Capacity Analysis Research Articles

An Analytical Study on Opportunities and Challenges towards Implementation of Industry 4.0 Tools for Manufacturing SMEs in Karnataka

In the era of Industry 4.0, there is a significant shift in manufacturing paradigms, offering substantial opportunities for operational efficiency, product quality, and supply chain integration. However, small and medium-sized enterprises (SMEs) in Karnataka face numerous challenges in adopting these advanced technologies. This study investigates the readiness and capacity of manufacturing SMEs in Karnataka to implement Industry 4.0 tools, focusing on financial capacity, workforce skills, infrastructure support, and comparative regional analysis. Data were collected from ten SMEs through structured questionnaires and discussions with officials, supplemented by secondary data from books, research papers, journals, annual reports, and websites. The data were analyzed using SPSS software, employing descriptive statistics, correlation analysis, and ANOVA. The findings reveal moderate to strong correlations between financial capacity, workforce skills, and infrastructure support, highlighting the interconnected nature of these factors. Despite uniform challenges across industries, Karnataka's SMEs demonstrate a high level of readiness and capacity for digital transformation, suggesting that broad-based initiatives could effectively support their adoption of Industry 4.0 technologies. The study provides actionable insights for policymakers and business leaders to facilitate the successful implementation of these advanced manufacturing tools.

Kinematic numerical analysis of bending plate bearing capacity under cyclic loads

Kinematic numerical analysis of bending plate bearing capacity under cyclic loads

Identification of waste lithium-ion battery cell chemistry for recycling.

Battery technology has attained a key position as an energy storage technology in decarbonization of energy systems. Lithium-ion batteries have become the dominant technology currently used in consumer appliances, electric vehicles (EVs), and industrial applications. However, lithium-ion batteries are not alike and can have different cathode chemistries which makes their recycling more complex. In addition, as larger quantities of batteries are starting to enter their end-of-life (EOL) stage, efficient handling and management of batteries with different cathode chemistry types are required. By identifying the cathode chemistry type prior to mechanical treatment, mixing of different cathode chemistries could be decreased, resulting in an increase in overall recycling efficiency. This study investigated the applicability of a non-destructive battery diagnostic methods, namely incremental capacity analysis (ICA), for identifying EOL lithium-ion battery chemistry. The study conducted ICA both on known reference batteries and EOL batteries from the recycling industry. Next, EOL batteries were crushed and the resulting fine active material was analysed to validate the ICA result. In addition, released gaseous and airborne particles were measured during crushing. The ICA results showed reliable identification of lithium iron phosphate (LFP) from other chemistries. In addition, lithium cobalt oxide (LCO), lithium nickel cobalt aluminum oxide (NCA) and lithium nickel manganese cobalt oxide (NMC) could be identified with various degrees. The identification may suffer if the battery is heavily used, and its state of health is low.

Predicting the evolution from first-episode psychosis to mood or psychotic disorder: A systematic review of biological markers.

The development of paraclinical tools to assist clinical assessment is already widespread in nearly all other medical specialties. In psychiatry, many efforts are being made to improve management strategies using these new techniques. The first episode psychosis (FEP) is a clinical entity whose evolution after onset is difficult to predict in the current state of our practices. Our main objective was to identify from the literature the most promising biological markers for early prediction of thymic or psychotic trajectories following FEP. We performed a systematic literature review on 4 databases: PubMed, Scopus, PsycINFO, and Web of Science following PRISMA guidelines and using search terms related to FEP and biomarkers. Eight studies were included in our final analysis. Several biomarkers showed promising discriminatory capacities for predicting post-FEP evolution: the interleukins IL-6, IL-12p40, IL-1β, and the mRNA expression levels of the DICER-1 and AKT-1 genes. Other studies that opted for broad-spectrum strategies also highlighted new leads for the discovery of additional biomarkers. Overall, our results indicate the value of replicating studies targeting the analysis of the predictive capacities of several biological markers. It also appears important to homogenize methodologies and favor the construction of predictive models on several of these markers to reinforce their statistical significance.

A gendered analysis of adaptive capacity and food security in Makueni County, Kenya

A gendered analysis of adaptive capacity and food security in Makueni County, Kenya

Iron nanoparticle/carbon nanotube composite as oxidase-like nanozyme for visual analysis of total antioxidant capacity.

Total antioxidant capacity (TAC) is an important indicator for assessing the merit of natural plants and foods. Herein, a visual TAC assay is developed based on the oxidase-like activity of nitrogen-doped carbon nanotubes loaded with Fe nanoparticles (FeNPs@NCNT), which is prepared via high-temperature pyrolysis of metal-organic framework precursors and can catalyze the oxidation of colorless o-phenylenediamine (OPD) to colored 2,3-diaminophenazine (DAP). The addition of antioxidants (e.g., quercetin) impedes the formation of DAP, diminishing the color change, which can be analyzed via the RGB values obtained with a smartphone color-recognition APP, "Color Picker". The change of the optical signal can also be analyzed in the fluorescence mode. These two detection modes yield consistent TAC analysis of actual plant samples, in accord with results from the standard ABTS method. Results from this study highlight the unique potential of nanozymes in the development of effective TAC analysis platforms for natural plants and food.

Analysis of emergency load capacity of ±500kV sea wind power transmission line

Analysis of emergency load capacity of ±500kV sea wind power transmission line

Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models.

This study addresses the critical environmental concerns surrounding microplastics, aiming to elucidate the intricate factors influencing their behavior and interactions with organic pollutants. Utilizing advanced artificial neural network modeling techniques, including GRU, LSTM, RNN, and CNN, a comprehensive analysis of microplastic sorption capacity and underlying mechanisms is conducted. The research relies on a meticulously curated dataset encompassing fundamental parameters such as organic compound composition, n-octanol/water partition coefficient, covalent acidity, covalent basicity, molecular polarizability to volume ratio, and the logarithm of the partition coefficient. Findings underscore the significance of understanding the n-octanol/water distribution coefficient (Log D) in predicting organic pollutant fate in aquatic environments, with compounds displaying higher Log D values exhibiting heightened affinity for microplastics, posing substantial ecological and human health risks. Additionally, the study highlights the importance of selecting appropriate models to accurately capture complex sorption processes, especially in varied aquatic environments. Furthermore, the profound impact of acidity, molecular polarizability to volume ratio, and covalent basicity on microplastic behavior is elucidated. Notably, machine learning models and CNNs demonstrate remarkable speed in prediction generation. A comparative analysis of four robust machine learning models establishes fundamental alignment between model predictions and empirical findings. Particularly noteworthy is the RNN model, emerging as the most accurate with an impressive accuracy of 0.967 and a minimum absolute error of 0.38. These results underscore the efficacy of the RNN model in predicting microplastic dynamics, holding promise for significant contributions to addressing microplastic pollution.

From Fragmentation to Coherence: Enhancing Human Resource Capacity in Indonesian Law Reform for Effective Justice Delivery

Indonesian law reform faces persistent challenges stemming from fragmented human resource capacity, which undermines the coherence and effectiveness of justice delivery. This study critically examines the interplay between human resource development and the success of legal reform in Indonesia, emphasizing the urgent need to address systemic inefficiencies and skill gaps. As globalization and complex socio-legal issues demand more sophisticated legal systems, the pressure on Indonesia’s legal institutions to enhance their human resource capabilities has intensified. The novelty of this research lies in its focused analysis of human resource capacity as a critical yet underexplored dimension of Indonesian law reform. By employing a socio-legal methodology, the study identifies key factors contributing to fragmentation, including uneven competency levels, inadequate training, and lack of coordination among legal institutions. It further evaluates the role of education, professional development, and policy frameworks in fostering a coherent and competent legal workforce. The findings demonstrate that a robust, well-coordinated human resource strategy is essential for advancing legal reforms and delivering justice effectively. This research contributes to the discourse by proposing actionable solutions, including curriculum reforms, capacity-building initiatives, and collaborative networks among legal practitioners, academics, and policymakers. By addressing the critical gap in human resource capacity, this study provides a pathway for achieving a coherent legal system that upholds justice and aligns with Indonesia’s broader development goals.

Linear elastic iterative method for stability ultimate capacity of equal-leg angle towers

An efficient linear elastic iterative method is proposed for the stability ultimate capacity of equal-leg angle towers, using an elastic modulus adjustment strategy in this paper. The angle steel stability generalized yield function (GYF) of AS/NZS4600 is selected, on which a precise homogeneous generalized yield function (HGYF) is developed through dimensionless analysis and regression. Based on the HGYF, the element bearing ratio is proposed as a dynamic threshold for distinguishing high-stress and low-stress elements in equal-leg angle elements. Then, an adaptive elastic modulus adjustment strategy is proposed for the linear elastic iterative analysis of the stability ultimate capacity of equal-leg angle towers. Compared to analytical solutions and traditional numerical methods, it can be observed that the linear elastic iterative method for the stability ultimate capacity of equal-leg angle towers is accurate and efficient.

Nanobubbles Adsorption and Its Role in Enhancing Fine Argentite Flotation.

The efficient recovery of fine argentite from polymetallic lead-zinc (Pb-Zn) sulfide ore is challenging. This study investigated nanobubble (NB) adsorption on the argentite surface and its role in enhancing fine argentite flotation using various analytical techniques, including contact angle measurements, adsorption capacity analysis, infrared spectroscopy, zeta potential measurements, turbidity tests, microscopic imaging, scanning electron microscopy, and flotation experiments. Results indicated that the NBs exhibited long-term stability and were adsorbed onto the argentite surface, thereby enhancing surface hydrophobicity, reducing electrostatic repulsion between fine argentite particles, and promoting particle agglomeration. Furthermore, the NBs formed a thin film on the argentite surface, which decreased the adsorption of sodium diethyldithiocarbamate. Microflotation tests confirmed that the introduction of NBs considerably enhanced the recovery of argentite using flotation technology.

Probabilistic analysis of bearing capacity of footings on unsaturated soils with non-stationary characteristics subjected to rainfall infiltration

Probabilistic analysis of bearing capacity of footings on unsaturated soils with non-stationary characteristics subjected to rainfall infiltration

Probabilistic analysis of the bearing capacity of spatially random Hoek‒Brown rock masses by integrating finite element limit analysis, random field theory, and XGBoost models

Probabilistic analysis of the bearing capacity of spatially random Hoek‒Brown rock masses by integrating finite element limit analysis, random field theory, and XGBoost models

Impact of Third-Party Payment on Banks Risk-taking Capacity and Empirical Analysis

Impact of Third-Party Payment on Banks Risk-taking Capacity and Empirical Analysis

Analysis of Carbon Dioxide Injectivity and Dynamic Storage Capacity in Shale Reservoirs

Abstract Carbon dioxide could be stored in unconventional shale reservoirs in a supercritical state due to available pore volume, infrastructure, and injectivity. However, there is a lack of knowledge about the injectivity and storage capacity in shale reservoirs. In this paper, a two-dimensional dual-porosity, dual-permeability model was built to investigate CO2 injectivity and dynamic storage capacity spatially and temporally. Parametric studies are conducted to evaluate the effect of matrix permeability, fracture conductivity, fracture half-length, operating conditions, and near-wellbore connectivity on storage factors. Systematic and comprehensive numerical experiments are carried out using random sampling to generate a probability distribution of CO2 storage factors and replacement ratio. Results showed the parameters with the most impact to least impact on injectivity and storage factor: matrix permeability, near-wellbore connectivity, bottomhole pressure, fracture half-length, and fracture conductivity. The methodology in this study provides a foundation to examine how CO2 storage factors change spatially and temporally in and outside the stimulated reservoir volume. The new understanding can be applied to optimize field development, well spacing, and infill drilling to increase economic storage.

STRATEGI PENGEMBANGAN WISATA BAHARI BERDASARKAN ANALISIS KESESUAIAN DAN DAYA DUKUNG WISATA BAHARI DI PANTAI PENIDA (CRYSTAL BAY)

Crystal Bay is one of the favorite tourist destinations for foreign tourists. This research aims to determine the suitability of marine tourism for snorkeling, diving, and beach recreation activities, measure the carrying capacity of nautical tourism, and formulate a strategy for developing marine tourism on Penida Beach. The method used to analyze the suitability of marine tourism is the concept of suitability by Yulianda et al. 2010, analysis of environmental carrying capacity according to Cifuentes, and formulation of a maritime tourism development strategy through SWOT. The results of the study of the suitability of marine tourism carried out by Penida Beach are in the S2 category with an IKW of 66.75% for snorkeling and diving of 64.81% and the beach recreation tourism category with an IKW value of 81.11%. The physical carrying capacity analysis calculation at Penida Beach showed that permitted tourist visits were for diving tourism activities of 5,082 people per year, snorkeling activities of 1,545,291 people per year, and beach recreation of 103,092 people per year. Analysis of the actual carrying capacity was obtained at 2,730 people per year for diving activities, snorkeling activities at 736,826 people per year, and beach recreation activities at 99,999 people per year. The practical tourism carrying capacity calculation results are 1815 people per year, 508,563 for snorkeling and beach recreation activities, and 68,970 people annually. Marine tourism development strategies include carrying out beach clean-up activities, monitoring and monitoring coral reef ecosystems, providing diving equipment, public education, rubbish bins, changing rooms, showers, clean water, signage, information, and selling areas. Souvenirs and wave break buildings to support the Nusa Penida Festival Event. Maximizing awig - awig, patrol facilities to be carried out daily, additional security facilities, and restrictions on tourist visits. They are conducting outreach to the community, requesting funds for developing tourism facilities, providing information related to the MPA, English language training, and preserving awig - awig. Keywords: tourism suitability; carrying capacity; sustainable tourism; SWOT

Topology identification and parameters estimation of LV distribution networks using open GIS data

The topology of low-voltage distribution networks (LVDNs) is crucial for system analysis, e.g., distributed energy resources (DERs) integration, network hosting capacity analysis, state estimation, and electric vehicle charging management. However, it is frequently unavailable or incomplete. This paper develops a data-driven topology identification approach for LVDNs with a high proportion of underground cables. The proposed approach exploits the fact that underground cables usually follow the street pattern, thus relying on open street map (OSM) and smart meter (SM) data. Three stages compose the proposed approach: In the first stage, a hierarchical minimum spanning tree algorithm is proposed to generate the initial topology with an accurate number of sub-branches from the pre-processed OSM data and peak demand. In the second stage, based on the limited SM data, the location of breakpoints in mesh topology caused by circle roads is verified and reconstructed to guarantee the radial structure of LVDNs. Finally, given multiple incomplete SM datasets, three data-driven optimization models based on a state estimation model are constructed to mitigate the error of cable length induced by OSM data. The feasibility of the proposed topology identification approach is verified on three actual LVDNs in The Netherlands and multiple incomplete SM datasets. Furthermore, the minimal amount of SM data needed to minimize the error of cable length is analyzed.

Capacity Analysis and Throughput Maximization of NOMA With Non-Linear Power Amplifier Distortion

Capacity Analysis and Throughput Maximization of NOMA With Non-Linear Power Amplifier Distortion

Multi-HAPS THz Satellite Communication: Error and Capacity Analyses Under I/Q Imbalance

Multi-HAPS THz Satellite Communication: Error and Capacity Analyses Under I/Q Imbalance

Numerical Analysis of Pullout Capacity of Composite Suction Caisson Foundation Used For Large Scale Underwater Compressed Gas Energy Storage

Abstract The suction caisson foundation, characterized by its unique installation methodology and excellent bearing capabilities, has emerged as a crucial supporting structure for marine constructions. However, the distinctive alternating cyclic high load patterns exhibited by underwater compressed gas energy storage systems significantly challenge the vertical pullout bearing capacity of regular suction caisson foundations. In this study, a novel composite suction caisson foundation is proposed to enhance the vertical pullout capacity. The pullout capacity under perfectly drained conditions is investigated by finite element analysis with ABAQUS/Standard 2020. A comparative analysis of the pullout capacity between regular suction caisson (RSC) and composite suction caisson (CSC) is conducted, focusing on aspect ratios of 0.5, 1, and 1.5. The results show that the pullout load of the proposed CSC, with the same aspect ratio, increased by a range of 12.8% to 100% compared to that of the RSC. As the aspect ratio increases, the trend of increasing pullout load decreases. The variation of displacement for the caisson at its ultimate pullout capability is relatively small, between 0.01D and 0.027D.