bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors Controlling Differences in Morphology and Fractal Characteristics of Organic Pores of Longmaxi Shale in Southern Sichuan Basin, China
Authors: Wang Yuanlin , Han Denglin , Lin Wei , Jia Yunqian , Zhang Jizhen , Wang Chenchen , Ma Binyu
Published: September 2024

Shale gas is a prospective cleaner energy resource and the exploration and development of shale gas has made breakthroughs in many countries. Structure deformation is one of the main controlling factors of shale gas accumulation and enrichment in complex tectonic areas in southern China. In order to estimate the shale gas capacity of structurally deformed shale reservoirs, it is necessary to understand the systematic evolution of organic pores in the process of structural deformation. In particular, as the main storage space of high-over-mature marine shale reservoirs, the organic matter pore system directly affects the occurrence and migration of shale gas; however, there is a lack of systematic research on the fractal characteristics and deformation mechanism of organic pores under the background of different tectonic stresses. Therefore, to clarify the above issues, modular automated processing system (MAPS) scanning, low-pressure gas adsorption, quantitative evaluation of minerals by scanning (QEMSCAN), and focused ion beam scanning electron microscopy (FIB-SEM) were performed and interpreted with fractal and morphology analyses to investigate the deformation mechanisms and structure of organic pores from different tectonic units in Silurian Longmaxi shale. Results showed that in stress concentration areas such as around veins or high-angle fractures, the organic pore length-width ratio and the fractal dimension are higher, indicating that the pore is more obviously modified by stress. Under different tectonic backgrounds, the shale reservoir in Weiyuan suffered severe denudation and stronger tectonic compression during burial, which means that the organic pores are dominated by long strip pores and slit-shaped pores with high fractal dimension, while the pressure coefficient in Luzhou is high and the structural compression is weak, resulting in suborbicular pores and ink bottle pores with low fractal dimension. The porosity and permeability of different forms of organic pores are also obviously different; the connectivity of honeycomb pores with the smallest fractal dimension is the worst, that of suborbicular organic pores is medium, and that of long strip organic pores with the highest fractal dimension is the best. This study provides more mechanism discussion and case analysis for the microscopic heterogeneity of organic pores in shale reservoirs and also provides a new analysis perspective for the mechanism of shale gas productivity differences in different stress–strain environments.
The First World War, Madness, and Reading between the Lines of The Marsden Case
Authors: Gustar Gillian
Published: September 2024

The Marsden Case, Ford’s first published novel after the First World War, has received relatively little critical attention. This paper aims to redress the balance by offering a sustained reading which illustrates how the context of the First World War interacts with a major theme in Ford’s oeuvre, madness. It follows Ford’s maxim that the novel was a place for inquiry and illustrates how Ford’s narrator explores the questions of who succumbs to madness and why. It highlights a debate at work in the novel on the role of talk in creating or curing nervous breakdowns. The novel’s opacity is part of a challenge to the wisdom of directly confronting or revisiting painful experiences, which speaks not only to the effects of the war but to the value of emerging Freudian psychotherapy.
A Comparative Study of Pavement Roughness Prediction Models under Different Climatic Conditions
Authors: Al-Samahi Soughah , Zeiada Waleed , Al-Khateeb Ghazi G. , Hamad Khaled , Alnaqbi Ali
Published: September 2024

Predicting the International Roughness Index (IRI) is crucial for maintaining road quality and ensuring the safety and comfort of road users. Accurate IRI predictions help in the timely identification of road sections that require maintenance, thus preventing further deterioration and reducing overall maintenance costs. This study aims to develop robust predictive models for the IRI using advanced machine learning techniques across different climatic conditions. Data were sourced from the Ministry of Energy and Infrastructure in the UAE for localized conditions coupled with the Long-Term Pavement Performance (LTPP) database for comparison and validation purposes. This study evaluates several machine learning models, including regression trees, support vector machines (SVMs), ensemble trees, Gaussian process regression (GPR), artificial neural networks (ANNs), and kernel-based methods. Among the models tested, GPR, particularly with rational quadratic specifications, consistently demonstrated superior performance with the lowest Root Mean Square Error (RMSE) and highest R-squared values across all datasets. Sensitivity analysis identified age, total pavement thickness, precipitation, temperature, and Annual Average Daily Truck Traffic (AADTT) as key factors influencing the IRI. The results indicate that pavement age and higher traffic loads significantly increase roughness, while thicker pavements contribute to smoother surfaces. Climatic factors such as temperature and precipitation showed varying impacts depending on the regional conditions. The developed models provide a powerful tool for predicting pavement roughness, enabling more accurate maintenance planning and resource allocation. The findings highlight the necessity of tailoring pavement management practices to specific environmental and traffic conditions to enhance road quality and longevity. This research offers a comprehensive framework for understanding and predicting pavement performance, with implications for infrastructure management both locally and worldwide.
Effects of Powder Reuse and Particle Size Distribution on Structural Integrity of Ti-6Al-4V Processed via Laser Beam Directed Energy Deposition
Authors: Mahtabi MohammadBagher , Yadollahi Aref , Morgan-Barnes Courtney , Priddy Matthew W. , Rhee Hongjoo
Published: September 2024

In metal additive manufacturing, reusing collected powder from previous builds is a standard practice driven by the substantial cost of metal powder. This approach not only reduces material expenses but also contributes to sustainability by minimizing waste. Despite its benefits, powder reuse introduces challenges related to maintaining the structural integrity of the components, making it a critical area of ongoing research and innovation. The reuse process can significantly alter powder characteristics, including flowability, size distribution, and chemical composition, subsequently affecting the microstructures and mechanical properties of the final components. Achieving repeatable and consistent printing outcomes requires powder particles to maintain specific and consistent physical and chemical properties. Variations in powder characteristics can lead to inconsistencies in the microstructural features of printed components and the formation of process-induced defects, compromising the quality and reliability of the final products. Thus, optimizing the powder recovery and reuse methodology is essential to ensure that cost reduction and sustainability benefits do not compromise product quality and reliability. This study investigated the impact of powder reuse and particle size distribution on the microstructural and mechanical properties of Ti-6Al-4V specimens fabricated using a laser beam directed energy deposition technique. Detailed evaluations were conducted on reused powders with two different size distributions, which were compared with their virgin counterparts. Microstructural features and process-induced defects were examined using scanning electron microscopy and X-ray computed tomography. The findings reveal significant alterations in the elemental composition of reused powder, with distinct trends observed for small and large particles. Additionally, powder reuse substantially influenced the formation of process-induced defects and, consequently, the fatigue performance of the components.
Cardiac Magnetic Resonance Speckle Tracking Analysis of Right Ventricle Function in Myocarditis with Preserved Right Ventricular Ejection Fraction
Authors: Özden Özge , Ünlü Serkan , Şahin Ahmet Anıl , Barutçu Ahmet , Gövdeli Elif Ayduk , Sherif Sara Abou , Papadopoulos Konstantinos , Bingöl Gülsüm , Kılıç Ismail Doğu , Özmen Emre , Seçkin Göbüt Özden , Landra Federico , Cameli Matteo , Göktekin Ömer
Published: September 2024

Background and Objectives: Diagnosis of myocarditis remains a challenge in clinical practice; however, magnetic resonance imaging (CMRI) can ease the diagnostic approach by providing various parameters. The prevalence of right ventricular involvement in acute myocarditis is suggested to be more frequent than previously hypothesized. In this study, we sought to investigate subclinical RV involvement in patients with acute myocarditis and preserved RV ejection fraction (EF), using CMRI RV speckle-tracking imaging. Materials and Methods: CMRI of 27 patients with acute myocarditis (nine females, age 35.1 ± 12.2 y) was retrospectively analyzed. A control group consisting of CMRI images of 27 healthy individuals was included. Results: No significant differences were found regarding left ventricle (LV) and atrium dimensions. LV ejection fraction was significantly different between groups (56.6 ± 10.6 vs. 62.1 ± 2.6, p < 0.05). No significant differences were present between parameters used for conventional assessment of RV. However, RV strain absolute values were significantly lower in the acute myocarditis group in comparison with that of the control group (18.4 ± 5.4 vs. 21.8 ± 2.8, p = 0.018). Conclusions: Subclinical RV dysfunction detected by CMR-derived strain may be present in patients with acute myocarditis even with preserved RVEF.
Assessing the Tibial Tubercle–Posterior Intercondylar Eminence Distance as a Superior Indicator for Patellar Instability and Surgical Planning in Tibial Tubercle Osteotomy
Authors: Iacobescu Georgian-Longin , Corlatescu Antonio-Daniel , Munteanu Octavian , Serban Bogdan , Spiridonica Razvan , Cirstoiu Catalin
Published: September 2024

Background and Objectives: This study aimed to evaluate the tibial tubercle–posterior intercondylar eminence (TT-IC) distance as a diagnostic tool and surgical guide for correcting extensor apparatus misalignment through tibial tubercle osteotomy. Materials and Methods: A retrospective analysis was conducted on patients with extensor apparatus misalignment. The TT-IC distance was measured using MRI. Patients underwent tibial tubercle osteotomy, guided by the TT-IC distance for correction. Post-operative outcomes, including alignment, pain scores, and functional recovery, were assessed. Results: A significant correlation was found between the TT-IC distance and the degree of extensor apparatus misalignment. Utilizing the TT-IC distance as a surgical guide led to improved alignment in majority of patients. Post-operative outcomes showed reduced pain and enhanced functional recovery. Conclusions: The study established the TT-IC measurement as a valuable tool for determining the need for tibial tuberosity osteotomy in patients with patellar instability, particularly those with trochlear dysplasia, by providing a more precise criterion than the traditional TT-TG distance.
Magnetic Resonance Imaging of Temporomandibular Joint and Aortic Root Score in Fibrillinopathies
Authors: Moisii Paloma , Naum Alexandru Gratian , Ursu Andra Mara , Vilcu Adrian , Esanu Irina , Jari Irina
Published: September 2024

Background and Objectives: Fibrillinopathies have different phenotypic expression: Marfan-like skeleton features, MLSF; mitral valve prolapse syndrome, MVPS; MASS phenotype, M = mitral valve prolapse, MVP, A = aortic root dilation, S = skeletal features, and the second S = (cutaneous) striae; Marfan Syndrome, MS. The study had the following main objectives: the correlation between disc displacement, DD (a major sign for temporomandibular joint dysfunction, TMDs) on magnetic resonance imaging, MRI, and aortic Z score (a major sign for aortic root dilation) on echocardiography; the predictive value of DD towards aortic Z score. DD had 2 types of severity: DD with reduction (the mild type, DDwR), and DD without reduction (the severe type, DDwoR). Materials and Methods: The type of fibrillinopathy was precised by clinical exam (systemic score), ophthalmic exam (for ectopia lentis), and echocardiography (aortic Z score, MVP). Medical treatment consisted of betablockers, BB (for patients with tachycardia), or angiotensin II receptor blockers, ARB. Surgical treatment was addressed to aortic root aneurysm, and severe mitral regurgitation, MR. DD benefited from dental conservatory treatment or surgical restoration. Results: DD-Z score had a powerful correlation in MASS (Rho = 0.787, p < 0.01), and in MS patients (Rho = 0.819, p < 0.01). For the entire sample, both DDwR-Z score and DDwoR-Z score had a moderate correlation (Rho = 0.469, and respectively 0.669). Furthermore, DD was an important predictor for Z score. DDwoR had a double power of prediction for the Z score compared with DDwR (B coefficient = 1.661 for DDwR and 3.281 for DDwoR). Conclusions: TMDs had a powerful correlation with aortic root dilation in MASS and MS patients from the sample. Likewise, TMDs was a major predictor for aortic root dilation, in the entire sample. In clinical practice, we can utilize an extracardiac finding, TMDs, obtained by a non-invasive technique, MRI, for cardiac severity stratification of fibrillinopathies.
Recent Advances in Robotic Surgery for Urologic Tumors
Authors: Hong Sen-Yuan , Qin Bao-Long
Published: September 2024

This review discusses recent advances in robotic surgery for urologic tumors, focusing on three key areas: robotic systems, assistive technologies, and artificial intelligence. The Da Vinci SP system has enhanced the minimally invasive nature of robotic surgeries, while the Senhance system offers advantages such as tactile feedback and eye-tracking capabilities. Technologies like 3D reconstruction combined with augmented reality and fluorescence imaging aid surgeons in precisely identifying the anatomical relationships between tumors and surrounding structures, improving surgical efficiency and outcomes. Additionally, the development of artificial intelligence lays the groundwork for automated robotics. As these technologies continue to evolve, we are entering an era of minimally invasive, precise, and intelligent robotic surgery.
Adhesin Antibody-Grafted Mesoporous Silica Nanoparticles Suppress Immune Escape for Treatment of Fungal Systemic Infection
Authors: Cheng Mengjuan , Liu Suke , Zhu Mengsen , Li Mingchun , Yu Qilin
Published: September 2024

Life-threatening systemic fungal infections caused by Candida albicans are significant contributors to clinical mortality, particularly among cancer patients and immunosuppressed individuals. The evasion of the immune response facilitated by fungal surface components enables fungal pathogens to evade macrophage attacks and to establish successful infections. This study developed a mesoporous silica nanoplatform, i.e., MSNP-EAP1Ab, which is composed of mesoporous silica nanoparticles grafted with the antibody of C. albicans surface adhesin Eap1. The activity of MSNP-EAP1Ab against C. albicans immune escape and infection was then evaluated by using the cell interaction model and the mouse systemic infection model. During interaction between C. albicans cells and macrophages, MSNP-EAP1Ab significantly inhibited fungal immune escape, leading to the enhanced phagocytosis of fungal cells by macrophages, with phagocytosis rates increasing from less than 8% to 14%. Furthermore, after treatment of the C. albicans-infected mice, MSNP-EAP1Ab drastically prolonged the mouse survival time and decreased the kidney fungal burden from >30,0000 CFU/g kidney to <100 CFU/g kidney, indicating the rapid recognition and killing of the pathogens by immune cells. Moreover, MSNP-EAP1Ab attenuated kidney tissue inflammation, with remarkable attenuation of renal immune cell accumulation. This study presents an innovative nanoplatform that targets the C. albicans adhesin, offering a promising approach for combatting systemic fungal infections.
Latin American Christology: A God Who Liberates
Authors: Bolaños Amanda Rachel
Published: September 2024

This paper will investigate the dynamic nature of Latin American Christology, a Christology that cannot be separated from the tenets of liberation theology. I will first offer an overview of the development of Latin American Christology and liberation theology, along with its unique features; then, I will analyze some major representatives of Latin American Christology, specifically Jon Sobrino and St. Óscar Romero (through the research of Edgardo Colón-Emeric). Lastly, I will conclude with the relevance of Latin American Christology within the greater landscape of Christian theology today. The theologians considered in this paper are primarily Catholic theologians, with the exception of Edgardo Colón-Emeric, a Methodist pastor, who has become a global voice of authority on the life, thought, and vision of the martyred St. Óscar Romero. Latin American Christology, as will be argued in this paper, cannot be understood separately from the space, culture, and identity of Latin America—the land and the context. This measures to a pivotal pedagogical claim of Latin American Christology as a global teaching pillar for all Christologies and theologies, Catholic or Protestant, within Latin America or outside Latin America.
Research on a 3D Point Cloud Map Learning Algorithm Based on Point Normal Constraints
Authors: Fang Zhao , Liu Youyu , Xu Lijin , Shahed Mahamudul Hasan , Shi Liping
Published: September 2024

Laser point clouds are commonly affected by Gaussian and Laplace noise, resulting in decreased accuracy in subsequent surface reconstruction and visualization processes. However, existing point cloud denoising algorithms often overlook the local consistency and density of the point cloud normal vector. A feature map learning algorithm which integrates point normal constraints, Dirichlet energy, and coupled orthogonality bias terms is proposed. Specifically, the Dirichlet energy is employed to penalize the difference between neighboring normal vectors and combined with a coupled orthogonality bias term to enhance the orthogonality between the normal vectors and the subsurface, thereby enhancing the accuracy and robustness of the learned denoising of the feature maps. Additionally, to mitigate the effect of mixing noise, a point cloud density function is introduced to rapidly capture local feature correlations. In experimental findings on the anchor public dataset, the proposed method reduces the average mean square error (MSE) by 0.005 and 0.054 compared to the MRPCA and NLD algorithms, respectively. Moreover, it improves the average signal-to-noise ratio (SNR) by 0.13 DB and 2.14 DB compared to MRPCA and AWLOP, respectively. The proposed algorithm enhances computational efficiency by 27% compared to the RSLDM method. It not only removes mixed noise but also preserves the local geometric features of the point cloud, further improving computational efficiency.
Finite Element Analysis of Electrostatic Coupling in LISA Pathfinder Inertial Sensors
Authors: Zhang Wenyan , Lei Jungang , Wang Zuolei , Li Cunhui , Yang Shijia , Min Jian , Wen Xuan
Published: September 2024

In the LISA Pathfinder (LPF) mission, electrostatic noise can reach the femto-Newtonian level despite the fact that the LPF’s sensors are equipped with potential shielding. Most of the existing simulation studies focus on the electrostatic edge effect and related fields, while the simulation study of the patch effect is neglected. For that reason, this paper analyzes the basic principle of electrostatic noise and constructs a simulation model for studying the coupling effects of a TM’s residual charge and stray bias voltage. The patch effect and other perturbation factors are simulated by the simulation model with finite element operation, focusing on the suppression effect of the protective ring on the edge effect, the realization of the patch effect in the simulation model, and the possible influence. The results show that electrode area and the spacing between the electrode and the TM together limit the suppression effect of the protective ring on the edge effect. The spatial and temporal variations of the patch effect significantly affect the distributed electric field between the electrodes and the TM, as well as the charge distribution density of the TM. In the worst-case scenario of LPF electrostatic input parameters, the electrostatic noise is about 1.03 × 10−15 m/s2/√Hz at 1 mHz, which is about 6% different from the expected performance estimate. Finally, considering the limitations of multiple environmental factors on the inertial sensors, the present model will be useful to explore the interactive effects of multi-field coupling and to further investigate the impact of low-energy electron charging on the performance of the inertial sensors.
Smart Rumble Strip System to Prevent Over-Height Vehicle Collisions
Authors: Chan Ricky W. K.
Published: September 2024

Collisions of over-height vehicles with low clearance bridges is commonly encountered worldwide. They have caused damage to bridge structures, interruption to traffic, injuries or even fatalities to road users. To mitigate such risks, passive systems that involve warning gantries, flashing lights and illuminated signage are commonly installed. Semi-active systems using laser- or infrared-based detection systems in conjunction with visual warnings have been implemented. Nevertheless, some drivers ignore these visual warnings and collisions continue to occur. This paper presents a novel concept for a collision prevention system, which makes use of a series of sensor-activated, motorized rumble strips. These rumble strips span across a certain distance ahead of a low clearance bridge. When an over-height vehicle is detected, a mechanism is triggered which elevates the rumble strips. The noise and vibrations produce a vigorous alert to the offending driver. They also increase effective friction of the road surface, thus assisting to slow down the vehicle and shorten the stopping distance. The strips will be lowered after a certain time has elapsed, thus minimizing their effects on other vehicles. This article presents a conceptual framework and quantifies the vibration and noise caused by rumble strips in road tests. Road tests indicated that the vibration level typically exceeded 1 g and noise level reached approximately 90 dB in the cabin of a 3.5-ton truck. Fabrication of a proof-of-concept mechanized rumble strip model was presented and verified in an outdoor environment. The circuitry and mechanical design, and requirements in actual implementation, are discussed. The proposed event-triggered rumble strip system could significantly mitigate over-height vehicle collisions that cause major disruptions and injuries worldwide. Further works, including a comprehensive road test involving various types of vehicles, are envisaged.
Airflow Modeling for Citrus under Protective Screens
Authors: Kurafeeva Liubov , Wolski Rich , Krintz Chandra , Smyth Thomas
Published: September 2024

This study explores the development and validation of an airflow model to support climate prediction for Citrus Under Protective Screens (CUPS) in California. CUPS is a permeable screen structure designed to protect a field of citrus trees from large insects including the vector that causes the devastating citrus greening disease. Because screen structures modify the environmental conditions (e.g., temperature, relative humidity, airflow), farm management and treatment strategies (e.g., pesticide spraying events) must be modified to account for these differences. Toward this end, we develop a model for predicting wind speed and direction in a commercial-scale research CUPS, using a computational fluid dynamics (CFD) model. We describe the model and validate it in two ways. In the first, we model a small-scale replica CUPS under controlled conditions and compare modeled and measured airflow in and around the replica structure. In the second, we model the full-scale CUPS and use historical measurements to “back test” the model’s accuracy. In both settings, the modeled airflow values fall within statistical confidence intervals generated from the corresponding measurements of the conditions being modeled. These findings suggest that the model can aid decision support and smart agriculture solutions for farmers as they adapt their farm management practices for CUPS structures.
Sequence Decision Transformer for Adaptive Traffic Signal Control
Authors: Zhao Rui , Hu Haofeng , Li Yun , Fan Yuze , Gao Fei , Gao Zhenhai
Published: September 2024

Urban traffic congestion poses significant economic and environmental challenges worldwide. To mitigate these issues, Adaptive Traffic Signal Control (ATSC) has emerged as a promising solution. Recent advancements in deep reinforcement learning (DRL) have further enhanced ATSC’s capabilities. This paper introduces a novel DRL-based ATSC approach named the Sequence Decision Transformer (SDT), employing DRL enhanced with attention mechanisms and leveraging the robust capabilities of sequence decision models, akin to those used in advanced natural language processing, adapted here to tackle the complexities of urban traffic management. Firstly, the ATSC problem is modeled as a Markov Decision Process (MDP), with the observation space, action space, and reward function carefully defined. Subsequently, we propose SDT, specifically tailored to solve the MDP problem. The SDT model uses a transformer-based architecture with an encoder and decoder in an actor–critic structure. The encoder processes observations and outputs, both encoded data for the decoder, and value estimates for parameter updates. The decoder, as the policy network, outputs the agent’s actions. Proximal Policy Optimization (PPO) is used to update the policy network based on historical data, enhancing decision-making in ATSC. This approach significantly reduces training times, effectively manages larger observation spaces, captures dynamic changes in traffic conditions more accurately, and enhances traffic throughput. Finally, the SDT model is trained and evaluated in synthetic scenarios by comparing the number of vehicles, average speed, and queue length against three baselines, including PPO, a DQN tailored for ATSC, and FRAP, a state-of-the-art ATSC algorithm. SDT shows improvements of 26.8%, 150%, and 21.7% over traditional ATSC algorithms, and 18%, 30%, and 15.6% over the FRAP. This research underscores the potential of integrating Large Language Models (LLMs) with DRL for traffic management, offering a promising solution to urban congestion.
Artificial Intelligence for the Evaluation of Postures Using Radar Technology: A Case Study
Authors: De Vittorio Davide , Barili Antonio , Danese Giovanni , Marenzi Elisa
Published: September 2024

In the last few decades, major progress has been made in the medical field; in particular, new treatments and advanced health technologies allow for considerable improvements in life expectancy and, more broadly, in quality of life. As a consequence, the number of elderly people is expected to increase in the following years. This trend, along with the need to improve the independence of frail people, has led to the development of unobtrusive solutions to monitor daily activities and provide feedback in case of risky situations and falls. Monitoring devices based on radar sensors represent a possible approach to tackle postural analysis while preserving the person’s privacy and are especially useful in domestic environments. This work presents an innovative solution that combines millimeter-wave radar technology with artificial intelligence (AI) to detect different types of postures: a series of algorithms and neural network methodologies are evaluated using experimental acquisitions with healthy subjects. All methods produce very good results according to the main parameters evaluating performance; the long short-term memory (LSTM) and GRU show the most consistent results while, at the same time, maintaining reduced computational complexity, thus providing a very good candidate to be implemented in a dedicated embedded system designed to monitor postures.
Enhanced Tetracycline Adsorption Using KOH-Modified Biochar Derived from Waste Activated Sludge in Aqueous Solutions
Authors: Ding Jiazheng , Liang Jiahao , Wang Qinghong , Tan Xiang , Xie Wenyu , Chen Chunmao , Li Changgang , Li Dehao , Li Jin , Chen Xiaoqing
Published: September 2024

Antibiotic pollution poses a serious environmental concern worldwide, posing risks to ecosystems and human well-being. Transforming waste activated sludge into adsorbents for antibiotic removal aligns with the concept of utilizing waste to treat waste. However, the adsorption efficiency of these adsorbents is currently limited. This study identified KOH modification as the most effective method for enhancing tetracycline (TC) adsorption by sludge biochar through a comparative analysis of acid, alkali, and oxidant modifications. The adsorption characteristics of TC upon unmodified sludge biochar (BC) as well as KOH-modified sludge biochar (BC-KOH) were investigated in terms of equilibrium, kinetics, and thermodynamics. BC-KOH exhibited higher porosity, greater specific surface area, and increased abundance of oxygen-based functional groups compared to BC. The TC adsorption on BC-KOH conformed the Elovich and Langmuir models, with a maximum adsorption capacity of 243.3 mg/g at 298 K. The adsorption mechanisms included ion exchange, hydrogen bonding, pore filling, and electrostatic adsorption, as well as π-π interactions. Interference with TC adsorption on BC-KOH was observed with HCO3−, PO43−, Ca2+, and Mg2+, whereas Cl−, NO3−, and SO42− ions exhibited minimal impact on the adsorption process. Following three cycles of utilization, there was a slight 5.94% reduction in the equilibrium adsorption capacity, yet the adsorption capacity remained 4.5 times greater than that of unmodified sludge BC, underscoring its significant potential for practical applications. This research provided new insights to the production and application of sludge biochar for treating antibiotic-contaminated wastewater.
Smart Monitoring of Microgrid-Integrated Renewable-Energy-Powered Electric Vehicle Charging Stations Using Synchrophasor Technology
Authors: B Deepa , Hampannavar Santoshkumar , Mansani Swapna
Published: September 2024

With the growing concern over climate change and energy security, the Government of India expedited enhancing the share of renewable energy (RE) derived from solar, wind and biomass sources within the energy blend. In this paper, a techno-economic and environmental analysis of a microgrid-integrated electric vehicle charging stations fueled by renewable energy is proposed for a typical area in the State of Karnataka, South India. The power transaction with the grid and the sell-back price to the national grid were investigated. Carbon emissions were also assessed, and 128,406 CO2 kg/Yr can be saved in the grid-connected mode. Also, in this work, different scenarios such as injecting active power, reactive power, and active and reactive power, and injecting active and absorbing reactive power to the grid are comprehensively assessed. Out of four types, type 3 (inject real and reactive power) provides significant reduction in power losses by up to 80.99%. The synchrophasor-technology-based monitoring method is adopted in order to enhance the microgrid system’s overall performance. The execution times for different cases with distributed generators (DGs) and electric vehicle charging stations (EVCSs) for conventional systems and micro-phasor measurement units (µPMU) were observed to be 19.07 s and 5.64 s, respectively, which is well accepted in the case of online monitoring.
Implementación de estrategias de reciclaje de bolsas de polietileno para la sostenibilidad en empacadoras del cultivo de banano
Authors: Diaz Baltazar Sánchez , Lorenzo Yareli Naythel Bolaina , Márquez Fernando Pérez , Cornelio Catalina del Socorro Vidal , Jesús Raúl Enrique Islas , Hernández Fidel Olive
Published: September 2024

El cultivo de banano, especialmente de la especie Musa paradisiaca, es una actividad económica significativa en regiones tropicales, el uso de bolsas de polietileno para proteger los frutos de plagas y daños físicos es común, pero su disposición incorrecta plantea riesgos ambientales y de salud. El objetivo es aprovechar las bolsas de polietileno usadas en la protección de bananos, dándoles un segundo uso o reciclándolas, para reducir la contaminación ambiental y generar beneficios económicos y sociales. Utilizando la Matriz de Leopold, se evaluaron los impactos negativos del almacenamiento directo en el suelo, la quema y el traslado al basurero de cielo abierto de las bolsas de polietileno. Estos impactos incluyen la contaminación del suelo, la liberación de sustancias tóxicas y la generación de empleo mediante el reciclaje. Se estimó que semanalmente se generan aproximadamente 1300 bolsas desechadas en la empacadora, las cuales serán recolectadas y recicladas por Reciclaje de la Sierra S.A. de C.V., convirtiéndolas en nuevas bolsas de polietileno para diversos usos. La implementación de estrategias de reciclaje de bolsas de polietileno en la empacadora "Mi Ranchito" ha demostrado ser una solución viable y beneficiosa para abordar el problema de los desechos plásticos. Las alianzas estratégicas con empresas de reciclaje, como Reciclaje de la Sierra S.A. de C.V., han permitido establecer un canal eficiente para la reutilización de estas bolsas. Las propuestas innovadoras presentadas han mejorado significativamente los procesos de manejo de desechos en la empacadora, reduciendo el impacto ambiental y generando beneficios económicos.
Análise da estabilidade dimensional e solubilidade dos cimentos obturadores endodônticos
Authors: Gomes Isabelly Batista , Albuquerque Sthefanie Lucy Melo de , Aguiar Bernardo Almeida , Batista Williams Pereira
Published: September 2024

No intuito de viabilizar a previsibilidade e o sucesso do tratamento endodôntico faz-se necessário o conhecimento sobre as propriedades físicas, químicas e biológicas ideais. O objetivo do presente estudo foi avaliar a estabilidade dimensional e a solubilidade dos cimentos utilizados durante a obturação, para um adequado selamento radicular. Para a estabilidade dimensional os cimentos recém manipulados foram testados no período de 24 horas e 30 dias. Com os cimentos recém manipulados, o cálculo da estabilidade dimensional foi realizado em função da seguinte fórmula [(CFINAL – C)/C] x 100, onde “CFINAL” = comprimento da amostra após o período de imersão e “C” = comprimento inicial da amostra. A média aritmética de cinco medições para cada cimento foi registrada como a alteração dimensional de cada cimento testado. Para análise de solubilidade foram usados anéis de teflon preenchidos de cimento, após 30 dias esses anéis foram pesados, devolvidos ao dessecador por 24 horas e após, nova pesagem, a solubilidade do cimento foi determinada como uma porcentagem do peso perdido em relação ao peso original. Os resultados demostram que durante o período de 24 horas todos os cimentos estão condizentes com as normas, o cimento N- Rickert® apresentou melhor estabilidade dimensional durante o período de 30 dias sendo o único aprovado com relação as normas ISO/ADA neste período. Na solubilidade os resultados apontam que o cimento Endofill® apresentam menor solubilidade e o cimento N-Rickert um pior resultado, porém todos encontram a porcentagem dentro das normas ISO.
أثر سياسات الإصلاح الاقتصادي على التنمية البشرية في مصر
Authors: توني محمود عبدالعزيز
Published: September 2024

باستخدام نموذج متجه الانحدار الذاتي، تبحث هذه الورقة تأثير سياسات الإصلاح الاقتصادي التي اتخذتها الحكومة المصرية منذ بداية التسعينات من القرن الماضي على التنمية البشرية في مصر. وتشير النتائج إلى أن كلا من التضخم وعجز الموازنة له أثر سلبي على مؤشر التنمية البشرية. إضافة إلى ذلك، فإن الأثر التراكمي للمتغيرات المبطأة للإصلاحات النقدية وسعر الصرف لها تأثير سلبي على مؤشر التنمية البشرية. في المقابل، فإن السياسات التي تهدف إلى تحرير التجارة الدولية لها تأثير إيجابي على معدل التنمية البشرية. كما أشارت النتائج إلى أن الصدمات غير المتوقعة في معدل التضخم أو المعروض من النقود لها تأثير دائم على مؤشر التنمية البشرية في مصر. إلى جانب ذلك، فإن التنبؤ بمؤشر التنمية البشرية في مصر يشير إلى وجود اتجاه تناقصي خلال الفترة (2015-2020). وتقدم الدراسة بعض التوصيات لتعزيز التنمية البشرية في مصر جنباً إلى جنب مع استهداف إصلاح الاختلالات في الاقتصاد الكلي وتعزيز النمو الاقتصادي.
هل أسواق الدول النامية تتبع فرضية كفاءة السوق؟ دليل من بيانات كويتية حديثة
Authors: المجمد هشام إبراهيم , فيصل صبار العنزي  , الفريح مشاري محمد
Published: September 2024

تدرس هذه الدراسة صلاحية الشكل الضعيف من فرضية السوق الكفء كما يُطبق على بورصة الكويت (KSE) باستخدام بيانات الفترة من 2000 إلى 2015 وثلاث فترات فرعية. من خلال تطبيق التحليل الإحصائي وقواعد المتوسطات المتحركة، تقدم هذه الدراسة أدلة جديدة على عدم كفاءة بورصة الكويت. تشير النتائج التجريبية بشكل خاص إلى أن استراتيجيات المتوسطات المتحركة تنجح في التنبؤ بعوائد مؤشر البورصة. علاوة على ذلك، تقترح نتائج الفترات الفرعية أن بورصة الكويت لن تحقق كفاءة أكبر على الرغم من إدخال تنظيمات جديدة، وزيادة في الإفصاحات المحاسبية، وتطوير الهياكل الدقيقة للسوق.
Miocene vegetation and climate in the eastern North Sea Basin, onshore Denmark, compared to the present
Authors: Śliwińska Kasia K , Denk Thomas , Dybkjær Karen , Fredborg Julie Margrethe , Lindström Sofie , Piasecki Stefan , Rasmussen Erik Skovbjerg
Published: September 2024

Despite often being referred to as a ‘coolhouse climate’, the climate during the Miocene (23.03–5.33 Ma) was overall humid, warm and temperate. It was paced by orbitally driven cooler periods (the Oligocene–Miocene Transition and Mi-events) overprinted by a climatic optimum. Global cooling during the Late Miocene brought more arid conditions with climate seasonality, which varied across western Eurasia. Sedimentary archives from onshore Denmark comprise shallow marine siliciclastic deposits and discrete brown coal layers. Hence, they allow us to infer past climates and environments using both marine and terrestrial fossils. The backbone for Miocene stratigraphy and palaeoclimate reconstruction in the eastern North Sea Basin (present-day Denmark) is the Sønder (Sdr.) Vium sediment core, which penetrates a shallow marine succession and spans an interval from c. 22 to 8 Ma. Here, we present an improved age model for the core. During the Miocene, forested lowlands predominated in the eastern North Sea Basin. Coastal areas included rich riparian landscapes and delta areas of lignite-forming swamp forest. Compilations of existing proxy records (pollen, spores, leaves, plant fragments and the organic biomarkers alkenones and membrane lipids) collectively show that the climate here was warm and moist during the Early and Middle Miocene, while the Late Miocene was characterised by climate cooling and modernisation of the vegetation. The interval preceding the Miocene Climatic Optimum was already warm and moist, and the onset was not characterised by a significant increase in temperature and precipitation. Instead, the palynoflora indicates homogeneous vegetation and only a weak signal of warming shown by a minor increase of, for example, sabaloid palms and Mastixiaceae.
Health Infrastructures in India with Special Reference to MSME Sector - An Assessment
Authors: Chikkannaswamy G.B. , Rajendra Prasad T.
Published: September 2024

The healthcare enterprise consists of each the general public and business sectors and consists of scientific tourism, hospitals, fitness insurance, scientific equipment, and outsourcing. The creation of healthcare products, inclusive of scientific equipment, instruments, and services, in addition to for biotechnology and diagnostic laboratories via way of means of Indian Startups affords an answer within side the shape of healthcare services and products and quickens technological innovation to face up to international competition. The National Health Policy, which changed into posted in 2017 to construct the fitness care infrastructure, and the Pradhan Mantra Ayushman Bharat understand the significance of pharmaceutical agencies for enhancing healthcare. The pinnacle 20 markets for scientific gadgets are closely encouraged with the aid of using the scientific tool sector. MSME makes up 6.11% of the GDP from manufacturing, 24.63% of the GDP from services, and 45% of the whole exports. According to the Medical Tourism Index (MIT) for 2020–21, scientific era in India is predicted to attain US $50 billion with the aid of using 2025 and is now positioned 10th. Out of forty six international locations, India`s healthcare marketplace is predicted to attain US$372 billion with the aid of using 2022.usedsecondary data in this paper for discussed Health infrastructures and evaluate role of Health facilities and problems in Health sector in India by secondary source.
The Impact of Russia-Ukriane War on Indian Stock Market
Authors: Kulasekhar M.
Published: September 2024

War, the most exceedingly terrible calamity, obliterates nation-building and social union. Fights are horrible to the point that they can become around the world, influencing the whole globe. War attacks all nations. After the unexpected strike of the COVID-19 infection, the world’s significant economies were attempting to recuperate. North of three years after the fact, broad inoculation crusades saved individuals from the destructive infection. The most terrible times appeared to be past, and the world’s driving economies started to recuperate. Be that as it may, something should occur. The morning of February 24, 2022, shocked individuals once more. Russia went after Ukraine on the morning of February 22, 2022.Russia’s activities in Ukraine have brought Western condemnation and weighty punishments. North of 2,700 limitations have frozen $300 billion in Russian gold and unfamiliar trade holds. American and associated bans of Soviet oil caused record-high crude oil prices in the months that followed. Notwithstanding cultural expenses, the fight impacted essentially all significant economies around the world. Influence is felt in India too. Thump on impacts arrived at India. Stock prices declined, inflation arrived at new highs, the rupee fell against the dollar, unfamiliar trade saves dwindled, and that’s only the tip of the iceberg, as per outside markers. Since the 2020 COVID-19 pestilence, the worldwide economy has endured twice. This paper looks at what the Russia-Ukraine war might mean for Indian imports, exports, trade rates, stock market, and inflation.
Private Space and Scheduled Caste Colonies in Kerala
Authors: Manuraj Siyar , Nisha K.S.
Published: September 2024

Central and state governments have been spending huge amounts year after year for the development of scheduled caste people in India. The state of Kerala is also a good role model in this regard. Social integration of the Scheduled Castes in India with the rest of the communities is still an unfinished agenda of independent India. In this regard, Kerala, one of the states in India having highest rate of social development, is not an exception. The present article tries to theoretically contextualize the socio-economic backwardness of Scheduled Castes in Kerala by analysing to what extent a scheduled caste house property in Scheduled caste Colonies is an economic good. The study uses a theoretical concept-private space which is extracted from Henri Lefebvre’s social space.
An Economic Analysis of Dairy Sector in India with Special Reference to Milk Dairy Co-Operatives in Karnataka
Authors: Munishami Gowda N. , Yogish S.N.
Published: September 2024

Dairy activities play a predominate role in the Indian economy. Due to fail in agricultural crops the farmers not only depending upon cropping pattern alone, indeed they depend on other allied agricultural activities like poultry farming, fishing, agro based activities, family enterprises, food products. Among the allied agricultural activities, dairy is one of the prominent activities to the farmers. Dairying is not only cheap but also yield more returns. This is especially where more of woman are engaged in this activity. Due to various constraints in this dairy activity, co operative sector play a very important role in not only protecting the dairy activities but also promote it with various polices and packages of co operative sector. With this background the present study is more relevant as well to identify various issues of the cooperative dairy sector both in Karnataka and Tamilnadu.
From Pixels to Prose: Redefining Literary Expression through Digital Mediums
Authors: Jeya Jeevakani G
Published: September 2024

This abstract introduces a compelling exploration into the transformative intersection of literature and digital mediums. “From Pixels to Prose” delves into the evolving landscape where traditional literary expression converges with cutting-edge digital technologies. The abstract highlights the impact of pixels on the narrative canvas, highlighting how authors and creators are pushing the boundaries of storytelling through immersive experiences, interactive narratives, and experimental forms. This study investigates the symbiotic relationship between pixels and prose, unveiling new dimensions in literary expression that challenge conventional norms. The abstract emphasizes the significance of this dynamic interplay, shedding light on the ways in which digital mediums redefine the very essence of storytelling, inviting readers and audiences into a captivating realm where words and pixels coalesce to shape the future of literary artistry.
Cultural Collisions in Things Fall Apart: Unraveling the Dynamics of Cultural Conflicts
Authors: Sangeetha M G
Published: September 2024

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AI-Powered Knowledge and Skill Transfer: Navigating the Intersection of Technology and Education
Authors: Sarsha T S
Published: September 2024

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The Role of Myth in Indian Context with Special Reference of Amish Tripathi’s Shiva Trilogy
Authors: Kamaladevi D , Sathyakala T
Published: September 2024

This story by Amish Tripathi Shiva Trilogy explores the leadership quality and Adventures of Shiva. Shiva is one of the principal God of Hindu Mythology. Amish creates a world of Fantasy including Corruption, Caste system and Unnecessary Laws. Because, Indian Literature is based on religion, deeds, human value, obedience, bravery, morality, human nature and love. A Myth is a traditional story, specifically about the early history of people or explaining some natural or social context and involving supernatural beings or events. Myths are the primogenital and most powerful of all story forms. It carries an important message for a culture or group to the next generation. Myths are stories that provide people a relationship with the world. Some myths give the formal view of creation, other are a way to explain natural events. Myth generally has a meaning and refers to the stories and world of Gods and Goddesses. Myth is a constant among all human beings in all times. Here, Amish also spotlights the external world of supernatural beings as in the name as Myth/Mythology.