bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart System to Detect Brain Age Using Machine Learning
Authors: Ahamed Yasir. H  , S. Anu Priya
Published: July 2024

Detecting brain ageing is of paramount importance in the medical field due to its significant contribution to the rising number of deaths each year. Brain ageing stands out as a prevalent health concern, characterized by a high mortality rate and widespread occurrence. Extensive research endeavors are underway to address this issue, with Magnetic Resonance Imaging (MRI) emerging as a pivotal tool for identifying and tracking the progression of brain ageing. MRI scans offer detailed insights into the ageing process, facilitating superior outcomes compared to alternative methodologies. In our paper, we propose an innovative approach for detecting brain ageing using MRI scanned images. The methodology encompasses several crucial steps, beginning with image preprocessing, where the application of a median filter enhances image quality. Subsequently, segmentation techniques employing mathematical morphological operations isolate regions indicative of brain ageing. Geometric features such as area, perimeter, and eccentricity are then computed for the identified ageing regions. The culmination of our approach involves the utilization of an Iterative Convolutional Neural Network (CNN) classifier. This classifier distinguishes between ageingous (malignant) and normal (benign) brain regions based on the extracted features. To further enhance the accuracy of our classification, we employ both Artificial Neural Network (ANN) as a baseline method and introduce the Optimistic Convolutional Neural Network (OCNN), a novel algorithm proposed in our research. Through rigorous experimentation and evaluation, we compare the performance of ANN and OCNN, analyzing their respective accuracies. Our findings unequivocally demonstrate that the OCNN outperforms the traditional ANN, offering superior accuracy and efficacy in detecting brain ageing from MRI scans. This underscores the potential of advanced neural network architectures in revolutionizing medical image analysis and diagnosis. In conclusion, paper presents a robust methodology for detecting brain ageing using MRI scanned images, leveraging state-of-the-art image processing techniques and innovative neural network algorithms. By enhancing the accuracy and efficiency of brain ageing detection, our research contributes significantly to the ongoing efforts aimed at mitigating the adverse impacts of this pervasive health issue.
Machine Learning Based Mammogram Classification from Mnist
Authors: Romario Dicruz  , Dr. H. Jayamangala
Published: July 2024

Breast cancer is one of the most leading causes of death among women. The early detection of abnormalities in breast enables the radiologist in diagnosing the breast cancer easily. Efficient tools in diagnosing the cancerous breast will help the medical experts in accurate diagnosis and timely treatment to the patients. In this work, experiments were carried out using Wisconsin Diagnosis Breast Cancer database to classify the breast cancer as either benign or malignant. Supervised learning algorithm -Support Vector Machine (SVM) with kernels like Linear, and Neural Network (NN) are used for comparison to achieve this tasks. The performances of the models are analysed where Neural Network approach provides more ‘accuracy’ and ‘precision’ as compared to Support Vector Machine in the classification of breast cancer, ANN seems to be fast and efficient method. In our project we have used the following algorithms Support Vector Machine (SVM) as existing and Artificial Neural Network (ANN) as proposed system compared in terms of accuracy
Crsv Score Dashboard to Predict Car Resale Price using Deep Neural Network
Authors: Kalisamy. R  , Jayamangala. H
Published: July 2024

With an increasingly flourishing quantity of private cars and the advancement of the used car market, used cars have to become the top priority for buyers. The price of a used car is an important aspect of a successful transaction for both buyers and sellers. However, used car transactions are much more complex than other commodity transactions, as the sale price is influenced not only by the basic features of the car itself, such as brand, power, and structure, but also by the condition of the car, such as mileage and usage time, as well as a lack of presently available methods determining which factors hit the sale price most dramatically. Traditionally, used car price appraisal methods include the replacement cost method, the present value of earnings method, the current market value method, and the liquidation price method. However, the traditional appraisal methods are difficult to select uniform indicators for and overly rely on the subjective judgment of appraisers, which is beyond the limits of online trading in the used car market. The accurate evaluation of used cars should be based on a standardized value evaluation system. As a scientific and effective model, deep residual networks will become an important method of used car value evaluation. This project aims to build a model to predict used cars' reasonable prices based on multiple aspects, including vehicle mileage, year of manufacturing, fuel consumption, transmission, road tax, fuel type, and engine size. An iterative framework LSTM is proposed in this project. First, the relevant data processing is carried out for the initial recognition features. Then, by training the deep residual network, the predicted results are fused with the original features as new features. Finally, the new feature group is input into the iteration framework for training, the iteration is stopped, and the results are output when the performance reaches the highest value. We will be integrated to the web-based application where the user is notified with the status of his product
Real-Time Image Forgery Detection through Machine Learning
Authors: Waship W  , Dr. H. Jayamangala
Published: July 2024

Digital Image Forgery can be done by deceiving the digital image to mask some meaningful or important data of the image. It is usually difficult to spot out the manipulated region of the original image. To sustain the uprightness and legitimacy of the image, the detection of forgery in the image is mandatory. Acclimation of the modern way of life and advancement in photography gadgetry has made exploitation of digital image easy with the help of image editing software. Therefore, it is crucial to detect such image forgery operations in the images. The image forgery detection can be done based on object removal, object addition, and unusual size modifications in the image. Images are one of the powerful media for communication. In our project we have used algorithms such as Copy Move Technique (CMT) as existing and Multi Support Vector Machine (MSVM) as proposed systems and both will be compared in terms of accuracy
Parking Slot Prediction and Face Recognition Based Parked Vehicle Theft Prevention in Smart System using Deep Learning
Authors: N. Mohan Raj  , P. Kavitha  , S. Kamalakkannan
Published: July 2024

More than a million cars are on the roadways of a contemporary major city, but more parking spots are needed to accommodate them. Locating vacant parking places in most contemporary cities might take time, especially during busy periods like festival seasons. In the traditional parking system, drivers face considerable losses in terms of money, productivity and time which is wasted in search of parking spots in densely populated areas. Hence, it can be said that the traditional parking systems are not capable of providing a smooth parking experience to the drivers along with reducing the parking search traffic on the roads. This highlights the rationale of adopting advanced technologies to make the urban transport system modern and ease the problem faced by the drivers. This project proposes a Smart Parking System utilizing Edge Computing and Deep Learning algorithms to seamlessly link multiple parking stations into a unified network, establishing a shared parking system. To address security concerns in highly restricted areas such as residential zones, military bases, and government buildings, the system functions as a centralized automatic vehicle identifier for owner verification. Deep Learning algorithms, such as Convolutional Neural Networks used to recognize the driver/owner face of a vehicle during the departure phase, fortifying security measures and thwarting potential vehicle theft
Perceptions of Advanced Level Students and Teachers Towards the Learning of Poetry in Literature in English in the Zimbabwean Classroom
Authors: Bhebhe P.
Published: July 2024

This paper is a desktop review of the perceptions of advanced-level students and teachers towards learning poetry in English literature in the Zimbabwean classroom. English language is one of the core subjects in the Zimbabwean education curriculum. From early childhood development to the university level, students are taught and examined in English. In advanced level (‘A’ level) classes, particularly in Nkayi District, students even learn English and communication skills and write them as a fourth subject. Although it does not contribute towards an individual student’s points, it is considered a desirable subject. English and communication skills are compulsory in almost all the schools in Nkayi District. The subject of Literature in English comprises three categories, which are prose, drama, and poetry. However, Poetry is the most complicated of the three. This paper examined perceptions of advanced-level students and teachers towards learning poetry in literature in English in the Zimbabwean classroom. The research objective was the perception of ‘A’ level students and teachers in Nkayi District, Zimbabwe, towards the learning of poetry in Literature in English. A desktop research methodology was utilized, along with a qualitative case study design, and a thorough evaluation of literature on the perceptions of advanced level students and teachers towards learning poetry in English literature, as emphasized in the literature review. Constructivism’s theoretical perspective underpinned the study. Data were also collected using face-to-face interviews and focused group discussion instruments. The research findings revealed that the perceptions of ‘A’ level students and teachers in Zimbabwe, towards studying poetry in English were that the nature of poetry in English is very complicated and open to many interpretations. The findings also revealed that the historical context of the poems makes the learners understand, associate, and enjoy the history of the different poems. However, the poems taught at the ‘A’ level were too old and foreign to learners. The results also disclosed that the challenge in poetry emanates from sounds and vocabulary. The poetic devices and their level of difficulty may become a hindrance to effecting learning. Learners prefer constructivism and interactive methodologies, if teachers properly implement them in the teaching process, they will tend to get best results out of it. It emerged that failure of students to use the dictionaries may hamper in seeing the aesthetics in poetry in literature in English. This paper recommended that the strategies that can be recommended in order to change these perceptions are the learner centred methods of teaching, availability of resources and provision of functional fully stocked library for research purposes. This will foster the studying of poetry in Literature in English.
Framework for Evaluating the Success of Integrated Project Delivery in the Industrial Construction Sector: A Mixed Methods Approach & Machine Learning Application
Authors: Wood Xavier , Ghimire Prashnna , Kim Suryeon , Barutha Philip , Jeong H. David
Published: July 2024

Integrated project delivery (IPD) has gained traction as a collaborative approach to managing complexity and uncertainty in large industrial capital projects. While IPD emphasizes team integration and process alignment to drive better outcomes, the lack of standardized benchmarks to evaluate its performance relative to traditional methods persists as a barrier. To bridge this gap, this study developed a practical, and unbiased Project Success Framework (PSF) for IPD on industrial projects. A mixed methods research approach including subject matter experts’ survey, research charrette, and validation survey was conducted to build and validate the PSF. In addition, this study proposed a machine learning (ML)-based application tool embedding PSF to enhance the practicality and applicability of PSF. The machine learning-based application tool was validated by comparing the results with the PSF suggested in this research. The PSF developed in this study allows researchers and practitioners to empirically evaluate the integrated project delivery's efficacy on key industrial project outcomes. In addition, it offers a method to compare project delivery methods across diverse projects, aiding organizations in precise selection using empirical evidence for optimal results. Moreover, this framework aids clients in crafting shared risk/reward models that foster successful outcomes by encouraging desirable behaviors.
Challenges in Implementation of 7D-BIM for Infrastructure Asset Management: A Systematic Review
Authors: Laishram Boeing , Sood Rhijul
Published: July 2024

Infrastructure Asset Management (InfraAM)/Facilities Management (FM) representing operation and maintenance (O&M) phase, accounts for a substantial portion (85%) of project’s total cost, and hence, there is urgent need to invest in technology for infrastructure maintenance, repair, and rehabilitation. This can be done by implementing digital technologies, like Building Information Modeling (BIM), that can help in 3D visualization, 4D scheduling, 5D costing, 6D sustainability, and 7D O&M throughout service life of project. But, BIM’s implementation during O&M faces various challenges and in order to understand those challenges, a systematic literature review (SLR) through PRISMA technique was conducted using 89 peer-reviewed papers from three databases and quantitative and qualitative analysis were performed. The literature revealed various critical challenges (CCs) and success factors (SFs) that influences BIM implementation in O&M phase, but lacks interrelationship between them. Hence, the current study linked various CCs and SFs through a theoretical approach. The study found that role of government and contractual frameworks can help to eliminate most of the challenges. This novel approach could provide significant contributions by helping practitioners and policymakers to understand connections between CCs and role of SFs as potential solutions for enhancing 7D-BIM implementation.
From Post-Communist to Anti-Canon: The Rebels
Authors: Marić Antonela , Ćosić Ana
Published: July 2024

This paper conducts a short survey of the shift in the literary canon typical of the post-Homeland War period in Croatia. It is mainly owing to Croatian-Dalmatian authors who gathered around the magazine Feral Tribune and were inspired paradoxically by a rude, direct, and at times heavy and disturbing humour, and veristic-like scenes of everyday life, that the change happened. The shift was slow, and the authors, who were often accused of dissenting and publicly accused of activism, insisted on writing about issues other than mere patriotism, persistently succeeded in changing the mindset of the public. This would not have been possible had it not been for the political changes that took place in the country. Among other things, the paper explains the gradual appearance of the anti-canon, and argues that humour, notwithstanding the huge amount of cynical denunciations of political elites, served as a cathartic means of introspection, and a collective way of awakening from past dilemmas. Furthermore, the paper presents the situation from the 1990s to today, arguing against the hyperproduction of patriotic books, and explaining the gradual shift in the literary canon, owing to the transformation of literary practice.
Strategi Pemasaran Meningkatkan Hunian Tamu di VILLA DESAMUDA Seminyak
Authors: Sekardewi Ariana , Dewi Luh Komang Candra , Ariesta I Putu Agus Suarsana
Published: July 2024

This study aims to determine the competitive strategy implemented by the company. This research was conducted at Villa Desamuda Seminyak. The subjects in this study were department head managers and customers, totaling 14 people. This research was tested using SWOT analysis, namely by identifying various internal and external factors of the company, namely analysis of internal factors (strengths and weaknesses) and external factors (opportunities and threats) which were then formulated in the SWOT Diagram and SWOT Matrix. From the results of the analysis on the SWOT Diagram it appears that the position of Villa Desamuda Seminyak is located in Quadrant II which is described as a growth position, where internal factors total (2.68 – 2.97) therefore, appropriate strategies and results are needed to increase the guest house by increasing market development, market penetration and product development. As well as facing several opportunities and having various strengths that push to get these opportunities and it is recommended to carry out the SO, ST, WO, WT strategy. Strategies that can be implemented by companies are always issuing promotional packages and disseminating this information to anticipate more attractive offers from competitors, such as working with travel agents, updating information technology through digital marketing such as honeymoon packages, wedding packages, and promotions. meeting room.
Pengaruh Motivasi dan Lingkungan Kerja terhadap Kinerja Karyawan pada HOTEL GRAND INNA KUTA
Authors: Widyatmika Dewa Made , Wartana I Made Hedy
Published: July 2024

Competition in the hotel business in Bali is very tight, so that they are competing to become a hotel with the best service, one of the most famous hotels in Bali and in demand by foreign and domestic tourists, namely the Grand Inna Kuta Hotel which is one of the five-star hotels in Bali which has artistic and philosophical characteristics in its buildings. The problem raised in this study is whether motivation (X1) affects employee performance (Y) at the Grand Inna Kuta hotel, does the work environment (X2) affect employee performance (Y) at the Grand Inna Kuta hotel. The population in this study amounted to 61 person. This study uses the population as a sample. The data analysis technique used is descriptive analysis, data quality test, classical assumption test, multiple linear regression analysis, t-test analysis, and determination analysis. The results of the analysis show the regression model Y = 12.043 + 0.190X1 + 0.251X2. The conclusion obtained is that motivation (X1) partially has a positive and significant effect on employee performance (Y) at the Grand Inna Kuta hotel as indicated by the regression coefficient b1X1 which is positive. Work discipline (X2) partially has a positive and significant effect on employee performance (Y) at the Grand Inna Kuta hotel, this can be seen in the b2X2 coefficient which is positive. The magnitude of the influence of Motivation and Work Environment on Employee Performance at the Grand Inna Kuta hotel is 69.6% and the remaining 30.4% is influenced by other variables not examined in this study. The independent variable that has a dominant influence on employee performance can be seen in the value of Standardized Coefficients Beta, namely the motivation variable (X1) which is equal to 0.423 while the work environment variable (X2) is equal to 0.455.
Pre-Service Teacher’s Views on the use of Metaphors for Describing the Concepts of Uncertainty and Entanglement in Teaching Quantum Physics
Authors: Pospiech Gesche
Published: July 2024

Quantum physics is a fundamental theory of physics heavily relying on its description by mathematical structures. However, its successful handling ensures in no way its conceptual understanding. So teaching quantum physics in high school faces the problem of adequate  strategies. Often visualisations are used in order to provide anchors for students. These have to be chosen carefully to avoid misconceptions. At the same time an adequate verbal explanation of quantum phenomena or of their visualization is sought as physics language is shaped by classical physics. As an additional method for teaching we propose the use of metaphors for making the quantum physical mechanisms more insightful without interference from classical physics.
Scaffolding the structure of organic chemistry students’ multivariate comparative mechanistic reasoning
Authors: Caspari Ira , Graulich Nicole
Published: July 2024

Problem solving in all sciences requires the integration of multiple causal variables. Organic chemistry students often limit their reasoning about multivariate mechanism problems to single variables. To our knowledge, no teaching instrument that uses the structure of mechanistic reasoning to explicitly foster the consideration of multiple variables has been empirically evaluated to date. To fill this gap, we developed a scaffold based on findings in philosophy of organic chemistry and tested it in a qualitative interview setting. The scaffold provides a stepwise reasoning structure to compare the activation energy required for two different molecules to undergo the same type of mechanistic step. We found that the scaffold builds on what students already do when engaging in comparative mechanistic reasoning by themselves and supports their multivariate reasoning. The applicability of the structure of the scaffold in other contexts of mechanistic reasoning including physics is discussed.
The Effect of Computer Assisted Instruction with Simulation in Science and Physics Activities on the Success of Student: Electric Current
Authors: Bakaç Mustafa , Kartal Tasoğlu Aslıhan , Akbay Turgay
Published: July 2024

The aim of this study is to observe the effect of computer assisted instruction (CAI) with simulation technique used in teaching the subject of “Electric Current” on the successes of students. In the study pretest-posttest control group quasi-experimental method was used. 28 students of 11th grade in the department of chemistry in an industrial vocational school in Izmir-Konak formed the study group; later on one experiment (n=14) and one control group (n=14) were formed of these students. 16 open-ended questions about electric current were prepared as data collection tool. Pretests were applied on groups a week before the application of activities. “Electric Current” was taught to experiment group using CAI technique and to control group with traditional teaching methods. Posttests were applied one week later the application of activities. In the analysis of data Mann Whitney U-test and Wilcoxon signed rank test which are both non-parametrical, were used. At the end of the study it was detected that of the two groups whose successes were the same at the beginning, experiment group students on whom CAI method was applied came out more successful than control group on whom traditional method was applied. We can result that CAI technique increase the academic successes of students in the subject of “Electric Current”.
Efficacy of Creative Drama Techniques in Teaching Changes in Matter
Authors: Meşeci Bahri , Karamustafaoğlu Sevilay , Çakir Recep
Published: July 2024

In this study, the efficacy of using creative drama techniques in teaching the subject “changes of matter” for to the students of 4th grade Science and Technology was investigated. The sample group consisted of 27 students from the experimental group and 26 students from the control group formed the sample of the study. In order to collect data, a multiple-choice achievement test was developed and applied to assess the level of achievement level from the concepts of the related subject. The subject and its concepts were taught to the experimental group of students by the developed creative drama activities and to the control group of students by conventional methods. T-test and one-way ANCOVA were used by means of statistical analysis. Collected data was presented in charts and interpreted. Knowledge levels of the experimental and the control groups of students were observed to increase. However, in the analysis based on the achievement pre-tests applied to the experimental and the control groups, the difference between post-test results was found to be significant in the advantage of the experimental group. Teaching by using creative drama techniques was proved to be more effective in improving students' success. It is suggested that teachers need to be good drama leaders as well as having enough content knowledge in order to use creative drama techniques and therefore The Ministry of National Education should provide in-service training seminars.
The Impact of Argumentation on High School Chemistry Students’ Conceptual Understanding, Attitude towards Chemistry and Argumentativeness
Authors: Yalçın Çelik Ayşe , Kılıç Ziya
Published: July 2024

Argumentation activities, which have become prominent in the education literature, are an important process to improve conceptual understanding. According to researchers there is a relationship between the argumentation and conceptual change, and thus argumentation enhances conceptual understanding since an argument deals with disagreement, which is the first step of conceptual change. The purpose of this research is to explore the impact of classroom-based argumentation on high school students’ conceptual understanding of chemistry concepts, their attitude towards chemistry, and argumentativeness when compared to traditional teaching approach. A quasi-experimental, pretest-posttest, control group design was used. The study was conducted with 53 students in Grade 9 and with the same students in the Grade 10. Implementations lasted 13 weeks in the first year and 8 weeks in the second year. The concept tests, attitude scale towards the chemistry, and argumentativeness scale were applied on both groups. Interviews to reveal the level of student understandings not defined by the concept tests were conducted at the end of each year with 6 students from each group. According to multivariate analysis of variance results, it was found that the experimental group students’ conceptual understanding, attitude toward chemistry, and argumentativeness were significantly higher than those of the control group students.
The Effect of Problem Based Learning Approach on Conceptual Understanding in Teaching of Magnetism Topics
Authors: Kartal Tasoğlu Aslıhan , Bakaç Mustafa
Published: July 2024

The aim of this research is to examine effect of problem based learning on conceptual understanding in teaching of magnetism topics. The research was conducted with 48 students attending of 1st class of the Department of Science Education in a state university in Turkey and a quasi-experimental, nonequivalent control group design was implemented. A concept test of magnetism topics was developed to identify students’ conceptual understanding about units of “Magnetic Field and Its Effects”, “Magnetic Field Sources” and “Magnetic Flux and Induction Law”. The control group was taught using traditional teaching methods. The traditional approach to concept teaching consists of the following steps; giving the student the word that expresses the concept, specifying the definition of the concept and identifying and distinguishing qualities needed to understand the definition, to ensure that students find examples related and unrelated to the concepts. However, the experimental group was exposed to Problem Based Learning (PBL) activities involving problem scenarios. PBL is informed in sessions within which there are small collaborative groups comprised of 6 or 8 students with guidance from a tutor. They deal with scenarios involving several problems that are authentic, complex, illstructured problems to help students make connections between theory and real-world application. Instruction took 18 class hours in total. The data were analyzed using ANCOVA (Analysis of Covariance). The findings of the study revealed that PBL is more effective than the traditional teaching methods in improving students’ conceptual understanding about magnetism topics.
National and International Policies on the Use of Biosimilars: An Environmental Scan
Authors: Kim Jaemin , Arias Jessica , Gavura Scott
Published: July 2024

Biosimilars are biologic drugs that are highly similar to their reference biologics that were already authorized for sale.
Interchangeability is a term used to describe when 1 drug can be exchanged for another and is expected to have the same clinical effect. Interchangeability may allow 1 medicine to be substituted for another at the time of dispensing (automatic substitution). However, the decision to allow automatic substitution is made by each jurisdiction according to its own regulations.
Interchangeability of a reference biologic (the originator product) and a biosimilar is a designation in the US and Finland. The US, France, Germany, Norway, and Australia allow automatic substitution between reference biologics and biosimilars, whereas other countries do not. Interchangeability is limited to select products in the US and Australia.
The countries included in this Environmental Scan (N = 13) endorse starting patients who have not yet received treatment on a biosimilar. Switching between reference biologics and biosimilars is generally allowed in all the countries included in this review; however, many jurisdictions prefer switching be clinician led with ongoing clinical monitoring of patients.
Practices such as target setting, quotas, and financial incentives, as well as guidelines and recommendations for prescription of biosimilars, can be effective ways to encourage biosimilar use. Mandatory switching is also implemented in 11 Canadian jurisdictions.
Extrapolation is the regulatory and scientific process of granting a clinical indication to a medicine without clinical efficacy and safety data to support that indication. Extrapolation of indications for reference biologics to biosimilars is reasonable, provided several factors are comparable: mechanism of action across indications, pharmacokinetics and biodistribution, safety, immunogenicity, and other factors that affect the safety and efficacy for each indication and patient population.
Pricing and procurement practices vary internationally. Some countries implement policies controlling the list price of a biosimilar (and its reference drug less commonly) at the time of biosimilar launch. Pricing policies include a free-pricing policy (i.e., manufacturers are free to set the price of biosimilars) and mandatory price reductions. Tendering is the most common practice in procurement to achieve lower prices and to increase biosimilar uptakes in 8 countries reviewed in this Environmental Scan.
Biosimilar-related policies and markets are rapidly evolving, so recent changes might have not been fully captured in this Environmental Scan. Therefore, caution is required in interpreting the findings.
Analyzing the Accuracy and Performance of the Wang-Landau Algorithm for Calculating the Density of States in the Ising Model
Authors: Егоров В. И. , Крыжановский Б. В.
Published: July 2024

проведен анализ точности результатов и скорости выполнения алгоритма Ванга– Ландау при расчете плотности состояний для двумерной модели Изинга. Показано, что вычисление плотности состояний одновременно по энергии и намагниченности способствует увеличению точности расчета статистических моментов энергии. Относительная ошибка определения плотности состояний по энергии уменьшается с ростом размера решетки. Обнаружено, что для больших решеток невозможно заранее оценить время выполнения алгоритма, так как критерий перехода в режим 1/t не выполняется.

we analyzed the accuracy and performance of the Wang-Landau algorithm in calculating the density of states for the two-dimensional Ising model. Our findings indicate that calculating the density of states simultaneously by energy and magnetization enhances the accuracy of energy moment estimations. As the lattice size increases, the relative error in the density of states decreases. However, for large lattices, it is not possible to estimate the execution time of the algorithm in advance, as the criterion for switching to the 1/t mode is never met.
Analysis of Occupational Injury Rate Assessment Procedures Used by the Russian Emergency Control Ministry
Authors: Бушмелева К. И. , Мягких К. П.
Published: July 2024

в последние годы отмечается высокий и растущий уровень травматизма среди сотрудников МЧС России при исполнении ими служебных обязанностей. Это связано со спецификой работы спасателей, которые нередко подвергают свою жизнь и здоровье опасности, оказывая помощь пострадавшим в чрезвычайных ситуациях. Управление производственным травматизмом требует комплексного подхода и вовлечения всех заинтересованных сторон. Важно не только реагировать на произошедшие травмы, но и предупреждать их возникновение. На основе анализа причин происшествий необходимо разрабатывать и внедрять меры по предотвращению травматических ситуаций. Кроме того, обучение и повышение осведомленности персонала по вопросам охраны труда, пожарной безопасности и медицинской помощи при травмах также являются важными элементами управления производственным травматизмом. Высокий травматизм приводит к снижению боеготовности подразделений МЧС, а также к социальным и экономическим потерям из-за временной нетрудоспособности пострадавших. Поэтому проблема профилактики и снижения травматизма среди спасателей является чрезвычайно важной и требует детального изучения для выработки эффективных мер по обеспечению безопасности личного состава МЧС при выполнении поставленных задач. Для этого необходимо выявить основные причины травматизма среди сотрудников МЧС и разработать рекомендации по его снижению.

in recent years, the staff of the Russian Emergency Control Ministry have experienced a significant and rising number of occupational injuries. This high risk is inherent in rescue operations, where personnel frequently jeopardize their lives and health to assist victims. Managing occupational injuries needs a comprehensive approach involving all the stakeholders. It is crucial not only to address injuries when they occur but also to implement preventive measures. An analysis of the causes of these accidents reveals the need to develop and enforce strategies to avert hazardous situations. Additionally, training and raising awareness regarding occupational safety, health protocols, fire safety, and medical care are essential components of effective injury management. High injury rates diminish the readiness of the Ministry’s units and result in social and economic losses due to temporary incapacities. Therefore, the prevention and reduction of injuries among rescuers is a critical issue that demands thorough investigation. This study aims to devise effective measures to ensure the safety of the Ministry’s personnel on their missions. Identifying the primary causes of injuries and developing targeted recommendations for their mitigation is paramount to enhancing the overall safety and effectiveness of the Emergency Control Ministry.
Categorization of Fistula Condition in Hemodialysis Patients Using Spectral Analysis of Audio Signals
Authors: Сазонов С. А. , Горбунов Д. В.
Published: July 2024

в современном мире пациентам, состоящим на гемодиализе, необходимо постоянно следить за состоянием своей фистулы либо самостоятельно, либо посещая специалиста. Это может вызывать определенные трудности у человека, так как у каждого может быть свое восприятие состояния артериовенозной фистулы. В статье представлена разработанная автором модель машинного обучения, позволяющего классифицировать фистулу. Также рассмотрены различные методы фильтрации признаков для использования этих обработанных данных в классификации состояния фистулы. Кроме этого, автором предложена новая методика с использованием спектральных признаков, позволяющих более точно определять состояние пациента, находящегося на гемодиализе.

patients on hemodialysis need to constantly monitor the condition of their fistula, either independently or by visiting a doctor. This can be challenging, as each person may perceive the condition of their arteriovenous fistula differently. In this paper, we present a machine learning model to categorize fistula conditions. We considered various feature filtering methods to enhance the accuracy of the categorization. Additionally, we proposed a new method using spectral features, which allows for a more precise determination of the condition of patients undergoing hemodialysis.
An In-Depth Analysis of Demographic Shifts and their Effects on HIV/AIDS Prevalence in Eastern African Countries
Authors: Tile Augustino , Lihawa Robert Michael , Marandu James
Published: July 2024

Eastern African countries rank in the top ten most highly infected nations globally. To shed light on this, therefore this study investigated the impact of population dynamics on Human Immunodeficiency Virus (HIV) prevalence using a two-stage residual inclusion (2SRI) regression model to address potential endogeneity. The Hausman Test confirmed endogeneity among the variables, justifying the 2SRI model's application. Key findings indicate that population growth rate, fertility rate, and the population aged 15-64 significantly and positively affect Human Immunodeficiency Virus (HIV) prevalence. The instrumental variable, Children ages 0 to 14 young individual infected by HIV, 15 to 24 newly affected by Human Immunodeficiency Virus (HIV), and Children 0 to 14 living with Human Immunodeficiency Virus (HIV), was validated for strength, demonstrating robustness against weak instrument issues. Results revealed that a 1% increase in population growth rate leads to a 53% increase in Human Immunodeficiency Virus (HIV) prevalence. Additionally, the Dumitrescu & Hurlin Granger non-causality test established that population growth rate Granger causes Human Immunodeficiency Virus (HIV) prevalence. These findings underscore the critical role of demographic factors in shaping Human Immunodeficiency Virus (HIV) prevalence and highlight the necessity for targeted public health interventions to manage and reduce Human Immunodeficiency Virus (HIV) prevalence effectively.
UJI STABILITAS TEH HERBAL AKAR KAYU KUNING (ARCANGELISIA FLAVA(L.) MERR) DENGAN PENAMBAHAN DAUN STEVIA (STEVIA REBAUDIANA) SEBAGAI PEMANIS ALAMI UNTUK MEMELIHARA PENDERITA DIABETES
Authors: Ratnasari Dewi , Handayani Reti Puji , Rahman Listhia Hardiati
Published: July 2024

Latar belakang: Hasil inovasi produk teh herbal agar aman untuk dikonsumsi tentunya harus diuji terlebih dahulu. Salahsatu uji yang dilakukan adalah uji stabilitas. Uji stabilitas merupakan salah satu parameter kualitas yang dilakukan untuk mengetahui kemampuan suatu produk makanan atau minuman untuk bertahan dalam batas spesifikasi yang ditetapkan sepanjang periode penyimpanan sehingga masih layak untuk dikonsumsi.
Tujuan penelitian: Penelitian ini bertujuan untuk menguji kestabilan teh herbal kayu kuning selama penyimpanan pada temperatur ruang.
Metode penelitian: Teh herbal disimpan pada temperatur ruang selama 90 hari, kemudian setiap hari dicek nilai pH, sifat organoleptis, homogenitas dan jamur.
Hasil: Sedian teh herbal mempunyai pH 7, rasa manis, berbau bunga melati, air seduhan berwarna kuning kecoklatan, homogen serta tidak ditumbuhi jamur selama 90 hari masa penyimpanan pada temperature ruang.
Simpulan: Sediaan teh herbal stabil selama penyimpanan 90 hari pada temperatur ruang.
Towards a sector-specific CO∕CO2 emission ratio: satellite-based observations of CO release from steel production in Germany
Authors: Schneising Oliver , Buchwitz Michael , Reuter Maximilian , Weimer Michael , Bovensmann Heinrich , Burrows John P. , Bösch Hartmut
Published: July 2024

Abstract. Global crude steel production is expected to continue to increase in the coming decades to meet the demands of the growing world population. Currently, the dominant steelmaking technology worldwide is the conventional highly CO2-intensive blast furnace–basic oxygen furnace production route (also known as the Linz–Donawitz process), which uses iron ore as raw material and coke as a reducing agent. As a result, large quantities of special gases that are rich in carbon monoxide (CO) are by-products of the various stages of the steelmaking process. Given the challenges associated with satellite-based estimates of carbon dioxide (CO2) emissions at the scale of emitting installations due to significant background levels, co-emitted CO may serve as a valuable indicator of the carbon footprint of steel plants. We show that regional CO release from steel production sites can be monitored from space using 5 years of measurements (2018–2022) from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite, benefiting from its relatively high spatial resolution and daily global coverage. We analyse all German steel plants with blast furnaces and basic oxygen furnaces and obtain associated CO emissions in the range of 50–400 kt yr−1 per site. A comparison with the respective CO2 emissions on the level of emitting installations available from emissions trading data of the European Union Emissions Trading System yields a linear relationship with a sector-specific CO/CO2 emission ratio for the analysed steelworks of 3.24 % [2.73–3.89; 1σ], suggesting the feasibility of using CO as a proxy for CO2 emissions from comparable steel production sites. An evaluation at other steel production sites indicates that the derived CO/CO2 emission ratio is also representative of other highly optimised state-of-the-art Linz–Donawitz steelworks outside Germany and that the emission ratio is potentially valuable for estimating sector-specific CO2 emissions from remotely sensed CO emissions, provided that the underlying CO emission estimate is not affected by other sources.
A lightweight NO2-to-NOx conversion model for quantifying NOx emissions of point sources from NO2 satellite observations
Authors: Meier Sandro , Koene Erik F. M. , Krol Maarten , Brunner Dominik , Damm Alexander , Kuhlmann Gerrit
Published: July 2024

Abstract. Nitrogen oxides (NOx = NO + NO2) are air pollutants which are co-emitted with CO2 during high-temperature combustion processes. Monitoring NOx emissions is crucial for assessing air quality and for providing proxy estimates of CO2 emissions. Satellite observations, such as those from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P satellite, provide global coverage at high temporal resolution. However, satellites measure only NO2, necessitating a conversion to NOx. Previous studies have applied a constant NO2-to-NOx conversion factor. In this paper, we develop a more realistic model for NO2-to-NOx conversion and apply it to TROPOMI data of 2020 and 2021. To achieve this, we analysed plume-resolving simulations from the MicroHH large-eddy simulation model with chemistry for the Bełchatów (PL), Jänschwalde (DE), Matimba (ZA) and Medupi (ZA) power plants, as well as a metallurgical plant in Lipetsk (RU). We used the cross-sectional flux method to calculate NO, NO2 and NOx line densities from simulated NO and NO2 columns and derived NO2-to-NOx conversion factors as a function of the time since emission. Since the method of converting NO2 to NOx presented in this paper assumes steady-state conditions and that the conversion factors can be modelled by a negative exponential function, we validated the conversion factors using the same MicroHH data. Finally, we applied the derived conversion factors to TROPOMI NO2 observations of the same sources. The validation of the NO2-to-NOx conversion factors shows that they can account for the NOx chemistry in plumes, in particular for the conversion between NO and NO2 near the source and for the chemical loss of NOx further downstream. When applying these time-since-emission-dependent conversion factors, biases in NOx emissions estimated from TROPOMI NO2 images are greatly reduced from between −50 % and −42 % to between only −9.5 % and −0.5 % in comparison with reported emissions. Single-overpass estimates can be quantified with an uncertainty of 20 %–27 %, while annual NOx emission estimates have uncertainties in the range of 4 %–21 % but are highly dependent on the number of successful retrievals. Although more simulations covering a wider range of meteorological and trace gas background conditions will be needed to generalise the approach, this study marks an important step towards a consistent, uniform, high-resolution and near-real-time estimation of NOx emissions – especially with regard to upcoming NO2-monitoring satellites such as Sentinel-4, Sentinel-5 and CO2M.
Measurement report: Size-resolved secondary organic aerosol formation modulated by aerosol water uptake in wintertime haze
Authors: Duan Jing , Huang Ru-Jin , Wang Ying , Xu Wei , Zhong Haobin , Lin Chunshui , Huang Wei , Gu Yifang , Ovadnevaite Jurgita , Ceburnis Darius , O'Dowd Colin
Published: July 2024

Abstract. This study investigated the potential effects of changes in inorganics on aerosol water uptake and, thus, on secondary organic aerosol (SOA) formation in wintertime haze based on the size-resolved measurements of non-refractory fine particulate matter (NR-PM2.5) in Xi'an, northwestern China. The composition of inorganic aerosol showed significant changes in winter 2018–2019 compared to winter 2013–2014, shifting from a sulfate-rich profile to a nitrate-rich profile. In particular, the fraction of sulfate and chloride decreased, but that of nitrate increased in the entire size range, while ammonium mainly increased at larger particle sizes. These changes thus resulted in a size-dependent evolution in water uptake. Increased water uptake was observed in most cases, mainly associated with enhanced contributions of both nitrate and ammonium, with the highest increase ratio reaching 5 %–35 % at larger particle sizes and higher relative humidity (RH>70 %). The non-negligible influence of chloride on aerosol water uptake was also emphasized. The random forest analysis coupled with a Shapley additive explanation algorithm (SHAP) further showed an enhanced relative importance of aerosol water in impacting SOA formation. Aerosol water exhibited a significant contribution to SOA formation during winter 2018–2019, particularly at larger particle sizes. The SHAP value of aerosol water increased alongside higher levels of aerosol water, indicating an enhanced contribution of aerosol water to SOA formation. This implies that the majority of enhanced aerosol water uptake at larger particle sizes and high RH might facilitate the efficient aqueous-phase SOA formation. This study highlights the key role of aerosol water as a medium to link inorganics and organics in their multiphase processes. As challenges to further improve China's air quality remain and because SOA plays an increasing role in haze pollution, these results provide insight into the size-resolved evolution characteristics and offer guidance for future controls.
Rapid communication: Distribute paleoscience information across the next IPCC reports
Authors: Kaufman Darrell , Masson-Delmotte Valérie
Published: July 2024

Abstract. Rather than reverting to a dedicated paleoclimate chapter, knowledge about pre-industrial climate should be further integrated with other lines of evidence throughout the 7th assessment reports by the Intergovernmental Panel on Climate Change.