γ-oryzanol content of SRBO-DS detected by reversed-phase HPLC with diode array detector (DAD) was the highest, with a value of 1.00 g/100 g oil. The DPPH scavenging activity of SRBO-DS was the highest while that of CRBO was the lowest. The ABTS radical scavenging activity of unstabilized RBO from the dough stage (URBO-DS), SRBO-DS, and URBO-MS were not significantly different and were higher than that of stabilized RBO from the mature stage (SRBO-MS) and CRBO. The peroxide and free fatty acid (FFA) contents of SRBO-DS were the lowest with values of 1.19 meg/kg and 4.84% (as oleic acid), respectively. This finding suggests that stabalizing rice bran at the dough stage can increase the color values (as L* and b* values), γ-oryzanol, and DPPH scavenging activity, and decrease peroxide and FFA values of RBO. Thus, stabilized RBO from the dough stage grain may be a functional food with antioxidant activity.

ABiLSTM with BERT Embedding for Classification of Imbalanced COVID-19 Rumors

Rakesh Dutta — 2024-10-17

The coronavirus emerged at the end of 2019 and has caused thousands of casualties all over the world. The pandemic has also been accompanied by loss of employment and economic down fall. Naturally, the pandemic and lack of knowledge of coronavirus has created public anxiety and panic. Nowadays, social medias like Twitter and Facebook and online news forum reach most people and have become popular channels of communication and information sharing. Unfortunately, these have become easy targets for rumors and fake news. The rapid flow of rumors and misleading information on the coronavirus over these online platforms has promoted public anxiety and fear. Consequently, the detection of rumors has become obligatory for economy and public safety. In this context, the present research focused on detecting and classifying rumors so that precautionary measures can be incorporated. Attention-based BiLSTM with BERT for rumor classification on the COVID-19 rumor dataset was proposed. The suggested classification model achieved an accuracy of 80.71% and a micro-F1 score of 90.85. Furthermore, the experimental outcomes affirm the superior efficacy of our proposed technique over existing methods.

Performance and Stability of Elite Wheat Genotypes under Irrigated, Heat Stress and Heat Drought Environment

Radha Krishna Bhandari — 2024-10-17

Heat stress and drought are a significant threat to wheat production globally. These abiotic stresses influence growth, physiology, and yield-attributing parameters of wheat. To evaluate the performance and stability of elite wheat genotypes, a field experiment was conducted in the western region of Nepal at Bhairahawa, Rupandehi comprising twenty elite wheat lines under irrigated, heat stress, and heat drought conditions using alpha lattice design with two replications. The combined ANOVA across environments and AMMI model ANOVA revealed that traits, days to booting (DTB), days to heading (DTH), days to anthesis (DTA), spike weight (SW), thousand-kernel weight (TKW), and grain yield (GY) were significantly influenced by the environment (p≤0.05). The yield of wheat was reduced by 20% and 39% under heat stress and heat drought environments as compared to irrigated environment. BL 4919, NL 1368, and Bhrikuti were the highest yielding genotypes under irrigated, heat stress, and heat drought environments with mean grain yields of 6254, 4261.5, and 3322.5 kg ha^-1, respectively. AMMI analysis revealed that BL 4919, NL 1417, and NL 1420 were the most adaptive genotypes under irrigated, heat-stress, and heat-drought environments. Whereas the Which Won Where (WWW) model revealed that BL 4919, NL 1368, and Bhrikuti were the most adaptive genotype under irrigated, heat stress, and heat drought environments. From Mean vs. Stability assessment, NL 1412 and NL 1369 were identified as high-yielding stable genotypes. Both the AMMI and WWW models identified NL 1386 as the most stable genotype with the lowest AMMI stability value (ASV) of 0.13. Hence, these selected genotypes should further be promoted in wheat improvement programs to further develop potential climate-resilient varieties.

Genome Characterization for the Antimicrobial Potential of Streptomyces samsunensis SA31, a Rhizospheric Actinomycete of Cymbopogon citratus (DC) Stapf.

Karn Wongsariya — 2024-10-17

Streptomyces species are promising resources of bioactive compounds that play a vital role in medicinal biotechnology. Streptomyces sp. SA31 was isolated from the rhizospheric soil of Cymbopogon citratus (DC) Stapf. The strain was identified as Streptomyces samsunensis based on genome-based taxonomic analysis. The draft genome of strain SA31 contained 11,850,342 bp with a high percentage of G+C at 71.0% and carried 9,350 predicted protein-encoding sequences (CDSs). Furthermore, the secondary metabolite biosynthesis gene clusters in the genome of strain SA31 were predicted by antiSMASH. In silico analysis showed 71 predicted biosynthetic gene clusters (BGCs) responsible for antimicrobial secondary metabolite synthesis. Most gene clusters were involved in the biosynthesis of polyketide synthase. The genome of strain SA31 harbored seven types of polyketide biosynthesis gene clusters that might be associated with antimicrobial activity. Additionally, the genome of strain SA31 contained unexplored secondary metabolite biosynthesis gene clusters. In vitro antimicrobial assay showed that an ethyl acetate extract from the culture broth of strain SA31 could inhibit the growth of Staphylococcus aureus ATCC 25923, Kocuria rhizophila ATCC 9341, Bacillus subtilis ATCC 6633, Candida albicans ATCC 10231, and Aspergillus flavus IMI 242684, implying that the genome of strain SA31 contained potential BGCs for the production of antimicrobial secondary metabolites and led to the isolation of geldanamycin and 17-O-demethylgeldanamycin. Therefore, it can be proved that the rhizosphere-associated soil of C. citratus (DC) Stapf. is a rich habitat for actinomycetes that are capable of producing promising biologically active compounds.

Seawater Characteristics and Their Influence on Green Mussel (Perna viridis) Production Potential

Chayarat Srisunont — 2024-10-17

Seawater fluctuation caused by climate change and domestic wastewater can affect the cultivation of green mussel (Perna viridis), which is a valuable marine food in the Indo-Pacific region. Hence, this research aimed to investigate the variation of seawater parameters in green mussel cultivation areas and the impact of changes in those parameters on mussel production. Three cultivation sites, pond, coastal line, and estuarine, were chosen to represent three cultivation methods. At each site, seawater variables and green mussels were collected monthly from January to December 2019. The results showed that seawater parameters varied significantly acroos the cultivation sites, and seasonal variations were found to be related to intense rainfall. The highest mussel production was found in estuarine areas followed by coastal line areas and ponds, which were 0.25±0.05, 0.01±0.003, and -0.01±0.02 kg/m²/month, respectively. Statistical analysis revealed that salinity and conductivity were factors that positively influenced mussel production potential. In estuarine areas, the salinity was suitable for mussel growth and there was abundant food for mussels; subsequently, estuarine areas had the highest mussel production. Meanwhile, ponds were not suitable for mussel cultivation due to low salinity. Although coastal line areas had the highest salinity, chlorophyll a levels were low, indicating a lack of food available for mussels. Consequently, the production potential was low. These results can assist farmers to select the best available areas for green mussel culture. Finally, in time of unstable seawater quality caused by environmental crises, our results can be useful for identifying the impact of seawater quality on green mussel production in each cultivation area.

Enhancing Workplace Safety for Disabled Farmers in Thailand: A Quasi-Experimental Study of Ergonomic Interventions in Vermicompost Production

Goontalee Bangkadanara — 2024-10-17

The aim of this study was to improve the working environment for disabled farmers in vermicompost production using participatory action-oriented training (PAOT). Potential hazards were identified through Job Safety Analysis (JSA), and improvements were implemented based on the analysis. The winnowing step was found to have the highest risk, as farmers had to manually separate vermicompost and earthworms by shaking the mixture through a filter. To address this, a vermicompost winnowing machine was developed specifically for disabled farmers, reducing their working time and the risk of muscle injuries. Ergonomic assessments were conducted using Rapid Entire Body Assessment (REBA). The assessments compared the risks associated with the manual process to those when using the newly developed winnowing machine. The results indicated a reduction in musculoskeletal disorder (MSD) risk for all disabled groups. The findings of this study emphasize the importance of considering occupational health and safety for disabled individuals in agriculture. By implementing ergonomic improvements such as redesigned tools and adjusted workstations, the safety and well-being of disabled farmers can be enhanced. This contributes to creating inclusive and productive work environments. In conclusion, through the application of PAOT and ergonomic assessments, this study successfully identified potential hazards and implemented improvements in vermicompost production for disabled farmers. The development of a specialized winnowing machine reduced the risk of musculoskeletal disorders. Promoting occupational health and safety measures is crucial for supporting the participation and well-being of disabled individuals in agricultural work.

Mechanical and Physical Properties of Binderless Particleboard from Rice Straw and Banana Pseudostem

Nutnaree Saropas — 2024-10-17

The commercial particleboards used nowadays are manufactured with synthetic adhesives containing formaldehyde which is considered harmful to health and has a negative impact on the environment. A binderless particleboard fabricated from agricultural waste materials can solve these issues. This research explored the feasibility of using rice straw and banana pseudostem to produce binderless particleboard. The optimal preparation conditions for production were carried out using the ratios of rice straw to banana pseudostem at 100:0, 75:25, 50:50, 25:75 and 0:100, the pressing temperatures of 140°C, 160°C, and 180°C, and the compression times of 10 and 30 min. The physical and mechanical properties of the particleboard including density, moisture content, thickness swelling, modulus of rupture and modulus of elasticity were investigated. Morphological analysis was studied by scanning electron microscopy. It was found that it was possible to produce binderless particleboard from rice straw and banana pseudostem using a hot press method. The results showed that a higher content of banana pseudostem led to good mechanical properties and adhesion with lower thickness swelling. Cross-section of the binderless particleboards revealed that banana pseudostem acted as a binder. Fourier transform infrared spectroscopy (FTIR) also confirmed the occurrence of self-bonding in these binderless particleboards. The optimum preparation conditions were achieved with the ratio of rice straw to banana pseudostem of 0:100, and a pressing temperature of 180°C for 30 min. The modulus of rupture (MOR) and modulus of elasticity (MOE) were approximately 12 MPa and 1800 MPa, respectively. This binderless particleboard is a potential candidate for use in green buildings.

Spore Germination and Gametophyte Development of Pleocnemia irregularis (C.Presl) Holttum (Dryopteridaceae) Using Modified Culture Media

Ermalene Taer — 2024-10-17

Pleocnemia irregularis is an economically important fern, with no known literature on its developmental biology. Thus, this study was aimed to document various aspects of its developmental stages including its patterns of spore germination, the morphology of various developmental stages, type of gametophyte development and percentage of gametophyte survival using modified culture media as the substrate. Morphological observations highlighted the distinctive monolete-bilateral, ellipsoidal, and reticulated perispores, while the prominent protuberance of club-shaped unicellular hairs persisted continuously from the germ filaments to the late gametophytic stages. Spore germination follows the Vittaria-type while Aspidium-type for the prothallial development. Among the treatments, T0 (garden soil), T3 (ground adventitious roots of tree fern + ground clay pots), and T1 (pure ground adventitious roots of tree fern) demonstrated a consistently prolific performances, from spore germination until the late gametophyte stage with rapid development led by T0. Conversely, consistent delayed development was observed for spores sown in T2 (ground clay pots). Regarding gametophyte survival, T0 significantly yielded the highest percentage of gametophyte survival (94%), while T2 obtained the lowest number (48.33%). No performance variation was observed in T3 and T1. As a result, T0 served as the best culture medium for gametophyte coverage. The utilization of accessible and cost-effective growing media provides a conducive substrate for the successful developmental biological study of P. irregularis. The information provided in this paper will certainly be useful in studying the developmental biology of those often overlooked but economically important pteridophytes.

Relevant Physical Factors for Estimation of Volatile Organic Compounds Emissions from Floating Storage and Offloading

Chalee Seekramon — 2024-10-17

Volatile organic compounds (VOCs) have harmful effects on human and the environment. Floating storage and offloading (FSO) vessels are recognized as one source of VOCs emissions. This study investigated the physical factors used to estimate the emission of VOCs from an FSO based on wave height, ambient temperature, storage temperature, storage quantity, Reid vapor pressure (RVP), and daily incoming rate. Daily data on the natural gas liquids were collected on the FSO. A second-order multiple linear regression (MLR) with interaction effects was used to analyze the relationship between the studied physical factors and VOC venting volumes. The set of relevant physical factors and interaction effects that produced the maximum adjusted coefficient of determination was selected. The significant factors and interaction effects were investigated based on a t-test at a significance level of 0.05. The results showed that the significant factors for estimation of the venting volume, corresponding to VOCs emissions, were wave height, storage temperature (which was related to the daily incoming rate), and RVP. Venting volume was negatively related to storage temperature, especially when the storage temperature was low, and wave height was positively related to venting volume when the RVP was high. The interaction effect showed that wave height was important when RVP was high and the second-order MLR showed that the storage temperature was important when it was low.