bluuebunny/crossref_metadata_2025 huggingface dataset:
Methodologies of meat analogue production and nutritional perspectives: a review
Authors: Shi Yizhe
Published: December 2024

With increasing global population and environmental concerns, the development of meat analogues, including plant-based proteins and cultivated meat, has become a solution for elevating global protein production and addressing sustainability issues. North America and Europe lead the meat analogue market, driven by elevated consumer awareness of health and environmental concerns. Under the influence of western diet, the Asian market is also poised for growth. While cultivated meat industry remains immature, advancements in production and cost reductions are expected to boost its market share over time. Although research on meat analogue methodology has increased in recent years, reviews that combine production methodologies and nutritional perspectives remain uncommon. This review comprehensively analyses the production methods, nutritional values, and market prospects of meat analogues. Meat analogue production has great potential in reducing water consumption, promoting sustainability, and improving animal welfare. Meat analogue provides high protein content and balanced amino acid profile, though certain micronutrient deficiencies due to production processes. This review outlines directions for further research in meat analogue production, emphasizing the importance of enhancing production efficiency and nutritional fortification to address food insecurity and environmental damage.
Overview of Diabetes mechanism and therapy
Authors: Ye Jiawen
Published: December 2024

The diabetes patients continuous increasing these days and many therapies come out. Till now, there is about 0.537 billion patients and mainly above forty years old and had a high proportion in Africa and Asia. Now drug treatment, operation and life management to reduce the negative effect cause by diabetes or even cure. The mechanism of diabetes type 1 is a kind of autoimmune disease and mostly mediated by T lymphocytes, islet beta cells are attacked and destroyed, causing inflammation, resulting in absolute insufficient insulin secretion and onset. Type 2 diabetes is caused by insufficient amount of inuslin.
Clinical application and future development trend of mRNA nanomedicine
Authors: Ren Jieyu
Published: December 2024

mRNA therapy is an emerging clinical therapeutic approach. According to studies, mRNA technology has entered into a stage of rapid development, and there are several significant achievements about some illness cancer such as cancer treatment, with various of mRNA nano-medicine have shown some promising results in clinical research. In recent years, with the deepening of research, mRNA nano-medicine shows the excellent potential in the prevention and treatment of diseases. 2020, with the first mRNA vaccines, which have been used for the treatment of the novel coronavirus, mRNA technology become the main focus of medical attention in the last decade. Based on the literature about mRNA in past five years and reference to the data and results of several clinical trials, this article adopts an approach of summary overview reviewing clinical applications of mRNA nano-medicine and predicting the tendency of future development. In the future, mRNA nanotechnology will become the mainstream method of diseases treatment, and bring hope to more patients. In this paper, we conduct a comprehensive description of mRNA nano-medicine from the following aspects: history and action mechanism, clinical application, current research status and future development trend.
Small-Molecule Drugs target Androgen Receptor (AR) signaling pathway for Prostatic Cancer Treatment
Authors: Wang Zian
Published: December 2024

The fourth most common cancer worldwide is prostate cancer (PCa), which is also a common cancer in men. Its still a serious health problem, even though the treatment is improving. The androgen receptor (AR), a nuclear receptor for steroid hormones, is a transcription factor that is ligand dependent. Small-molecule drugs targeting AR have been shown to contribute to the treatment of PCa. These drugs inhibit the growth of PCa cells by blocking or regulating the AR signaling pathway and inhibiting the binding of androgens (such as testosterone or dihydrotestosterone) to receptors. In this paper, the principle of AR signaling pathway in PCa and mature drugs, including abiraterone and bicalutamide, was discussed. The clinical application, efficacy, and limitation of castration-resistant prostate cancer (CRPC) were also analyzed. Through the in-depth discussion of PCa treatment of small and medium-molecule drugs and its underlying principles, this paper provides a theoretical basis for more accurate and effective treatment programs in the future.
The Resistance to EGFR-TKIs in Non-Small Cell Lung Cancer
Authors: Lyu Yi
Published: December 2024

Lung cancer has emerged as a highly aggressive malignancy posing a significant global health hazard, with a particular concern for the rising incidence and mortality of gene-altered non-small cell lung cancer (NSCLC). As the prevalence of NSCLC rises, the investigation and selection of tumor treatment techniques are gaining significance. The treatment of individuals with genetic mutations in advanced NSCLC has emphasized the application of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Early and subsequent generations of EGFR-TKIs have demonstrated clinical efficacy in NSCLC patients carrying select genetic alterations. Osimertinib, a third-generation EGFR-TKI, has been sanctioned as the standard first-line therapy and is also utilized as a second-line option for individuals who develop the T790M resistance mutation following prior EGFR-TKI treatment. Approximately 10 to 30 percent of patients diagnosed with NSCLC exhibit EGFR mutations. This leads to abnormal activation of cancer genes and inactivation of tumor suppressor genes, resulting in poor prognosis for patients. This paper aims to analyze the development and resistance processes of EGFR inhibitors, thereby enhancing the comprehension of the resistance pathways to EGFR-TKIs.
Effect of HNF4 on the Process of Liver Cancer and as a Potential Therapeutic Target
Authors: Zhang Nachuan
Published: December 2024

As a ligand-dependent transcription factor of the nuclear receptor family, HNF4 can be regulated by a variety of pathways, and can also be recruited to the DNA sequence through a variety of pathways to regulate downstream target genes by virtue of its three-dimensional structure. HNF4 is usually enriched in organs such as the liver, gallbladder, pancreas, kidneys, etc., and mutations in the HNF4A gene can cause lesions in these organs, including diseases such as liver cancer. However, the pathological role of HNF4 in different diseases is not well understood. Previous studies have shown that 12 variants of HNF4 are jointly regulated by the P1/P2 promoters. HNF4 can be recruited to specific DNA sequences by intermediates (including MLL4, KAT2B, etc.) through DNA-binding domain (DBD) after ligand-binding domain (LBD) has bound ligands. The review goes on to enumerate several pathways, pathways in which HNF4A expression is regulated, and HNF4 acts on promoters or enhancers to regulate the expression of downstream target genes. KDM1A regulates the HNF4A expression pathway, mutations in HNF1 POU domain to downregulate HNF4A promoter activity and NRF2-mediated STAT3 activation to silence HNF4A expression through miR-4, and the functional differences of different subtypes of HNF4 regulated by P1/P2, and the interaction between HNF4 and HIC1 affects the function of HNF4 in regulating FUF/FDF. This review aims to stimulate further research on HNF4, and the specific pathogenesis is clearly elucidated to find suitable targets to treat the corresponding diseases.
The Role of Circadian Rhythm Disruptions in Alzheimers disease Progression: Mechanisms, Implications, and Therapeutic Strategies
Authors: Cui Qianze
Published: December 2024

Circadian rhythm disruptions have emerged as a critical factor in the development and progression of Alzheimers disease (AD). These disruptions affect key processes such as beta-amyloid (A) aggregation, tau protein hyperphosphorylation, and impaired protein clearance, all of which contribute to neurodegeneration. Melatonin, a hormone that regulates the circadian cycle, plays a neuroprotective role but decreases with age, especially in AD patients. Research suggests that melatonin supplementation may help mitigate the effects of A accumulation, tau-related pathology, and oxidative stress. Additionally, bright light therapy (BLT) has been shown to improve circadian rhythm regulation, enhancing sleep quality and cognitive function in individuals with AD. This review highlights the intricate relationship between circadian rhythm disruptions and AD pathology and examines therapeutic interventions such as melatonin and BLT that offer potential benefits in managing the disease.
An Empirical Study of the Markowitz Mean-Variance Model on the Nasdaq Stock Market
Authors: Hu Ziyi
Published: December 2024

In the vast global investment market, balancing risk and return is a pressing issue for investors. A significant part is played by the Markowitz model, which provides investors with a means of calculating risk and return. This paper focuses on analyzing portfolios using the Markowitz mean-variance model by applying empirical daily stock data from 11 different companies (AAL, NYA, IXIC, HSI, GDAX, KS11, SSMI, SBUX, KDP, NSRGY, and SJM) over the period from January 2014 to April 2014. The study also optimizes investments by screening for short-selling opportunities. NYA, IXIC, HSIA, and SJM were the four stocks that were eliminated following four rounds of computation. As a result, the paper identifies the optimal portfolio strategy and concludes that KS11 stocks exhibit the best behavior. The Markowitz model allows investors to efficiently evaluate risk and return while increasing their income. In actual circumstances, the Markowitz model is quite useful and practical.
Nuclear Energy and Accident: A Case Study of the Fukushima Wastewater Release
Authors: Wang Ruiwen
Published: December 2024

The 2011 Fukushima nuclear disaster caused extensive, long-term damage to the surrounding ecosystem. Twelve years later, the Japanese government faces a contentious decision: releasing accumulated radioactive wastewater from the Fukushima site into the Pacific Ocean, sparking widespread debate over environmental and public health risks. This study takes the Fukushima wastewater release as a case study to examine the broader implications of nuclear energy and accidents. Using detailed comparisons, graphs, and calculations, we assess the potential environmental, economic, and political ramifications of the release, aiming to provide an approximate timeline and magnitude of effects, while addressing critical data gaps concerning nuclear wastewater discharge. The findings will offer essential insights for reducing, mitigating, and preventing detrimental impacts on people's lives. They will also guide policymakers in developing strategies that prioritize environmental protection, public health, and global economic stability, while applying lessons learned from Fukushima to prevent future disasters.
Research on the Application and Expansion of Fama-French Model in Healthcare Industry (ETF)
Authors: Hao Jiawen
Published: December 2024

Research about the Fama-French (F-F) model has long attracted significant academic attention. This study explores the application and extension of the F-F model within the healthcare sector. Using the Vanguard Health Care ETF (VHT) as a representative of the healthcare sector, this research examines its monthly returns over the period from 2014 to 2024. A comparison between the Fama-French three-factor (FF3) and five-factor models (FF5) reveals that the FF5 model is more suitable for the healthcare industry, the impact on ETF returns increased by 3.82%. To identify a model better suited for the healthcare sector, this study extends the FF5 model by incorporating an additional 11 factors. Through stepwise regression and significance testing, the final model with the highest adjusted R value and strongest explanatory power for ETF returns was constructed. The independent variables in this Extension model include market excess returns (Rm-Rf), HML, CMA, the momentum factor (MOM), inflation rate (INFR), employment change rate (EMP), and the PPI for medical laboratories (PPILAB). Compared to the original FF5 model, which had an adj R of 0.6980, the Adj R of the Extension model increased to 0.7359, demonstrating a better fit for the healthcare industry. As a result, with the help of this study, investors will be better equipped to use the F-F Model and make informed investments in the healthcare sector.
Analysis of the Development of Datong Tourism Industry from the Perspective of the Black Myth Wukong
Authors: Zhao Ziying
Published: December 2024

The explosive fire of the black myth Wukong is not only its technical production, but also its stunning location. This paper is going to explore six of these tourist venues and Datong, a city full of tourism consumption potential. The relationship between tourism and urban development will be explored through practical cases. This paper will refer to national policies and discuss related topics of tourism and urban transformation. And put forward ways to expand the international market. Datong has the most locations for the black myth of Wukong with six. At the same time, in the process of the transformation of Datong from an energy-based economic city, tourism needs to publicize Datong in the process of playing its advantages in promoting economic growth. This paper not only analyzes the benefits in other similar Internet celebrity tourism cities, but also analyzes the new opportunities in the continuous improvement of the transportation network.
Stock Price Forecasting for Xiaomi Auto: Application of ARIMA and GARCH Models
Authors: Cao Yaoyin
Published: December 2024

Since Xiaomi Corporation entered the market for electric vehicles, the volatility of its stock price has attracted a lot of attention from investors. This study's objective is to foresee the stock price of Xiaomi Auto by constructing GARCH and ARIMA models in R. By conducting a stationarity test and differencing the previous stock price information of Xiaomi Auto, and then the stock price for the upcoming 30 days is predicted using an ARIMA (0,1,0) model. The findings demonstrate that while the ARIMA model predicts a short-term phase of relatively stable stock price, the widening prediction intervals suggest increasing uncertainty. The construction of a GARCH (1,1) model aims to more accurately represent the fluctuations in the stock price. Predictions from the GARCH model point to higher price volatility in coming 30 days. Based on these model outcomes, this paper proposes short-term and medium- to long-term investment strategies for investors and discusses the limitations of the models as well as potential improvement for future research. This research improves the understanding of stock price trends and volatility in the electric vehicle market. It provides practical insights for better investment decisions. The study also advances financial forecasting methods, making them more applicable to real-world market behavior.
The Relationship Between US Dollar Index and US 10 Year Treasury Bond
Authors: Yan Shukun
Published: December 2024

As a key indicator of the global financial market, the relationship between the US 10-year treasury bond and the US dollar index has attracted extensive attention from the academic community. To explore the correlation and future trends between the two. This article collects relevant data, analyzes the relationship between ARIMA and VAR models, and makes future predictions. The research results show that in the future, the dollar index will remain around 80 points and treasury bond will remain around 4 points. But the correlation between them is weak. At the same time, because the trend of the 10-year treasury bonds of the United States is affected by many factors, more factors need to be considered for their future trend. This study provides empirical evidence for the development of the US economy and lays the foundation for future investors' asset allocation, which has important practical significance for the development of financial markets.
Study on Stock Price Fluctuation of DHL after Cross-border Merger and Acquisition
Authors: Bai Yawen
Published: December 2024

In the 21st century, global logistics companies have launched a huge wave of mergers and acquisitions (M&A), including many international logistics giants launching crazy M&A to adapt to the expansion strategy of globalization. The cross-border logistics market is an extremely attractive cake in the logistics market, but the express delivery business in many low tier cities in many countries has long been dominated by many local enterprises, and its market has not been fully developed and does not meet international standards. The world has experienced five waves of M&A, and now this trend is affecting the development of DHL and has a significant impact on the evolution of the logistics industry. This article introduces the background of the topic selection, research objectives and significance, as well as the examination of whether M&A are necessary. This article uses the ARIMA-GARCH model to predict DHL's future stock price, and confirms the relationship and impact between its stock price and M&A behavior by comparing actual data. Based on the company's stock liquidity, the M&A effect is evaluated. The research results indicate that M&A can enable companies to quickly acquire the resources needed for development, generate synergies through integration, establish core competitiveness, and gain competitive advantages.
The Shock of Emergencies on Financial Markets and Its Countermeasures
Authors: Li Xiaotong
Published: December 2024

In recent years, the frequent occurrence of major emergencies and their potential impact on the financial market have brought great challenges to the stability and development of the global economy. In this context, it has become an urgent issue to explore how major emergencies affect the financial market and take corresponding measures to deal with them. Through literature research and analysis, this paper concludes the impact of natural disasters, accidents and disasters, public health emergencies and social security emergencies on the financial market respectively, clarifies the transmission path of the impact including the social level, the real economy level and the policy level, and puts forward suggestions for the construction of financial emergency management. That is, to improve the precise prevention and control system, optimize the domestic market environment and the rule of law of financial emergency management rights. The research results are helpful to maintain the stability of the stock market and the overall situation of economic development in major emergencies.
Research on the Impact of ESG Rating Divergence on Financial Markets
Authors: Zhang Jinming
Published: December 2024

This study explores the multifaceted impacts of Environmental, Social, and Governance (ESG) rating divergence on financial markets, focusing on both equity and bond markets. Despite the growing importance of ESG criteria in investment decisions, discrepancies in ESG ratingsstemming from varying methodologies, standards, and data qualitypose significant challenges. We analyze how these divergences affect corporate reputations, influence investor behavior, and consequently, impact market volatility, funding costs, and liquidity. Our findings indicate that ESG rating discrepancies can lead to increased funding costs, heightened market volatility, and reduced market liquidity, all of which contribute to increased uncertainty for investors. The study suggests that the resolution of these issues requires the harmonization of ESG standards, enhanced regulatory oversight, and greater transparency in rating methodologies. Through comprehensive analysis, this paper contributes to understanding the implications of ESG rating divergence and proposes actionable strategies for stakeholders to mitigate its adverse effects, thereby fostering a more stable and transparent market environment.
Analysis of the Current Development Status and Problems of New Energy Enterprises: Taking Tesla as an Example
Authors: Zhang Lehan
Published: December 2024

This paper aims to address the current development status and problems of new energy vehicle companies, taking Tesla as an example. The research question is to understand the challenges of low brand awareness and inadequate crisis public relations handling faced by Tesla in emerging markets and second- and third-tier cities. This is important to the academic field because it provides insights into the development and challenges of the new energy vehicle industry. This study adopts a case analysis method, taking Tesla as an example to study the current development status of new energy companies and some related problems, and proposes some countermeasures and suggestions for the problems found. The results show that in some emerging markets and smaller cities, Tesla has limited brand awareness due to less promotion compared with traditional car brands and consumers' trust in traditional brands. In terms of crisis public relations, Tesla's response is sometimes not timely or transparent enough. The solutions proposed include holding more events and developing personalized marketing strategies in these areas, as well as establishing a rapid response mechanism and strengthening communication with consumers and regulators. The impact of this work is to provide Tesla with practical suggestions to improve its brand image and competitiveness, and also provide valuable lessons for other new energy vehicle companies to deal with similar problems.
Differential Analysis Based on Different Decomposition Methods of Time Series
Authors: Huang Ruiying
Published: December 2024

A detailed analysis of four popular time series decomposition methods: Classical, X11, SEATS, and STL is provided in this study, with a focus on their applications, strengths, and limitations. Understanding seasonal patterns in time series data is an important aspect in several fields such as economics or environmental science. The R package seasonal was employed to conduct the decompositions on the official data of National Oceanic and Atmospheric Administration (NOAA) Climate Data from January 1980 till July 2024. It offers a detailed analysis of the performance of each method in isolating trends, seasonal components, and residuals. Findings reveal that although all methods can be used for time series data decomposition, their success is influenced by data nature and particular analytical tasks. For instance, SEATS is robust enough to handle irregularities while Classical decomposition wins when it comes to simple understanding. Similarly, X11 methods were known for lack of flexibility as well as recurring seasonal changes sensitivity, where STL is particularly efficient for varying seasonal patterns datasets with nonlinearity trends. From the findings, it can be concluded that it is important to choose the appropriate decomposition method to increase reliability and make appropriate adjustments in the forecasts incorporating time series data.
Uhasta suojelun kohteeksi ja välineeksi
Authors: Kalakoski Iida , Sirén Riina
Published: December 2024

Katsausartikkeli tarkastelee suomalaisten, vuosina 1964, 1985 ja 2010 voimaanastuneiden rakennussuojelulakien suhdetta ihmisen toimintaan ja toimijuuteen. Keskeinen havainto on, että rakennussuojelulakiemme säädöskieli sivuuttaa ihmistoiminnan ja mikäli ihmisen toimintaan viitataan, se nähdään, erityisesti kahdessa ensimmäisessä laissa, ennen kaikkea rakennusperinnön arvoja uhkaavana tekijänä. Kun lakitekstejä  ja niiden muutosta seuraamalla voidaan huomata, että suomalainen lainsäädäntö kehittyy tiiviissä vuorovaikutuksessa kansainvälisen rakennus- ja kulttuuriperintöä käsittelevän keskustelun kanssa.
Neuvottomille
Authors: Lahtinen Anu
Published: December 2024

”Oletko neuvoton”, tiedusteli René Gothóni opiskelijoille tarkoitetussa oppaassaan kolmisenkymmentä vuotta sitten.1 Neuvottomaksi näytti julistautuvan muutama kirjallisuusalan toimija, kun Tekijänoikeusneuvosto antoi lokakuussa 2023 lausuntonsa teoksien lainaamisesta toisessa teoksessa.
Penerapan Model Integratif untuk Meningkatkan Pemecahan Masalah Siswa pada Mata Pelajaran IPA Kelas 7 di Sekolah Menengah Pertama
Authors: Fauziyyah Chintya Hana Dhiya , Arianto Fajar , Kholidya Citra Fitri
Published: December 2024

Penelitian ini bertujuan untuk menganalisis peningkatan penerapan model integratif terhadap pemecahan masalah siswa SMP pada mata pelajaran IPA. Dalam penelitian ini menggunakan jenis peneliatan quasi eksperimen dengan desain non-equivalent control group design. Terdapat dua kelompok, yaitu kelompok eksperimen yang menggunakan model integratif dan kelompok kontrol yang belajar melalui model discovery learning. Peneltian ini menunjukkan bahwa penerapan model integratif secara signifikan meningkatkan kemampuan siswa dalam memecahkan masalah di mata pelajaran IPA kelas 7 dibuktikan dengan menggunakan instrumen tes serta lembar observasi untuk mengamati keterlaksanaan model integratif dalam proses pembelajaran. Selain itu, dalam meningkatkan kemampuan memecahkan masalah model integratif ini juga memperkuat kemampuan berpikir kritis siswa, seperti menganalisis, mengidentifikasi, mengevaluasi, dan menyimpulkan berbagai persoalan. Dalam penelitian ini menunjukkan bahwa nilai rata-rata pretest kelas eksperimen sebesar 59,43, dan kelas kontrol sebesar 58,8. Kemudian untuk nilai posttest pada kelas eksperimen mempunyai nilai rata-rata sebesar 86, sedangkan kelas kontrol mempunyai nilai rata-rata sebesar 73. Oleh karena itu, model integratif terbukti dapat meningkatkan pemecahan masalah siswa pada mata pelajaran IPA di kelas 7 Sekolah Menengah Pertama.
Pengembangan Kurikulum PAI UIN Sunan Kalijaga Yogyakarta Mengacu pada KKNI dan SN-DIKTI
Authors: Khalimah Siti , Ratnasari Dwi , Zahroh Anita Intan Rohmatus
Published: December 2024

Artikel ini membahas tentang pengembangan kurikulum di UIN Sunan Kalijaga Yogyakarta yang mengacu pada KKNI dan SN-DIKTI. Hal tersebut dapat dilihat dari mata kuliah yang ditentukan oleh UIN Sunan Kalijaga mencerminkan keragaman pendekatan teori, strategi pengembangan, dan fokus yang diterapkan. Penyusunan mata kuliah dapat membantu mengambil kebijakan dan pihak terkait dalam meningkatkan kualitas pendidikan Islam, menyesuaikan kurikulum sesuai dan mengikuti perkembangan yang ada, serta memastikan bahwa kurikulum yang disusun sesuai dengan tujuan dan kebutuhan masing-masing institusi. Artikel ini menggunakan metode Library Research dengan mengkaji beberapa sumber data dari buku-buku dan jurnal-jurnal ilmiah yang berkaitan dengan perkembangan kurikulum. Hasil dari penelitian ini menunjukkan bahwa kurikulum PAI UIN Sunan Kalijaga, berdasarkan mata kuliah yang ada tidak banyak memunculkan mata kuliah kependidikan atau keguruan yang dikaitkan langsung dengan mata pelajaran-mata pelajaran rumpun Pendidikan Agama Islam yang nantinya akan diajarkan di sekolah ataupun madrasah. Oleh karena itu, perlu beberapa matakuliah tambahan yang mengkaji materi pembelajaran untuk mempersiapkan kemampuannya baik dari segi kompetensi profesional dan kompetensi pedagogik sesuai dengan kurikulum berbasis OBE (Outcome Based Education). Selain itu, kiranya Prodi PAI perlu juga memasukan mata kuliah statistika sebagai mata kuliah pendukung metodologi penelitian dalam pengolahan data penelitian.
Eksplorasi Etnomatematika pada Candi Jawi di Desa Candiwates Pasuruan sebagai Lembar kerja Peserta Didik Matematika SD
Authors: Azizah Nurul , Haryani Sri , Harianingsih Harianingsih , Avrilianda Decky , Subali Bambang
Published: December 2024

Penelitian ini mengeksplorasi konsep etnomatematika pada Candi Jawi di Desa Candiwates, Pasuruan, sebagai dasar pengembangan lembar kerja peserta didik matematika tingkat sekolah dasar (SD). Etnomatematika menghubungkan matematika dengan budaya, memungkinkan siswa memahami konsep abstrak matematika melalui objek sosial budaya. Candi Jawi, peninggalan Kerajaan Singosari, menyimpan unsur matematika dalam struktur bangunannya, seperti bangun datar, bangun ruang, kesebangunan, kekongruenan, dan transformasi geometri. Penelitian menggunakan metode kualitatif dengan pendekatan etnografi. Data dikumpulkan melalui observasi, wawancara, dan dokumentasi. Wawancara melibatkan juru pemelihara candi, panitia Balai Pelestarian Cagar Budaya (BPCB), dan tukang rekonstruksi. Hasil validasi menunjukkan semua instrumen penelitian valid (V > 0,5). Analisis data mengidentifikasi unsur matematika yang relevan untuk siswa SD, yaitu bentuk geometris dari bangun datar seperti persegi panjang, segitiga, segilima, dan trapesium, serta bangun ruang seperti limas segiempat dan balok. Selain itu, penelitian menghasilkan lembar kerja peserta didik dengan fokus pada materi volume bangun ruang. Lembar kerja ini divalidasi oleh ahli dengan hasil validitas tinggi (V > 0,5), sehingga layak digunakan dalam pembelajaran matematika. Penelitian ini memberikan kontribusi penting dalam mengintegrasikan nilai budaya ke dalam pendidikan matematika, menjadikan pembelajaran lebih kontekstual dan menarik bagi siswa.
Closing the financing gap for universal social protection
Authors:   International Labour Organization. Universal Social Protection Department,
Published: December 2024

This brief summarizes information about financing gaps preventing the achievement of universal social protection, and provides recommendations, including the establishment of targets on expanding social protection coverage, for consideration in the outcome document of 4th International Conference on Financing for Development (FfD4).
Nepal
Authors:   Fair Recruitment Initiative,,   International Labour Organization. Conditions of Work and Equality Department.,
Published: December 2024

This document highlights promising practices for fair recruitment in Nepal with a focus on the use of digital technology for increased harmonisation and oversight of migration processes.
CoESciTer. Un projet de transcription et d’édition numérique d’un corpus de sciences de la Terre
Authors: Mallevays Milène , Haraux Geoffrey , Cuvelier Jessie
Published: December 2024

Le projet CoESciTer, programmé de 2022 à 2024, a eu pour objectif la transcription et l’édition d’un corpus de manuscrits scientifiques en Sciences de la Terre, incluant des notes de cours de professeurs et d’élèves, avec une priorité sur les documents rédigés par Abel Briquet. La technologie HTR (Handwritten Text Recognition), via les logiciels Transkribus et eScriptorium, a été employée pour automatiser ce processus. Des modèles personnalisés ont été développés pour améliorer la précision des transcriptions, particulièrement pour les manuscrits dont l’écriture était complexe. Le texte issu des transcriptions a été encodé au format XML-TEI, facilitant ainsi leur utilisation et accessibilité. En complément de la transcription, le texte a été enrichi pour corriger certaines fautes d’orthographe et signaler les abréviations utilisées dans le texte original des notes de cours. La création d’un index permettant de naviguer dans les transcriptions par termes et notions scientifiques est un autre objectif du projet. Un script de reconnaissance a balisé automatiquement les termes scientifiques dans les fichiers XML-TEI, en utilisant le vocabulaire des « Sciences de la Terre » du « Thésaurus de la science ouverte » développé par l'INIST-CNRS. L’utilisation de la plateforme Heurist a permis ainsi de configurer une base de données et d’intégrer des filtres sophistiqués pour la recherche. Cet index comprend plus de 5 600 occurrences de termes scientifiques, dont 530 termes uniques, offrant une ressource précieuse pour les chercheurs en histoire des sciences. Le projet CoESciTer a de cette manière combinée des technologies avancées et des méthodes d’édition rigoureuses pour produire une ressource accessible et utile, contribuant significativement à l’étude de l’enseignement des sciences géologiques à la Faculté des Sciences de Lille.
The Four Dimensions of Xi Jinping's Thought on Comprehensively Governing the Party with Rigor
Authors: Qiong Liu
Published: December 2024

The Communist Party of China (CPC) is a party of courage and self-reform. Over the past century, it has united and led the Chinese people in overthrowing oppressive forces, transforming itself from a weak organization to a powerful one and guiding China from hardship to prosperity. One of the fundamental reasons for this success is the Party's constant attention to self-construction, recognizing governance and discipline as the basis of its development. Xi Jinping's thought on the comprehensive and strict governance of the Party in the new era integrates contemporary realities in China, imbuing the Marxist theory of Party building with new significance and further enriching and advancing its principles. This paper explores Xi's thought on comprehensively governing the Party with rigor through multiple perspectives, focusing on historical, substantive, contextual, and practical dimensions.
Exploring the Influence of Social Media and Online Communities on Affordances in ELT
Authors: Ngo Nguyen Thien Duyen , Pham Huong Ngoc Uyen
Published: December 2024

In modern times, the popularity of social media and online communities play an important role in both daily life and language learning. Social media and online communities have become integral to modern life, offering unique opportunities to transform English Language Teaching (ELT). This literature review examines how the affordances provided by these platforms are reshaping the current landscape of ELT through an ecological perspective. Specifically, the study investigates their influence on teaching and learning practices, focusing on how these affordances foster authentic language use, collaboration, and personalized learning experiences. Additionally, the review explores the implications of these affordances for teachers’ strategies in designing dynamic, multimodal learning environments that extend beyond traditional classrooms. By synthesizing findings from recent research (2014–2024), the study highlights the transformative role of social media and online communities in creating enriched affordance environments. These platforms enable greater learner autonomy, cultural awareness, and engagement. The study also identifies practical recommendations for educators to integrate these tools effectively while addressing challenges such as digital literacy and privacy concerns. This review provides a comprehensive understanding of how digital affordances are shaping ELT and suggests strategies for leveraging them in innovative and sustainable teaching practices.
Why is the uptake of decentralised elements in clinical trials slower than expected?
Authors: Theogaraj Elizabeth , Leyens Lada , Wingate Jamie
Published: December 2024

In the swiftly changing realm of clinical research, incorporating decentralised elements into clinical trials is becoming a transformative approach to drug development. Driving this approach is the need to not only improve the desirability of participating in clinical trials by reducing participant burden but also increase the utility of the data/evidence collected. The philosophy guiding this approach is both participant- and site-centred, thus ensuring decentralised elements truly add value to the clinical trial experience while still meeting a trial’s scientific objectives. As the potential benefits of these innovative trial methodologies have become more clear, regulatory agencies worldwide have released numerous guidelines for incorporating decentralised elements into clinical trials. Despite these promising benefits and regulatory guidance, the adoption of these elements has not progressed as rapidly as anticipated. This commentary delves into some of the factors sponsors consider with regard to integrating decentralised elements into clinical trials and discusses several challenges they face in practice.
Mindfulness Therapy for Autoimmune Diseases in Indonesia: Mechanisms, Applications, and Challenges
Authors: Sumah Dene Fries , Lameky Vernando Yanry , Parinussa Nenny
Published: December 2024

Mindfulness therapy, a psychological approach emphasizing awareness of the present experience without judgment, has gained attention as a potential intervention for improving the quality of life of patients with autoimmune diseases in Indonesia. With the increasing prevalence of autoimmune diseases and their associated physical and psychological symptoms, mindfulness therapy is highly relevant. This review explored the mechanisms of action, case studies, challenges, and recommendations for implementing mindfulness therapy in Indonesia. Mindfulness has been shown to modulate brain activity associated with emotional processing, reduce inflammation, improve pain management, enhance social relationships, and improve sleep quality. Case studies in Indonesia have demonstrated the effectiveness of mindfulness therapy in patients with rheumatoid arthritis and lupus, with participants reporting significant improvements in their physical and mental symptoms. However, challenges such as insufficient understanding among medical personnel, societal stigma, limited availability of programs, cultural factors, and lack of comprehensive research need to be addressed. Recommendations include enhanced education and training for medical personnel, public awareness initiatives, the development of culturally appropriate programs, improved accessibility, and further research on the effectiveness of mindfulness therapy in Indonesia. By addressing these challenges and implementing recommendations, mindfulness therapy can be effectively integrated into the Indonesian healthcare system to improve patient's quality of life with autoimmune diseases.
Diyarbakır Ekolojik Şartlarında Farklı Organik İçerikli Gübreler ile Yetiştirilen Keten (Linum usitatissimum L.) Çeşitlerinin Bazı Besin Bileşenlerinin Belirlenmesi
Authors: Çiçek Bayram Şilan , Başbağ Sema , Aybar Yalınkılıç Nazlı
Published: December 2024

Fonksiyonel bir gıda olarak kabul edilen keten tohumunun önemi, besin değerinin yüksek olması ve kullanım alanının çeşitliliği gibi nedenlerden dolayı giderek artmaktadır. Bu araştırmada, farklı organik gübreler kullanılarak yetiştirilen keten çeşitlerinin, bazı teknolojik özelliklerini kapsamlı bir şekilde değerlendirmek amaçlanmıştır. Diyarbakır ekolojik şartlarında iki yıl (2022, 2023) süre ile yürütülen çalışmada, Kara Kız, Sarı Dane ve Beyaz Gelin keten çeşitleri materyal olarak kullanılmıştır. Denemede, hayvan gübresi, deniz yosunu, hümik asit ve solucan gübresi kullanılmıştır. Çalışma, Dicle Üniversitesi İyi Tarım Uygulamaları sahasında, tesadüf bloklarında bölünmüş parseller deneme deseni uyarınca 4 tekerrürlü olacak şekilde yürütülmüştür. Deneme bulgularına göre; ham yağ oranının 2022 yılında % 32,05-36,12 ve 2023 yılında % 32,37-36,49 arasında değiştiği, protein oranının 2022 yılında %.23,29-24,67, 2023 yılında %23,11-24,18 arasında değiştiği, kül oranının 2022 yılında %3,22-3,32 ve 2023 yılında % 3,29-3,48 arasında değiştiği, karbonhidrat oranının 2022 yılında % 8,67- %8,90 ve 2023 yılında % 8,72- % 8,92 arasında değiştiği, nem oranının 2022 yılında % 6,85- %7,14 ve 2023 yılında % 6,83- % 7,17 arasında değişim gösterdiği saptanmıştır. Organik içerikli gübrelemenin ketende kalite parametrelerinde olumlu etki yaptığı, kullanılan gübre yöntemi bakımından solucan gübresi ve hayvan gübresinin diğer gübrelere kıyasla daha iyi sonuçlar verdiği saptanmıştır. Çeşit yönünden Beyaz Gelin çeşidinin bölgede tercih edilmesi önerilmektedir.
Data Migration and security in cloud
Authors: Srivastava Ankit
Published: December 2024

Data migration and security in the cloud" refers to the process of transferring data from an on-premises system to a
cloud environment while prioritizing security measures to protect sensitive information during transit and once stored
in the cloud, including implementing strong access controls, encryption, and regular monitoring to prevent data
breaches and ensure compliance with relevant regulations. In this time of digital evolution, cloud migration and its
security have become essential topics that cannot be avoided. With more companies turning to cloud services for
support, the demand for large-scale data storage and data management has also increased. Along with this rising need,
the risk of cyber attacks on cloud data has also increased. To better protect yourself from these risks, it’s essential to
ensure that you and your organization are up-to-date on the latest security technologies and safety precautions.
Keywords : Data Migration, Data Security, cloud, ETL, Data Integration
Quantitative Evaluation of Multi-Channel Campaign Effectiveness Using Analytical Tools
Authors: Mulla Faiz Mohiuddin
Published: December 2024

As a result, more businesses are harnessing multi-channel marketing campaigns to both reach and engage customers
spanning multiple channels in this competitive digital arena. Whether these campaigns succeed ultimately comes
down to one thing: the ability to analyze and assess their impact in a holistic, data-driven way. This paper discusses
how to measure multi-channel marketing campaigns quantitatively using various analytical tools. It focuses on the
different methods businesses can use, including A/B testing, attribution models and advanced analytics platforms, to
understand campaign performance across multiple touchpoints — from social media to email to search engines and
websites. It also covers the confusion about collecting data from several sources, shines light on how to best avail
and integrate analytical tools, talks about predictive analytics & machine learning and how can these technologies
enhance campaign results. With these tools, companies can get actionable insights that allow them to refine their
marketing campaigns, provide effective customer engagement or even make the most of return on investment (ROI)

In addition, the paper explores future directions of multi-channel campaign measurement with a trend toward real-
time analytics and AI in marketing decision-making. It touches upon how the grow in dependence on data point

integration across a variety of marketing channels and the multi-touch for customer journey tracking always leads to
value-added strategic decisions. As the technology grows, and businesses understand their own campaign efforts,
they can not only fine-tune their ongoing campaigns but also obtain insights into the future trends and outcomes—
thereby improving its long-term marketing results.
Keywords
Multi-Channel Marketing, Campaign Effectiveness, Analytical Tools, A/B Testing, Attribution Models, Predictive
Analytics, Machine Learning, ROI, Real-Time Analytics, Artificial Intelligence.
Balancing Profitability and Risk: The Role of Risk Appetite in Mitigating Credit Risk Impact
Authors: Yadav Sandeep
Published: December 2024

Balancing profitability and risk is a central challenge for financial institutions, especially in the context of
managing credit risk. This paper explores the concept of risk appetite as a strategic framework for aligning an
institution’s risk-taking activities with its financial objectives. By defining risk appetite in measurable terms,
institutions can calibrate their credit risk strategies to ensure optimal decision-making that mitigates potential losses
while maintaining profitability. The study examines how risk appetite influences credit decision-making processes,
including credit underwriting, portfolio management, and risk-adjusted return assessment. Through an empirical

analysis of credit portfolios across varying economic conditions, the paper demonstrates the effectiveness of a well-
defined risk appetite in reducing credit losses and enhancing risk-adjusted returns. Moreover, it highlights the

importance of integrating risk appetite frameworks with advanced analytics, such as machine learning and stress
testing, to dynamically adapt to changing market conditions. The findings provide actionable insights for financial
institutions seeking to strike a balance between risk and reward, ultimately contributing to long-term financial
stability and growth.
Key Words: Risk Appetite, Credit Risk Management, Profitability, Risk-Adjusted Returns, Credit Underwriting,

Portfolio Management, Financial Stability, Risk Mitigation Strategies, Stress Testing, Economic Conditions, Risk-
Reward Balance, Credit Decision-Making, Financial Institutions
Encryption and Security Enhanced Middleware SOA Solutions for High-Security Applications
Authors:   Product Engineer, Cardinal Health, Kalpinagarajarao Gopi Krishna
Published: December 2024

This paper examines the security enhancements for middleware layer that play a crucial role in protecting
information. In the digital age, the integration of security measures with software architecture is paramount,
especially for industries such as banking, healthcare, and high-security applications. These sectors handle sensitive
data that requires robust protection from cyber threats. The Service-Oriented Architecture (SOA) is a widely
adopted architectural pattern that facilitates the design of modular, interoperable systems. However, to address the
escalating risks associated with cybercrime and data breaches, traditional SOA solutions must evolve by

incorporating encryption and other advanced security measures. This paper explores how encryption and security-
enhanced middleware enhances the overall security for these high-stakes industries.

Keywords: SOA, OIC, Webservices, XML, TLS, SSL, Encryption, Data encryption, Encryption at rest. SAML,
SSO, Application Security
Telematics – Evolution of Stolen vehicle Tracking solutions in Automotive Engineering
Authors: Sureddi Suresh
Published: December 2024

The automotive industry has transformed drastically over the past two decades with the advancements in
IoT, connectivity and Artificial intelligence (AI). Among the connectivity features, technologies for stolen vehicle
tracking are continuously evolving as the battle between the car thieves and those committed to protect the vehicle
theft is ongoing. This article first details the evolution of stolen vehicle tracking technologies, provides insights into
the one of the typical early architectures of Stolen vehicle tracking system using GPS + GSM+ Immobilization
technique and then providesthe details of latest security technologies like IoT and LPWAN to recover stolen vehicles.
Keywords: Connected Vehicles, Stolen vehicle Tracking, GPS (Global Positioning System), GSM (Global System
for Mobile), Internet of Things (IoT), Connectivity, CAN (Controller Area Network), TCU (Telematics Control
Unit), Artificial Intelligence.
Elevating Salesforce Testing Efficiency with Copado Robotic Testing
Authors: Chandrika Asha Rani Rajendran Nair
Published: December 2024

Salesforce testing has undergone a significant transformation, driven by the platform's rapid innovation, frequent
updates, and growing implementation complexity. Traditional manual testing methods have struggled to keep pace
with Salesforce’s dynamic environment, often resulting in time-intensive processes, limited coverage, inconsistent
outcomes, and increased risk of human error. The need for accelerated release cycles without compromising quality
has led organizations to adopt automation, enabling comprehensive regression testing and early defect detection
within tighter timelines. Copado Robotic Testing (CRT) has emerged as a powerful solution specifically designed for
Salesforce DevOps, offering Salesforce-specific libraries, AI-driven test creation, and seamless CI/CD integration.
By providing faster execution, improved accuracy, and broader test coverage, CRT enables organizations to achieve
high-quality releases efficiently. This article explores how CRT revolutionizes Salesforce testing by delivering a
scalable and resilient approach that aligns with modern DevOps practices.

Keywords: Test automation, Copado Robotic Testing, AI-driven testing, Salesforce DevOps, CI/CD integration,
Cross-platform support, Automation frameworks.