bluuebunny/crossref_metadata_2025 huggingface dataset:
Stem cell-based therapy for Alzheimer’s disease
Authors:   Research Institute of Molecular and Cellular Medicine, RUDN Medical Institute, Belousova E.V. ,   Federal State Budgetary Institution “Research Medical Genetic Center named after N. P. Bochkov”,   Institute of Physiologically Active Compounds of Federal Research Center of Problems of Chemical Physics and Medicinal Chemistry of the Russian Academy of Sciences, Salikhova D.I. , Nebogatikov V.O. , Ustyugov A.A. , Goldshtein D.V.
Published: May 2024

Alzheimer’s disease is a neurodegenerative disease characterized by extracellular accumulation of β-amyloid and intracellular aggregation of hyperphosphorylated tau into neurofibrillary tangles in the brain. It leads to progressive memory impairment and loss of daily living skills. Currently, there is no effective treatment for this disease, but the potential of stem cells for the therapy of neurodegenerative pathologies, inclu­ding Alzheimer’s disease, is being actively explored. Stem cell-secreted growth factors, extracellular vesicles can attenuate neuroinflammation and slow down cognitive deterioration during disease progression. This review highlights progress in preclinical studies using mouse models of different stem cell types as treatment stra­tegies for Alzheimer’s disease and provides insights into their translational applications. The article reviews the benefits, therapeutic effects and prospects of stem cells and their differentiating descendants, and provides current information on the mechanisms by which different types of stem and pluripotent cells are involved endogenous neurogenesis in Alzheimer’s disease. The data presented in this review contain information on cell therapy methods, both those already used in clinical practice and those being studied in various models, including transgenic mice. In the future, effective methods of obtaining and delivering of stem cells and their pro­ducts to achieve significant clinical results in patients with Alzheimer’s disease will be developed.
Soil nematode Caenorhabditis elegans as a model to study parasitic Nematoda
Authors:   Research Institute for Problems of Ecology and Mineral Wealth Use of TatarstanAcademy of Sciences, Kalinnikova T.B.
Published: May 2024

The free-living soil nematode Caenorhabditis elegans has been used as model organism in biological researches since middle of the 1960th. The short lifecycle, small body size, high fecundity, simplicity and cheapness of cultivation in laboratory, and safety for researchers are advantages of C. elegans as experimental model to study biology of Metazoa. The discussion about the possibility to use C. elegans as the model for parasitic nematodes started with the first mention of this nematode in scientific literature. The present article is the review of experimental studies demonstrating that in many cases substances toxic for C. elegans are also toxic for parasitic nematodes, and vice versa. This allows making a conclusion about the prospectivity to use C. elegans for initial screening for substances with nematicidal activity followed by their testing in experiments with parasitic nematodes. The possibility to use C. elegans for understanding mechanisms of nematicides action is also indisputable. On the whole one may conclude that C. elegans is a useful model both for searching new substances with anthelmintic activity and solution of the problem to overcome drug resistance of helmints.
Restricted Childhood, Interrupted Youth
Authors: Helfer Alix , Trane Ibsen Jakob , Särkiluoto Viola , Aapola-Kari Sinikka
Published: May 2024

In this study, we conduct a research overview and report on the rights of Nordic children and youth in the spheres of education and leisure during the COVID-19 pandemic. We follow up on our first report, ‘Children and Young People’s Participation During the Corona Pandemic’ report (Helfer et al., 2023). In the first report, we explained how the COVID-19 pandemic was handled in the Nordic countries and related initiatives to safeguard the rights of children and young people. In all countries, there has been a great concern about the impact of the pandemic and how the restrictions have affected children and youth, particularly vulnerable groups. 
For this report, we have charted research on the consequences of the pandemic on children and young people’s situation within the spheres of education and leisure, particularly from the viewpoint of participation. The focus has been on research conducted during the years of the pandemic 2020–2022 in Sweden, Denmark, Finland, and Norway, including related studies in Iceland, Greenland, and the Faroe Islands. We have extensively searched publications and filtered the most relevant studies for closer inspection. We bring forward research perspectives on children and young people’s varied experiences during the pandemic, their learning results, and their possibilities for meaningful leisure activities. Furthermore, we look at to what extent children and young people have been informed about and included in decisions that affect their lives. 
We compile and synthesise findings from the research literature to illuminate these questions. We also highlight potential gaps in the research regarding those elements that need to be investigated more extensively and parts where the long-term effects of the pandemic on children and youth need to be examined in the coming years.
Politics and Sufi Brotherhoods in Turkey: The Case of the Menzil Community
Authors: Carlucci Angelo Francesco
Published: May 2024

The article describes the political viewpoints and the relations with the conservative Turkish political parties of the Menzil community. This religious group is one of the most important Sufi brotherhoods in modern-day Turkey and is renowned for its modest image, its wealth, and its purported links with the AKP, the country’s ruling political party since 2002. The piece gives a brief history of the Menzil community and provides an overview of their social and economic profile. It then goes on to evaluate the electoral statistics of the community’s place of origin. It is argued that these outcomes could be replicated in the rest of the country as well, according to studies on the voting behaviour and political mobilization of smaller religious groups. The statistics and their analysis confirm that the Menzil brotherhood has consistently voted for conservative parties, having supported both the ANAP and the AKP. The popularity of these parties within the Menzil community can be attributed to both the disciples’ support for conservatism, the evolution of their social composition and tactical voting considerations.
Do Iranian Female Dancers Face a Risk of Chronic Negative Energy Balance? A Study on Energy Intake and Expenditure Among Non-professional Female Dancers
Authors: Hajian Maryam , Mohaghegh Shahram
Published: May 2024

Background: Female dancers are at risk of negative energy balance and its adverse effects. However, there is no evidence regarding the energy balance of Iranian female dancers in the literature. Methods: In a cross-sectional study of 25 female nonprofessional dancers, dietary intake was assessed using self-reported food diaries and recall interviews on three different days: One dance day, one workday without dance, and one weekend day without dance. Nutrient intake was analyzed and converted into protein, carbohydrate, and fat components, and subsequently into energy equivalents. Total energy expenditure was calculated based on physical activity measurements taken on dance, work, and rest days. The average daily energy intake and expenditure over a 7-day period were then compared. Results: Significant daily energy deficiency was observed based on the average over 7 days (- 772.7 kcal +/- 450 kcal, P-value < 0.05). Dancers consumed less protein and carbohydrates and more fat than the recommended daily values (P-value < 0.05). Conclusions: It appears that Iranian female dancers suffer from negative energy balance and nutritional malpractice. This may be related to underlying eating disorders or perceptions of body image, as well as inadequate nutritional knowledge. Consulting experienced sports nutritionists and other necessary specialists is recommended.
Acrylic Cranioplasty for Cranial Defects Following Meningioma Surgery: A Case Series
Authors: Thohari Khamim , Siahaan Salmon Charles P. T. , Yuwono Natalia , Idarto Areta , Dzaky Rafi Daffa
Published: May 2024

Background: Meningiomas are the most prevalent primary intracranial tumors, which are treated with surgical resection. This procedure may result in cranial defects, leading to significant functional and aesthetic impairments. Lately, acrylic cranioplasty has emerged as a promising technique for repairing these defects. Objectives: The current retrospective review investigated patients, who underwent reconstructive cranioplasty following meningioma surgery between November 2021 and March 2023. Methods: Thirteen patients, who underwent cranioplasty surgery to repair extensive skull defects following meningioma surgery, were included as subjects. Eleven patients were female and all of them had a history of using progesterone contraception for 10 to 30 years. Two patients were male and had comorbid diabetes mellitus. Patients’ ages varied between 39 and 59 years old. The interval between craniectomy and cranioplasty was about 45 days. The material used for cranioplasty was polymethyl methacrylate prostheses. It started with a CT scan to determine the location and size of the skull defect. We reconstructed the defect, using computer-aided design and computer-aided manufacturing (CAD/CAM) to produce a prosthesis that was specific to each patient. This 3D-printed prosthesis was designed to manufacture a mold, which was sterilized and intraoperatively used. Results: We conducted post-operative surgery follow-up for up to 3 months. After 1 month of post-operative surgery follow-up, 2 out of our 13 patients developed cerebrospinal fluid leakage. Conclusions: Acrylic cranioplasty using CAD/CAM technology and 3D printing has shown potential for producing patient-specific implants to repair extensive skull defects. However, careful monitoring for post-operative complications is essential.
Sub-chronic Toxicity Study of Heracleumlasiopetalum Extract Towards Healthy Sprague Dawley Rats
Authors: Sabah Hassan Enas , Rahman Heshu , Hamasalih Omer Shirwan
Published: May 2024

Background: Heracleum species are commonly used as spices, flavorings, and food additives. Members of the genus Heracleum offer many medicinal benefits but may also pose adverse effects on human health. Objectives: To prepare a crude leaf extract of Heracleumlasiopetalum and assess its toxicity profile towards healthy rats. Methods: The H. lasiopetalum leaf extract was prepared using pure methanol and ethyl acetate (1:10) at room temperature over a period of 72 hours. After filtration, the crude extract was obtained using a rotary evaporator at 40 - 45°C. Subsequently, various doses of the H. lasiopetalum extract were administered orally to healthy Sprague Dawley rats at three doses (300, 600, and 900 mg/kg body weight) for four weeks to test for toxicity. Blood samples were examined for hematologic and biochemical changes, while the liver, kidneys, and heart were examined for histopathological changes. Results: The toxicity study revealed no mortality at low and medium doses, as well as no clinical toxicity indicators. Additionally, there were no significant alterations observed in the haematological, biochemical, and histopathological profiles of the treated animals throughout the 28-day experiment. However, at high doses, the mortality rate was significantly elevated, accompanied by notable histopathological changes. Conclusions: Continuous administration of high doses of H. lasiopetaum may induce potential toxic effects in the treated animals.
Corporate Restructuring
Authors: Fancy Too
Published: May 2024

A corporate entity which is in financial distress can resolve its predicament in two broad approaches. The first is by engaging in a formal bankruptcy procedure, which commonly involves a court, and enables the debtor to deal with creditors collectively. Alternatively, it can engage in an out of court restructuring based around negotiations with individual creditors. This article focuses on the engagements of corporate restructuring outside the formal statutory insolvency procedure and in particular prenegotiated deals, private workouts and pre-packs. The first section of the article provides a background to the out of court restructuring and underscores the many advantages it holds as compared to the formal insolvency proceedings. It then explores the development and usage of selected informal approaches to corporate restructuring. It concludes with an analysis of the place of informal strategies in Kenya. It is argues for the need to develop a functional equivalent of a workout which allows for the possibility of having mechanisms tailored on realities of a developing economy. However, having an effective workout is hugely dependent on the existence of reliable formal mechanisms to at least act as a threat of enforceable legal approach, and the weaknesses inherent in the Kenya formal mechanisms may be an impediment.
Separation of Powers in Judicial Enforcement of Governmental Ethics in Kenya and South Africa
Authors: Ochieng Walter Khobe
Published: May 2024

The Kenyan Constitution, 2010 and the 1996 South African Constitution prescribe eligibility criteria for appointment into public office. The courts in both countries have been vested with the role of policing the boundaries of constitutionality of the exercise of power by the other arms of government. This mandates courts to ascertain whether an appointment by the executive branch meets the constitutionally prescribed threshold. The power of judicial review of appointments by the executive branch has brought the question of separation of powers between the judiciary and the executive into sharp relief. This paper discusses the separation and intertwining of powers between these two branches of government in the context of their respective roles in public appointments.
The Independence, Accountability, and Effectiveness of Constitutional Commissions and Independent Offices in Kenya
Authors: Khobe Ochieng Walter
Published: May 2024

One of the concerns that animated the search for a new constitution in Kenya was how to build more effective mechanisms for accountability. Towards this end, the 2010 Constitution of Kenya establishes constitutional commissions and independent offices in an attempt to dismantle and democratize the Kenyan state. This paper proceeds on the basis that what determines whether an independent institution ends up as an effective force for accountability in governance is its institutional design. The paper thus interrogates the constitutional and statutory design of the regime meant to effectuate the independence, accountability, and effectiveness of these independent institutions to determine whether they can deliver on their mandate.
Editorial
Authors: Ethics Kabarak Journal of Law and
Published: May 2024

We are pleased to present the seventh volume of the Kabarak LawJournal of Law and Ethics (KJLE), which focuses on the Kenyan ChildrenAct of 2022.In the lead up to this publication, Kabarak University in collaborationwith Save the Children (Kenya and Madagascar) successfully organiseda hybrid half-day conference to commemorate the Day of the AfricanChild on 16 June 2023. The conference brought together child lawscholars and practitioners to reflect on the theme ‘The rights of the childin the digital environment’. Professor Robert Nanima, Expert Memberof the African Committee of Experts on the Rights and Welfare of theChild (ACERWC), and Justice Heston Nyaga, Judge of High Court ofKenya, were among the chief guests. We are proud to publish ProfessorNanima’s keynote address in this volume.
Towards a Grammar of the Heart: al-Qušayrī's Naḥw al-qulūb
Authors: Iványi Tamás
Published: May 2024

The article provides an edition of the shorter version of al-Qušayrī’s Naḥw al-qulūb, based on the apparently oldest manuscript, preserved in the Staatsbibliothek zu Berlin (Ms. or. oct. 3805). This treatise represents a serious attempt to present Ṣūfī thoughts in a form analogous to an acknowledged science which had been then on the curriculum of teaching institutions for a long time. Naturally, the seriousness of the attempt does not mean that it may be considered fully successful as well. It is, however, worth studying since it reflects many interesting basic features of Ṣūfī thinking and their way of linguistic expression.
The Oral and the Written: Some Thoughts about the Quranic Text
Authors: Jones Alan
Published: May 2024

The article draws attention to the linguistic affinity of the Quran to three literary prose registers that existed in pre-Islamic Arabia, together with the need for a differentiation of the written text and the oral tradition.
The Notion of Stone in the Qur’ān
Authors: Frolov Dmitry
Published: May 2024

Having treated the notion of stone in the Bible in previous papers, the topic of this paper is the Qur’anic treatment of the two closely related motifs of stone and stoning. This theme in the Qur’an appears as a direct recollection of the Biblical texts, where images and motifs from the New Testament are superimposed upon the images of the Old Testament, with the addition of non-Biblical, Arabian and Mesopotamian, matter. The true originality of the Qur’anic message becomes visible when we analyze the process of combination and reinterpretation of the heterogeneous elements.
AN ORGANOLEPTIC ANALYSIS ON CUSTOMER ACCEPTANCE OF ‘READY- TO-USE’ MILLET-MADE JALEBI BATTER
Authors: Khorwal Manish Kumar , T Raghavendra , Bhanu Thashneem T
Published: May 2024

The world is amid several health disorders and chronic diseases caused by an imbalanced diet. Millets can play a vital role in human life to live healthy as millets can fulfil the nutritional requirements of the human body. Millets being a traditional crop, yet, there is less demand for direct consumption and we take this as an opportunity and aim in developing valueadded products that are ready to use milletmade jalebi batter which would further suit the requirement of the modern population. Keeping in mind the health and other benefits of millets, this study is a four-fold comparative study. The comparison was done based on the organoleptic evaluation done by 30 respondents on 2 different days and it was a blind tasting session where the respondents were not aware of the composition of the jalebi, that is, foxtail millet or sorghum millet or maida. The nutritional composition of the samples was calculated using a database method. As a preliminary step to analyse the market availability and the level of acceptability between consumers a questionnaire survey was done with 429 respondents and the study show a high level of acceptance to millet-made jalebi batter. Statistical analysis was done to analyse the results of the study and the tools used were paired t-test and One-way Anova. All statistical analysis was done with the help of Minitab‘18 software. The findings prove that based on organoleptic evaluation the taste, aroma, flavour of jalebi made out of millet and maida batter were identical. The dietary fibre was found more in sorghum millet jalebi followed by foxtail millet jalebi and it was found less in maida made jalebi. Due to lack of time and budget, the study focused on respondents of Bengaluru
OVERVIEW: MACHINE LEARNING
Authors: Jain Vaishali , Tiwari Shiv Kumar
Published: May 2024

Machine learning is a subfield of artificial intelligence that involves the development of algorithms that allow computers to learn from data, without being explicitly programmed. It involves the use of statistical models and algorithms to analyze and identify patterns in data, and make predictions or decisions based on that data. Machine learning algorithms are capable of improving their performance as they are exposed to more data, allowing them to automatically adapt and improve over time. Machine learning is widely used in a variety of applications such as image and speech recognition, natural language processing, recommendation systems, and predictive analytics
A REVIEW PAPER ON SELF-DRIVING CAR USING MACHINE LEARNING AND ARTIFICIALINTELLIGENCE
Authors: Jain Neha , Shukla Richa , Tamrakar Deepesh
Published: May 2024

A self-driving car is one that can sense its environment and avoid traffic and other obstacles with little assistance from a human. In spite of years of discussion and development, TESLA has successfully produced this most recent emerging technology in the automobile sector. Recently, these vehicles have started to show up on worldwide markets for usage in both private and public transportation (taxis, etc.). Waymo, UBER, Nissan, and Nvidia are just a few of the businesses taking part in the product development. With this kind of vehicle, all forms of motor transportation are more effective, safe, and secure. Human error may also be prevented when driving is done safely. The project's goal is to make the process go more quickly
LOAD BALANCING TECHNIQUES IN CLOUD COMPUTING ENVIRONMENT
Authors: Choudhary Dr. Sapna Jain , Gupta Priyanka
Published: May 2024

Virtualization, cloud storage, and networking facilities, plus applications all fall under the rubric of "cloud computing." A cloud is a set of clients, data centres, and distributed servers working stations. this necessitates fault tolerance, rapid provisioning, increased availability, greater performance, and less customer involvement A critical problem is to tackle is an effective distribution algorithm. It could be any one of three: CPU, memory, or delay. Mechanisms that are implemented and operationalized by the receiver of the form We want to develop an efficient load-balancing algorithm that maximises the throughput and minimise the latency of clouds of varying sizes (virtual topology depending on the application requirement). Dynamically allocating system resources can increase application performance in cloud computing. The results of this research show a dynamic resource allocation and dynamic server distribution that is better than the traditional priority algorithm. On the Cloud Network, the experiment was conducted. Our goal is to have as little reaction time as possible. Using the proposed function has allowed VM function scaling and migration to boost application performance
IN A CLOUD COMPUTING ENVIRONMENT, A SECURE MULTI-TIER AUTHENTICATION SYSTEM
Authors: tiwari Shiwani
Published: May 2024

Owing to its safe service, remote storage solutions are becoming more and more popular. Yet, it's likely that eventually, information regarding the security measures put in place on the server side will become public. New security dangers and assaults are consequently occurring in the cloud. Thus, a modernised and secure authentication technique is needed. Any cloud service that transfers sensitive or private information cannot be secured with single-tier authentication. When compared to single-tier authentication, multi-tier authentication is substantially more secure. Many multi-tier authentication methods are employed in computer settings, but none of them provide security against virtualization or insider attacks. In a cloud context, the server handles all aspects of authentication control. With a cloud system, it is therefore challenging to believe in a third party server. This study recommends a more advanced and secure multi-tier authentication method for getting access to cloud services
Breast Cancer Detection Using Machine Learning: A Promising Path to Early Diagnosis
Authors: Agrawal Arun , Savita Pankaj , Kushwah Dr. Jitendra Singh , Shrivastava Sagar
Published: May 2024

Breast cancer remains one of the most prevalent and life-threatening diseases affecting women worldwide. Early detection is crucial for successful treatment and improved survival rates. Traditional screening methods like mammography have played a significant role in breast cancer detection, but they have limitations. However, recent advancements in machine learning have opened up new avenues for more accurate and efficient breast cancer detection. In this article, we will explore how machine learning is revolutionizing breast cancer detection and its potential impact on improving healthcare outcomes
Framework of Precision Farming: A Review
Authors: Saxena Parul , Kumar Rakesh
Published: May 2024

Precision Farming is the new age technology, one should adopt to boost the process of farming and receive better output. Here, A Framework is proposed for obtaining the desired standard quality of the crop providing all the required conditions to achieve this. Some Parameters related to soil, environment can be considered to observe the crops for their well-being and to check the original status of the crop. Using IoT device, with in-built sensors to detect soil moisture and its nutrients, environmental parameters such as temperature and humidity, data goes to Cloud Server for further processing by running algorithms. Here, a deep review is presented so as to gain the insight in the technologies being adapted till now for the betterment of the agriculture
Distant Hybridization
Authors: Sargar Pramod , Deshmukh Smita , Naik Gajanan , Baraskar Swapnil , Mehtre Shivaji
Published: May 2024

Distant hybridization, which can shatter species boundaries, boost genetic diversity, and blend the biological traits of existing species, refers to crossings between two distinct species, genera, or higher-ranking taxa. It is a crucial method for developing genetic diversity, viable strains, and superior traits in new strains and populations. Wide crosses play a crucial role in crop improvement because they are an effective tool for transferring genes from wild forms and relatives into cultivated cultivars for disease resistance and for enhancing various quality parameters in cultivated plant species. Wide crosses should have specific problems including cross incompatibility, hybrid inviability, hybrid breakdown, and hybrid sterility in addition to applications. To solve these problems, certain methods are employed, including pollen mixing, bridge crossings, ploidy level modification, and embryo rescue
CARDIOVASCULAR DISEASE DETECTION USING MACHINE LEARNING TECHNOLOGY
Authors: Kumar Dr. C. Daniel Nesa , Raja Dr. J. Jeyaboopathi , Manjutha Dr. M. , Pradeep Mr. T.
Published: May 2024

Cardiovascular illnesses, often known as heart diseases or CVIs, have been the leading cause of death worldwide in the past few decades that are now a particularly serious illness, not just in India but throughout the entire globe. Therefore, a system that is dependable, accurate, and workable is required to identify these illnesses early enough for proper therapy. Large-scale and sophisticated data processing has been automated by using machine learning techniques and algorithms to a variety of wellness databases. Recently, a number of researchers have started employing different approaches to machine learning to assist the medical community and experts in the detection of heart-related illnesses. In our bodies, the cardiovascular system is the second most important function after the nervous system, which is given greater attention. It circulates blood, supplying it to every organ in the human anatomy. In the medical world, predicting the onset of cardiac disorders is an important task. Data analytics helps the medical center anticipate different ailments and is valuable for making predictions based on additional information. Every month, an enormous variety of patient-related data is kept up to date. Chronic infections can be predicted with the assist of the information that has been stored. Cardiovascular disease can be predicted using a few data mining as well as machine learning techniques, including support vector machines (SVM), Random Forest (RF), and Artificial Neural Network (ANN).Cardiovascular disease diagnosis and prognosis have become difficult issues for medical professionals and institutions, both domestically and internationally. The enormous number of fatalities with heart disease must be decreased, hence a rapid and effective diagnosis method must be found. In this field, data mining methods and automated learning processes are crucial. Scientists are working more quickly to create systems that use machine learning algorithms to assist physicians in identifying and predicting cardiac problems. The study the endeavor's primary goal is to use algorithms powered by machine learning to anticipate an individual's cardiac condition
TACKLING OF ENVIRONMENT BY ARTIFICIAL INTELLIGENCE
Authors: Verma Dr. Purnima
Published: May 2024

Artificial intelligence is revolutionizing our approach to tackling environmental challenges. Through initiatives like the Environment Situation Room and the International Methane Emissions Observatory (IMEO), AI is being leveraged to monitor air quality, measure carbon footprints, and track environmental indicators in real-time. By collecting and analyzing data, AI enables us to reduce technology industry emissions, improve energy efficiency, and implement wildlife conservation efforts more effectively. Moreover, AI facilitates the reduction of ICT emissions and ensures justice for the environment and human rights by providing insights into environmental impacts and holding accountable those responsible for environmental degradation. With AI, we have the tools to measure environmental footprints accurately and address pressing global concerns. The innovative use of technology like AI presents an opportunity to make significant strides in protecting our planet and creating a sustainable future
A REVIEW ON RESEARCH ORIENTED DATA PROCESSING FOR CLASSIFICATION, REGRESSION AND CLUSTERING
Authors: Sivagaminathan Vaishnavi , Pohekar Sahil , Bondre Harshal , Gupta Manjeet , Asatkar Akanksha , Meharkar Amisha
Published: May 2024

This research project focuses on the development of a comprehensive data processing framework tailored for advanced machine learning applications in the domains of classification, regression, and clustering. The primary objective of this endeavor is to empower users with the tools and methodologies necessary to effectively explore and exploit their datasets for predictive and exploratory data analysis. The project leverages state-of-the-art machine learning algorithms and data processing techniques to facilitate the training, testing, and evaluation of machine learning models across diverse application scenarios. By offering a flexible and userfriendly environment, it enables researchers and data practitioners to harness the full potential of their data. Key components of this project include data preprocessing, feature engineering, and model evaluation. Data preprocessing encompasses various techniques such as data cleaning, transformation, and normalization to ensure data quality and consistency. clustering data points has found widespread applications across diverse domains, ranging from healthcare and finance to image recognition and natural language processing. In this context, the present research endeavors to address the critical need for a robust framework that empowers users to engage in comprehensive data exploration, model training, and evaluation for classification, regression, and clustering tasks. Feature engineering involves the creation of meaningful and informative features that enhance the performance of machine learning models. Model evaluation incorporates a variety of metrics and visualization tools to assess the effectiveness and robustness of the trained modelsA
Shred Central: Estimating the user benefits associated with large public skateparks
Authors: Kemp Thomas
Published: May 2024

Skateparks, often called 'wheel parks,' are becoming increasingly common within communities worldwide. Despite this growth in parks, estimates show that the development of parks needs to catch up to users. Using a count data travel cost model, we estimate the adult user benefits associated with the Lauridsen Skatepark in Des Moines, Iowa – the largest in the United States. We estimate adult user benefits to be $61 per user per day and roughly $488,000 annually. This work contributes to the literature by being the first study to use econometric techniques to estimate skatepark user benefits. Second, we develop a simple and easy-to-apply method to assist municipalities in determining community skatepark needs. Third, our results support the literature showing that skateboarders are increasingly diverse.
Assessing the impact of digitalization on environmental efficiency: Do population factors and institutional factors Matter?
Authors: Hao Xiaoli , Li Yuhong , Wen Shufang , Zhang Lulu
Published: May 2024

The digital transformation provides an opportunity for the development of a green and low-carbon economy. This study used panel data collected from 30 Chinese provinces between 2011 and 2018, and assessed the impact of digitization (Dig) on environmental efficiency (EE). Quantile regression is employed to scrutinize the evolution of the marginal effect. From the perspectives of population and institutional factors, this study empirically investigates nonlinear relationships and potential mechanisms using Hansen threshold and mediation models. The findings reveal several key insights. Overall, levels of digitization and environmental efficiency (EE) are increasing with regional dispersion expansion, indicating a “polarization” characteristic. The impact of digitization on EE exhibits noticeable stage and regional heterogeneity. Analysis of population factors reveals that population structure, population size, and human capital trigger a sharp “marginal increase” of positive effects with single thresholds of 0.8155, 7.2284, and 11.0497, respectively. Analysis of institutional factors highlights the significance of fiscal policy quality (tax proportion), education expenditure, and tax system structure as important intermediaries. Finally, this paper presents corresponding policy implications.
Digging the Archives in Composition Stretch Pedagogies: Reclamation of Historical Rhetorics to Support Chicanx Emotions of Belonging
Authors: Ramirez Loretta Victoria
Published: May 2024

Initiating a transdisciplinary composition stretch pedagogy, I examine students’ excavations of archives to advance epistemological freedoms in support of rhetorical sovereignty in student writings. Grounded in Latinx studies first-year composition, I analyze archival projects wherein Chicanx students seek rhetorical inheritances, questing to locate textual homes and emotions of belonging.
Guided Pathways as Diverging Interest for the Two-Year College
Authors: Higgins Kirsten , Warnke Anthony
Published: May 2024

This article critiques the whole-college reform project dubbed Guided Pathways. The article describes how Guided Pathways research has failed to provide data that support the reform project’s claims, disputes the extent to which Guided Pathways can claim to be equity-oriented work, and ultimately identifies Guided Pathways as a reform project that diverges from the interests of the two-year college.
Symposium: Students Guiding Pathways
Authors: Toth Christie , Brown Emily , Hansen Priscilla , Burnham Laura , Zarate Adriana , Soranno Aloyious , Sanders Trey , Henderson Kathryn
Published: May 2024

In this symposium, seven community college transfer students present their perspectives on Guided Pathways curricular reforms. Drawing on published scholarship and policy documents as well as their own lived experiences, they identify positive aspects of the Guided Pathways model as well as shortcomings in its conceptualization and local implementation.
Editorial Introduction: A Critical Road Map: Introduction to the Special Issue on Guided Pathways
Authors: Toth Christie
Published: May 2024

We are now a decade into the call for comprehensive community college “redesign” known as Guided Pathways. This introduction provides an overview of the Guided Pathways model and its advocacy arm and reviews critiques of the model in education research and two-year college literacy studies. These reviews contextualize the contents of the special issue.
A mesterséges intelligencia lehetséges alkalmazása az egyetemi jóllét fejlesztésében
Authors: Gács Boróka , Varga Zsuzsanna
Published: May 2024

CÉLKITŰZÉS: A szervezeti és egyéni jóllét jelentőségének felismerésével a felsőoktatási intézmények megpróbálják megérteni és előmozdítani a jóllétet az egyetemi környezetben. A jóllét sokrétűsége, értelmezése és a felsőoktatásban való helye és alkalmazhatósága azonban még nem teljesen tisztázott. Célunk annak feltárása, hogy a mesterséges intelligencia milyen mértékben tudná támogatni az ezzel kapcsolatos tudományos kutatásokat és szervezetfejlesztést.
TELJESÍTÉS: Egy feltáró kísérletet végeztünk a ChatGPT 4.0 verziójával, amely lehetővé tette a Bing keresőmotor használatát. Összesen három kérdést (és egy tisztázó kérdést) tettünk fel angol nyelven 2023. október 5-én. Egyrészt arra voltunk kíváncsiak, hogy milyen tudással rendelkezik a mesterséges intelligencia (MI) az elmúlt évek átfogó jóllét kutatásainak tekintetében, vagyis tudományos célra alkalmazható-e az általa adott információ. Másrészt arra kerestük a választ, hogy erre a tudásra építve képes-e szervezeti és egyéni szinten a jóllét fejlesztésére vonatkozó tanácsokat adni. A javaslatok között szerepeltek mentálhigiénés szolgáltatások kialakítására, támogató környezet létrehozására, rugalmas tanulmányi irányelvekre, fizikai egészségre vonatkozó kezdeményezések és a személyes jóllét fejlesztésére vonatkozó tanácsok.
KÖVETKEZTETÉSEK: Az eredmények alapján a ChatGPT 4.0 hasznos kiindulópontot és inspirációt nyújthat a jólléti kutatások és a szervezetfejlesztési kezdeményezések terén, bár az így kapott válaszok minősége korlátozott a tudományos hitelesség és a valós források tekintetében. A mesterséges intelligencia alkalmazása elsődleges betekintést és inspirációt nyújthat a felsőoktatásban dolgozók és a felsőoktatás színvonalát fejlesztők számára, miközben támogatja a jólléti programok kialakítását és finomítását a felsőoktatási intézményekben.
Cikkismertetés: Az oktatás és az egészségmagatartás relatív jelentősége az egészség és a jóllét szempontjából
Authors: Dürgő Hajnalka
Published: May 2024

HÁTTÉR: A társadalmi-gazdasági pozíció és az egészségmagatartás mutatói az egészségi állapot változásainak széles körben használt prediktorai. Fontossági sorrendet közöttük nehéz megállapítani, mert az egészségmagatartás közvetítő szerepet tölt be a társadalmi-gazdasági pozíció és az egészség kapcsolatában. A cikk szerzőinek célja új ismeretek nyújtása volt arról, hogy a társadalmi-gazdasági pozíció és az egészségmagatartás hogyan kapcsolódik az egészséghez és a jólléthez.
MÓDSZER: A szerzők összesen 14.713 40–63 év közötti norvég állampolgár adatait elemezték. Külön regressziót végeztek az egészséggel összefüggő életminőségre (EQ-5D-5 L; EQ-VAS)és a szubjektív jóllétre vonatkozó két eredmény felhasználásával. Prediktorként az iskolai végzettséget és az egészségmagatartás összetett mérőszámát használták, mindkettőt négy kategóriába sorolva és illesztve a gyermekkori anyagi körülmények, a nem és életkor különbségeihez. Megbecsülték az egyes prediktorok százalékos arányát a teljes variációban, valamint az egészségmagatartás relatív jelentőségétaz oktatás-egészségügy összefüggésében.
EREDMÉNYEK: A referencia-modell — az egészségmagatartás kivételével — konzisztens lépcsőzetes grádienseket mutat az egészséggel összefüggő életminőségben. A legalacsonyabb és legmagasabb iskolai végzettség közötti különbség 0,042 volt az EQ-5D-5 L-nél és 0,062 az EQ-VAS esetén. Az egészségmagatartás paraméterének bevonásával az oktatási hatások jelentősen csökkentek, így az egészségmagatartás vette át a magyarázott egészségi variáció oroszlánrészét. Az egészségmagatartás az oktatás-egészségügyi grádiens 29%-át adta EQ-5D-5 L-rel mérve, és 40%-át EQ-VAS-val mérve. A szubjektív jóllét esetén erős egészség-magatartás-grádienst figyeltek meg, ellenben végzettség-grádiens nem volt meg-figyelhető.
KÖVETKEZTETÉS: Norvégiában, mint erősen egyenlőségpárti országban, intézményi kontextusban az egészség és a jóllét különbségeit inkább magyarázza az egyének egészségmagatartása, mint az iskolai végzettségük.
Introduction: The Stuff of Time
Authors: Eräsaari Matti
Published: May 2024

The introductory chapter outlines the book’s theoretical grounds. This is accomplished by building on E. P. Thompson’s classic conception of clock time in 19th-century UK, presented in an essay that contains more than just the task time/clock time binary it is best known for. Armed with Thompson’s conviction that clock time also has the capacity to stand for a wider scope of ideas than just puritan time thrift, the introduction weaves a route through anthropology’s recent temporal concerns to argue that many of the temporal anxieties reported by ethnographers worldwide could be viewed as questions of value rather than as ruptures in the temporal fabric. The trick, so to speak, is not to cast time in the role of the universal equivalent like the 1960s and 1970s time-allocationists did, but rather to understand that people allocate different values onto their time.
Literary journalism in Pakistan: A History of Magazines
Authors: Mustafa Abbas  , Dr.Samra Zameer
Published: May 2024

Prior to the establishment of Pakistan, the centers of literary journals were Bambi, Lucknow, Hyderabad, Delhi, Lahore, and Bhopal. After independence, only one literary center came to Lahore in the part of Pakistan. Although Rawalpindi, Karachi, Multan, Peshawar had the status of big cities, and various magazines were also published from these cities, it is not possible to count any of them as epoch makers. Only magazines published from Lahore were nurturing the mentality of the people of Pakistan. However, after the creation of Pakistan, after being cut off from the literary center, there was a vacuum in the literary atmosphere of Pakistan. But the process of filling this gap stated and many magazines which were published from Lahore before independence were re-published.it can be concluded from the above discussion that the role of magazines published before independence is more in the continuity of literary journalism in Pakistan. Which promotes literary journalism in Pakistan. This article covers the history of literary journalism and magazines in Pakistan.
Modelling wildfire risk using GIS and Analytical Hierarchy Process (AHP) in Aberdare afromontane forest ranges, Kenya
Authors: Kigomo John , Kuria Margaret
Published: May 2024

The knowledge of wildfire risk is crucial to sensitize and create awareness on fire prevention strategies and mobilization of resources to counter the spread after early detection.  This study was undertaken to determine the most important environmental and anthropogenic factors associated with wildfire risk in Aberdares ranges. An integrated participatory decisions and geospatial analysis was used. A pair wise comparative analysis of seven factors namely: proximity to roads, proximity to farming areas within the forest, mean precipitation, elevation, slope, land cover and NDVI was undertaken to attribute weight of each factor in relative to the other though Analytical Hierarchy Process (AHP). A wildfire risk equation was developed using the criteria weights of respective factors and risk map developed using QGIS version 3.16. Results indicated that land cover (0.39) and NDVI (0.23) were the most important factors in developing wildfire risk maps while proximity to roads (0.04) was the least. Wildfire risk maps shows that Aberdare ranges is within low (43%) and moderate (30%) risk zone and the area occupied by high and very high zones is 13% and 4 % respectively. The study recommends testing the applicability of developed method in other areas with different climatic and land cover characteristics.
คุณภาพชีวิตในการทำงานและความผูกพันต่อองค์กรของผู้ปฏิบัติงานฝ่ายบำรุงรักษาเครื่องกล การไฟฟ้าฝ่ายผลิตแห่งประเทศไทย
Authors:   , รัชตมุทธา พรรณอร
Published: May 2024

งานวิจัยฉบับนี้มีวัตถุประสงค์เพื่อศึกษาอิทธิพลของปัจจัยส่วนบุคคลและปัจจัยคุณภาพชีวิตในการทำงานที่ส่งผลต่อความผูกพันต่อองค์กรของผู้ปฏิบัติงานฝ่ายบำรุงรักษาเครื่องกล การไฟฟ้าฝ่ายผลิตแห่งประเทศไทย ซึ่งเป็นการวิจัยเชิงสำรวจ (Survey Research) ในรูปแบบการวิจัยเชิงปริมาณ(Quantitative Research) โดยการสำรวจความคิดเห็นและใช้การเก็บข้อมูลด้วยแบบสอบถาม จากกลุ่มตัวอย่างจำนวน 231 คน ที่มาจากการสุ่มตัวอย่างแบบโควตา (Quota Sampling) จากผู้ปฏิบัติงานฝ่ายบำรุงรักษาเครื่องกล การไฟฟ้าฝ่ายผลิตแห่งประเทศไทย แล้วจึงดำเนินการสุ่มตัวอย่างตามความสะดวก (Convenient sampling) ให้ครบตามจำนวนที่กำหนด จากนั้นนำมาประมวลผลผ่านโปรแกรมสำเร็จรูปทางสถิติ SPSS และใช้การวิเคราะห์สถิติเชิงพรรณนาด้วยวิธีแจกแจงความถี่ ค่าเฉลี่ย ค่าร้อยละ และค่าส่วนเบี่ยงเบนมาตรฐาน อีกทั้งในกรณีวิเคราะห์สถิติเชิงอนุมาน ได้เลือกใช้เทคนิคการทดสอบด้วยวิธีการถดถอยแบบพหุคูณ (Multiple Regression) เพื่อวิเคราะห์หาปัจจัยที่ส่งผลต่อระดับความผูกพันต่อองค์กร

ผลการศึกษาพบว่า ในแง่ภูมิหลัง ปัจจัยส่วนบุคคลด้านอายุ และด้านระยะเวลาการทำงานส่งผลต่อความผูกพันต่อองค์กรอย่างมีนัยสำคัญทางสถิติ กล่าวคือระยะเวลาและประสบการณ์ที่เพิ่มมากขึ้นตามอายุมีส่วนเหนี่ยวนำให้เกิดความผูกพันต่อองค์กรอย่างเห็นได้ชัด ทั้งนี้เมื่อพิจารณาถึงปัจจัยคุณภาพชีวิตในการทำงานของผู้ตอบแบบสอบถามในภาพรวมอยู่ในระดับมาก และมีค่าเฉลี่ยรายด้านอยู่ในระดับมากเช่นเดียวกัน อีกทั้งเมื่อนำไปใช้พยากรณ์ระดับความผูกพันต่อองค์กร ก็พบว่าปัจจัยคุณภาพชีวิตในการทำงานทั้ง 3 ด้าน ได้แก่ (1) ด้านชีวิตและการทำงานที่มีความสมดุลกันโดยส่วนรวม (2) ด้านลักษณะงานที่ส่งเสริมให้เกิดการเติบโตและมั่นคงในงาน และ (3) ด้านการได้รับค่าตอบแทนที่เป็นธรรมและเพียงพอ ต่างส่งผลต่อระดับความผูกพันต่อองค์กรอย่างมีนัยสำคัญทางสถิติ ดังนั้นปัจจัยทั้ง 3 ด้านนี้จึงเป็นสิ่งที่องค์กรต้องหันมาให้ความสำคัญ เพื่อเป็นรักษาไว้ซึ่งผู้ปฏิบัติงานของตนให้เกิดความผูกพันและคงอยู่กับองค์กรอย่างยั่งยืน