bluuebunny/crossref_metadata_2025 huggingface dataset:
Neonatal encephalopathy due to suspected hypoxic ischemic encephalopathy: pathophysiology, current, and emerging treatments
Authors: Babbo Carina Corte-Real , Mellet Juanita , van Rensburg Jeanne , Pillay Shakti , Horn Alan Richard , Nakwa Firdose Lambey , Velaphi Sithembiso Christopher , Kali Gugulabatembunamahlubi Tenjiwe Jabu , Coetzee Melantha , Masemola Mogomane Yvonne Khomotso , Ballot Daynia Elizabeth , Pepper Michael Sean
Published: September 2024

Background

Neonatal encephalopathy (NE) due to suspected hypoxic-ischemic encephalopathy (HIE), referred to as NESHIE, is a clinical diagnosis in late preterm and term newborns. It occurs as a result of impaired cerebral blood flow and oxygen delivery during the peripartum period and is used until other causes of NE have been discounted and HIE is confirmed. Therapeutic hypothermia (TH) is the only evidence-based and clinically approved treatment modality for HIE. However, the limited efficacy and uncertain benefits of TH in some low- to middle-income countries (LMICs) and the associated need for intensive monitoring have prompted investigations into more accessible and effective stand-alone or additive treatment options.

Data sources

This review describes the rationale and current evidence for alternative treatments in the context of the pathophysiology of HIE based on literatures from Pubmed and other online sources of published data.

Results

The underlining mechanisms of neurotoxic effect, current clinically approved treatment, various categories of emerging treatments and clinical trials for NE are summarized in this review. Melatonin, caffeine citrate, autologous cord blood stem cells, Epoetin alfa and Allopurinal are being tested as potential neuroprotective agents currently.

Conclusion

This review describes the rationale and current evidence for alternative treatments in the context of the pathophysiology of HIE. Neuroprotective agents are currently only being investigated in high- and middle-income settings. Results from these trials will need to be interpreted and validated in LMIC settings. The focus of future research should therefore be on the development of inexpensive, accessible monotherapies and should include LMICs, where the highest burden of NESHIE exists.

Graphical abstract
A proof of the Elliott–Rödl conjecture on hypertrees in Steiner triple systems
Authors: Im Seonghyuk , Kim Jaehoon , Lee Joonkyung , Methuku Abhishek
Published: September 2024

Hypertrees are linear hypergraphs where every two vertices are connected by a unique path. Elliott and Rödl conjectured that for any given

$\mu>0$

, there exists

$n_0$

such that the following holds. Every n-vertex Steiner triple system contains all hypertrees with at most

$(1-\mu )n$

vertices whenever

$n\geq n_0$

. We prove this conjecture.
A Statistical Survey of E‐Region Anomalous Electron Heating Using Poker Flat Incoherent Scatter Radar Observations
Authors: Zhang Yizhe , Varney Roger H.
Published: September 2024

This work presents an algorithm for automatic detection of anomalous electron heating (AEH) events in the auroral E‐region ionosphere using data from the Poker Flat Incoherent Scatter Radar (PFISR). The algorithm considers both E‐region electron temperature and magnetically conjugate electric field measurements. Application of this algorithm to 14 years of PFISR data spanning 2010 through 2023 detected 505 AEH events. Measured electron temperatures increase linearly with plasma drift speeds. Statistical trends of AEH occurrence as a function of space weather indices (AE and F10.7) demonstrate correlations with the solar cycle and geomagnetic activity levels. The magnetic local time occurrence rates show preferences for dusk and dawn with most events in the dusk sector. Observed AEH events tend to appear in regions of relatively low electron density and do not appear inside intense auroral arcs with high electron density. Furthermore, AEH detection requires a higher electric field than predicted by the threshold for a positive growth rate of the Farley‐Buneman instability (FBI), according to linear fluid theory. The implications of these findings for kinetic theories of FBI and AEH are discussed.
Data to Decisions: Changing Priorities for Earth Observations
Authors: Brown Molly , Neeley Aimee , Neumann Thomas
Published: September 2024

NASA is updating how it designs and implements Earth science missions to ensure their data and science reach users and decisionmakers faster and more effectively.
Distinct stabilization of the human T cell leukemia virus type 1 immature Gag lattice
Authors: Obr Martin , Percipalle Mathias , Chernikova Darya , Yang Huixin , Thader Andreas , Pinke Gergely , Porley Dario , Mansky Louis M. , Dick Robert A. , Schur Florian K. M.
Published: September 2024

Human T cell leukemia virus type 1 (HTLV-1) immature particles differ in morphology from other retroviruses, suggesting a distinct way of assembly. Here we report the results of cryo-electron tomography studies of HTLV-1 virus-like particles assembled in vitro, as well as derived from cells. This work shows that HTLV-1 uses a distinct mechanism of Gag–Gag interactions to form the immature viral lattice. Analysis of high-resolution structural information from immature capsid (CA) tubular arrays reveals that the primary stabilizing component in HTLV-1 is the N-terminal domain of CA. Mutagenesis analysis supports this observation. This distinguishes HTLV-1 from other retroviruses, in which the stabilization is provided primarily by the C-terminal domain of CA. These results provide structural details of the quaternary arrangement of Gag for an immature deltaretrovirus and this helps explain why HTLV-1 particles are morphologically distinct.
Insights into particle dispersion and damage mechanisms in functionally graded metal matrix composites with random microstructure-based finite element model
Authors: Naguib M. E. , Gad S. I. , Megahed M. , Agwa M. A.
Published: September 2024

This study investigates the impact of $$\mathrm {Al_2O_3}$$

Al
2

O
3

particle volume fraction and distribution on the deformation and damage of particle-reinforced metal matrix composites, particularly in the context of functionally graded metal matrix composites. In this study, a two-dimensional nonlinear random microstructure-based finite element modeling approach implemented in ABAQUS/Explicit with a Python-generated script to analyze the deformation and damage mechanisms in $$\mathrm{AA6061\mbox{-}T6/Al_2O_{3}}$$

AA
6061
-
T
6
/

Al
2

O
3

composites. The plastic deformation and ductile cracking of the matrix are captured using the Gurson–Tvergaard–Needleman model, whereas particle fracture is modelled using the Johnson–Holmquist II model. Matrix-particle interface decohesion is simulated using the surface-based cohesive zone method. The findings reveal that functionally graded metal matrix composites exhibit higher hardness values ($$\textrm{HRB}$$
HRB
) than traditional metal matrix composites. The results highlight the importance of functionally graded metal matrix composites. Functionally graded metal matrix composites with a Gaussian distribution and a particle volume fraction of 10% achieve $$\textrm{HRB}$$
HRB
values comparable to particle-reinforced metal matrix composites with a particle volume fraction of 20%, with only a 2% difference in $$\textrm{HRB}$$
HRB
. Thus, $$\textrm{HRB}$$
HRB
can be improved significantly by employing a low particle volume fraction and incorporating a Gaussian distribution across the material thickness. Furthermore, functionally graded metal matrix composites with a Gaussian distribution exhibit higher $$\textrm{HRB}$$
HRB
values and better agreement with experimental distribution functions when compared to those with a power-law distribution.
Activation of an atypical plant NLR with an N-terminal deletion initiates cell death at the vacuole
Authors: Sunil Sruthi , Beeh Simon , Stöbbe Eva , Fischer Kathrin , Wilhelm Franziska , Meral Aron , Paris Celia , Teasdale Luisa , Jiang Zhihao , Zhang Lisha , Urban Moritz , Aguilar Parras Emmanuel , Nürnberger Thorsten , Weigel Detlef , Lozano-Duran Rosa , El Kasmi Farid
Published: September 2024

Plants evolve nucleotide-binding leucine-rich repeat receptors (NLRs) to induce immunity. Activated coiled-coil (CC) domain containing NLRs (CNLs) oligomerize and form apparent cation channels promoting calcium influx and cell death, with the alpha-1 helix of the individual CC domains penetrating the plasma membranes. Some CNLs are characterized by putative N-myristoylation and S-acylation sites in their CC domain, potentially mediating permanent membrane association. Whether activated Potentially Membrane Localized NLRs (PMLs) mediate cell death and calcium influx in a similar way is unknown. We uncovered the cell-death function at the vacuole of an atypical but conserved Arabidopsis PML, PML5, which has a significant deletion in its CCG10/GA domain. Active PML5 oligomers localize in Golgi membranes and the tonoplast, alter vacuolar morphology, and induce cell death, with the short N-terminus being sufficient. Mutant analysis supports a potential role of PMLs in plant immunity. PML5-like deletions are found in several Brassicales paralogs, pointing to the evolutionary importance of this innovation. PML5, with its minimal CC domain, represents the first identified CNL utilizing vacuolar-stored calcium for cell death induction.
Unusual linkage photoisomerization in [Co(NH3)2NO2]2I3Cl single crystals
Authors: Kalinina Polina P. , Zakharov Boris A.
Published: September 2024

The reaction [Co(NH3)5NO2]2+ → [Co(NH3)5ONO]2+ proceeds under visible light for cations in certain crystallographic positions only in [Co(NH3)5NO2]2I3Cl, that suggests “crystallographic control” of reactivity within the same crystal structure.
Excitation wavelength-dependent fluorescence anisotropy of 3-hydroxyflavone: revisiting the solvation processes and high-energy state excitation in ESIPT-active compounds
Authors: Ushakou Dzmitryi , Józefowicz Marek
Published: September 2024

The fluorescence anisotropy of 3HF normal form changes abruptly with decreasing excitation wavelength. This phenomenon can be explained by breaking of solute–solvent hydrogen bonds and excitation of ESIPT-active fluorophores to high-energy states.
Synthesis, photo-physicochemical and biological properties of novel tetrahydropyrimidone-substituted metallo-phthalocyanines
Authors: Harmandar Kevser , Kaya Esra Nur , Tollu Gülşah , Sengul Ibrahim F. , Özdemir Sadin , Atilla Devrim
Published: September 2024

New Zn(ii) and Mg(ii) phthalocyanines having tetrahydropyrimidone units were synthesized and characterized to be antioxidant and antimicrobial agents.
Spiers Memorial Lecture: NMR crystallography
Authors: Emsley Lyndon
Published: September 2024

We present an overview of current methods for chemical shift driven NMR crystallography, illustrated with applications to complex materials.
Modular synthesis of unsymmetrical indolyl diketones from ynediones via sequential aza-Michael addition/C–H functionalization
Authors: Naveed Abdul , Bag Debojyoti , Sawant Sanghapal D.
Published: September 2024

Herein, we disclose an efficient approach for the synthesis of unsymmetrical indolyl diketones from easily accessible 1,2-alkynediones involving a sequential aza-Michael addition/C–H Functionalization process.
Substrate-dependent regiodivergence in [3 + 2] annulation reactions of 2-(phenacylethylidene)cyclobutanones with thioureas
Authors: Barranco Stefano , Pagnanini Alessio , Cuccu Federico , Caboni Pierluigi , Guillot Régis , Aitken David J. , Frongia Angelo
Published: September 2024

We report here a successful synthesis of previously unknown cyclobutane-fused imidazolidine-2-thione and thiazolidine-2-imine derivatives in good to high yields.
“I’m still here and I want them to know that”: experiences of chemists with concealable identities in undergraduate research
Authors: Boyd Evelyn A. , Lazar Kelly Best
Published: September 2024

Students with concealable identities, those which are not always visually apparent, must navigate the difficult choice of whether to reveal their concealed identities—a choice that has been found to impact an individual's psychological well-being. Research that gives voice to those with concealable identities is highly lacking, and subsequently, work that describes the experiences of undergraduate chemists participating in engaged learning opportunities is even more limited. This study utilizes a phenomenographic approach through the theoretical lens of Undergraduate Research Science Capital (URSC), to analyze the experiences of six students as they navigate undergraduate research experiences and the effect of their visible and concealable identities. Though all six students described similar levels of URSC, their experiences, especially as they relate to their concealable identities, help to construct a multi-faceted perspective of undergraduate chemists who engage in undergraduate research. These results highlight the need for multiple approaches to equity efforts to ensure that high-impact practices such as undergraduate research are accessible to all students.
Resource allocation scheduling scheme for task migration and offloading in 6G Cybertwin internet of vehicles based on DRL
Authors: Wei Rui , Qin Tuanfa , Huang Jinbao , Yang Ying , Ren Junyu , Yang Lei
Published: September 2024

As vehicular technology advances, intelligent vehicles generate numerous computation‐intensive tasks, challenging the computational resources of both the vehicles and the Internet of Vehicles (IoV). Traditional IoV struggles with fixed network structures and limited scalability, unable to meet the growing computational demands and next‐generation mobile communication technologies. In congested areas, near‐end Mobile Edge Computing (MEC) resources are often overtaxed, while far‐end MEC servers are underused, resulting in poor service quality. A novel network framework utilizing sixth‐generation mobile communication (6G) and digital twin technologies, combined with task migration, promises to alleviate these inefficiencies. To address these challenges, a task migration and re‐offloading model based on task attribute classification is introduced, employing a hybrid deep reinforcement learning (DRL) algorithm—Dueling Double Q Network DDPG (QDPG). This algorithm merges the strengths of the Deep Deterministic Policy Gradient (DDPG) and the Dueling Double Deep Q‐Network (D3QN), effectively handling continuous and discrete action domains to optimize task migration and re‐offloading in IoV. The inclusion of the Mini Batch K‐Means algorithm enhances learning efficiency and optimization in the DRL algorithm. Experimental results show that QDPG significantly boosts task efficiency and computational performance, providing a robust solution for resource allocation in IoV.
Design and analysis of DC to DC converter with PID controller for fast charging electrical vehicle application
Authors: Pranay M. , Pala Prasad Reddy M.
Published: September 2024

As a consequence of the exponential growth of the electric vehicle (EV) market, DC fast charging infrastructure is being rapidly deployed all around the world. Stations for ultra-fast charging (UFC) are beginning to seriously test the electrical grid. Installing local energy storage can solve these problems by guaranteeing a smoother grid power absorption profile and enabling the provision of grid-supporting features. In this paper, a grid-side AC/DC converter control strategy for next-generation EV UFC stations is developed. In this study, the performance of a 2kW Cuk converter running in Continuous Conduction Mode (CCM) and Discontinuous Inductor Conduction Mode (DICM) for Ultra-Fast Charging (UFC) of low voltage EV batteries with PID controller, similar to that seen in golf carts, is evaluated. Moreover, state-space modelling is done to build the output current controller for the Cuk converter working in DICM. The designs were simulated and verified using MATLAB/Simulink, and the results show that the size and the complexity of the controller can be reduced when the Cuk converter operates in DICM, meeting the requirements of international standards.
Energy Storage System Modelling For Hybrid Electric Vehicle
Authors: Mohammed G. , Srividya Devi P. , Durgadevi G. , Subramani R. , Husain Saif O.
Published: September 2024

The equivalent circuit model (ECM)-based traditional state-of-charge (SoC) estimate approaches combine all state variables into a single enhanced state vector. However, the stability and accuracy of the estimates are compromised by the correlations between RC voltages and SOC. In this article, the four battery chemistries have been discussed for their state variable characterization i.e. state of charge (SOC). The battery types considered are lead acid, nickel metal hydride, lithium ion. The manufacturer’s battery discharge curves are used to determine the model parameters, and a method is also described for doing this. An improved battery model is suggested in this study that can be applied to HEV design and analysis. By incorporating the electrical characteristics of the battery, the model generates precise results.
Enhanced Optimization Model for Inverter Short Circuit Prediction Using Machine Learning Techniques
Authors: Priyadarshini R. , Arul R. , Sharma Sumukh , Kadam Aum Sharad , Rawat Nikita , Bajaj Mohit
Published: September 2024

Short circuits are common faults that occur in inverters, which can lead to device damage, safety hazards, and downtime. Early detection of short circuits can help prevent these issues and improve the reliability of inverters. Suggest a machine learning method in this research approach short circuit prediction in inverters. Collected data from various sensors installed in the inverter system, such as voltage, current, and temperature sensors, and used this data to train several machine learning models, such as the Multilayer Perceptron (MLP), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). Also utilized artificial intelligence algorithms such as Firefly Algorithm (FA) to optimize the model parameters. One could assess the effectiveness of the models by measuring their performance using different metrics such as accuracy, specificity, and convergence curve, and found that our proposed approach achieved high accuracy and robustness in predicting short circuits. Our results demonstrate the potential of using machine learning and artificial intelligence techniques for early detection of short circuits in inverters, which can contribute to improved system reliability and safety.
Iot Gas Pipe Leakage Detector Using Solar Based Robot
Authors: Bezawada Pangedaiah , Naga Supriya T. , Venu Madhavi V. , Sai Durga Prasad K.
Published: September 2024

Gas pipeline leaks pose a significant safety hazard in various areas, requiring effective detection systems to mitigate them on time. This paper presents a novel solution that combines Internet of Things (IoT) technology with solar- powered robots equipped with cameras to detect gas pipe leaks, along with a microcontroller for sensor data processing and robotic monitoring of hazardous gases such as methane or LPG. Integrating gas comes with visible sensors, ensures continuous operation through solar panels, and facilitates seamless data transmission. It will adopt remote monitoring and real-time alerts using IoT systems that do not require external power sources. In addition, the addition of cameras allows for visual inspection of gas pipelines, allowing the system to detect leaks. The autonomous robot moves through the environment, examines gas lines, and sends information, including images, to a central server. This advanced approach enhances safety measures by enabling them to detect and respond to air leaks, effectively reducing potential hazards. The proposed system provides a practical, scalable, and environmentally friendly solution for gas pipeline cage detection in various environments.
Enhanced Performance of Hybrid Photovoltaic-Based Multilevel Inverters Using Pulse Width Modulation Techniques
Authors: Bhaskar Rajeev Kumar , Kumaraswamy Balasubramaniam
Published: September 2024

The fundamental purpose of this research is to develop a photovoltaic-based MLI that implements a pulse width modulation strategy as its mode of operation. Within the context of this specific illustration of a multilayer inverter, two switches are used so that the fundamental frequency and the carrier frequency may be switched. The first three sections of this article focus on analyzing and discussing the impact that varied levels of carrier signal have on inverters. Determine the effect that it has on the voltage, current, and harmonics distortion. This study will thoroughly examine the impact of changing the carrier signal level shift on hybrid PV-based MLIs as well as how multilayer PV-based inverters count harmonics. These two techniques boost voltage while sharply cutting losses. These two elements are both crucial to our investigation. Both of these subjects will be covered in-depth in this test. To study the voltage and current harmonics in a multilayer cascaded hybrid PV-based inverter, a level shift approach simulation is run using Matlab Software. This simulation is employed in order to fulfil the purpose.
Creation and Assessment of Herbal Gel with Guava Leaf Extract
Authors: Deepika K. , Sairoja A. , Jyothi P. Sri
Published: September 2024

Mouth ulcers, a common oral mucosal disorder, can cause discomfort and interfere with daily activities. Natural remedies like guava leaves extract have shown promising potential in managing such conditions due to their anti-inflammatory and antimicrobial properties. This study aimed to formulate and evaluate an aqueous gel of guava leaves extract for the treatment of mouth ulcers. The guava leaves extract was prepared using a maceration method and incorporated into a gelbase consisting of Carbopol 934P. Various formulations were prepared with different concentrations of guava leaves extract to optimize the formulation for maximum efficacy. The formulated gels were evaluated for their physicochemical properties, including pH, viscosity, spreadability, and drug content. The results indicated that the formulated aqueous gel exhibited desirable physicochemical properties, with optimal viscosity and spreadability for application on oral mucosa. The release studies demonstrated sustained release of active constituents from the gel matrix, ensuring prolonged therapeutic effect. Moreover, the optimized gel formulation showed significant antimicrobial activity against oral pathogens, suggesting its potential for managingmouth ulcers. In conclusion, the formulated aqueous gel of guava leaves extract holds promise as aneffective and natural treatment option for mouth ulcers.
Automated street light control and manhole monitoring with fault detection & reporting system for municipal department
Authors: Narasimharao Jonnadula , Fallah Mohammed H. , Joshi Ankita , Nagendrudu P.V.V.S.D. , Bindu V. Hima
Published: September 2024

This paper presents a novel, integrated system for smart city infrastructure management, combining automated street light control with real-time underground drainage monitoring. The system leverages GSM technology for data transmission and fault detection, offering significant benefits for municipal departments. Automated street light control utilizes light-dependent resistors (LDRs) for automatic activation and deactivation based on ambient light levels. This approach optimizes energy consumption, enhances public safety through consistent lighting, and reduces maintenance needs. Real-time underground drainage monitoring employs ultrasonic sensors within manholes to measure water levels. This enables proactive identification of potential blockages, minimizing the risk of flooding and associated public health hazards. Additionally, the system can monitor manhole lid status through sensors like magnetic reed switches, ensuring public safety and preventing theft. The system transmits data via the GSM network, enabling real-time monitoring and automated alerts for various scenarios. A central control center processes data and provides visualization tools, empowering informed decision-making for municipal authorities. This integrated approach fosters efficient resource allocation, improved infrastructure management, and enhanced public safety within the cityscape.
Theft intimation of the vehicle over SMS to owner who can stop the engine remotely
Authors: Pilomina P. S. , Harshavardhan K. P. , M Shamila , Laxmi V. Soma , Muhsen Muntadar
Published: September 2024

This paper addresses vehicle stealing with the help of alert SMS notifications and remotely controlling the engine. A microcontroller detects unauthorized access by any doubtful person and triggers a GSM modem to alert the owner’s phone by sending an SMS notification. This message would indicate potential stealing. In response, the actual owner could remotely transmit a specific SMS command back to the device, instructing it to stop the engine through a relay switch interrupting the ignition system. However, it’s crucial to acknowledge limitations. SMS transmission delays and potential for signal interference could hinder timely notification. Additionally, disabling a moving vehicle remotely introduces significant safety risks, potentially causing accidents or loss of control. While the concept offers theft intimation, a more secure and comprehensive approach integrating real-time tracking, GPS location services, and contacting authorities should be prioritized for actual implementation.
Enhanced Energy Management Strategy for Standalone Systems Integrating Fuel Cells, Batteries, and Supercapacitors
Authors: Mokrani Zahra , Oubelaid Adel , Rekioua Djamila , Rekioua Toufik , Avikal Shwetank , Bajaj Mohit
Published: September 2024

Hybrid systems combining fuel cells with battery and supercapacitor storage offer a promising solution for efficient and flexible energy management. Fuel cells, which convert chemical energy into electrical energy, provide a clean and sustainable power source but face challenges like slow response times and limited power density. Integrating batteries and supercapacitors addresses these issues: batteries offer high energy density and stable power supply over longer durations, while supercapacitors deliver rapid bursts of energy and quick charge-discharge cycles. Effective power management in hybrid fuel cell systems is crucial for maximizing efficiency, performance, and lifespan while ensuring reliable energy supply. The hybrid system consists of a PEM fuel cell, batteries, and a supercapacitor (SC) and introduces a power management strategy to ensure the supply of the load.
Battery management system life cycle estimation and degradation
Authors: Sridevi J. , Padmavathy R. , Ayswarya R. , Shnain Ammar Hameed , Abed Z. , Vivek V.
Published: September 2024

An essential component of using electric mobility is a battery management system (BMS), which is used to improve battery quality and guarantee safe operation. To avoid battery failure and minimise potentially dangerous situations, a monitoring system that ensures batteries function properly in the intended application is required. In terms of lifetime, the shelf storage time or calendar ageing discharge rate for primary cells is crucial because it determines how long you can keep the cell in storage before using it. For secondary or rechargeable cells, both calendar ageing and cycle ageing are of interest. The calendar ageing will show how the capacity deteriorates over time, even when the battery cell is not in use. The cycle ageing will show how many cycles the cell can produce at a particular charge and discharge rate. Before the capacity decreased to 80% of the initial Ah value when new, an energy cell would last for 1000 complete cycles and a power cell for 3000 complete cycles.
Life Cycle Assessment of Battery Energy Storage Technologies for Vehicular Applications
Authors: Sridevi J. , Ananthi S. , Gokilavani R. , Al-Farouni Mohammed , Ameer S. Abdul
Published: September 2024

The necessity of sustainable energy sources and storage technologies is emerging due to growing energy demands. Thus, it encourages the need to perform sustainability analysis in terms of energy efficiency. For battery technologies, energy production and recycling holds a significance. In this study, the direct and indirect requirements of various battery technologies including production to transportation . The five battery technologies taken into account for the analysis are Lithium ion , Nickel Metal Hydride , Lead acid , Valve Regulated lead Acid, and Nickel Cadmium . The characteristics analyzed here are cycle life, energy density and energy efficiency . The study also covers the life cycle assessment in an structured way from raw to evaluation of materials , energy flow, installation , usage to end of life.
Finite element analysis of internal combustion engine cylinder head
Authors: Joshi Abhishek , Vivek Kumar C. , Kavitha Rani B. , Hussain Muhamed , Suvonova L.
Published: September 2024

The cylinder head is a vital component of an internal combustion engine (ICE), playing a critical role in the combustion process, sealing the combustion chamber, and facilitating efficient heat dissipation. With the increasing demand for higher performance, efficiency, and durability of engines, the design and analysis of cylinder heads have become paramount. Finite Element Analysis (FEA) has emerged as a powerful tool for assessing the structural integrity, thermal behavior, and performance of cylinder heads under various operating conditions.This abstract presents a comprehensive review of recent advancements in FEA studies focused on ICE cylinder heads. The analysis encompasses aspects such as static and dynamic structural integrity, thermal stress distribution, and fluid-structure interaction within the combustion chamber. Various loading conditions including thermal loads from combustion, mechanical loads from valve actuation, and pressure loads from combustion gases are considered in the simulations.
Finite element analysis of composite leaf spring for automotive vehicle
Authors: Kotha Rajesh , Misra Neeti , Karthikeyan R. , Udayakumar R. , Hussain Muhamed
Published: September 2024

In the modern car industry, suspension setups and mass balance in heavy-duty trucks determine wear and tear. The truck’s key component is connected to the spring design in a semi-elliptical quadrilateral cross- section. Most of the suspension system is connected via a leaf spring and shackle bracket. The primary leaf spring assembly in the car, which dampens vibration across the whole vehicle, is linked to the shackle bracket. It is essential for minimizing losses in the car’s tires and body. The focus of this research’s suggested application is on car suspension and its constituent parts. In accordance with accepted design principles, the design is developed using the current dimensions. SOLID WORKS software is used to produce the 3D model, which is then loaded into FEA software (ANSYS) for structural parameter analysis with respect to various composite materials.
Investigation of electrochemical micro- machining process parameters on stainless steel 316 by sodium chloride electrolyte
Authors: Prabagaran S. , Dhandapani N. V. , Elukaturi Sammaiah , Karuna Gotlur , Fallah Mohammed H.
Published: September 2024

The exact and effective shaping of complicated geometries on a variety of materials, including Stainless Steel 316 (SS316), an alloy that is extensively utilized in the automotive, aerospace, and medical industries, is possible through the application of electrochemical micro-machining (ECMM). This study uses sodium chloride electrolyte to examine how process factors affect the ECMM of SS316. The literature study emphasizes how crucial process parameter optimization is to improving surface quality and machining efficiency in ECMM. The effects of voltage, electrolyte concentration, and machining time on surface roughness (Ra), material removal rate (MRR), and other machining properties have been well-explained by earlier research. The precise impacts of these parameters on SS316 machining with sodium chloride electrolyte still need to be investigated, though. The main ideas behind ECMM and the electrochemical behavior of SS316 in sodium chloride electrolyte are explained by the theoretical background. Researchers can create practical plans for managing machining settings and accomplishing desired machining results by comprehending the electrochemical reactions and material dissolving mechanisms. The experimental design and protocols used in this work are described in full in the methodology. We prepared and ran ECMM on SS316 specimens with various voltage levels, electrolyte concentrations, and machining times. In order to assess machining performance, MRR and surface roughness were evaluated. The data was analyzed using statistical analytic techniques in order to pinpoint important variables influencing the machining process.The experimental results and their implications for SS316 machining are presented in the results and discussion section. In order to achieve high machining efficiency and surface quality, the best parameter combinations are found by analyzing the effects of voltage, electrolyte concentration, and machining time on MRR and surface roughness. Furthermore, the impact of additional variables on machining performance is examined, including the geometry of the tool and the substance of the electrode. The study’s main conclusions are outlined in the conclusion, along with suggestions for more research. By offering insightful information about the ECMM process parameters for SS316 machining with sodium chloride electrolyte, the study advances machining technology in sectors where SS316 components are often used.
Mechanical and microstructural characteristics of additive manufactured material under room and elevated temperatures
Authors: Prabagaran S. , Dhandapani N. V. , Potharaju Raju , Hassan Muntather M. , Lalitha Y. Sri
Published: September 2024

Significant advancements in the process of producing information and space have been made possible by the application of additive manufacturing (AM). Geometric patterns and unique designs. This study’s primary goal is to Section the impacts of temperatures ranging from room temperature to high temperature are reflected in the microstructure and attributes of items manufactured using Additive Manufacturing Technology. Microstructural examination can be done in a variety of ways, such as optical and scanning electron microscopy. Section: Grain sample evaluation using X-ray diffraction (XRD) and scanning electron microscopy (SEM) Phase composition and porosity. Measure mechanical attributes including hardness, fracture toughness, and tensile strength using accepted measurement methods. Temperature measurement techniques, such as Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC), are used to control temperature and change phase. This study investigates the effects of different printing parameters, including design direction, printing speed, and layer thickness. Characteristics and microstructure. Eliminating the gap between theory and practice is the goal of this study. Recognize and implement Section to encourage the application of additive manufacturing for companies that require increased performance in several areas, this is perfect.
Process parameters and tool geometry in machining of ss316 material using ECM
Authors: Kalidas N. , Goshteeswaran S. , Muhamed Hayidr , Polepaka Sanjeeva , Babu Pidaparthy Mahesh
Published: September 2024

Electrochemical Machining (ECM), an unusual machining method, seems to be a promising approach in the automotive and other industrial industries. According to current trends, industries including biotechnology, electronics, optics, medicine, and others have seen a massive increase in demand for stainless steel micro goods and components. Because it is corrosion-resistant and easily sterilizable, this stainless-steel material is perfect for a sanitary setting. This study examined the experimental process parameters of ECM for SS material. The SS 316 alloy has made the decision to alter the electrochemical machining procedure using various electrodes and to investigate the process parameters using scanning electron microscopy (SEM) analysis. To investigate the improved quality of ECM process parameters, several tool materials have been used.
Effect of pollution to man and his environment
Authors: Vijayshankar G. R. , Dhivya K. , Pradeep B. , Hussain Muhamed , Buddi Tanya
Published: September 2024

Numerous environmental toxins have a significant effect on both individual and public health, increasing rates of morbidity and death while also contributing to climate change and human illness. Due to the lack of data on exposure to pollution from undeveloped nations with poor waste management, high poverty rates and a delayed adoption of modern technologies, more research is necessary to fully understand the relationship between pollutants and health effects. Similar circumstances exist in many industrialised nations, where the need for precautions has diminished and remedies are found only after damage has already been done. Given the challenges associated with measuring exposure levels and the absence of systematic monitoring, a deeper knowledge of the connection between pollutants in the environment and health is necessary. Pollutants can have negative impacts on soil, water, plants, and animals in addition to their effects on human health. This paper will address the many forms of pollution, their detrimental effects on natural ecosystems, and the disturbing effects they have on all living things. A thorough debate is also provided.
Analyses of the Power Flow through Distributed Generator based on Unsynchronized Measurements
Authors: Almoussawi Zainab Abed , Raju V. Vijaya Rama , Venkatasubramanian R. , R. Hariharan , Mundher Adnan Myasar
Published: September 2024

Based on measurements taken from the main substation and the connections between distributed generators and micro-grids that are not in sync, this study suggests a new way to look at the load flow of distributed generation. The conclusions are based on data from a distribution generator’s Load Flow Analysis that was not in sync. Distributed generation is what this approach is based on. Creating a strong communication system and using measurement data from the past are two ways to make this happen. This objective may be achieved with the use of previously gathered measurements. The time-tested backward-forward sweep method is the method of choice for analyzing power flow using unsynchronized data. This is the preferred approach. The angles of synchronization are likely to be unknowns that must be estimated. On a smart grid system with a large number of distributed generation and microgrids, a range of mathematical computations are conducted to verify the correctness of performance predictions produced by the suggested theory. The classic backward-forward sweep was shown to be the most effective method for analyzing power flow based on data that was not synchronized in many instances. This is the strategy that is presently being recommended. Because the angles of synchronization are presumed to be unknown, a mathematical equation must be devised to determine them.
Smart Solutions for Safer Water: Integrating Machine Learning into the Inspection and Optimization of Treatment Facilities
Authors: Niederländer Marie , Biswas Rajarshi , Mutz Marcel , Limbachiya Dhavalkumar , Werth Dirk
Published: September 2024

Ensuring the effective treatment of wastewater is essential for the safety of people and the environment, as the discharge of contaminated water into natural waters has disastrous consequences. In Germany and other European countries, the number of trained professionals in the field of wastewater treatment plant (WWTP) operation is constantly decreasing, which is why the optimization and inspection of WWTPs is a relevant field for the application of innovative approaches such as artificial intelligence and machine learning. This study provides an overview of the current progress in the application of machine learning from different perspectives relevant to WWTPs and other critical infrastructure. The perspectives include critical infrastructure monitoring, optimization of treatment processes, monitoring of water bodies and WWTP inspection. In addition, a concept for an automated, AI-based remote inspection system for rural WWTPs using a cloud edge approach and intelligent camera systems is presented for performing daily plant inspection tasks and detection of critical events.
Assessing the Feasibility of Waste-to-Energy Projects for Sustainable Solid Waste Management in the National Capital Region, Philippines
Authors: De La Cruz Arvin , Bernal Carlo
Published: September 2024

The study assesses the feasibility of Waste-to-Energy (WTE) projects as an alternative to traditional landfilling for solid waste management in the National Capital Region (NCR) of the Philippines. Waste analysis from 11 NCR cities reveals an average processing fee of 1,610.00 Pesos per ton for WTE, three times higher than landfilling costs. Despite this cost disparity, implementing WTE projects could offer significant land savings, crucial in densely populated areas like the NCR. Preliminary designs of WTE power plants provide estimates for construction and operational expenses, aiding in cost-benefit analyses. The findings highlight the urgent need to address the economic challenges associated with WTE, possibly through policy interventions such as subsidies or incentives. This study provides valuable insights for policymakers, emphasizing the potential of WTE projects in addressing solid waste management issues in urban areas. However, overcoming the cost disparity between WTE and landfilling remains a critical barrier to widespread adoption. Future efforts should focus on developing strategies to make WTE economically competitive while leveraging its potential benefits in land conservation and sustainable energy production.
Greenhouse Gases Emissions and Factors Influencing Sustainable Solid Waste Management Based on The Circular Economy Indicators: The City Case in Thailand
Authors: Dubsok Atima , Limphitakphong Nantamol , Sugsaisakon Sittisak , Kittipongvises Suthirat
Published: September 2024

Climate change is currently recognized as one of the most sustainability challenges of our era. Accelerated actions to mitigate greenhouse gas (GHG) emissions are urgently needed in all sectors, including the waste sector. This study aimed to qualify GHG emissions from waste management in one of high-income cities in Thailand and to evaluate factors influencing effective solid waste management based on the Analytic Hierarchy Process (AHP) for weighting the modified OECD inventory of circular economy indicators. By employing the IPCC default method and the Global Protocol for Community-Scale Greenhouse Gas Emissions, the key findings showed that municipal landfill located in the case city emitted the largest share of total emissions in the waste sector between 2018 and 2022 (445,112 – 501,761 tCO2e/year, 0.21-0.24 tCO2e/capita/year of emission intensity). Meanwhile, biological treatment of municipal solid waste (composting) emitted only 24,240.45 tCO2e/year (506.33 tCH4/year and 37.97 N2O/year). Besides, the AHP analysis revealed that governance factors (i.e., awareness raising, stakeholder engagement) had the highest AHP score (0.3717), followed by environmental benefits (i.e., emission reduction) (0.3542), infrastructure and technology (0.1754), respectively. Interestingly, economic aspects and job creation represented the lowest AHP score (0.0475 – 0.0512). Overall, co-benefits of GHG mitigation and sustainable municipal solid waste (i.e. environmental and socio-economic aspects), stakeholder partnership and good governance in municipal solid waste management should be holistic integrated in strategic planning at city level.
Environmental and Climate Impacts Associated with Refuse Derived Fuel (RDF) Production: A Case Study in Thailand
Authors: Dubsok Atima , Niyommaneerat Wilailuk , Suphasomboon Tawalhathai , Sugsaisakon Sittisak , Kittipongvises Suthirat
Published: September 2024

Improper waste management poses considerable risks to both the environment and human health. Despite Refuse Derived Fuel (RDF) is one of promising alternative technologies of waste management, however, it is necessary to gain insight into all environmental impacts of RDF as alternative fuel. This study, therefore, aimed to investigate potential environmental footprints and climate change related impacts from a case study of RDF power plant in Thailand. By employing the life cycle assessment (LCA) concept, gate-to-gate approach was selected as a study boundary. Functional unit was defined as “1MWh of electricity generation”. IMPACT2002+, Greenhouse Gas Protocol and IPCC2013 methods were chosen to determine life cycle potential environmental impacts and carbon- based emission. The key findings revealed that resources impact showed the highest environmental footprint, followed by climate change, human health, and ecosystem quality categories, respectively. Electricity consumption was considered the most important environmental burden associated with the RDF production (1.66 mPt). By considering the climate change impacts, the results shown that electricity-consumed in the RDF generation emitted the largest share of greenhouse gas emissions (6.81 kgCO2e), compared to diesel and natural gas utilizations. Overall, proper management efforts to minimize all negative environmental and climate impacts are necessary in the RDF electricity operation.
Training on making painting works for arts and culture teachers
Authors: Taswadi
Published: September 2024

The rapid progress of computer and internet technology has had a big influence on the implementation of learning in schools, so that educators can be sure that every time they teach they will definitely use Power Point media. The negative impact of using Power Point media is that educators forget about other types of learning media. However, when studying, students need a variety of media. No matter how sophisticated Power Point is, it cannot present a real, original form in the classroom. In fact, when learning, students’ memory will be stronger if stu-dents’ learning is proven with concrete evidence. The impact of the habit of using PowerPoint on teachers is that they increasingly forget to create original media. To remind people of the importance of original media and upgrade their skills in making them, researchers conducted painting-making training for 20 Arts and Culture teachers in Bandung. The results of the training are works of painting, which can be used by teachers as learning media in schools.
Vocational teacher training in the utilisation of barcode scanner technology as cultural arts learning media in Bandung
Authors: Falah Kholik Muslim , Nugraheni Trianti , Sunaryo Ayo , Pratiwi Selvi Rahmadani
Published: September 2024

The utilization of technology in education is very important to improve the quality of learning. This article discusses training for SMK teachers in Bandung in the use of barcode scanners as a medium for cultural arts learning. Using a qualitative approach and descriptive analysis, data were obtained through observation, interviews and documentation. The workshop was attended by 16 teachers and showed high enthusiasm and increased competence in integrating this technology into teaching. Although the limited infrastructure and short duration of the training were obstacles, the results showed the potential of barcode technology to improve student interaction and engagement. Recommendations include continuous training, infrastructure improvement, and evaluation of technology-based materials.