bluuebunny/crossref_metadata_2025 huggingface dataset:
Spin-state reconfiguration of single-atom dimers via superexchange interactions enables nitrate reduction to ammonia
Authors: Shan Yun , Li Tinghui , Liu Lizhe
Published: October 2023

Electrochemical reduction of nitrate to ammonia faces the competition of multiple reactions. Herein, we focus on the spin-related reconfiguration of diatomic catalysts via their super-exchange interaction to enhance the reduction performance.
Structure and properties of metal–organic frameworks modulated by sulfate ions
Authors: Guo Yuan-Yuan , Wang Rui-Dong , Wei Wei-Ming , Fang Fang , Zhao Xu-Hui , Zhang Suo-Shu , Shen Tian-Ze , Zhang Jun , Zhao Qi-Hua , Wang Juan
Published: October 2023

Anions play a significant role in the construction of metal–organic frameworks (MOFs).
Fucoxanthin alleviated myocardial ischemia and reperfusion injury through inhibition of ferroptosis via the NRF2 signaling pathway
Authors: Yan Jing , Li Zehua , Liang Yu , Yang Chaobo , Ou Wen , Mo Huaqiang , Tang Min , Chen Deshu , Zhong Chongbin , Que Dongdong , Feng Liyun , Xiao Hua , Song Xudong , Yang Pingzhen
Published: October 2023

FX stimulated NRF2 to ameliorate mitochondrial dysfunction and inhibit overloading ROS and Fe2+, which contribute to lipid peroxidation and thus lead to ferroptosis, alleviating MIRI.
On a single method for determining As and Hg in dietary supplements by CVG-MIP OES: optimization of the multimode sample introduction system
Authors: Bitencourt Gustavo Rossato , Duarte Fabio Andrei , Dressler Valderi Luiz , Bolzan Rodrigo Cordeiro , Flores Érico Marlon de Moraes , Mello Paola Azevedo
Published: October 2023

A single method was developed for the determination of As and Hg in dietary supplements by CVG-MIP OES using a multimode sample introduction system (MSIS).
Alignment-free construction of double emulsion droplet generation devices incorporating surface wettability contrast
Authors: Aslan Yunus , McGleish Olivia , Reboud Julien , Cooper Jonathan M.
Published: October 2023

We demonstrate a simple method to assemble polydimethylsiloxane (PDMS) microfluidic chips with areas of different wettability, without requiring alignment, to generate double emulsion droplet generation devices.
Single-shot multi-channel plasmonic real-time polymerase chain reaction for multi-target point-of-care testing
Authors: Kang Byoung-Hoon , Jang Kyung-Won , Yu Eun-Sil , Jeong Hyejeong , Jeong Ki-Hun
Published: October 2023

A multi-channel plasmonic real-time reverse-transcription polymerase chain reaction system is used to demonstrate high-throughput and multi-target detection of the SARS-CoV-2 virus with four simultaneous reactions in a single assay within 15 min.
Construction of a hierarchical CoP@ZnIn2S4 heterojunction for photocatalytic hydrogen evolution
Authors: Liu Yuqin , Ding Liyong , Xu Qian , Ma Yu , Hu Juncheng
Published: October 2023

The close interfacial contact facilitates the light-induced electron separation and transfer from ZIS to CoP, which synergistically yields an efficient hydrogen production performance.
Preparation, characterization and biochemical studies of nanoformulations of chlorambucil to enhance anticancer efficacy
Authors: Ahmed Shahbaz , Nadeem Masood , Hussain Irfan , Fatima Sana , Rizvi M. Moshahid A. , Tabish Mohammad
Published: October 2023

Cancer, as a multifactorial disease, damages healthy cells and organs.
β-Peptides incorporating polyhydroxylated cyclohexane β-amino acid: synthesis and conformational study
Authors: Reza David , Balo Rosalino , Otero José M. , Fletcher Ai M. , García-Fandino Rebeca , Sánchez-Pedregal Víctor M. , Davies Stephen G. , Estévez Ramón J. , Estévez Juan C.
Published: October 2023

We describe the synthesis of trihydroxylated cyclohexane β-amino acids from (−)-shikimic acid, in their cis and trans configuration, and the incorporation of the trans isomer into a trans-2-aminocyclohexanecarboxylic acid peptide chain.
Reticular materials for wastewater treatment
Authors: Mou Yi , Yuan Xingzhong , Chen Haoyun , Yang Yi , Dai Huan , Bai Jing , Chen Junying , Chew Jia Wei , Wang Hou , Wu Yan
Published: October 2023

The competitive advantages and limitations based on the infrastructure of reticular materials for wastewater treatment applications were systematically evaluated.
A Ti3C2 MXene-integrated near-infrared-responsive multifunctional porous scaffold for infected bone defect repair
Authors: Zhang Linli , Zhang Hui , Zhou Hongling , Tan Yi , Zhang Zhengmin , Yang Wei , Zhao Lixing , Zhao Zhihe
Published: October 2023

The porous PMME/PEI/PDA/MXene scaffold was fabricated through the VIPS and dopamine-assisted co-deposition processes. The as-prepared scaffold possesses anti-bacterial, ROS scavenging, and osteogenic abilities.
Teaching Receptive Vocabulary to Minimally Verbal Preschoolers With Autism Spectrum Disorder: A Single-Case Multiple Baseline Design
Authors: Muldoon Deirdre M. , Gray Rebecca
Published: October 2023

Purpose:

The purpose of this multiple probe design was (a) to investigate whether the use of the match-to-sample (MtS) procedure would result in independent identification of objects and (b) to examine whether the participants could generalize to matching objects and nonidentical pictures.

Method:

Using a nonconcurrent multiple baseline design, three minimally verbal preschoolers with autism spectrum disorder and receptive language impairment were taught to identify common objects using a MtS procedure and physical prompts. Participants were taught to match identical objects to identical pictures. Maintenance checks were completed following mastery of vocabulary for a total of 22 words. Generalization probes were conducted with the objects and nonidentical pictures. Intervention was completed by a speech-language pathologist during typical speech-language pathology sessions.

Results:

Results illustrated that all of the participants learned to match and generalize the pictures. All were able to independently identify the objects at 1-month follow-up.

Conclusions:

MtS and prompting appear to be effective procedures for teaching receptive vocabulary and can be easily implemented by education professionals. Learner profiles varied for the participants in this study and are an important aspect when teaching students with autism spectrum disorder and co-occurring receptive language impairment.
Undifferenced precise time transfer with information‐constraints
Authors: Liu Mingyue , Tu Rui , Chen Qiushi , Li Qi , Chen Junmei , Zhang Pengfei , Lu Xiaochun
Published: October 2023

Satellite navigation systems enable long‐distance and high‐precision time transfers. The authors proposed an undifferenced precise time transfer method with information constraints in this study. A more accurate receiver clock offset can be obtained by constraining the station coordinate parameters and receiver clock offset parameters to achieve a precise time transfer. In this example, the research object is the time transfer link established by the Global Positioning System observation station using a caesium clock, rubidium clock, and hydrogen clock. The clock difference sequence of the time‐transfer link was calculated by combining the observation data and precise products. Following analysis of the examples, the following conclusions were reached. The undifferenced precise time transfer method based on information constraints can effectively be used to smooth the clock difference sequence of the receiver and the clock difference sequence of the time transfer link. To some extent, this method can also be used to reflect the performance of atomic clocks at Global Positioning System stations and is better suited for the precise time transfer of the equal‐clock long‐baseline time transfer link. Simultaneously, the frequency stability of this method is improved significantly in the short term compared to the traditional scheme without any constraints. The improvement of frequency stability is helpful to improve the accuracy of time transfer.
A sensitive, high-resolution, wide-field IRAM NOEMA CO(1–0) survey of the very nearby spiral galaxy IC 342
Authors: Querejeta Miguel , Pety Jérôme , Schruba Andreas , Leroy Adam K. , Herrera Cinthya N. , Chiang I-Da , Meidt Sharon E. , Rosolowsky Erik , Schinnerer Eva , Schuster Karl , Sun Jiayi , Herrmann Kimberly A. , Barnes Ashley T. , Bešlić Ivana , Bigiel Frank , Cao Yixian , Chevance Mélanie , Eibensteiner Cosima , Emsellem Eric , Faesi Christopher M. , Hughes Annie , Kim Jaeyeon , Klessen Ralf S. , Kreckel Kathryn , Diederik Kruijssen J. M. , Liu Daizhong , Neumayer Nadine , Pan Hsi-An , Saito Toshiki , Sandstrom Karin , Teng Yu-Hsuan , Usero Antonio , Williams Thomas G. , Zakardjian Antoine
Published: October 2023

We present a new wide-field 10.75 × 10.75 arcmin2 (≈11 × 11 kpc2), high-resolution (θ = 3.6″ ≈ 60 pc) NOEMA CO(1–0) survey of the very nearby (d = 3.45 Mpc) spiral galaxy IC 342. The survey spans out to about 1.5 effective radii and covers most of the region where molecular gas dominates the cold interstellar medium. We resolved the CO emission into > 600 individual giant molecular clouds and associations. We assessed their properties and found that overall the clouds show approximate virial balance, with typical virial parameters of αvir = 1 − 2. The typical surface density and line width of molecular gas increase from the inter-arm region to the arm and bar region, and they reach their highest values in the inner kiloparsec of the galaxy (median Σmol ≈ 80, 140, 160, and 1100 M⊙ pc−2, σCO ≈ 6.6, 7.6, 9.7, and 18.4 km s−1 for inter-arm, arm, bar, and center clouds, respectively). Clouds in the central part of the galaxy show an enhanced line width relative to their surface densities and evidence of additional sources of dynamical broadening. All of these results agree well with studies of clouds in more distant galaxies at a similar physical resolution. Leveraging our measurements to estimate the density and gravitational free-fall time at 90 pc resolution, averaged on 1.5 kpc hexagonal apertures, we estimate a typical star formation efficiency per free-fall time of 0.45% with a 16 − 84% variation of 0.33 − 0.71% among such 1.5 kpc regions. We speculate that bar-driven gas inflow could explain the large gas concentration in the central kiloparsec and the buildup of the massive nuclear star cluster. This wide-area CO map of the closest face-on massive spiral galaxy demonstrates the current mapping power of NOEMA and has many potential applications. The data and products are publicly available.
The Cygnus Allscale Survey of Chemistry and Dynamical Environments: CASCADE
Authors: Skretas I. M. , Karska A. , Wyrowski F. , Menten K. M. , Beuther H. , Ginsburg A. , Hernández-Gómez A. , Gieser C. , Li S. , Kim W.-J. , Semenov D. A. , Bouscasse L. , Christensen I. B. , Winters J. M. , Hacar A.
Published: October 2023

Context.Molecular outflows are believed to be a key ingredient in the process of star formation. The molecular outflow associated with DR21 Main in Cygnus-X is one of the most extreme molecular outflows in the Milky Way in terms of mass and size. The outflow is suggested to belong to a rare class of explosive outflows formed by the disintegration of protostellar systems.

Aims.We aim to explore the morphology, kinematics, and energetics of the DR21 Main outflow, and to compare those properties to confirmed explosive outflows in order to unravel the underlying driving mechanism behind DR21.

Methods.We studied line and continuum emission at a wavelength of 3.6 mm with IRAM 30 m and NOEMA telescopes as part of the Cygnus Allscale Survey of Chemistry and Dynamical Environments (CASCADE) program. The spectra include (J= 1−0) transitions of HCO+, HCN, HNC, N2H+, H2CO, and CCH, which trace different temperature and density regimes of the outflowing gas at high velocity resolution (~0.8 km s−1). The map encompasses the entire DR21 Main outflow and covers all spatial scales down to a resolution of 3″ (~0.02 pc).

Results.Integrated intensity maps of the HCO+emission reveal a strongly collimated bipolar outflow with significant overlap of the blueshifted and redshifted emission. The opening angles of both outflow lobes decrease with velocity, from ~80 to 20° for the velocity range from 5 to 45 km s−1relative to the source velocity. No evidence is found for the presence of elongated, “filament-like” structures expected in explosive outflows. N2H+emission near the western outflow lobe reveals the presence of a dense molecular structure, which appears to be interacting with the DR21 Main outflow.

Conclusions.The overall morphology as well as the detailed kinematics of the DR21 Main outflow are more consistent with a typical bipolar outflow than with an explosive counterpart.
Gaia data processing
Authors: Harrison D. L. , van Leeuwen F. , Osborne P. J. , Burgess P. W. , De Angeli F. , Evans D. W.
Published: October 2023

Aims. Our goal is to describe two potential options for the Source Environment Analysis pipeline (SEAPipe) for the Gaia mission. This pipeline will enable the discovery of sources that are new to Gaia, in the sense that they were not found by the on-board detection algorithm. These additional sources (secondaries) are discoverable in the vicinity of those Gaia sources (primaries) that were found by the on-board detection.

Methods. The main algorithmic steps required are described: the two dimensional image reconstruction of one dimensional transit data; the analysis of these images to find the additional sources present, and the determination of the mean positions; proper motions, parallaxes, and brightness of these sources. Additionally, the Monte Carlo simulations used to characterise the performance of the pipelines are described.

Results. The performance of the two options for SEAPipe, the vanilla and image-subtraction versions, are compared. Their selection functions were computed in terms of the magnitude of the secondary sources and their angular separations from their corresponding primary source. The completeness and purity of the resultant catalogue of secondary sources as found by each of the pipelines, given the expected magnitude distribution of the primary sources and the magnitude and angular separation distributions of the secondary sources, is also presented. The image-subtraction pipeline is shown to outperform the vanilla pipeline.
Enhancement of Quality of Power by Multilevel D-STATCOM in Distribution Network for Sustainable Power Networks
Authors: V. Vijay Rama Raju , Doddi Bhavya , Dixit Saurav , B. Lingam
Published: October 2023

Utility distribution networks, crucial commercial operations, and critical industrial loads can suffer considerable financial losses as a result of a variety of service interruptions and outages. In developing countries like India, where alterations in power frequency and numerous other factors affecting power quality are a worry, it is crucial to take appropriate action to make power networks sustainable. To control and reduce voltage disturbances, a variety of techniques are available. For their benefits, including suitable output waveforms, inverters with multilevel outputs, such as multilevel D-STATCOMs, are frequently utilized in the power system and industry (voltage and current). Multilevel D-STATCOM control can be accomplished with several controllers. A closed loop controller is one of the controllers that use a feedback system to automatically control a system that ensures a desirable state or accepted value. Among the improvements are voltage sags and swells. The performance of the suggested controller is explained by contrasting it with both multilevel D-STATCOM and traditional PWM controls. In addition to its simplicity, robustness, and flexibility, the proposed method allows for all defects to be compensated.
Implementation of three stage comparator using a modified latch with sustainable resources
Authors: Navya Galla , Jamal K. , Valiveti Hima Bindu , Kumar Gupta Jitendra , Vandana B.
Published: October 2023

In this paper, the current study uses a lector technique to modify the latch. The Lector approach is one of the top low-power methods for IC technologies. The locking mechanism is the third stage in our proposed design for a three-stage comparator. The lector approach is used for the three-stage comparator circuit in this case and its modified version. Pre-amplifier stages are the first two levels. The improved performance of this comparator circuit uses two sets of complementary biased two-stage preamplifiers. The traditional three-stage amplifier decreased the latency, while the modified version of the modified three-stage amplifier focused on the kickback noise. The proposed design of this three-stage comparator, which employs a lector approach, concentrates mainly on lower consumption. Tanner EDA was used to build and simulate this complete schematic. Materials having a lesser environmental effect are chosen, such as those that use fewer resources or are simpler to recycle after a product’s lifespan and sustainability.
Sleep Track: Automated Detection and Classification of Sleep Stages
Authors: Ram Kumar R.P. , Rithesh A. , Josh Pranav , Karthik Raj B. , John Vivek , Shiva Prasad Doma
Published: October 2023

Sleep is vital for our body’s physical restoration, but sleep disorders can cause various problems. Determining sleep stages is essential for diagnosing and curing such disorders. Polysomnography (PSG) signals are recordings of brain activity, eye movements, muscle activity and other physiological signals that are collected during a sleep study. Insomnia, Sleep Apnea, and Restless Legs Syndrome are some of the sleep problems that can be identified using these signals. However, analysing PSG signals manually can be time-consuming and prone to errors. Deep Learning Models such as Convolutional Neural Networks (CNN), can be used to automate the analysis of PSG signals. CNN is followed by Long-Short Term Memory (LSTM) and CNN are used as a stack ensemble method to recognize patterns in the signals that correspond to different sleep stages and events. By training these models on large datasets of PSG signals, they can detect the disorders. The dataset is collected from PhysioNet Sleep-EDF dataset that consists of PSG signals. The accuracies obtained using different training and testing data using CNN and CNN-LSTM are 95.15% and 83.9% respectively, and using metadata classifier the overall accuracy is increased by 1%. The future enhancement of the paper can be done by considering Heart rate, EEG Pz-oz signals and EEG Pz-oz along with EEG Fpz-cz.
Smart E-Commerce: A Novel Lease Option Model for HealthCare Equipment
Authors: Anjaneyulu M. , Shreyas Rao Phuke , Rakesh Madasi , Shiridi Sirigiri , Khanduja Manisha , Jhade Srinivas
Published: October 2023

The swift development of e-commerce has significantly altered consumer behavior and the availability of products and services. Online platforms have become essential for both healthcare providers and patients within the field of medical equipment. However, the high cost of purchasing healthcare equipment hinders affordability and accessibility. This research paper introduces a sustainable lease option model for healthcare equipment on e-commerce websites to address this issue. This research paper examines the theoretical framework and benefits of introducing a lease option model to online healthcare equipment platforms. This paper analyzes a sustainable e-commerce platform, which benefits of implementing a lease option model. These benefits include increased affordability, enhanced accessibility to specialized equipment, and reduced financial burdens for patients and healthcare facilities. The proposed structure outlines the essential elements of incorporating lease options into e-commerce websites, such as pricing structures, contract terms, maintenance and support services, and user experience considerations. Risk assessment, legal considerations, and customer service are just a few of the potential challenges and strategies for risk mitigation that are discussed. It highlights the potential impact of lease options on the accessibility and affordability of healthcare equipment and emphasizes the need for additional research and implementation efforts to optimize this model in real-world settings. The introduction of a lease option model on healthcare equipment e-commerce websites presents a promising opportunity to revolutionize the industry. This work leads to the actual value of sustainable web application in health care sector.
Automated Cricket Score Prediction
Authors: Sanjeeva Polepaka , Ajith Varma Jampana , Sathvik Valaparla , Abhinav Sai Ratan Attemla , Mishra Sanjay
Published: October 2023

Cricket is a popular sport that involves a high degree of variability in terms of game conditions and player performance. The ability to accurately predict cricket scores could provide valuable insights for coaches, analysts, and fans, as well as offer opportunities for sports betting and fantasy games. This paper explores the use of machine learning techniques to predict cricket scores based on a variety of contextual and historical factors. The publicly available cricket dataset is used to build and evaluate several regression models that predict the total runs scored by a team in a limited-overs cricket match. This analysis includes feature engineering to extract and transform relevant input variables, model selection to compare and choose among different regression algorithms, and performance evaluation to assess the accuracy and robustness of the models. This paper also conducts sensitivity analysis to identify the most influential predictors and explore the potential biases and limitations of the models. The results indicate that machine learning techniques can effectively predict cricket scores and provide valuable insights into the factors that contribute to team performance. Automated cricket prediction is useful for cricket teams, coaches, and analysts who seek to improve their game strategies and player selection, as well as for sports betting and fantasy game platforms that seek to provide more accurate experiences for users.
Feasible Criminal Identification using Image Recognition
Authors: Sreevani V. , Eakshith Kumar N. , Rishith Nayak B. , Sai Shashank H. , Vyeshikha
Published: October 2023

Criminal identification using image recognition is a crucial task for law enforcement agencies. It involves identifying and tracking down criminals by analysing their facial features from images and videos. The system aims to improve the efficiency and accuracy of criminal identification while reducing human error. The system will be trained on large datasets of criminal images to ensure high accuracy and reliability. The paper will use publicly available datasets such as the Face Recognition Technology (FERET) and the Labelled Faces in the Wild (LFW) dataset to train and test the model. Metrics including accuracy, precision, recall, and F1-score will be used to assess the system’s efficacy. The results and discussions will focus on the strengths and weaknesses of the model, and potential avenues for improvement. In conclusion, the proposed face recognition system shows promising results in identifying criminals and reducing the burden on law enforcement agencies. The manuscript discusses the objective of the paper, provides an overview of facial recognition technology, and summarizes existing approaches in criminal identification using image recognition.
A Real-time Automated System for Object Detection and Facial Recognition
Authors: Reddy K. Shyam Sunder , Ramesh G. , Praveen J. , Surekha P. , Sharma Ayushi
Published: October 2023

Object detection, facial recognition, and person identification are important tasks in computer vision with numerous real-life applications. The major goal of the proposed model is to identify people and recognize them in the images. In this paper, we propose a real-time automated system that combines power of both EfficientDet model for object detection and the FaceNet model for facial recognition to detect persons in an input image, recognize their faces, and label them with their corresponding names. The experimental study of the model takes place on COCO dataset and a custom dataset of images of students. This solution can be applied to various scenarios beyond education, such as in security and surveillance, healthcare, transportation, retail, and entertainment etc. The importance of the model lies in its ability to efficiently and accurately perform person identification and recognition in real-time scenarios, which can save time and resources and improve overall efficiency.
IoT Sensor-based sustainable smart home management for human needs through Micro Controller
Authors: Gopal Krihsna P. , Subbarayudu Yerragudipadu , Sai Siva Kumar S. , Naveen D. , Srivastava Abhishek , Thangamani K.
Published: October 2023

Smart home technology is emerging rapidly as an exciting new paradigm. Appliances inside the home can be watched over, managed, and controlled by the consumer. Additionally, the gadgets are linked together via the internet, enabling the user to remotely control features like home lighting, air conditioner, and security systems providing sustainable approach. To aid the elderly and others with disabilities, this paper’s major goal is to teach consumers how to properly handle their household appliances. Thus, a smart home is being developed where the environmental conditions like air conditioner, television and lights adjust themselves with the person entering the room or even according to the weather conditions. Due to the complexity, in this paper an Microcontroller, LCD and other necessary materials in place of TV, AC and light are used to show that if a house consists of two or more people how the LCD will adjust itself and displays the standard required channel, likewise same LCD adjusts itself to the standard temperature required by the person and similarly adjusts itself according to the person entering into the room. Additionally, if it is raining outside the LCD will display a monsoon mood song, this is done using rain sensor. If these sensors are connected to the cloud, then the information related to the person entering the room is stored. This information can be accessed using your mobile.
Clickbait Post Detection using NLP for Sustainable Content
Authors: Ganapati Raju N.V. , Nyalakanti Nikhil , Kambampati Premsai , Kanthali Yeshwanth , Pandey Shivam , Maithili K.
Published: October 2023

Clickbait is a significant problem on online media platforms. It misleads users and manipulates their engagement. A user who clicks on a clickbait link may be taken to a website full of ads, or that requires them to pay for something. The goal of this project is to create a system that can recognize clickbait posts so that user can access only to sustainable content. The system will analyze data using natural language processing (NLP) and machine learning techniques. NLP pre-processing techniques, such as tokenization, lemmatization, and stemming, will be utilized to extract essential elements from the headlines. These features will subsequently be used to train a machine learning model, specifically a supervised classifier, to distinguish between clickbait and non-clickbait news headlines. The project will explore a range of algorithms and techniques, including popular text representation models such as TF-IDF or word embeddings, as well as classifier models like logistic regression or random forests. The model will be evaluated using a variety of metrics, such as Accuracy, Precision, Recall, and F1 score. By making it easier for users to identify clickbait, the system can help to reduce the amount of time and money wasted on this type of content.
A Sustainable and Efficient IoT Approach for Fire Department Alerting System
Authors: Vidyadhari Ch. , Pavan Pendli , Tharun Mudavath , Kundu Vinayak , Dulta Kanika
Published: October 2023

The creation of sophisticated fire detection systems is necessary given the rising danger of fire occurrences. The system described in this abstract uses IoT components such an Arduino board, flame sensor, buzzer, SIM800L module, and SIM800L to detect fires in real time and inform users. The flame sensor is the main element of the system, and it uses infrared radiation to identify flames when they are present. The Arduino board receives the signal from the sensor and activates the alarm system when it detects a flame. A loud audible alarm is produced by the buzzer when it is linked to the Arduino board to alert residents to a potential fire threat. The system includes the SIM800L module to support distant notifications in addition to local alerts. Once a fire has been identified, the Arduino board and SIM800L module connect to send an SMS or place a call to preset emergency contacts. This makes it possible to quickly take the necessary action, even if the affected properties are unattended. The IoT device connection with the Arduino board gives the fire detection system flexibility and scalability making it reliable and sustainable. By adding more sensors or integrating with current home automation systems, it is simple to customize and expand. Real-time fire detection, remote alerting capabilities, and IoT ecosystem integration are just a few of the advantages the suggested fire detection system has over conventional fire alarm systems.
Sustainable Utilization of Natural Stone Resources: Environmental Impacts and Preservation of Cultural Heritage
Authors: Sonia Pankaj , Sravanthi G. , Khan Irfan , Pahwa Shilpa , Salman Zahraa N. , Sethi Gaurav
Published: October 2023

The sustainable exploitation of natural stone resources poses a multifaceted dilemma that lies at the confluence of environmental protection and the preservation of cultural heritage. This study explores the complex interplay between the exploitation and use of natural stone resources, the consequent environmental ramifications, and the necessity of preserving cultural legacy for posterity. The procurement of natural stone resources, although being indispensable for the purposes of building, architecture, and artistic endeavours, sometimes gives rise to substantial ecological ramifications. Quarrying activities have been found to result in a range of detrimental consequences, including deforestation, soil erosion, water pollution, and habitat destruction. The intricate equilibrium between the preservation of natural resources and their utilisation necessitates the implementation of inventive approaches to minimise ecological harm and save cultural heritage. In order to effectively tackle these difficulties, it is imperative to adopt a holistic strategy. The use of circular economy concepts has the potential to significantly improve the utilisation of stone resources in a more effective manner. The preservation of cultural heritage necessitates thorough documentation, continuous monitoring, and proper care, as well as the use of protective coatings and materials that effectively minimise degradation while preserving the aesthetic and historical significance. This study argues for the cohabitation of natural stone extraction with cultural heritage preservation by examining the intersection of environmental issues and cultural relevance.
Towards a Circular Economy: Challenges and Opportunities for Recycling and Re-manufacturing of Materials and Components
Authors: Rakesh C. , Harika Ala , Chahuan Neeraj , Sharma Niti , Zabibah Rahman S. , Nagpal Amandeep
Published: October 2023

The transition towards a circular economy is a critical step in achieving sustainable development and mitigating environmental degradation. This study explores the challenges and opportunities associated with recycling and re-manufacturing of materials and components within the context of a circular economy. We conducted a comprehensive analysis of the current state of recycling and re-manufacturing technologies, identifying key barriers such as material degradation, contamination, and technological limitations. We also examined the potential for innovative solutions, including advanced material characterization techniques, additive manufacturing, and digital twin technologies, to address these challenges. Our findings reveal that the integration of these technologies can significantly enhance the efficiency and effectiveness of recycling and re-manufacturing processes, enabling the recovery of high-quality materials and components. Furthermore, we highlight the importance of establishing a robust regulatory framework and incentivizing industry participation to accelerate the transition towards a circular economy. This study provides valuable insights for policymakers, industry stakeholders, and researchers working towards the development and implementation of sustainable materials management strategies. By addressing the challenges and harnessing the opportunities identified in this study, we can pave the way for a more sustainable and resource-efficient future.
Smart Iot Based Solar Panel Cleaning System
Authors: Singarapu Sathish , Swaraja K. , Kirola Madhu
Published: October 2023

The goal of this project is to make life better for people who use solar panels. We provide an open and honest dust- and speck-removal system that makes use of cutting-edge technology that has improved performance, honesty, uniformity, cost, and scalability. These days' cleaning systems provide roughly 32% greater power output than a dirty solar panel. The universe itself is the controller of this system. This technique also reduces the number of people needed to clean solar panels. This is a method for automatically washing solar panels. Manually washing the solar panels is a tedious and time-consuming task. In this study, we propose a timed system that uses water and wipers to clean solar panels. Internet of Things (IoT) technology is used to carry out the operation. microcontroller and several sensor modules will undoubtedly handle system management. The Android application may be used to control the system. The system sends the consumer a notification message informing them of the various processes that have been run. It’s possible that the system may be made transportable so that it can be deployed in a variety of settings. A 5V, 500mA controlled power supply is used in this project. For voltage regulation, the 78053 authority is used, which is incurable. The second 230V to 12V step down transformer’s AC output is rectified by a full-wave bridge rectifier.
Performance optimization for Intrusion Detection by Long Short Term Memory (LSTM)
Authors: Khatkar Monika , Kumar Kaushal , Kumar Brijesh , Sohal Asha , Sharma Kriti , Bisht Amita , Sankara Babu B. , Gulati Monica , Manasa M.
Published: October 2023

Concerns about cyber threats have emerged as the expansion of system connectivity and the proliferation of system applications intensified in the industry. This has underscored the necessity for a robust defense mechanism against various cyber threats, including potential intrusions from malicious actors within the network. A specially targeted system is the intrusion detection system (IDS), designed to safeguard the confidentiality, integrity, and availability of network traffic, especially in critical sectors like healthcare. Recent advancements in the area of IDS involve the utilization of artificial intelligence (AI) and deep learning (DL) based IDS to efficiently recognize network issues. Notably, the research at hand adopts a deep learning approach employing Long Short Term Memory (LSTM) models, applied to the CICIDS-2019 dataset that is sourced from New Brunswick University’s website. The focal point of evaluation lies in the precision, recall, F1-score, and accuracy metrics, specifically analyzing its performance in identifying Denial-of-Service (DoS) cyber-attacks. The findings of this study lighten the superior performance of the Long Short Term Memory method in the realm of intrusion detection systems. The LSTM model showcases its proficiency, particularly in discerning Denial of Service attacks by giving a loss of less than 0.03%.
Methods of Ensuring Information Security in BIM
Authors: Maksudovna Vafaeva Khristina , Anatolyevna Gaevskaya Zlata , Dixit Saurav , Suthar Bhivraj , Kampani Shivani , Kumar Mamidi Kiran , Shamila M. , Nijhawan Ginni , Prasad G. Venkata Sai
Published: October 2023

Information security in BIM (Building Information Model) platforms is crucial, especially for mission-critical projects. Improper distribution and loss of confidential information can potentially lead to threats to physical security, financial losses, and loss of trust and reputation. The article discusses common methods of ensuring cybersecurity, potential threats, and measures to prevent them for the preparation and development of conceptual foundations for the Information Security Strategy of the process of building and structure information modeling. Tasks: 1) Identification of the most common information protection methods and identification of BIM security elements; 2) Analysis of potential cybersecurity threats for the information modeling process; 3) Consideration of common collaboration models in BIM. This work will allow developing an Information Security Strategy in BIM processes, improving the approach to ensuring an appropriate level of cybersecurity in BIM platforms, and developing universal steps for planning and implementing an effective information security strategy.
Breast Cancer Diagnosis from Histopathology Images Using Deep Learning Methods: A Survey
Authors: Patel Vivek , Chaurasia Vijayshri , Mahadeva Rajesh , Ghosh Abhijeet , Dixit Saurav , Suthar Bhivraj , Gupta Vinay , Siri D. , Kumar Y. Jeevan Nagendra , Dhaliwal Navdeep , Bommala Harikrishna , Kumar Kaushal
Published: October 2023

Breast cancer is a major public health issue that may be remedied with early identification and efficient organ therapy. The diagnosis and prognosis of severe and serious illnesses are likely to be followed and examined by a biopsy of the affected organ in order to identify and classify the malignin cells or tissues. The histopathology of tissue is one of the major advancements in modern medicine for the identification of breast cancer. Haematoxylin and eosin staining slides are used by pathologists to identify benign or malignant tissue in clinical instances of invasive breast cancer. A digital whole slide imaging (WSI) is a high-resolution digital file that is permanently stored in memory for flexible use. This article will look at and compare how breast cancer cells are categorised manually and automatically. lobular carcinoma in situ and ductal carcinoma in situ are the two types of breast cancer. Here, detailed explanations of numerous techniques utilised in histopathology pictures for nucleus recognition, segmentation, feature extraction, and classification are given. The pre-processed image is utilised to extract the nucleus patch using several feature extraction approaches. Thanks to the great computational capability of the general processing unit (GPU), algorithms may be implemented effectively and efficiently. Deep Convolution Neural Network (DCNN), Support Vector Machines (SVM), and other machine learning methods are the most popular and effective computer algorithms.
Geopolymerization of Plastic Waste for Sustainable Construction: Unveiling Novel Opportunities in Building Materials
Authors: Haq Md. Zia ul , Sharma Vishal , Sood Hemant , Kumar Rajesh , Joshi Kapil , Manisha Kumari , Lakhanpal Sorabh , Chary M. Rathna , Kumar Kaushal
Published: October 2023

This study provides an in-depth bibliometric analysis of the research land-scape of Geopolymer concrete using data from two of the leading scientific databases, Scopus and Web of Science. The analysis covers a time span of 2010 to 2022 and provides a comprehensive evaluation of the growth, age, impact, and collaboration of research in the field. The results show that the annual growth rate of research in Geopolymer concrete is substantial, with a 43.92% increase in the number of documents in Scopus and 15.76% in Web of Science. Furthermore, the document average age is relatively low, with 1.59 years in Scopus and 3.11 years in Web of Science, suggesting that the research in this field is recent and dynamic. The study also found that the research in Geopolymer concrete is highly cited, with an average of 11.69 ci-tations per document in Scopus and 18.69 in Web of Science.The authorship and document type analysis provides valuable insights into the research col-laboration and output in the field. The results show a high level of collabora-tion, with an average of 4.29 co-authors per document in Scopus and 3.47 in Web of Science. Additionally, the majority of the documents in the field are articles, with a smaller number of conference papers, book chapters, and re-views. In conclusion, this study provides a comprehensive overview of the research landscape of Geopolymer concrete and highlights the areas of strength and potential for future research. The results of the analysis can be useful for researchers, policymakers, and stakeholders in the field of Geopol-ymer concrete to understand the current state of the research, identify poten-tial gaps and opportunities, and plan future research activities.Page layout
Incorporating Sustainability: A Comprehensive Review of Factors Influencing Consumer Acceptance of Mobile Wallets
Authors: Bhardwaj Himanshi , Kapoor Pooja , Kumar Avnish , Ganapathi N.V. , Madhu Bhukya
Published: October 2023

Mobile wallets have gained widespread popularity as a convenient, secure, and user-friendly payment method embraced by consumers. However, the pace of mobile wallet adoption has exhibited variations across different markets, primarily due to a range of factors. In this study, we present an all-encompassing examination of existing literature, aiming to pinpoint the fundamental elements influencing the sustainable acceptance of mobile wallets by consumers. Through an exhaustive analysis of 80 research papers published between 2010 and 2022, we discern the prevailing factors that hold sway over the adoption of mobile wallets. Our scrutinization highlights that factor such as perceived sustainability, usefulness, ease of use, security, social influence, trustworthiness, and compatibility stand out as the most formidable propellants of mobile wallet adoption. Furthermore, our investigation uncovers hurdles that hinder the wider acceptance of mobile wallets, encompassing insufficient awareness, perceived intricacies, and lingering uncertainties regarding the technology’s sustainability. Our in-depth evaluation underscores the necessity of comprehending consumer perspectives and dispositions towards mobile wallets to galvanize their adoption sustainably. The culmination of our inquiry involves a discourse on the implications drawn from our discoveries, catering to researchers and practitioners vested in fostering the sustainable adoption of mobile wallets.
Performance of Powder mixed Drilling EDM on Biomedical Ti-6Al-4V Alloy
Authors: Nauryz Nurlan , Omarov Salikh , Talamona Didier , Perveen Asma
Published: October 2023

Titanium alloys have gained a lot of attention in biomedical due to their novel properties. In fact, their low elastic modulus and good biocompatibility have promising potential in load bearing bone replacement implants. However, a big part of successful implantation relies on proper surface treatment, which can enhance its performance. Electro discharge machining (EDM) is one of the surface treatment techniques that can be beneficial for proper surface forming. For that reason, this study investigates the machining conditions of EDM on Ti-6Al-4V titanium alloy. In details, this paper evaluates the effect of machining parameters of pulse current, time-on, time-off, gap voltage and powder on material removal rate (MRR) and overcut. Moreover, an experiment set based on L9(34) Taguchi’s orthogonal array was conducted and the analysis of variance was observed. In order to investigate the optimum machining condition, grey relation analysis (GRA) and analysis of variance (ANOVA) were used. In conclusion, the best performance parameters for MRR, overcut and multiple characteristics of the orthogonal array were observed and predicted improvements are calculated in this paper.
Computational fluid dynamics simulation of detonation wave propagation in modified pulse detonation combustor
Authors: Debnath Pinku , Pandey K.M.
Published: October 2023

In this paper effect of Schelkin spiral material on thermal load and detonation combustion wave propagation in pulse detonation combustor has been simulated. As detonation combustion is supersonic combustion process and energy release rate is very high. In this regards present researches are focusing on flame acceleration process to reduce the DDT run up length. Hence the Schelkin spiral is inserted in detonation tube, which creates a bluff body and enhanced the turbulence of flame propagation. During simulation three turbulence models are used to carry out the reliable and repeatable detonation wave in pulse detonation combustor near thin boundary layer of helical shape Shchelkin spiral. The computational fluid dynamics (CFD) simulation has been performed using Ansys fluent platform. The Large Eddy Simulation (LES), detached eddy simulation with realizable k-ε turbulence model and detached eddy simulation with SST k-ω turbulence model are used for reacting flow simulation. From this simulation the LES turbulence model shows better turbulence initiation of detonation wave with velocity magnitude of 3040 m/s in detonation tube compared to other two turbulence models. This velocity is higher than C-J velocity of 1800 m/s. Further computational result shows that deflagration to detonation transition take place at several waves traveling region, in presence of Shchelkin spiral in detonation tube.
Influence of Process Parameters on Sheet Lamination Method-based 3D printing: A Review
Authors: Reddy B. Yashwanth , Siddhartha M. , Reddy P. Sai Rakesh , Lakshmi A. Anitha
Published: October 2023

Additive manufacturing of carbon fibre reinforced thermoplastic composites” provides us advantages to create lightweight structures with great strength and stiffness over traditionally developed carbon fibre manufacturing techniques, because of enhanced design freedom. This paper is a summary of scholarly sources on Additive manufacturing. This study is a summary of state-of-art techniques this study allows us to identify gaps in the existing research, and also discusses the results of the study and the conclusions derived from it.
Modeling, Simulation and Optimization of Agricultural Tillage Process Vibrations using an Interactive Active Control System
Authors: Singh Harbhinder , Mehta Munish
Published: October 2023

Tractor operators have to work for long hours to perform different tasks. During tillage, implements are attached to the tractor for soil preparations for crop production. The attached implements also have direct effect on vibrations of tractors. Drivers of tractors are exposed to different frequency vibrations which effect their health badly. In this study, the vibrations transmitted during tillage to seat of operator were measured using accelerometer and root mean square (RMS) accelerations was analysed according to ISO standard. Tests were carried out with different type of implements (Cultivator and Disc Harrow) and at different forward speeds of tractor. The dynamic model of tractor and tillage implements was created in MATLAB-Simulink software. An active seat suspension was designed with PID and Fuzzy Logic Controllers and was analysed for improvement in ride comfort level of driver. The results reveal that designed controllers reduce the RMS accelerations at operator’s seat base by 69% as compared to passive seat.