CURRENT APPLIED SCIENCE AND TECHNOLOGY

Synthesis and Cytotoxicity Evaluation of Novel C-3 Aminocarbamate Pregnenolone Derivatives

Patchanee Charoenying — 2024-12-09

Cancer is one of the leading causes of death worldwide. There are many ongoing studies in the search for new treatments or drugs to combat cancer. Similarly, in this research, twelve 3-aminocarbamate pregnenolones (2a–2l) were designed, synthesized, and evaluated for their cytotoxicity against five cancer cell lines: Human hepatocellular carcinoma (HepG2), Human colon adenocarcinoma (HT-29), Human oral cavity carcinoma (KB), Human breast adenocarcinoma (MCF-7), Murine leukemia (P388), and one normal cell line, African green monkey kidney fibroblast (Vero), using the MTT assay. Notably, 3-aminobenzylcarbamate pregnenolone (2b), 3-diaminoheptylcarbamate pregnenolone (2f), and 3-diaminopropanolcarbamate derivative (2i) were the most potent against these cancer cell lines. Specifically, for P388 cell lines, these compounds were more potent than the positive control drug, vinblastine sulfate salt. Results from the SAR study demonstrated that the length of the alkyl chain of diaminocarbamate derivatives was crucial for their anticancer properties. These findings will be useful in the future research and development of anticancer drugs.

Genomic Insights into Rheumatoid Arthritis through computational Profiling for Hub Genes

Sushma Thandal Anantharaman — 2024-12-09

Rheumatoid arthritis (RA) is a complex autoimmune disorder predominantly affecting joints, with its etiology and response to treatment still not fully understood despite extensive historical documentation. This study aims to shed light on the differentially expressed genes (DEGs) associated with RA progression, potentially identifying new drug targets and management strategies. This study analyzed gene expression data (GSE193193) from the Gene Expression Omnibus (GEO) database, identifying 3672 significant DEGs out of 36107 initially retrieved genes. Among these, 283 genes were up-regulated and 360 were down-regulated. Gene enrichment analysis was performed to uncover relevant gene ontology terms and pathways. Subsequently, network construction and analysis, along with hub gene prediction using Cytoscape's MCODE and CytoHubba plugins, were conducted. Key genes identified in this study include HBB, ALAS2, GATA1, AHSP, HBG1, HBG2, HBD, KLF1, SLC4A1, EPB42, ZMYND10, DNAJC7, HYDIN, LRRC6, FN1, NCAM1, FASLG, CTCF, SMAD4, and STAT1. These genes are implicated not only in RA but also in other diseases, presenting them as potential therapeutic targets. Additionally, three transcription factors (GATA1, NFKB1, and RELA) and one miRNA (has-mir-27a-3p) were identified as key regulators of these hub genes. In conclusion, this study not only enhances our understanding of the molecular mechanisms underlying RA but also identifies several critical DEGs and regulatory factors that could serve as promising targets for therapeutic intervention. The identification of these genes and regulatory elements paves the way for the development of targeted treatments, which could significantly improve disease management and patient outcomes. Future research focusing on these identified targets may lead to innovative strategies for combating RA and potentially other autoimmune disorders, thereby offering new hope to patients affected by these conditions.

Effects of Nitrogen Fertilizer Rate with Urease and Nitrification Inhibitors on Certain Morphological Traits and Quality of Sugarcane (Saccharum officinarum L.)

Phatchariya Welutung — 2024-12-09

In this study, we investigated the effects of the N fertilizer rates (commonly applied by farmers compared to rate based on soil analysis) with an appropriate N fertilizer rate associated with urease inhibitors (UIs), nitrification inhibitors (NIs) and their combinations (UINIs) on sugarcane (Saccharum officinarum L.) growth, morphological traits, and quality. The treatments consisted of 2 UIs (N-(n-butyl) thiophosphoric triamide (NBPT) and garlic (Allium sativum L.)) and 3 NIs (dimethylpyrazole phosphate (DMPP), ground neem seed (Azadirachta indica A. Juss. var. siamensis Valeton) and praxelis (Praxelis clematidea (Griseb.) R.M. King & H. Rob)). The results showed that increasing the N fertilizer rate encouraged sugarcane growth by up to 4.5% and increased N content by 16.2% in the cane yield. Adding inhibitors produced positive responses in plant growth and yield, possibly due to prolonging N fertilizer in the soil and extending the supply of N to the plant. Compared to biological inhibitors, the synthetic inhibitors resulted in longer stalk lengths but lower stalk diameters. The inhibitor treatments significantly enhanced the aboveground biomass and N content in plants by up to 41.5 and 41.9%, respectively, compared to only fertilizer. The inhibitor treatments in commercial cane sugar (CCS) increased by up to 13.6%. However, decreasing the N fertilizer rate with addition of inhibitors assisted in keeping mineral N in the soil, which further enhanced N uptake and led to improved plant growth and yield. Added DMPP showed the potential to slow down N loss from soil, which enhanced rapid growth and resulted in higher aboveground biomass.

Improvement of the Electrical Properties of ZnO Nanomaterials with Fe by Co-precipitation Method

Pitchaporn Kingpho — 2024-12-09

Fe-doped ZnO nanomaterials were prepared by the co-precipitation method. The experiments used a solution of 0.5 M for ZnCl₂, doped with FeSO₄ in proportions of 0-100 wt.%, followed by the addition of 1 M for NaOH solution until a pH of 12 was reached. Next, the precipitated substances were calcinated at 550ºC for 3 h in air. SEM image analysis showed that the nanoparticles formed in the condition of pure ZnO and Fe₂O₃ whereas rod-shaped formed with Fe doping. Nanoparticles of ZnO transformed into nanorods when doped with Fe. EDS analysis detected Fe under the conditions of 3 and 5 wt.% doping. XRD patterns of ZnO and all doping of Fe in ZnO nanostructures were corresponded to a hexagonal wurtzite structure of ZnO which showed crystallite size in the range of 25-29 nm. The electrical properties of Fe-doped ZnO nanostructures were identified by the spectroscope measurements of fluorescence and ultraviolet-visible absorption, and the electrical conductivity was calculated. It was found that Fe doping at 3 wt.% produced the lowest energy band gap (based on spectroscopy results) and this condition was associated with the highest electrical conductivity of 0.21 x 10^-3 (Ω.cm)^-1 which was calculated from the measurement of electrical resistance by two probes. Therefore, Fe doping can improve the electrical properties of ZnO nanostructures.

Optimizing Energy Efficiency of Adiabatic Frequency Conversion in an Add-Drop Resonator

Busara Pattanasiri — 2024-12-09

Adiabatic frequency conversion (AFC) in add-drop resonators holds promise for enhancing energy efficiency in photonic applications. This theoretical study investigates the conditions for optimizing the energy efficiency of the drop port within an add-drop resonator configuration. The analysis considers both fixed input pulse shapes and continuous wave inputs, taking into account AFC's relative timescales. Specifically, the critical coupling regime is explored, and it is observed that the extrinsic decay rates into the drop port and through port converge to nearly equal values, thereby maximizing drop port efficiency. Moreover, when a global parameter is swept, it is demonstrated that the maximal efficiency of the drop port is achieved when the extrinsic decay rates of both ports are equal. This optimization strategy extends to scenarios involving continuous wave inputs as well. These findings provide valuable insights for designing high-performance add-drop resonators and advancing the practical implementation of AFC in photonic systems.

Sugarcane Yield Estimation Using UAV-Based RGB Images and Allometric Equations

Chitsanuphong Pratum — 2024-12-09

Accurately estimating pre-harvest sugarcane yield has long been a challenge. There are many methods for predicting sugarcane yield, ranging from simple empirical equations to complex physiological models. This paper reports a study on a method for predicting sugarcane yield using allometric equations combined with UAV-based RGB images (UAVI). UAVI were used for the estimation of the sugarcane height, which is in the form of the sugarcane height model (HM). Sugarcane height is one of the key factors in calculating sugarcane yield in the allometric equation. The results showed that the HM could be used in the allometric equation. There was only a slight discrepancy compared to measurement with a tape measure in the field. In developing the allometric equation, the authors created regression models to estimate aboveground biomass weight in leaf bush (W_l) and millable stalk (W_ms) based on sugarcane height (H) and diameter measured from the first segment of sugarcane aboveground (D_fs). The model estimated aboveground biomass weight sufficiently for all stages of cultivation. Based on this model, the authors developed two general equations: Y = 0.0842 H * D_fs^0.9827; R² = 0.93 (used for leaf bush), and Y = 0.1254 H * D_fs^1.3926; R² = 0.93 (used for millable stalk). The decision correlation coefficient (R²) was 80% reliable. The HM models were slightly different from field measurements with a tape measure. Also, there was a little inaccuracy in the root-mean-square error (RMSE) between the sugarcane heights analyzed from UAVI and field measurements using tape measure. The RMSE values, arranged from highest to lowest according to the sugarcane growth stage were: 0.35 m (tillering phase, T_P), 0.25 m (grand growth phase, G_P), and 0.24 m (ripening phase, R_P). Using the HM value in the allometric equation effectively estimated the sugarcane yield at different growth stages. Sugarcane growth at T_P and G_P phases gave the highest sugarcane yield at 200 cm of the HM value, with total yields of 11.49 and 16.75 ton/hectare, respectively. Whereas, R_P gave the highest sugarcane yield at 350 cm of the HM value (total yield at 42.97 ton/hectare). Overall, an accurate estimation of the aboveground biomass of leaf bush and millable stalk can be obtained using these equations. The authors believe that the research methods presented here can help sugarcane farmers to better estimate yield prior to harvest.

Plankton Assemblages and Water Quality in Kirulapone, Wellawatte, and Dehiwala Canals, Colombo, Sri Lanka

Madhavi Kolambage — 2024-12-09

Plankton are significant bioindicators that can be employed in water quality assessments. However, there is a notable scarcity of plankton-based water quality studies in the Colombo South canal system. The present study was carried out to assess water quality in three selected canals belonging to the Colombo South canal system with special reference to the plankton community. Plankton and water samples were collected from November 2022 to February 2023 from twelve locations along the three canals of the Colombo South canal system. During the study, nine physiochemical parameters were measured and the biotic indices were calculated. Pollution status and the suitability of the canals for aquatic life were assessed using the water pollution index (WPI) and the weighted arithmetic water quality index (WAWQI), respectively. Overall, forty-six phytoplankton species and seventeen zooplankton species were recorded during the study. Chlorophyceae (48%) and Rotifera (59%) were the dominant plankton groups. More than 50% of the total recorded plankton species were pollution indicators. According to Principal Component Analysis (PCA), plankton abundance showed a weak positive correlation with nitrate, phosphate, TDS, BOD₅, salinity, electrical conductivity, and temperature while negatively correlated with dissolved oxygen. The Shannon-Weiner diversity index and WPI revealed a moderate pollution level in the canals. WAWQI indicated that the canals were unsuitable for aquatic life. Moreover, moderate and high pollution-tolerant organisms were more dominant in the canals. Hence, the proper measures must be taken to restore the canal ecosystem. This study could significantly guide future research and highlight the importance of plankton in water quality assessments.

Drought Index Assessment Using Thermal Vegetation Index (TVI) Method and Soil Physic Approaches (A Case study: Manyaran District, Central Java, Indonesia)

Mujiyo Mujiyo — 2024-12-09

The early detection of areas that have the potential to experience drought is necessary to minimize the hazards of land drought. The study aimed to identify the current conditions of drought by TVI with actual soil physic characteristic approaches, and to find the determinant factors related to the dynamics of agricultural land drought conditions so as to determine land management strategies that are considered appropriate and efficient to prevent agricultural land drought. The method for analyzing the drought index was the Thermal Vegetation Index (TVI) method, which involved the calculation of the ratio between the Land Surface Temperature (LST) and the vegetation index using Normalized Difference Vegetation Index (NDVI). The method in this research was modified by adding soil physical indicators, including soil moisture content, bulk density, and pF value. The results showed that the land drought classes were normal drought (46.89% study area), mild drought (20.62% study area), moderate drought (14.10% study area), severe drought (8.58% study area), and extreme drought (9.81% study area). Land drought was highly correlated to the soil's physical condition, negatively correlated with the moisture content (r -0.403) and bulk density (r -0.317), and positively correlated with the pF (r 0.429). Enhancing the soil’s capacity to absorb water and retain moisture through the addition of organic matter is one of the required techniques as a suitable recommendation to the issue after determining the determinant factors and present conditions.

The Effects of Different Plant Growth Regulators and Nutrient Solutions on Leaf Bud Propagation in Different Cassava Varieties

Sovannara Moun — 2024-12-09

Cassava mosaic virus is a growing threat to cassava cultivation, and the rapid propagation of disease-free cassava stems offers an alternative approach to producing planting material. This study investigated the effects of different plant growth regulators and nutrient media on leaf bud propagation among different cassava varieties. A 3 x 4 factorial with a randomized complete block design (RCBD) was used with three replications. Three cassava varieties, Kasetsart 50 (KU50), Rayong 9 (RY9), and Huay Bong 60 (HB60) were assigned as factor A, and four different media, i.e., control treatment (distilled water), indole-3-butyric acid (IBA) at 500 mg/L, Semi-Autotrophic Hydroponic (SAH) nutrient solution, and IBA+SAH, were assigned as factor B. Data were recorded for growth and survival traits at 30 days. The results showed that the RY9 variety exhibited superior growth parameters, whereas the KU50 and HB60 varieties showed a higher survival rate. Applying IBA, alone or with SAH, negatively affected cassava plantlet growth and survival rate. On the other hand, applying SAH alone yielded results comparable to the control treatment, significantly differing from the IBA and IBA+SAH treatments. This study also noted that IBA applications enhanced root traits in the RY9 variety but not in other varieties. The HB60 variety outperformed the survival rates and dry shoot weights of RY9 and KU50 under SAH treatment. This finding can be used to select an effective method for leaf bud multiplication in response to the demand for disease-free cassava planting materials.

Transformation towards Organic Cassava Production in Yasothon Province, Thailand

Benjamas Kumsueb — 2024-12-09

With the marked increase in consumer and commercial demand for organic foods and products, organic cassava production has become a viable alternative for small growers because it can lead to the sustainability of the agriculture and food production system. However, few studies have been conducted to enable a more comprehensive understanding of the factors that contribute to the transformation from chemical into organic cassava production systems. This study quantitatively aimed to identify socioeconomic, cassava profitability, and institutional factors that influence the cultural practice transformation towards organic cassava production in a district of Yasothon province, Thailand. We used a structured interview schedule to collect data from 283 sampled cassava growers comprising 236 chemical cassava growers and 47 organic cassava growers in the district during the period from August 2020 to November 2020. Quantitatively, we used the binary logistic regression method to identify the positive and negative factors contributing to the transformation of cassava production systems including growers’ motivations for the transformation. The study findings indicated that income from organic cassava was taken as the main motivation for growers’ decisions to transform (40.3%). We found that organic cassava farm gate price, access to formal credit, labor used and membership in growers’ organizations were positive significant factors that affected the cultural practice transformation. Finally, small cassava growers as well as stakeholders should systemically be considered by policymakers and in strategic intervention through relevant institutions.

Development of Latent Fingerprints on Wet, Non-Porous Surfaces by Small Particle Reagent with Zinc Oxide Nanoparticles

Penpicha Mode-on — 2025-01-22

Small particle reagent (SPR) technique is a method used for detecting latent fingerprints on wet, non-porous surfaces by suspending nanoparticles in a reagent that binds with fatty acid residues on fingerprints. The small particle reagent technique is particularly effective for detecting latent fingerprints on evidence that has been submerged underwater for prolonged periods. However, due to its reliance on imported reagents, SPR is often expensive and involves a lengthy waiting period. Consequently, many researchers have attempted to develop SPR formulations using easily obtainable, cost-effective, and safe chemicals. In this study, we prepared two new SPR formulations containing zinc oxide nanoparticles mixed with diethylene glycol monoethyl ether. Both formulations used a surfactant composed of two types (sodium tetradecyl sulfate and Tergitol NP-9) for the development of latent fingerprints on wet surfaces. Latent fingerprints were deposited on four different non-porous surfaces, including stainless-steel spoons, glass slides, aluminum foil, and plastic slides. These surfaces were immersed in tap water for 1, 3, 7, 14 and 30 days. The resulting latent fingerprints were analyzed using the Mini Automated Fingerprint Identification System and were shown to produce clear, sharp, and detailed fingerprints on the non-porous surfaces. The best results were found on the surfaces of stainless-steel spoons with both formulations, where minutiae were detectable at more than 40 points even after the surfaces had been immersed in water for up to 30 days. This study provides forensic scientists and crime scene investigators with a faster and safer method for developing latent fingerprints using non-hazardous materials, which could serve as an alternative to conventional formulations.

Intrusion Detection System: An Ensemble Deep Learning Approach for Cloud Computing Using EBWO

Vinolia Alexander Moudiappa — 2025-01-22

Cloud computing is the industry standard for data storage, sharing, processing, and other services. It experienced numerous security problems as a result of the regular attacks. These security issues are worsened by the variety of attack situations that exist. One of the most established safety measures applied to cloud computing is the intrusion detection system (IDS). An effective security model is necessary for the IDS system, though, to increase cloud security. In this study, we used ensemble categorization methods and a feature selection algorithm to construct an effective IDS for the cloud environment. The proposed BOT-IOT, CSE-CIC-IDS 2018, and Ciciddos datasets were pre-processed, which involved cleaning the data, applying one hot encoding, and normalizing steps. The Enhanced Black Widow Optimization (EBWO) algorithm was employed to choose the most advantageous reduced feature sets from the provided incursion datasets. We used an ensemble of Hierarchical Multi-scale LSTM (HMLSTM) and Darknet Convolutional Neural Network (DNetCNN) to categorize the attacks. The combination of DNetCNN and HMLSTM was used to identify intrusions, effectively classifying attacks, lowering false alarm rates, and increasing detection rates. Simulation research showed that the proposed strategy performed better than the baseline in terms of F-Score, DR, and FPR, as well as accuracy, detection rate, and precision.

Effect of Rice Input Variables and Climate Change Factors on Total Factor Productivity of Rice in Nigeria

Governor Ekene Oyita — 2025-01-27

This study evaluated the effect of rice production input variables and climate change variables on rice total factor productivity (TFP) in Nigeria. The research utilizes various data sets obtained from reputable organizations to analyze the period from 1961 to 2020. Descriptive and inferential statistics were employed to analyze the data. The study findings indicate an upward trajectory in rice TFP in Nigeria over the examined period. Regression analysis reveals that labor and capital have a significant positive effect on rice TFP, indicating that increased labor and capital investments can enhance productivity. Rainfall and sunlight duration also show a significant positive relationship with rice TFP, emphasizing their crucial role in rice farming. The study highlights the importance of addressing labor scarcity and promoting access to capital for farmers. Moreover, it emphasizes the quest for optimal rainfall and sunlight conditions throughout the rice cultivation process. The model's diagnostic tests confirm its reliability, and the findings demonstrate the statistical significance of the independent variables in explaining rice TFP. Overall, this research gives insightful information on the factors influencing rice TFP in Nigeria. It offers recommendations for stakeholders and decision-makers to enhance productivity by addressing labor scarcity, promoting capital access, and optimizing climatic conditions for rice cultivation.

Evaluation of Peppercorn Quality from Ba Ria - Vung Tau, Viet Nam

Xuan-Tien Le — 2025-01-27

In this study, the quality of some pepper species, collected in Ba Ria – Vung Tau, Vietnam in March 2022, was investigated. The content of oleoresin and piperine was evaluated based on the species, size, ripeness, and density of the peppercorn. Piperine content in the peppers was determined by spectrophotometry (UV-Vis) and high-performance liquid chromatography (HPLC). In addition, the study also examined the quality of white pepper. The results showed the Vinh Linh pepper had high oleoresin content (23.72±0.01%, second only to Sri Lankan pepper) but there were no outstanding records in piperine content among all investigated pepper species. For the size parameter, the piperine content on the dry material declined from the smallest peppercorn size of 2.50-4.00 mm (4.94±0.32%) to the largest size > 5 mm (2.66±0.09%). The oleoresin and piperine recovery efficiency of Vinh Linh pepper tended to stop or decrease when entering the ripening stage. Specifically, ripe peppercorns had low oleoresin content (15.92±0.51%). Similarly, from density of 600 to 300 g/L, the lower the density of pepper, the higher the piperine content (3.11±0.09% to 5.04±0.05%) was found. Furthermore, black pepper obtained 2 times higher oleoresin content than white pepper, but the piperine content was lower by many times. This research shredded light on the classification of the Vietnamese pepper for suitable applications in the commercial market.

Sustaining Productivity of Egyptian Water Resources Under Climate Changes – A Review

Sayed Abdeen — 2025-01-27

One of the biggest economic and social concerns of the century will be the issues of water resources in the arid regions of the Mediterranean, where mismanagement of water resources is a threat to sustainable development. Egypt is one of the nations that will face significant issues due to its steady portion of the Nile water. Climate change influences the spatial and temporal distribution of water supplies and the amount of crop evapotranspiration. In addition, water use in agriculture is by far the highest and is frequently criticized as being the least efficient. So, gaining more output per unit of utilized water is the idea behind improving agricultural water productivity. Identifying water resources and improving water productivity techniques are essential in making the most effective use of agriculture in the Mediterranean regions. Freshwater resources in Egypt include the flow of the Nile, precipitation, and groundwater. Egypt also uses a variety of low-quality water sources including treated wastewater and agricultural drainage water, and desalination is also utilized to provide residential water for several regions along the Mediterranean and Red Sea coasts. In this paper, water resources in Egypt, its irrigation systems, methods of water-saving and improving water productivity are discussed.