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Avifaunal Biodiversity and Abundance in Organic and Conventional Rice Ecosystem in the Cauvery Deltaic Region of Tamil Nadu
Full text linkMany studies have looked into the benefits of organic farming on soil ecology, but their effectiveness in biodiversity conservation, especially in bird communities in the organic ecosystem of Tamil Nadu, is less investigated. This research was conducted to determine the effects of organic farming methods on bird species, frequency and diversity in the Cauvery deltaic region of Tamil Nadu specifically, in rice ecosystems. In the Thaladi season of September and October 2022, bird monitoring was carried out in five pairs of organic and conventional rice habitats. This research documented a total of 726 birds, represented by 31 species, 19 Families and 11 Orders. Insectivorous birds were the most abundant species in organic rice ecosystems when compared to conventional ecosystems. This was observed across all three dietary guilds namely insectivore, granivore, and omnivore. A study on birds indicated that they had a higher value of species diversity in organic ecosystems (H = 3.06 Shannon-Weiner Diversity Index, R = 31 Species richness, J = 0.89 Evenness). In contrast, species diversity in conventional ecosystems was lower (H = 2.80, J = 0.87 and r = 25). This research has empirically demonstrated the advantages of organic farming, particularly in the Cauvery Deltaic region's organic rice habitat. It also provides quantifiable evidence that clearly shows its effectiveness in increasing the number of avian insectivores
A Comprehensive Analysis of Water Budget Components and Water Yield in the Upper Awash Sub-Basin, Central Ethiopia Using the SWAT Model
Full text linkThis study employed the Soil and Water Assessment Tool (SWAT) model to analyze the water budget components and water yield of the Upper Awash River sub-basin in Central Ethiopia. Utilizing data from 1986 to 2013, the model was calibrated from 1988 to 2008 following a three-year warm-up period and subsequently validated over five years at two gauging stations. Sensitivity analyses were conducted using t-stat and p-values, while model uncertainty was assessed using the p-factor and r-factor indices. The model's performance was evaluated using Nash-Sutcliffe efficiency (NSE), coefficient of determination (R²), and Percent Bias (PBIAS). Calibration results yielded p-factors and r-factors of 0.801 and 0.9 for Hombele, and 0.808 and 0.98 for Melkakuntro. The calibration R², NSE, and PBIAS values were 0.82, 0.82, and-2.3, respectively, for Hombele, and 0.79, 0.78, and-13.1, respectively. Validation R², NSE, and PBIAS values were 0.71, 0.67, 11.2 for Hombele, and 0.7, 0.66, 1.9 for Melkakuntro. The average annual groundwater recharge rate ranged from 0 to 904.3 mm, averaging 181.1 mm/yr, which accounts for 19.1% of the mean annual rainfall. The simulated mean annual surface runoff and evapotranspiration were 93.4 mm and 682.5 mm, respectively, constituting 9.8% and 71.8% of the mean annual rainfall. The average annual water yield of the study area was 233.4 mm. These findings provide important insights into the hydrological dynamics of the Upper Awash River sub-basin, deepening our understanding of this water system. This information is essential for establishing sustainable water management practices and optimizing resource use for socioeconomic growth
A Review of the Intrinsic Parameters Affecting the Elastic Characteristics of Heterogeneous Carbonate Reservoirs: Insights from Laboratory Assessments
Full text linkThis research provides an in-depth analysis of how various parameters such as mineralogy, density, porosity, temperature, pressure, and structural features impact the velocities of sonic waves in carbonate rocks. Our findings reveal that the mineral composition significantly influences the elastic behavior of these rocks. The density and elastic properties of minerals, especially clay minerals, play a crucial role in affecting porosity and predominant pore types. The porosity of carbonate reservoirs impacts their elastic properties, leading to variations in sonic wave velocities depending on the different pore types present. For a given porosity, the velocities can vary considerably due to the presence of diverse pore types within the pore space. Non-interconnected porosities with spherical or near-spherical shapes, along with microporosity, alter the effective elastic properties of the rock. Additionally, temperature affects the velocity-porosity relationship in rocks, with experimental results showing a decrease in P-wave velocity as temperature increases. Under reservoir conditions, wave velocity in carbonate rocks is influenced by factors such as confining pressure, temperature, gas saturation, and effective stress. Specifically, P-wave velocity increases with confining pressure as soft pores and cracks gradually close, enhancing the dry rock bulk shear modulus. Conversely, rising temperatures cause a slight decrease in velocities and an increase in attenuation. In conclusion, this study enhances our understanding of the physical properties and behavior of carbonate rocks under reservoir conditions, thereby contributing to the exploration and production of hydrocarbon resources
Unraveling the Potential of Micro-nano Bubbles in Water Treatment: A Review Focusing on Physicochemical Properties, Generation Methods, and Environmental Impacts
Full text linkWith the advancement of industrialization, water pollution has become a pressing global environmental issue. Traditional water treatment technologies are struggling to remove emerging contaminants and meet current discharge standards, against this backdrop, micro-nano bubbles (MNBs) technology has attracted considerable research attention due to its unique physicochemical properties, such as long-term stability, high internal pressure, photoelectric characteristics, and reactive oxygen species (ROS) generation capabilities, especially in its combination with advanced oxidation processes (AOPs). A comprehensive understanding of MNBs generation and utilization is significant for developing green, economical, and highly effective wastewater treatment technologies. Herein, on the basis of the comprehensive literature survey, this review article systematically studied the distinctive characteristics of MNBs, along with the methodologies employed for their generation. It concurrently explores the characterization methods used to assess the properties of MNBs, which is instrumental for subsequent analyses on how these properties can enhance the catalytic performance of AOPs. Finally, this article explores the potential applications of MNBs in the environmental sector and points out the direction for future research, including the development of more efficient and cost-effective MNBs generation technologies, in-depth exploration of their mechanisms in AOPs, and comprehensive environmental impact assessments. This review aims to provide readers with an in-depth understanding of the intrinsic correlation between the properties and applications of MNBs, thereby enabling their optimal utilization in the environmental remediation
On Continuities via P-Statistical Convergence
Full text linkThis study investigates the concepts of P-statistical continuity (statistical continuity with respect to power series method) and P-statistical ward continuity (statistical ward continuity with respect to power series method) within the framework of power series methods, which extend the scope of statistical convergence beyond classical matrix methods. In the background, the limitations of traditional methods in capturing generalized continuity behaviors are explored and the use of power series as a versatile tool is motivated. Connections between these specialized forms of continuity and standard continuity are established, providing proofs and detailed properties. The results include several foundational theorems characterizing P-statistical continuity and ward continuity under various settings. These findings contribute to a more profound comprehension of continuity concepts within the context of regular summability methods.
MSC: 26A15, 40A05, 40G10
Selective Laser Sintering: Processing, Materials, Challenges, Applications, and Emerging Trends
Full text linkSelective laser sintering (SLS) has revolutionized manufacturing by enabling the production of intricate designs with enhanced flexibility and material efficiency. The present review delves into the SLS process, its compatibility with materials such as polymers, metals, and composites, and its influence on microstructure, mechanical properties, and overall performance. It addresses challenges like dimensional accuracy, surface finish, and residual stress while highlighting applications across various industries. Additionally, the review explores emerging trends, including hybrid manufacturing and the integration of artificial intelligence, to shape future developments in SLS technology
Biobased Construction from Agricultural Crops: Paper 1 - A State of Play of Commercial Solutions in Europe
Full text linkIn response to environmental concerns and the global warming issue in particular there is a growing drive to decarbonise the building sector and transition it to more circular practices.
Biobased construction materials, products and systems are an important low carbon and circular strategy as they can enable low to negative carbon construction and have strong circularity advantages notably being able to enter the bio cycle, using renewable, low to zero toxic resources and provide a range of other performance benefits, including moisture and vapour regulation.
This novel research presents a unique state of play on the commercial application of biobased construction from selected agricultural crops, straw, miscanthus and hemp, focused on the European context. A desk-based review of known biobased material producers and manufacturers is undertaken, supplemented with semi structured interviews and site visits, to provide a comprehensive overview of the sector and detailed account of the types of biobased materials, products and systems that are being applied in buildings across Europe and beyond.
The findings show that a diversity of agricultural crops are being utilised at different process, manufacture and construction technology levels, providing a range of tested and certified materials and products for application in mainly timber frame construction, but also some masonry solutions, and a growing number of modular systems. These operate in a diversity of supply chains and are being applied in a wide range of building types, both domestic and non-domestic, including multi story and complex buildings
Effect of Hot-rolling Deformation on Microstructure and Mechanical Properties of Nd2Fe14Bp/Al-5Co-0.4Sm Composites
Full text linkNd2Fe14Bp/Al-5Co-0.4Sm composites were prepared via microwave sintering and hot rolling. The effects of hot-rolling deformation on the microstructure and mechanical properties of Nd2Fe14Bp/Al-5Co-0.4Sm composites were studied. The results showed that the internal porosity of the composites significantly decreased when the hot-rolling deformation rate was 45%. The Nd2Fe14B particles were broken into fine particles under rolling stress. Consequently, the particles were uniformly distributed. Moreover, numerous high-density dislocations were observed around the particles, which improved the strength and toughness of the material. When the deformation rate was 45%, the micro-nano hardness and elastic modulus of the interface of the composites were 3.6 and 91 GPa, respectively. The interfacial deformation resistance of the composites was significantly higher than that of the composites before rolling. The tensile strength of Nd2Fe14Bp/Al-5Co-0.4Sm composites increased as the deformation rate increased, whereas the elongation gradually decreased. Furthermore, when the deformation rate was 45%, the tensile strength and elongation of the composites were 161 MPa and 6.5%, respectively. The tensile strength was 14.2% higher than that of the unrolled sample
Certain Fixed Point Results via Contraction Mappings in Neutrosophic Semi-Metric Spaces
Full text linkIn this work, the authors introduce the concept of neutrosophic semi-metric spaces and prove several common fixed-point theorems for countable and uncountable family of mappings via an implicit relation of contractive and integral type by utilizing locally integrable functions. These results improve and generalize the several results in the existing literature. Further, the authors present some non-trivial examples to support our main results.
Mathematics Subject Classification: 46S40, 47H10, 54H25
Forecasting Non-stationary Time Series Using Deep Learning in a Fuzzy Time Series Framework and its Application to Stock Markets
Full text linkNon-stationary time series prediction is challenging due to its dynamic and complex nature. Fuzzy time series models offer a promising solution for forecasting such data, but a key challenge lies in partitioning the universe of discourse, which significantly impacts forecasting accuracy. Traditional fuzzy time series models often use equal-length interval partitioning, which is more suited for stationary data and limits their adaptability to non-stationary time series. This paper introduces a novel variable-length interval partitioning method designed specifically for non-stationary time series. The developed method combines a Long Short-Term Memory (LSTM) Autoencoder with K-means clustering, enabling dynamic, data-driven partitioning that adapts to the changing characteristics of the data. The LSTM Autoencoder encodes the time series, which is clustered using K-means, and intervals are defined based on cluster centers. Furthermore, the Variable Length Interval Partitioning-based Fuzzy Time Series model (VLIFTS) is developed by incorporating this partitioning method and the concepts of Markov chain and transition probability matrix. In this model, fuzzy sets are viewed as states of a Markov chain, and transition probabilities are used in the forecasting phase. The model is validated on stock market indices Nifty 50, NASDAQ, S&P 500, and Dow Jones. Stationarity and heteroscedasticity are tested using Augmented Dickey-Fuller (ADF) and Levene's tests respectively. Statistical forecast accuracy metrics Root Mean Squared Error (RMSE) and Mean Absolute Percent Error (MAPE) show that VLIFTS significantly improves forecasting accuracy over traditional models. This hybrid approach enhances fuzzy time series modelling and can be applied to various non-stationary time series forecasting problems