bluuebunny/crossref_metadata_2025 huggingface dataset:
Increased Frequency but Decreased Intensity of Marine Heatwaves Around Coral Reef Regions in the Southern South China Sea
Authors: Lyu Yushan , Xiao Fuan , Lu Mengqian , Wang Dongxiao , Wu Qiaoyan , Wang Pin , Zeng Yinghai
Published: September 2024

Marine heatwaves (MHWs) in the South China Sea (SCS) significantly affect both fishery resources and marine ecosystems. The characteristics and causal mechanisms of MHWs occurring in the southern SCS (SSCS) are not yet fully understood. In this study, the properties of MHWs, their long‐term trends, and how these compare to those in the coastal shelf region in the northern SCS were explored. It was revealed that the coral reef regions in the SSCS exhibit more frequent but less intense MHWs. Over the past four decades, the average frequency, duration, and total days of MHWs have increased and could be attributed to rising mean sea surface temperature (SST), primarily driven by the horizontal advection, particularly the zonal advection. The associated advections result from the long‐term wind stress curl change in the SSCS and strengthened Kuroshio Current, which are due to global warming‐induced enhanced vertical density stratification and wind speed acceleration. Furthermore, significant decrease in the MHW intensity around coral reef regions is mainly due to a negative SST–cloud feedback mechanism: during MHW events, enhanced latent heat loss intensifies convection, leading to total cloud formation, which in turn reduces solar radiation and subsequently decreases the MHW intensity. Interestingly, this increase in deep convection and decrease in the MHW intensity appear to coincide with the phase transition of the Interdecadal Pacific Oscillation. Our findings underscore the divergent trends in MHW properties in the SSCS, providing valuable insights into their potential impact on the region’s coral reefs.
Osteopontin deficiency promotes cartilaginous endplate degeneration by enhancing the NF-κB signaling to recruit macrophages and activate the NLRP3 inflammasome
Authors: Wang Yanqiu , Zhang Wanqian , Yang Yi , Qin Jinghao , Wang Ruoyu , Wang Shuai , Fu Wenjuan , Niu Qin , Wang Yanxia , Li Changqing , Li Hongli , Zhou Yue , Liu Minghan
Published: September 2024

Intervertebral disc degeneration (IDD) is a major cause of discogenic pain, and is attributed to the dysfunction of nucleus pulposus, annulus fibrosus, and cartilaginous endplate (CEP). Osteopontin (OPN), a glycoprotein, is highly expressed in the CEP. However, little is known on how OPN regulates CEP homeostasis and degeneration, contributing to the pathogenesis of IDD. Here, we investigate the roles of OPN in CEP degeneration in a mouse IDD model induced by lumbar spine instability and its impact on the degeneration of endplate chondrocytes (EPCs) under pathological conditions. OPN is mainly expressed in the CEP and decreases with degeneration in mice and human patients with severe IDD. Conditional Spp1 knockout in EPCs of adult mice enhances age-related CEP degeneration and accelerates CEP remodeling during IDD. Mechanistically, OPN deficiency increases CCL2 and CCL5 production in EPCs to recruit macrophages and enhances the activation of NLRP3 inflammasome and NF-κB signaling by facilitating assembly of IRAK1-TRAF6 complex, deteriorating CEP degeneration in a spatiotemporal pattern. More importantly, pharmacological inhibition of the NF-κB/NLRP3 axis attenuates CEP degeneration in OPN-deficient IDD mice. Overall, this study highlights the importance of OPN in maintaining CEP and disc homeostasis, and proposes a promising therapeutic strategy for IDD by targeting the NF-κB/NLRP3 axis.
Continuous-time robust frequency regulation in isolated microgrids with decentralized fixed structure μ-synthesis and comparative analysis with PID and FOPID controllers
Authors: Mohammed Abdallah , Kadry Ahmed , Abo-Adma Maged , Samahy Adel El , Elazab Rasha
Published: September 2024

Isolated microgrids, which are crucial for supplying electricity to remote areas using local energy sources, have garnered increased attention due to the escalating integration of renewable energy sources in modern microgrids. This integration poses technical challenges, notably in mitigating frequency deviations caused by non-dispatchable renewables, which threaten overall system stability. Therefore, this paper introduces decentralized fixed structure robust μ-synthesis controllers for continuous-time applications, surpassing the limitations of conventional centralized controllers. Motivated by the increasing importance of microgrids, this work contributes to the vital area of frequency regulation. The research challenge involves developing a controller that not only addresses the identified technical issues but also surpasses the limitations of conventional centralized controllers. In contrast to their centralized counterparts, the proposed decentralized controllers prove more reliable, demonstrating enhanced disturbance rejection capabilities amidst substantial uncertainties, represented through normalized co-prime factorization. The proposed controllers are designed using the D-K iteration technique, incorporating performance weight filters on control actions to maintain low control sensitivity and ensure specific frequency band operation for each sub-system. Importantly, the design considers unstructured uncertainty up to 40%, addressing real-world uncertainties comprehensively. Rigorous robust stability and performance tests underscore the controller's superiority, demonstrating its robustness against elevated uncertainty levels. Robust stability is verified for all controllers, with the proposed controller showing robust stability against up to 171% of the modeled uncertainty. Notably, the controller boasts a fixed structure with lower order compared to other H-infinity controllers, enhancing its practical implementation. Comparative analyses against Coronavirus Herd Immunity Optimizer tuned Proportional-Integral-Derivative (CHIO-PID) controller and CHIO tuned Fractional-Order Proportional-Integral-Derivative (CHIO-FOPID) controller further validate the superior performance of the proposed solution, offering a significant step towards ensuring the stability and reliability of microgrid systems in the face of evolving energy landscapes.
Fluid bolus increases plasma hyaluronan concentration compared to follow-up strategy without a bolus in oliguric intensive care unit patients
Authors: Serlo Maija , Inkinen Nina , Lakkisto Päivi , Valkonen Miia , Pulkkinen Anni , Selander Tuomas , Pettilä Ville , Vaara Suvi T.
Published: September 2024

Fluid therapy is a fundamental part of supportive therapy in critical care. However, it is also a suspected risk for endothelial glycocalyx degradation which is associated with poor clinical outcomes. This secondary analysis of RESPONSE randomized trial compares the effect of follow-up strategy (FU) on endothelial biomarkers to that of 500 ml crystalloid fluid bolus (FB) in oliguric, hemodynamically optimized intensive care unit (ICU) patients. 130 adult subjects were enrolled in two Finnish ICUs from January 2017 to November 2020. Blood and urine samples of 63 patients in FU group and 67 patients in FB group were collected before and after the intervention and analyzed using enzyme-linked immunosorbent assays. Single fluid bolus, given after median of 3887 ml (interquartile range 2842; 5359 ml) resuscitation fluids in the preceding 24 h, increased plasma hyaluronan concentration compared to the follow-up strategy (difference in medians 29.2 ng/ml with 95% CI [14.5ng/ml; 55.5ng/ml], P < 0.001). No treatment effect was detected in the plasma levels of syndecan-1, , angiopoietin-2, angiopoietin receptors Tie2 and Tie1, or in soluble thrombomodulin in the adjusted median regression analysis. The increase in hyaluronan was independent of its simultaneous renal clearance but correlated moderately with the increase in endothelium-specific Tie1. The follow-up strategy did not show consistent endothelium-sparing effect but protected against hyaluronan increase. The mechanisms and consequences of hyaluronan fluctuations need further clarification. Trial registration: clinicaltrials.gov, NCT02860572. Registered 1 August 2016, https://www.clinicaltrials.gov/study/NCT02860572?term=NCT02860572&rank=1
Histamine synthesis and transport are coupled in axon terminals via a dual quality control system
Authors: Peng Lei , Wang Tao
Published: September 2024

Monoamine neurotransmitters generated by de novo synthesis are rapidly transported and stored into synaptic vesicles at axon terminals. This transport is essential both for sustaining synaptic transmission and for limiting the toxic effects of monoamines. Here, synthesis of the monoamine histamine by histidine decarboxylase (HDC) and subsequent loading of histamine into synaptic vesicles are shown to be physically and functionally coupled within Drosophila photoreceptor terminals. This process requires HDC anchoring to synaptic vesicles via interactions with N-ethylmaleimide-sensitive fusion protein 1 (NSF1). Disassociating HDC from synaptic vesicles disrupts visual synaptic transmission and causes somatic accumulation of histamine, which leads to retinal degeneration. We further identified a proteasome degradation system mediated by the E3 ubiquitin ligase, purity of essence (POE), which clears mislocalized HDC from the soma, thus eliminating the cytotoxic effects of histamine. Taken together, our results reveal a dual mechanism for translocation and degradation of HDC that ensures restriction of histamine synthesis to axonal terminals and at the same time rapid loading into synaptic vesicles. This is crucial for sustaining neurotransmission and protecting against cytotoxic monoamines.
C–H amination chemistry mediated by trinuclear Cu(i) sites supported by a ligand scaffold featuring an arene platform and tetramethylguanidinyl residues
Authors: Sharma Meenakshi , Fritz Reece M. , Bhatia Himanshu , Adebanjo Joseph O. , Lu Zhou , Omary Mohammad A. , Cundari Thomas R. , Choudhury Amitava , Stavropoulos Pericles
Published: September 2024

A crown-shaped Cu3Cl3 fragment captured by a ligand that features tetramethylguanidinyl residues and an apically oriented arene platform gives rise to a potent benzylic and tert-C–H bond amination catalyst via a computed dicopper nitrene oxidant.
Bioactive Ag(i) coordination complexes as dopants for castor oil plasticized ethylcellulose films
Authors: Scarpelli Francesca , Crispini Alessandra , Aiello Iolinda , Godbert Nicolas , Marchetti Fabio , Xhafa Sonila , De Filpo Giovanni , Baratta Mariafrancesca , Berardi Riccardo , Alfano Pasquale , Giorno Eugenia
Published: September 2024

New ethylcellulose films doped with bioactive Ag(i) complexes and a natural plasticizer are prepared and characterized. Their antibacterial activity makes them potential active food packaging materials.
Structural dynamics and optimal transport of an active polymer
Authors: Khalilian Hamidreza , Peruani Fernando , Sarabadani Jalal
Published: September 2024

The present study shows that the transport properties of active polymers are intrinsically coupled with the polymer configuration dynamics and unveils the existence of an optimal self-propelling force that maximizes the active polymers diffusivity.
Racial and Ethnic Disparities in Speech-Language Pathology Utilization for Patients With Oropharyngeal Dysphagia in Acute Care
Authors: Mormer Elizabeth , Terhorst Lauren , Coyle James , Freburger Janet
Published: September 2024

Purpose:

Disparities in health care utilization are modifiable drivers of disparities in health outcomes but have not been explored regarding speech-language pathology utilization for patients with dysphagia. This study explores racial and ethnic disparities in the utilization of speech-language pathology services among adult patients diagnosed with oropharyngeal dysphagia during acute care hospitalizations.

Method:

We analyzed New York State Inpatient Data on acute care hospitalizations in 2019. We identified adults with a diagnosis of oropharyngeal dysphagia and determined whether they received speech-language pathology services via revenue center codes, which indicate receipt of a speech-language pathology evaluation or treatment. Using generalized estimating equations, we estimated the effect of race/ethnicity (White, Black, Hispanic, and Other race) on speech-language pathology utilization (yes, no) during the acute care hospitalization, controlling for patient clinical characteristics (e.g., acute diagnoses and clinical comorbidities), demographic characteristics (e.g., insurance status, rural–urban status), and health system factors (e.g., hospital size). Subgroup analyses were conducted for select primary diagnoses (i.e., stroke, sepsis, and aspiration pneumonia).

Results:

We identified 56,198 individuals with a diagnosis of oropharyngeal dysphagia; 60.7% received speech-language pathology services. In the full sample analysis, the adjusted odds of speech-language pathology utilization were lower in Black relative to White individuals (odds ratio [
OR
] = 0.87 [0.76, 0.98],
p
= .026). Racial and ethnic disparities were present in the subgroup analyses, most notably for sepsis, where speech-language pathology utilization was significantly lower for Black, Hispanic, and Other race individuals (
OR
s from 0.61 to 0.77) relative to White individuals.

Conclusions:

We found evidence of racial and ethnic disparities in the utilization of speech-language pathology services for patients with oropharyngeal dysphagia in the acute care setting that varied by primary diagnosis. Further research is needed to replicate these findings and to begin to understand the reasons behind these disparities.

Supplemental Material:

https://doi.org/10.23641/asha.26791741
Autonomous Energy Management Strategy in the Intermediate Circuit of an Electric Hybrid Drive with a Supercapacitor
Authors: Vacarda Milan
Published: September 2024

Hybrid electric vehicles (HEVs) require the design of an energy management strategy (EMS). Many EMS are solved using different types of deterministic rules (rule‐based (RB)) or optimization‐based (OB) methods. The disadvantage of these strategies is that the primary energy flows in the drive are only solved “ex post,” when in principle, they cannot bring a substantial increase in energy recovery. A little‐studied HEV traction drive topology is an internal combustion engine (ICE), supercapacitor (SC), traction motor (TM), and electric power divider (EPS) assembly. The original EMS method implemented in this assembly is based on the control of energy flows at the physical level in the DC link node. Changes in the power of the TM, under the condition of zero summation of currents in the DC link, will spontaneously induce energy spillover from and to the supercapacitor. The state of energy (SOE) in the supercapacitor can then be maintained by the balanced power of the ICE. This makes it possible to achieve a reduction in accelerations of approximately 30%. In principle, the presented EMS makes it possible to absorb all the kinetic and potential energy of negative driving resistances, thereby significantly reducing vehicle consumption. The strategy does not even require knowledge of the driving profile and bypasses complicated optimization algorithms. When validating the EMS method on an experimental test bench by implementing the driving cycle into real prototype components of the HEV physical model, a recovery rate of 14% was achieved, but the potential is up to twice that.
Finite‐time H∞${{H}_\infty }$ fault detection for large‐scale power system via Markov jumping mechanism
Authors: Wang Xunting , Xu Bin , Ding Jinjin , Ren Chengcheng , Zhang Qian
Published: September 2024

This paper investigates the finite‐time fault detection problem for large‐scale power systems via the Markov jumping mechanism subject to unknown disturbances. The novel power system is described by a large‐scale system model, and the residual dynamic properties of unknown input signals and fault signals, including unknown disturbances and modelling errors, are obtained by reconstructing the system. Then, the energy norm indicators of the residual disturbance signal and fault signal are, respectively, selected to reflect their suppression effect on disturbance and sensitivity to faults. Moreover, the design of a fault detection observer is formulated as an optimisation problem. Based on Lyapunov theory and linear matrix inequalities (LMI), sufficient conditions for the designed fault detection observer solutions are given, and an optimisation design method is provided. Finally, the simulation results show that the optimised observer can detect the fault signal effectively and can contain the effect of unknown disturbances on the residuals within a given range when a fault occurs.
Multi‐image encryption and authentication using computational ghost imaging and singular value decomposition
Authors: Huang Hong , Han ZhiGuang
Published: September 2024

The non‐local imaging characteristics of computational ghost imaging (CGI) make it widely used in the field of information security. However, the information processing method based on traditional CGI has some problems in the process of multi‐image encryption, such as low efficiency and unsatisfactory reconstruction quality. Therefore, this article proposes to use wavelet transform and singular value decomposition technology to help computational ghost imaging to efficiently complete the coding and encryption of multiple images, and use alternating direction multiplier method (ADMM) in the process of image restoration to carry out high‐quality reconstruction of the original encrypted image. The results show that the scheme has good reconstruction effect, strong security and robustness even at a low sampling rate. It provides some reference for digital watermarking technology and cryptography.
Matched cross‐spectrum phase processing for source depth estimation in deep water
Authors: Zhou Lisheng , Yang Xiaohong , Zheng Guangying , Zhu Fangwei , Wang Fangyong
Published: September 2024

Zhou et al. (2022) proposed a method for instantaneous source depth estimation in deep water using matched beam intensity processing (MBIP) that leverages depth‐related oscillatory features arising from Lloyd's mirror interference in the frequency domain (Appl. Acoust., 2022, 186, 108493). However, the efficacy of MBIP diminishes with a random source spectrum. To counteract the effect of a random source spectrum, a vertical line array (VLA) positioned near the sea bottom is employed and a cross‐spectrum is generated from the conventional beamforming output, which is achieved by dividing the VLA into upper‐half and lower‐half arrays. The authors find that the cross‐spectrum phase interference pattern is determined by the source depth and is unaffected by the source spectrum. Consequently, a matched cross‐spectrum phase processing method is proposed, which demonstrates appreciable depth estimation accuracy compared to that of the existing techniques, as evidenced by the results from both simulated and experimental data.
Leveraging Renewable Energy Solutions to Enhance Language Acquisition in English Classrooms
Authors: Shaik Iliyas Ali , Begum B. Rasheeda , Athahar Sameena , Hussain S. Ansar
Published: September 2024

The integration of renewable energy solutions in educational settings can change traditional teaching methods and enhance learning outcomes. This paper examines the creative usage of renewable energy technologies aimed at creating sustainable environments that are conducive to learning and facilitate English language acquisition in classrooms. By looking into case studies and empirical data, this study shows how renewable energy sources like solar energy or wind power may be utilized as a support for digital learning tools such as interactive language software and as a reliable power source for rural and disadvantaged schools. The study found significant increases in student engagement, language skills, overall student performance, stressing the role of sustainable power supply in modern education systems.
Machine Learning Models for Predicting and Managing Electric Vehicle Load in Smart Grids
Authors: Manoj Vasupalli , Ramasekhara Reddy M. , Nooka Raju G. , Raghutu Ramakrishna , Mohanarao P.A. , Swathi Aakula
Published: September 2024

The integration of electric vehicles (EVs) into smart grids provides major issues and prospects for effective energy management. This research examines the actual utilization of machine learning models to forecast and manage EV demand in smart grids, intended to increase grid effectiveness and dependable operation. We acquire and preprocess different datasets, considering elements such as time of usage, characteristics of the environment, and user behaviors. Multiple machine learning models, combining neural networks, support vector machines, and forests that are random, are developed and rated for their projected accuracy. Our results imply that enhanced prediction algorithms may considerably raise all the level of detail of EV load forecasts. Furthermore, we recommend load management systems based on real-time forecasts to enhance energy distribution and lower peak demand. This study presents a potential of machine learning that would promote the integration of EVs into smart grids, that tie in to more capable and efficient energy systems.
TIDF Controller for Optimal Performance of the Automatic Voltage Regulator
Authors: Naga Sai Kalyan Ch. , Bajaj Mohit , Prasad Brijesh
Published: September 2024

This work mainly focused on the development of the controller for performing the automatic voltage regulation (AVR) action in the most optimal way. In this regard, the tilt-integral-derivative-filter (TIDF) controller is suggested in this work. Moreover, the controller TIDF requires soft computing methodologies for its optimal functioning, and hence the donkey and smuggler optimization algorithm (DSOA) is conceived. However, the efficacy of the TIDF is demonstrated with the other controllers that emerged from the background of intelligence and fractional calculus. Further, the dominance of DSOA is also established with other soft computing techniques. The optimization of TIDF using DSOA is performed under the integral square error (ISE) index, and a comparative analysis is made among the several time domain indices to establish its dominance. Finally, the simulation analysis revealed the overall efficacy of the DSOA-tuned TIDF controller under the ISE criteria and confirmed the optimal AVR performance.
Resilient Operation of PV Systems in Weak Grids by adjusting of Flexible Grid Conditions through Artificial Neural Networks (ANNs) to Improve Power Quality
Authors: Madhuri Mora , Gatla Ranjith Kumar
Published: September 2024

The solar Photovoltaic Array (PVA) producing unit reported in this study is conducted to an inadequate utility grid for distribution. A boost converter using the incremental conductance (InC) approach optimizes PVA power. The weak grid can be affected by distortions, imbalances, voltage sags, and voltage swells. Grid Voltage Filtering (GVF) is a stage in the control system that prevents errors in the grid voltage that might affect the controlled grid current. Furthermore, any DC offset in the voltage signal is neutralized by the GVF. When operating under poor grid conditions, the DC link voltage is flexible-regulated to prevent excessive modulation. Grid power quality is maintained by flexible regulation, even in severe instances of voltage imbalance. Variations in PVA power, load currents, and grid voltages can all be tolerated by the system. Accurate measurement of load current weights can help avoid DC link voltage discrepancies during load swings.
Evaluation Of the Functionality of Germanium Arsenide Solar Cells at Multiple Sites Following Distinction In Irradiation
Authors: Al-Farouni Mohammed , Ramadan Ghazi Mohamad , Bobba Phaneendra babu , Saritha G. , Rajasekar Arockia , Senthil Kumar R.
Published: September 2024

The efficiency of a GaAs solar cell was 24.3 percent, which at the time was the best of any single-junction solar cell. This paper shows the variation of output power when subjected to a variety of irradiation at different locations in India When compared to the previous record efficiency of 24.3%, set by direct deposition of the III-V semiconductor layer on silicon, the efficiency of wafer-bonded silicon-on-gas-silicon (S-S) cells has increased to 34.1%. The maximum power per unit area (Pm) and open circuit voltage (Voc) of GaAs/Ge solar cells are also temperature dependent. Thin film cells are now more adaptable and less voluminous as a result. This semi-transparent solar glazing material is laminated onto windows in building-integrated photovoltaic systems. Because solar panels cannot work in these conditions, realistic solar arrays will produce less power per unit area. To make matters worse, we don’t account for losses caused by shadowing from electrical connections or the close proximity of solar cells on panels.
Scrutinization of Solar Thermal Energy On Heat and Mass Transfer Within a Micropolar Flow Over a Stretching Surface, Featuring Bioconvective Heat Generation and Chemical Reaction
Authors: Adegbite P. , Avikal Shwetank , Bajaj Mohit , Ajala O. A. , Obalalu A. M , Abdul-Yekeen A. M.
Published: September 2024

Enhancing heat and mass transfer efficiency is crucial for reducing energy consumption and mitigating environmental impact in various industries, including power generation, electronics cooling, and chemical processing. This study explores the impact of solar radiation, bioconvection, micropolar fluid properties, and nanoparticle and chemical reactions on a stretching surface. The research uses mathematical modeling and analysis to solve the 2-dimentional laminar bioconvection boundary layer flow of micropolar based nanofluids. The study concludes that bioconvection significantly enhances heat transfer and fluid flow characteristics, with heat generation and chemical reactions playing a crucial role. The thermophysical properties of the fluid, bioconvection parameters, and chemical reaction rates also have a significant impact on flow and heat transfer characteristics. The analysis reveals that increased heat generation leads to increased temperature, while chemical reactions decrease concentration flow. Unsteadiness parameters also impact velocity, energy, concentration, and microorganism. The findings can provide valuable insights for researchers and engineers in designing and optimizing heat transfer systems involving micropolar nanofluids with bioconvection, heat generation, and chemical reactions.
Enhancing Heap-Based Optimizer for Better Dispatching of Combined Heat and Power Units
Authors: Jaleel Uruj , Lalmawipuii R.
Published: September 2024

The present state of the energy industry has led to increased energy prices and restrictions on the use of fossil fuels as a source of energy. As a result, combined heat and power units evolve more quickly than they would in the existing systems. An actual optimization problem with several intricate constraints is the best way to dispatch CGUs. This study therefore proposes an enhanced heap-based optimizer approach that strikes a healthy balance between the beginning and end phases of global search and convergence, respectively, in order to address the optimal dispatch problem. This problem provides the optimal scheduling for heat and power producing units while considering their working constraints in order to reduce the overall fuel cost supplied for the combined units. Three test systems—a 7-unit, a 24-unit, and a 48-unit system—have been utilized to confirm the efficacy of the proposed IHBO algorithm. At three distinct power and heat loading levels, the anticipated MSA is demonstrated to be superior for both a smaller 7-unit system and a larger 84-unit system. The method was improved in this work to solve the system of nonlinear equations that arises from explicitly describing the EDP lossy optimization issue.
Development of Facial Detection System for Security Purpose Using Machine Learning
Authors: Sai M. Srinivasa Sesha , Gatla Ranjith Kumar , Vijaya Lakshmi Ch. , Prashanth Addagatla , Malleswara Rao D. S. Naga , Gatla Anitha
Published: September 2024

Face recognition is a technique for recognizing or authenticating someone’s identification based on a quick glance at their face. After that, this application can employ computer vision to discover a potential face inside its stream. Facial recognition is been used in a various routine operation, from mobile phone unlocking to ATMs. Individuals and businesses use automated teller machines (ATMs) to conduct a spectrum of financial activities, includes banking, for both individuals and organizations. There seem to be ATMs everywhere, such as in restaurants, supermarkets, convenience stores, malls, schools, gas stations, hotels, workplaces, banking facilities, airports, entertainment venues, transportation facilities, and numerous other locations. Consumers often have access to ATMs on a continuous basis, allowing them to conduct financial transactions at any time of day or week. In this project, face recognition and a tiered security mechanism are used. Machine learning, OpenCV, and Python are used to implement face recognition. In this situation, Face embeddings are used to extract characteristics from the face. A neural network uses a picture of a person’s face as input and generates vectors representing the most important face attributes. This vector is called an We refer to it as face embedding since it occurs in machine learning. The project aims to reduce the risks associated with remote ATMs and the problems associated with fraudulent transactions, such as misusing someone else’s card to withdraw money. Therefore, to overcome this problem, we developed a solution using ML to limit card use to just authorized individuals who can be recognized using face recognition software.
Intelligent drip irrigation: Leveraging embedded systems and sensor networks for real-time monitoring and fault diagnosis
Authors: Kalidas N. , Goshteeswaran S. , Hussain Muhamed , Kumar Mamidi Kiran , Rao Kondaveeti Srinivas
Published: September 2024

Recent advancements in wireless sensor networks (WSNs) and precision agriculture have captured significant interest in both research and industry. Integrating WSNs into agriculture offers numerous benefits, including enhanced crop quality, improved production efficiency, resource conservation (water and energy), and optimized crop management practices (such as irrigation and fertilization). Irrigation, a crucial factor for agricultural success, is often hampered by current systems’ inefficiencies and rising production demands. Water scarcity, drought, and limited water resource waste further complicate conventional irrigation. To address these issues, we propose an intelligent irrigation system prototype that combines WSN technology with drip irrigation. This system utilizes WSNs and ZigBee wireless communication to create an automated and intelligent irrigation solution that conserves water, enhances irrigation system performance, and improves efficiency. Sensor data collected from strategically placed sensors near plant roots (including temperature and soil moisture) is used to control irrigation. The system analyses this data against predefined thresholds for each parameter and activates or deactivates irrigation accordingly. This approach aims to achieve significant water, time, and energy savings.
Tampered energy meter information conveyed to concerned authority by wireless communication
Authors: Chandra Prasad S. Hari , Fallah Mohammed H. , Rahul D. , Gehlot Anita , Satyanarayana Kosaraju
Published: September 2024

Utility companies face a serious problem with energy metre manipulation, which can result in lost income, inaccurate invoicing, and safety issues. Maintaining fair billing practices and the integrity of energy distribution systems depend on the prompt detection of tampering incidents. Nevertheless, current detection techniques frequently fall short in terms of effectiveness and fail to promptly notify authorities. In order to overcome this difficulty, our research suggests a novel method for identifying energy metre tampering and sending pertinent data via wireless communication technologies. The principal objective is to create a dependable system that can precisely identify instances of tampering in real-time and send alerts to relevant authorities with ease. Our solution is carefully designed to fill in the research gaps by drawing on a thorough assessment of the literature on wireless communication protocols and tampering detection techniques. Our solution delivers accurate and quick detection of tampering situations by utilising complex wireless communication protocols, modern sensor technology, and sophisticated data processing algorithms. The system architecture combines a wireless communication module with tampering detection sensors to quickly transmit notifications to the relevant authorities. Extensive tests are carried out to verify the functionality of the system, assessing critical parameters including alert reliability, response speed, and detection accuracy. Our experimental results highlight the effectiveness and reliability of the suggested approach in real-time alerting authorities and identifying tampered energy metres. This study makes a substantial contribution to the field of energy metre tampering detection and emphasises the critical role that wireless communication technologies play in preserving the integrity and security of energy distribution networks. In conclusion, our study presents a novel method for identifying energy metre tampering and wirelessly communicating vital information to authorities. Our research establishes a new benchmark in energy metre tampering detection by providing improved accuracy, efficiency, and timeliness, which promotes increased resilience and security in energy distribution networks.
Assessment of physiochemical properties of grey water
Authors: Mouli K. Chandra , Jyothsna K. , Appalakonda V. , Muhsen Muntadar , Balmiki Vinod
Published: September 2024

Greywater, a type of domestic wastewater, is a potential solution to global water shortages, which are expected to affect 2.7 billion people by 2025. Greywater is safer to handle and treat than black water, making it suitable for non-potable uses like toilet flushing and landscaping. It also promotes ecologically sustainable development by reducing freshwater extraction, energy use, and chemical pollution. The process of processing greywater involves considering factors like biological oxygen demand, surfactants, oil and grease, and detergent residues. This study was evaluated greywater’s physical and chemical parameters in accordance with Indian standards.
Ferpesto 2.0: Elevate Green, Hydro-organic Fusion
Authors: Abdul Jamal Adam , Hasnur Izwan Akmal Hakimi , Sa’adon Amir Asyraf , Ahmad Zulfaa Eisya Syifaa , Mohd Azhar Muhammad Azfar Isma , Wafdi Auni Nur Aisyatul Auni , Abd Rahman Norilyani , Mohd Salleh Sariah
Published: September 2024

Ferpesto, an innovation that combines the properties of a pesticide and fertiliser. While the successful Ferpesto 1.0 project was focusing on the growth of the ground plants, we evolved the original Ferpesto to the upgraded version which now focuses on the aquatic plants. This evolution was made as we discovered that the concerns arose regarding eutrophication in aquatic ecosystems due to excessive nitrates. This led to harmful algae blooms depleting oxygen, releasing toxins, and elevating Biochemical Oxygen Demand (BOD). In response, Ferpesto 2.0 prioritises the growth of aquatic plants, aiming to improve water quality by reducing BOD. Expanding on the original formula with watermelon rind, onion peel, fermented rice, and filtered water, Ferpesto 2.0 introduces a key addition which is hydrogen peroxide (H₂O₂). Observations show that polluted water treated with Ferpesto 2.0 took a longer time to decolorize the methylene blue, indicating the decrease in BOD compared to untreated water. From our survey, individuals that own aquatic ecosystems seek an alternative to maintain the water quality that is both sustainable and affordable. By reusing household wastes, Ferpesto 2.0 contributes to environmentally friendly practices, contributing a healthier and balanced ecosystem for current and future generations.
Evaluation of Particulate Matter 2.5 Pollution Prevention and Control Effectiveness around Coal-fired Power Plants in Jiangsu Province, China based on Remote Sensing Data
Authors: Yin Bangyao , Fang Dongming , Chen Jun
Published: September 2024

Based on the China High-resolution Air Pollution near-surface air pollutant remote sensing dataset, the spatiotemporal variation characteristics of PM2.5 and four chemical components around 6 coal-fired power plants in fine particulate matter pollution hotspots in Jiangsu Province, China from 2016 to 2020 were analyzed. Combined with the power plant installed capacity and the power generation data is studied from three perspectives: inter-annual characteristics, seasonal changes and trend analysis. The results show that the concentrations of PM2.5 and chemical components (Cl-, NH4+, SO42-, NO3-) around major coal-fired power plants in Jiangsu Province have dropped significantly, with an average annual reduction of 3.43, 0.12, 0.32, 0.54 and 0.54μg/m3 respectively.The seasonal variation characteristics of chemical components are obvious, the seasonal variation of NO3- is the most significant, and the proportion of SO42- reaches its peak in summer. Spatial heterogeneity is significant. Compared with the northern region, the proportion of NO3- in the three power plants in southern Jiangsu is 3 percentage points higher overall, and the concentrations of SO42- and NO3-have dropped even more. In addition, secondary inorganic aerosols (SIA) represented by NH4+, SO42-, and NO3- have become the main driving factors of PM2.5 pollution from coal-fired power plants in areas along the Yangtze River in Jiangsu Province, among which NO3- is the main cause of PM2.5 pollution around coal-fired power plants in Jiangsu Province. The most important secondary components highlight the importance of NH3 and NOX control for the future prevention and control of PM2.5 pollution from coal-fired power plants in Jiangsu Province, China.
Tin, Ponds, Mangroves, and Tourism on Bangka Coast: The Dilemma of Money and Conservation
Authors: Ibrahim Ibrahim , Zulkarnain Ariandi A. , Kurnia Muhammad
Published: September 2024

The extensive expansion of tin mining in Bangka Island and a small part of the open sea is causing environmental damage in coastal areas. In recent years, the damage has been increased by the opening of shrimp ponds, leading to the reduction of mangrove areas and the disturbance of coastal tourism assets. Therefore, this study aims to explore the dilemma between the economic activities of tin mining and shrimp pond openings in coastal areas through qualitative methods using interviews, observations, and documentation. Investors manage tin and shrimp pond potentials by compensating residents. In contrast, the residents have predominantly accepted tin mining as primary employment, serving as an alternative economic opportunity for individuals previously engaged with the company. Furthermore, mangrove areas experience habitat destruction and a decrease in coastal support capacity. Tourism assets and potentials are also disrupted because of the reduction in the naturalness of coast and the disturbance of coastal habitat ecosystems. The results show that the persistence of the dilemma is due to inadequate law enforcement measures and the impartiality of village officials. Consequently, the situation remains stagnant since the parties maintain divergent perspectives without reaching an agreement. Making money and conserving is still a big challenge in saving the environment, especially when each actor chooses not to take a firm position.
Expected value for the k-distance degree index of a graph
Authors: Aram Hamideh
Published: September 2024

For a graph G, the k-distance degree index is

Nκ(G) = ∑κ=1diam(G) ( ∑w∈V(G)  dκ(w) ) κ.

In this article, we calculate the accurate formula of the expected value for k-distance degree index in a random arranged polygonal string with m-arranged polygons. Finally, we determine the average value of this index in the collection of all those arranged polygonal strings.
Analysis of the dance teaching module in the dance education course in the elementary school teacher education study program
Authors: Hikmawaty Lisna , Masunah Juju , Julia J.
Published: September 2024

The existence of dance teaching modules for elementary school teacher education students in the form of textbooks still persists and is used as a learning resource to this day. The aim of this research is to analyze and determine the similarities and differences in the content of the two dance teaching modules in the dance education courses of the Teacher Education study program elementary school. The research method used in this research is the content analysis method. Research data was obtained from the results of reviewing two dance teaching modules. Data analysis is presented descriptively to describe the content of the material, similarities and differences as well as the advantages and disadvantages of the dance teaching module. The findings show that there are several similarities and differences in stages in the discussion of the process of creating dance for elementary school students. Apart from that, the advantages and disadvantages between the two teaching modules can be seen in the availability of supporting equipment for the module in the form of audio-visual media.
The use of angklung toel as music learning media at SMP PGRI 1 Cimahi
Authors: Gumilar Teguh , Masunah Juju , Julia
Published: September 2024

Angklung Toel is a modified bamboo musical instrument that originated from the diatonic angklung. Angklung Toel has developed in terms of shape and how to play it, but the type of Angklung Toel used in music education does not yet have a type that is considered suitable for music learning media. The purpose of this study is to identify the use of Angklung Toel as a music learning media. The method used is a qualitative method with a case study design. The data collection techniques used were observation and interviews with resource persons of Angklung Toel innovators, teachers, lecturers and Angklung Toel trainers. The results of this study on the use of Angklung Toel are used as a medium for learning music in playing songs. The type of Angklung Toel used as a learning medium is the type of Angklung Toel that was inaugurated in 2012.
The effect of education supervision from school supervisors on teacher competence and its impact on the quality of digital learning
Authors: Rahyasih Yayah , Syarifah Johar Permana , Syarifah Liah Siti
Published: September 2024

This research aims to explain the effect of educational supervision on the quality of digital learning which is mediated by the teacher Competences to manage digital learning. The research used a quantitative approach with sur-vey method. The research population was junior high school teachers in the city of Bandung, Indonesia. There were 357 respondents with random sampling technique. Data collection was carried out by surveys and document studies. The questionnaire as a research instrument uses a Likert scale, for exogenous variables, namely educational supervision, endogenous variable, namely the quality of digital learning and intervening variables, namely the ability of teachers in digital learning. Further-more, the analysis process in this research uses a multivariate test using Smart PLS 3.0 software. Based on the research, there is a positive and significant effect of the educational supervision variable on the quality of digital learning through teacher competences. It means that the better of supervision, so the quality of digital learning will be better, and to achieve this, a good teacher’s ability to man-age digital learning is needed. This implies that there is a need to increase the understanding of school supervisors on the quality of digital learning so that it has a good impact on their supervision.
Construction of the meaning of parenting styles and their relationship with visual mother character design on Instagram (Study of phenomenology in new parents Gaia Parenting followers)
Authors: Argani Palupi , Sihombing Riama Maslan
Published: September 2024

This study aims to examine how the construction of meaning formed in new parents who follow parenting education accounts on Instagram, especially those formed in parenting patterns, and the appearance of the character de-sign of the mother figure. The world of parenting education is currently growing rapidly because young parents now have more access to parenting information from new sources such as social media. As a medium for sharing visual content, the appearance of Instagram content is an important aspect that must be considered because it influences and increases audience interest. The character design itself has a role in the delivery of communication on the shared content. This research was conducted to determine the construction of the meaning of parenting formed among new parents and whether the character designs dis-played are by the meaning of the formed parenting. Learning in parenting education is essential because it is related to parenting patterns formed in Indonesia, which will affect the quality of human resources. This research was conducted using a qualitative method with a phenomenological approach to digging deeper into the meaning and experience of new parents on the design of the visual char-acter of the mother figure in parenting style.
Transformation from manual to digital: Artificial Intelligence in batik education for 5.0 society
Authors: Abdullah Farid , Basar Suhaila Bt. , Sya’bany Dewi M. , Adnan Aneeza Mohd.
Published: September 2024

The problem of transformation from manual to digital in Indonesia and Malaysia faces many obstacles. The phenomenon of society maintaining traditions or manuals is still very dominant, but solutions must be implemented. Education at the tertiary level studying batik in Indonesia and Malaysia is still very manual, based on ideas, cultural influences and the skills of the maker. The existence of artificial intelligence is not yet optimal in Society 5.0 which is very human-centered and supported by continuously developing technology such as Artificial Intelligence. Technological advances including artificial intelligence have been widely used, but there is still little in the creation of batik patterns. The method in this paper is conceptual and review based. The future direction from manual to digital transformation is that the support of Artificial Intelligence technology is very helpful and makes it easier for hu-mans to create new batik which can enrich Indonesian and Malaysian batik higher education.
Dancing in the digital domain: Facilitating collaborative learning in the digital age
Authors: Saearani Muhammad Fazli Taib
Published: September 2024

Technological advancements have brought about significant changes in many aspects of life, including dance education. Technology not only makes information and communication more accessible, but it also enables more participative and collaborative learning methods. Digital technology has had a transformative impact on dance education by providing tools and platforms for remote learning, virtual workshops, and online dance competitions. Students may utilise smartphone applications to record and share practice sessions, get feedback from the educator, and access online learning courses. Teachers may also utilise this technology to share materials, examine data, and get criticism from peers. Individual recordings, online practice sessions, and pre-recorded performance assessments enable dancers to collaborate on performance projects. The use of technology in dancing classes boosts diversity, accessibility, engagement, and responsiveness. Real-time communication and feedback enabled by information technology improves learning efficiency and motivation. However, access to digital content continues to be an issue, especially in Southeast Asia. As a consequence, dance educators must become innovative instructional material suppliers in order to maximise the benefits of technology in dance education.