Small Amount Research Articles

Consistency Self-Training Semi-Supervised Method for Road Extraction from Remote Sensing Images

Road extraction techniques based on remote sensing image have significantly advanced. Currently, fully supervised road segmentation neural networks based on remote sensing images require a significant number of densely labeled road samples, limiting their applicability in large-scale scenarios. Consequently, semi-supervised methods that utilize fewer labeled data have gained increasing attention. However, the imbalance between a small quantity of labeled data and a large volume of unlabeled data leads to local detail errors and overall cognitive mistakes in semi-supervised road extraction. To address this challenge, this paper proposes a novel consistency self-training semi-supervised method (CSSnet), which effectively learns from a limited number of labeled data samples and a large amount of unlabeled data. This method integrates self-training semi-supervised segmentation with semi-supervised classification. The semi-supervised segmentation component relies on an enhanced generative adversarial network for semantic segmentation, which significantly reduces local detail errors. The semi-supervised classification component relies on an upgraded mean-teacher network to handle overall cognitive errors. Our method exhibits excellent performance with a modest amount of labeled data. This study was validated on three separate road datasets comprising high-resolution remote sensing satellite images and UAV photographs. Experimental findings showed that our method consistently outperformed state-of-the-art semi-supervised methods and several classic fully supervised methods.

A Study of Heat Recovery and Hydrogen Generation Systems for Methanol Engines

Biofuels are the most essential types of alternative fuels, which currently have significant potential to reduce CO2 emissions compared to fossil fuels. Methanol is a more efficient fuel than petrol due to its physicochemical properties, such as a higher latent heat of vaporization, research octane number, and heat of combustion of the fuel–air mixture. Also, biomethanol is cheaper than traditional petrol and diesel fuel for agricultural countries. The authors have proposed a new approach to improve the characteristics and efficiency of methanol diesel engines by using biomethanol mixed with hydrogen instead of pure biomethanol. Using a hydrogen–biomethanol mixture in modern engines is an effective method because hydrogen is a carbon-free, low-ignition, highest-flame-rate, high-octane fuel. A small quantity of hydrogen added to biomethanol and its combustion in an engine with a heat exchanger increases the combustion temperature and heat release, increases engine power, and reduces fuel consumption. This article presents experimental results of methanol combustion and a hydrogen-in-methanol mixture if hydrogen was retained due to the utilization of the heat of the exhaust gases. The tests were carried on a single-cylinder experimental engine with an injection of liquid methanol and gaseous hydrogen mixtures. The experiments showed that green hydrogen generated onboard the car due to the utilization of heat significantly reduced fuel costs of engines of vehicles and technological installations. It was established a hydrogen gaseous mixture addition of up to 5% by mass to methanol requires a corresponding change in the coefficient of excess air to λ = 1.25. Also, using an additional hydrogen mixture requires adjustment at the ignition moment in the direction of its decrease by 4–5 degrees of the engine crankshaft. Hydrogen gas mixture addition reduced methanol consumption, reaching a maximum reduction of 24%. The maximum increase in power was 30.5% based on experimental data. The reduction in the specified fuel consumption, obtained after experimental tests of the methanol research engine on the stand, can be implemented on the vehicle engines and technological installations equipped with an onboard heat recovery system. Such a system, due to the utilization of heat and the supply of additional hydrogen, can be implemented for engines that work on any alternative or traditional fuels.

Reverse Engineering to Design an Ergonomic Bio Briquette Packaging Machine

Briquettes are solids that are produced through the process of compression and pressure applicationand if burned will produce a small amount of smoke. Briquette production is carried out using ahammer mill where the raw material for briquettes is charcoal which is then crushed into charcoalgranules. The packaging process is still done manually using a shovel to fill the 50kg sack and thentake it to the sewing machine. The worker's posture when using a shovel has a Rapid Entire BodyAssessment (REBA) score of 12 so it has a high work risk of musculoskeletal disorders (MSDs) andrequires immediate improvement. The working environment at the company produces pollutants,meaning that there is no capture container for the fall of charcoal grains from the hammer mill. Basedon the existing problems, a redesign of the existing machine is needed. The proposed machine wasdesigned using the Reverse Engineering method because the existing condition already uses themachine then the existing machine is decomposed to find out the components and functions of theexisting machine to find alternative concepts. The ergonomic approach uses REBA and LBA todetermine changes in worker posture and the forces acting in the human spine. The DEM approachwas chosen to find out if the charcoal grains dropped from the hammer mill were successfully capturedand to find out the flow of the charcoal grains. The results of the proposed machine design have agood impact on workers in the packaging process.

Experimental Investigation on Compact Current Non Thermal Plasma Assisted Hydrocarbon Reforming Hydrogen Rich Gas

On-board vehicle hydrogen-rich gas extraction of gasoline reforming utilizing for fuel cells and GDI-engine lean burn combustion enhancement NOx trap applications. A non-thermal plasma discharge electrode that produces a reduce current, increased voltage 15kV source arc plasma fuel reformer is designed to operate at an arc frequency of 50 Hz. The operating factors gasoline equivalence ratio between 4 and 6.and electronically control by the fuel injector and eliminating ground spark plug plasma arc generation. The plasma arc non-thermal reformer gasoline converted into gas that contains partial oxidation contains combustible gases like hydrogen (H2), CO, non-combustible gases like CO2, N2, and a small quantity of H2O. The nonthermal plasma technology alternative for on-board hydrogen vehicle applications.

A pH Measurement of Acetic Acid-Sodium Acetate Buffer Solutions Using a pH Meter at Ambient Temperature

In article, we have reported the preparation of acetic acid-sodium acetate buffer solutions and determined its pH by using pH meter at about 25˚ C, as room temperature. In preparation of buffer solutions, firstly, we have taken 1.5 ml of glacial acetic acid into 100 ml of standard flask for making up 0.2M of acetic acid solution, and 0.64 gm of sodium acetate were dissolved into 100 ml distilled water. Then, taken 36.2 ml prepared solution of sodium acetate into 100 ml of standard flask and added 14.8 ml of prepared acetic acid to make its volume 100 ml by using distilled water, it is a buffer. In measuring the pH of prepared buffer solutions, we have been using a calibrated digital pen pH meter for quick resolution of reading with accuracy. The pH of acetic acid-acetate buffer solutions have gradually raised by adding small quantity of 5N NaOH solution into buffer sample, and adjusted pH was being to 4.7.

Effects of oil-water interfacial properties on protein structuring and droplet deformation in high moisture meat analogues containing oil

Adding oil to high moisture meat analogues (HMMA) can increase juiciness, and can be achieved by incorporating emulsion droplets during extrusion. Since these droplets can coalesce when subjected to high shear, selecting appropriate emulsion stabilisers is important. For several commercial plant-protein emulsion stabilisers, it was investigated how oil-water interfacial mechanical properties affect droplet deformation and protein structuring in extrusion of HMMAs. Emulsions with 10 wt% or 15 wt% oil, stabilised by potato protein isolates (POPI-1 (Rich in patatin) and POPI-2 (rich in protease inhibitor)) and pea protein isolate PPI, were used to make extrudates with 5.7 wt% and 8.5 wt% oil, respectively. In 8.5 wt%-extrudates, POPI-2 had the most oil leakage from the cooling die, while PPI had the smallest amount despite having softer and more stretchable interfaces. Blade-cutting tests showed the highest maximum force for 8.5 wt%-extrudates with POPI-1, likely because POPI-1 formed the stiffest interfaces. Tensile stress testing showed the largest fracture strain in 8.5% wt%-extrudates with PPI, corresponding to its longer wedge length. Multiphoton excitation microscopy was used to visualise the extrudates protein structure and oil droplets. This showed that droplets near the surface of the extrudate were less deformed than droplets in the centre. There were only small differences between protein stabilisers regarding oil droplet deformation, indicating droplet deformation was dominated by deformation of the protein matrix. The O/W interfacial properties significantly affected oil leakage, cutting force, and tensile strength of extrudates. These results are important to consider when designing emulsions for HMMAs processed by extruders.

A novel circularly polarized antenna array methodology for early identification of kidney tumors

Kidney cancer is a significant health concern worldwide, with early detection crucial for successful treatment outcomes. Recently, there has been an increasing focus on investigating affordable and non-intrusive methods for detecting cancer at its early stages. This proposed approach delves into the utilization of antenna arrays to identify kidney cancer. Specifically, antenna array with circular polarization has been crafted to identify tumors in the human kidney. This array design has been implemented using CST software, operating at 2.4 GHz. The antenna array having a dimension of 150 mm x 150 mm. The array consists of four-square patches each having a length of 30 mm and the spacing between the patches is preferred to be 20 mm for ensuring the mutual coupling. FR4 substrate is used with the relative permittivity 4.3 and 1.6 mm thickness. The axial ratio of the circularly polarized antenna is 0.9 dB at 2.4 GHz. The reflection coefficient S 11 = –30dB. The renal phantom in humans has been built with the kidney, adrenal gland, ureter, skin, fat, and muscle components to allow for precise simulation. Following that, four stages of cancer tumors were built employing all of the necessary qualities. For every stage of the cancer tumor, the reflection coefficient growth and resonance frequency shift are calculated. For the initial stages, the resonance frequency shift is very low. Consequently, the primary determinant of detection is the rise in S 11 . For 3rd and 4th stages of the tumor, there is a significant change in resonance frequency and increase S 11 , which facilitates identification. The calculated specific absorption rate (SAR) is a smaller amount than the safety thresholds, indicating that using this method is safe. Overall, this research points to a novel, easy-to-use method for kidney cancer screening. This method has the following benefits: it is non-invasive, safe, quick, affordable, and comfortable, and it emits no ionizing radiation during the measurement process. Furthermore, a range of output parameters such as gain, directivity, and polar radiation have been accurately computed.

Prediction of the Remaining Useful Life of Lithium-Ion Battery Using Multilayer Perceptron

Cogitating the reliability of the supply and ensuring continuous delivery of power to the loads, especially in the growing demand for Lithium-Ion batteries in electric vehicle applications, prediction of the remaining useful life of Lithium-Ion batteries is crucial for the timely replacement. For prediction of non-linear and chaotic relationship, experience-based approach, physics-based approach and data driven approach are used among which data driven approach is a model free, accurate and reliable approach. Therefore, a driven approach in predicting remaining useful life can be implemented in the battery management system. This research uses a multilayer perceptron to predict the remaining useful life of the battery. The NASA Ames Prognostics Center of Excellence (PCoE) battery dataset is used to test the proposed methodology. The use of multilayer perceptron for remaining life prediction seems promising despite the significant number of jump points, gaps in data and a small quantity of experimental data in the National Aeronautics and Space Administration (NASA) dataset. The predicted result was obtained with 8.52 % mean absolute error and 9.59 % root mean square error. When compared with the predicted results of different literatures, proposed multilayer perceptron with sliding window approach outperforms most of the existing approach. Incorporation of optimization techniques and hybrid algorithm in proposed approach can further enhance the accuracy of the model.

Insects as Sustainable Feed: Enhancing Animal Nutrition and Reducing Livestock Environmental Impression.

Insects are emerging as a promising alternative source in animal nutrition, offering high protein content and a low environmental impression compared to traditional feed sources. This abstract explores the potential role of insects in reducing the environmental impact of livestock production. Insects such as black soldier fly larvae, mealworms, and crickets are rich in essential nutrients, including proteins, amino acids, fatty acids and so on. They can be efficiently farmed on organic waste streams, contributing to resource efficiency and waste lessening. Additionally, insect farming needs a small quantity of water, less land, and emits fewer greenhouse gases than conventional animal feed production. Despite these benefits, several challenges must be addressed to realize their potential, including regulatory approval, consumer acceptance, production scalability, and ensuring consistent nutritional quality. By overcoming these challenges through research, innovation, and policy support, insects can be integrated into mainstream animal feed systems, significantly reducing the environmental impact of livestock farming and contributing to a more sustainable agricultural future.

Decision Transformer-Based Efficient Data Offloading in LEO-IoT.

Recently, the Internet of Things (IoT) has witnessed rapid development. However, the scarcity of computing resources on the ground has constrained the application scenarios of IoT. Low Earth Orbit (LEO) satellites have drawn people's attention due to their broader coverage and shorter transmission delay. They are capable of offloading more IoT computing tasks to mobile edge computing (MEC) servers with lower latency in order to address the issue of scarce computing resources on the ground. Nevertheless, it is highly challenging to share bandwidth and power resources among multiple IoT devices and LEO satellites. In this paper, we explore the efficient data offloading mechanism in the LEO satellite-based IoT (LEO-IoT), where LEO satellites forward data from the terrestrial to the MEC servers. Specifically, by optimally selecting the forwarding LEO satellite for each IoT task and allocating communication resources, we aim to minimize the data offloading latency and energy consumption. Particularly, we employ the state-of-the-art Decision Transformer (DT) to solve this optimization problem. We initially obtain a pre-trained DT through training on a specific task. Subsequently, the pre-trained DT is fine-tuned by acquiring a small quantity of data under the new task, enabling it to converge rapidly, with less training time and superior performance. Numerical simulation results demonstrate that in contrast to the classical reinforcement learning approach (Proximal Policy Optimization), the convergence speed of DT can be increased by up to three times, and the performance can be improved by up to 30%.

Beta-Hydroxybutyric Acid as a Template for the X-ray Powder Diffraction Analysis of Gamma-Hydroxybutyric Acid

In this paper, we report the possibility of using the X-ray powder diffraction (XRPD) technique to detect gamma-hydroxybutyric acid (GHB) in the form of its sodium salt in different beverages, but because it is not possible to freely buy GHB, beta-hydroxybutyric acid (BHB) and its sodium salt (NaBHB) were used as a model to fine-tune an X-ray diffraction method for the qualitative analysis of the sodium salt of GHB. The method requires only a small quantity of beverage and an easy sample preparation that consists only of the addition of NaOH to the drink and a subsequent drying step. The dry residue obtained can be easily analyzed with XRPD using a single-crystal X-ray diffractometer, which exploits its high sensitivity and allows for very fast pattern collection. Several beverages with different NaBHB:NaOH molar ratios were tested, and the results showed that NaBHB was detected in all drinks analyzed when the NaBHB:NaOH molar ratio was 1:50, using a characteristic peak at very low 2θ values, which also permitted the detection of its presence in complex beverage matrices. Moreover, depending on the amount of NaOH added, shifting and/or splitting of the characteristic NaBHB salt peak was observed, and the origin of this behavior was investigated.

MORE THAN FOSSILS: PALEOBURROWS AS GEOHERITAGE AND PALEOENVIRONMENTAL ARCHIVES IN THE CAMINHOS DOS CÂNIONS DO SUL UNESCO GLOBAL GEOPARK, SOUTHERN BRAZIL

The paleoburrows (paleotocas) are ichnofossils produced by the autochthonous megafauna of South America. The Caminhos dos Cânions do Sul UNESCO Global Geopark (CCSUGG), Southern Brazil, contains a large amount of these ichnofossils, which are regarded as internationally relevant. This article aims to discuss paleoburrows as geoheritage and paleoenvironmental records, using the examples present in the CCSUGG. For this purpose, bibliographic research, paleoburrows cataloguing fieldwork and mapping routine were carried out. So far, 24 paleoburrows have been compiled. Mostly found in sedimentary friable rocks, such as the Botucatu Formation sandstones, can also occur in harder, weathered lithologies in a smaller amount. Some bioerosive structures show claw scrapping and digging signs, attributed to the Pliocene-Pleistocene South American megafauna, such as the giant sloths and the giant armadillos. Despite these 24 paleoburrows, four of them are recognized as geosites of regional and international value. These ichnofossils provide geological and paleontological values, considering their builders are already extinct and their presence allows to infer paleoenvironmental changes and megamammals distributions. Besides tangible values, these burrows evoke myths and histories about indigenous people and settlers who used these burrows as shelter, representing intangible cultural heritage. Even though these values, paleoburrows face threats that endanger their conservation, like unguided visitors, water flow and block falls. Hence, there are geoeducational efforts to preserve these ichnofossils for future generations. All these processes are evident in geosites with scientific, scenic and touristic values, the paleotocas giant paleoburrows.

Poly(N-isopropylacrylamide)-chitosan nanogels for nanotechnological and catalytic applications

Polymer nanogels consisting of poly(N-isopropylacrylamide) and chitosan [P(NC)] were synthesized using a free radical precipitation polymerization technique in an aqueous environment. This process involved the polymerization of N-isopropylacrylamide (NIPAAM) with chitosan (CS) and a cross-linker. These P(NC) nanogels were utilized as nano-reactors for the synthesis of gold nanoparticles (AuNPs), which were formed within the polymeric network through an in-situ reduction process using chloroauric acid [H(AuCl4)] as precursor salt and sodium borohydride (NaBH4) as the reductant. Various analytical methods, including transmission electron microscopy (TEM), Thermogravimetric analysis (TGA), ultraviolet–visible spectroscopy (UV–Vis), and Fourier transform infrared spectroscopy (FTIR), were employed to confirm the formation of P(NC) nanogels and the incorporation and durability of AuNPs within the P(NC) nanogels. The AuNPs loaded P(NC) nanogels were utilized as catalysts for the reduction of 4-nitrophenol (4-NiP) into 4-aminophenol (4-AmP) in the presence of NaBH4. This system was also used to degrade a number of dyes including methylene blue (MB), methylene orange (MO), Rhodamine B (RhB), brilliant blue (BB) and eosin Y ((EY) by using NaBH4 as reducing agent. The Au-P(NC) catalyst exhibited remarkable efficiency, facilitating the fast reduction of 4-NiP and degradation of dyes within a very short interval of time. This system stands out for its economic usage, as even a small quantity of it can efficiently reduce toxic pollutants like 4-NiP and dyes. The results of the reactions highlighted exceptional yield, emphasizing the effectiveness and recyclability of the Au-P(NC) hybrid nanogels as highly capable catalysts.

Hydrothermal synthesis of three-dimensional snowflake-like MgCO3@MnCO3@Mn3N2 composite materials and their application in aqueous zinc-ion battery cathodes

Aqueous zinc-ion batteries have attracted considerable interest in the energy storage sector due to their distinctive advantages. The use of water as an electrolyte enhances their environmental friendliness, and the abundant and low-cost nature of zinc resources confers a significant economic edge. Manganese-based materials, utilized as cathode materials in these batteries, offer favorable electrical conductivity, high theoretical capacity, and superior stability. The paper describes the hydrothermal synthesis of magnesium- and manganese-based composite material MgCO3@MnCO3@Mn3N2, through the optimization of the amounts of magnesium nitrate and urea, as well as the hydrothermal and calcination conditions. Under the optimal synthesis conditions, the composite material achieved a high capacity of 457.8 mAh/g at the current density of 50 mA/g, with capacity of 391.5 mAh/g at the current density of 100 mA/g. Notably, even at the current density of 200 mA/g, the capacity remained above 300 mAh/g. The SEM tests reveal that the MgCO3@MnCO3@Mn3N2 composite material exhibits three-dimensional snowflake-like morphology at the microscopic level. The EDS tests indicate a very uniform distribution of manganese and magnesium elements. Both infrared and Raman spectroscopy tests detected characteristic peaks of carbonate groups. The XPS tests show that the oxidation states of Mn and Mg elements are consistent with those of MgCO3 and MnCO3. In the XRD test, data fitting analysis indicates that the predominant components of the composite material are MgCO3 and MnCO3, with a ratio approximating 5:4. The presence of a small quantity of Mn3N2 is also identified within the composite material. The composite material synthesized under this composition exhibits superior electrochemical performance.

The transformation of type-I La2O3/α-Bi2O3 into multi-heterojunctions during photocatalysis with enhanced photoreactivity

A small quantity of broad bandgap rare earth lanthanum oxide (La2O3) was incorporated into monoclinic bismuth oxide (α-Bi2O3) through a one-step facile calcining route to construct an efficient type-I La2O3/α-Bi2O3 heterojunction photocatalyst for pollutant degradation under UV-light irradiation. The effect of adding La2O3 on the morphology, textural, optical, photoelectrochemical, and photocatalytic properties of α-Bi2O3 was investigated. Interestingly, feeding as low as five molar percent (5 %) La2O3 could significantly increase the BET surface area and generate more h+ and •O2− for photocatalytic reaction. Moreover, the calcining-induced carbon in La2O3/α-Bi2O3 revealed a vital role in suppressing the charge carrier recombination by quickly transferring charges to the photocatalyst's surface. In particular, during the recycling process, the in-situ formed Bi2O2CO3 changes the charge carrier transferring pathway and reveals a transformation of type-I La2O3/α-Bi2O3 into multi-heterojunction of type-I and type-II. Furthermore, the formation of Bi2O2CO3 results in more active sites for the photocatalytic reaction with improved reaction kinetics. This work provides a new direction for understanding a photocatalytic system's recycling phenomena and intrinsic kinetics.

Mast cells as indicators of foreign particle biocompatibility

The key problem of introducing nanoparticles into clinical practice for diagnostic and therapeutic purposes is their safety. Connective tissue, an important component of which are mast cells, reacts actively in response to foreign particles. The reaction of mast cells can be an indicator of the biocompatibility of foreign particles. The study was conducted on male Wistar rats. Iron-carbon nanoparticles in the FeC modification stabilized in an aqueous medium using an auxiliary substance were used. Tissue examination (liver, lungs, heart, thymus, kidneys) was performed 1, 7 and 30 days after injection. After the injection of nanoparticles, the largest quantity of them is found in the liver and lungs, a smaller quantity is found in the heart, kidneys and thymus. The liver and lungs are the main organs of excretion of nanoparticles due to phagocytes. The accumulation of nanoparticles in the liver leads to the development of destructive processes and to the activation of compensatory and adaptive mechanisms in the form of cellular and intracellular regeneration of hepatocytes. In organs with a low content of nanoparticles, structural changes are poorly expressed. The mast cells of the studied organs react differently to the introduction of nanoparticles. The first to react are the mast cells of the liver by reducing the quantity and increasing degranulation. The population of lung mast cells reacts unidirectionally by sharply activating degranulation without changing the amount. An increase in the secretory activity of mast cells in the lungs and liver indicates the participation of mast cells in the regulation of particle elimination through intercellular signaling pathways of interaction with the system of phagocytic mononuclear cells. Heart mast cells are involved in maintaining the inflammatory process in the early period of the experiment, contribute to the return of myocardial parameters to homeostatic norm in the late period of the experiment. Mast cells can be considered as indicators of biocompatibility nanoparticles. The absence of an inflammatory process and the preservation of the structural and functional characteristics of the tissues where nanoparticles accumulate, as well as the reaction of mast cells in them, indicate the relative safety of the particles under study.

Derived Amharic alphabet sign language recognition using machine learning methods

Hearing-impaired people use sign language as a means of communication with those with no hearing disability. It is therefore difficult to communicate with hearing impaired people without the expertise of a signer or knowledge of sign language. As a result, technologies that understands sign language are required to bridge the communication gap between those that have hearing impairments and those that dont. Ethiopian Amharic alphabets sign language (EAMASL) is different from other countries sign languages because Amharic Language is spoken in Ethiopia and has a number of complex alphabets. Presently in Ethiopia, just a few studies on AMASL have been conducted. Previous works, on the other hand, only worked on basic and a few derived Amharic alphabet signs. To solve this challenge, in this paper, we propose Machine Learning techniques such as Support Vector Machine (SVM) with Convolutional Neural Network (CNN), Histogram of Oriented Gradients (HOG), and their hybrid features to recognize the remaining derived Amharic alphabet signs. Because CNN is good for rotation and translation of signs, and HOG works well for low quality data under strong illumination variation and a small quantity of training data, the two have been combined for feature extraction. CNN (Softmax) was utilized as a classifier for normalized hybrid features in addition to SVM. SVM model using CNN, HOG, normalized, and non-normalized hybrid feature vectors achieved an accuracy of 89.02%, 95.42%, 97.40%, and 93.61% using 10-fold cross validation, respectively. With the normalized hybrid features, the other classifier, CNN (sofmax), produced a 93.55% accuracy.

Confocal image of three oxoaporphine alkaloids in cancer cell lines and their interaction with DNA by multispectroscopic and molecular docking techniques

Dicentrinone (Di), liriodenine (Li) and lysicamine (Ly) are three natural oxoaporphine alkaloids (OAs), which revealed significant biological activity such as anticancer, anti-inflammatory and antimicrobial activities and were considered as potential lead compounds for the development of new clinical chemicals. In the present study, confocal laser scanning fluorescence microscopy observation demonstrated these three natural OAs could traverse inside of the nucleus and get an opportunity to interact with DNA. Their interaction properties with DNA were then investigated simultaneously by two spectral fluorescent probes of ethidium bromide (EB) and methyl green (MG), as well as UV–vis absorption and cyclic voltammetry measurements, and further verified by the molecular docking analysis. Results indicated Di and Li were distinctly classified as the intercalative molecules to DNA, however, Ly was confirmed with a mixed-mode binding of partial intercalation and groove affinity. Their binding ability was revealed as the follows: Di ≥ Li > Ly, which was correlated with their structural changes. Thermodynamic studies revealed the binding process of Li and Ly with ctDNA was all spontaneous, the hydrophobic interaction was the major binding force for Li-ctDNA complex, however, the interaction between Ly and ctDNA relied on both hydrophobic and hydrogen binding force. Molecular docking provided detailed computational interaction of Di, Li and Ly with DNA, which proved the intercalation binding of Li-DNA complex and Di-DNA complex stabilizing mainly by the π-π binding force, however, apart from a small quantity of π-π interaction, another binding force in the Ly-DNA complex mainly was supplied from the weaker Pi-Alkyl, hydrogen bond and Pi-Anion interactions.

Efficiency Evaluation of DNA Isolation Techniques in Fins of Channa marulius Using PCR Amplification and NanoDrop

Highly pure and good-quality extracted DNA is vital for PCR amplification, gene sequencing, and species identification. Seven genomic DNA isolation techniques were used to isolate the DNA from the fins of Channa marulius. The concentration and purity of isolated DNA were assessed with PCR amplification of the mitochondrial COI gene and NanoDrop. The phenol-chloroform method was found significantly (P<0.05) higher in concentration (1001 ng.ul-1) as compared to all other six evaluated DNA isolation methods. In terms of purity of isolated DNA GeneJET, the Genomic DNA Purification Kit was found significantly (P<0.05) higher among all analyzed methods. Both the Phenol chloroform method and GeneJET Genomic DNA Purification Kit were successfully used in PCR amplification. Concluding that the Phenol chloroform method and GeneJET Genomic DNA Purification Kit may be successfully used in PCR amplification. The phenol-chloroform method and GeneJET Genomic DNA Purification Kit proved the best in the extraction of DNA in high concentration with maximum yield and purity from fins of C. marulius and can be helpful to isolate DNA from fish species because a small quantity of fin tissues is required for DNA isolation without harm to fish. Moreover, data reported from this study about DNA isolation techniques may be used for molecular approaches like PCR amplification and gene sequencing of fishes.

Uncovering the spatial characteristics of global net anthropogenic nitrogen input at high resolution and across 1.42 million lake basins

Global Net Anthropogenic Nitrogen Input (NANI) at high resolution is crucial for assessing the impact of human activities on aquatic environments. Insufficient global high-resolution data sources and methods have hindered the effective examination of the global characteristics and driving forces of NANI. This study presents a general framework for calculating global NANI, providing estimates at a 5-arc-minute resolution and over 1.42 million lake basins in 2015. The results highlight the region near the Tropic of Cancer as a concentration area for high NANI and an inflection point for latitude-based accumulation variation. It also emphasizes the uneven distribution of NANI among continents, with Asia and Africa having the highest proportions, yet their high and low values are notably lower than those of Europe and South America. A similar pattern is observed in global lakes, where Asia has the smallest quantity and volume, but the highest NANI intensity. In contrast, North America and Europe have larger quantities and volumes but the lowest NANI intensity. The global distribution characteristics reveal a clustering pattern in high and low values, with 1.25 % of the area having a sum of NANI exceeding 20 %. The uncertainty analysis regarding model parameters indicates that continents with the highest NANI do not always exhibit the highest uncertainty. These results bridge the gap between global nitrogen sustainable management and anthropogenic nitrogen input. They support research on spatiotemporal changes and controlling factors of global river nutrient loads, as well as the impact of climatic factors on basin nitrogen loss and its variability.