bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Impact of Financial Modeling on Profit Growth in the Jordanian Industrial Sector: a Pathway to Sustainable Industry
Authors: Alawneh Ateyah Mohammad , Shawaqfeh George Nasser , Shehab Saad Taha Mohammed , Al-Attar Mohammad Khalid 
Published: February 2025

Objective: This study examines the impact of financial modeling on profit growth in Jordanian industrial sector, aligning with Sustainable Development Goals (SDG 9) – Industry, Innovation, and Infrastructure. The research aims to analyze how internal financial indicators (company size, paid-up capital, liquidity, long-term loans) and external economic indicators (GDP, inflation rate) influence profitability, measured by return on equity (ROE), return on assets (ROA), and net income.

Theoretical Framework: The study is grounded in financial modeling theory, which integrates quantitative financial analysis with economic indicators to enhance corporate decision-making. The research builds on prior studies analyzing the relationship between financial structures, economic conditions, and corporate profitability, emphasizing the role of financial modeling as a strategic tool.

Method: The study employs multiple regression analysis and Fully Modified Ordinary Least Squares (FMOLS) estimation to analyze financial data from Jordanian industrial companies listed on the Amman Stock Exchange between 2005 and 2021. Interaction effects between internal financial indicators and macroeconomic conditions are also examined.

Results and Discussion: The findings indicate that company size, paid-up capital, and liquidity positively impact profitability, while long-term loans have a negative effect. GDP growth and inflation rates show a significant positive influence, suggesting that industrial firms benefit from economic expansion. The interaction analysis reveals that financial modeling enhances profitability when internal indicators align with favorable economic conditions.

Research Implications: The study provides insights for financial managers and policymakers on optimizing capital structures, liquidity management, and leveraging macroeconomic trends. It highlights the necessity of integrating financial modeling techniques into strategic planning for improved financial performance. These insights contribute to achieving SDG 9 by supporting sustainable industrialization and financial stability.

Originality/Value: This study contributes to the literature by demonstrating the interaction between internal and external financial factors in an emerging market context. Unlike prior research, it integrates financial modeling with macroeconomic indicators, offering a comprehensive perspective on profit growth dynamics in Jordan’s industrial sector.
Frequency of Tuberculosis Diagnosed on Histopathology of Pleural Peel Biopsy Post Decortication In Patients with Chronic Empyema
Authors: Khaskheli Abdul Jabbar , Majeed Farhan Ahmed , Ashraf Imran , Khan Umair Aslam Shahzad , Rahim Kamran , . Farhanullah 
Published: February 2025

Objective: To elucidate the frequency and characteristics of TB in Chronic Empyema, emphasizing the role of histopathology in diagnosis, post-decortication.
Study Design: Retrospective Analytical study
Place and Duration of Study: Thoracic surgery Department Combined Military Hospital Rawalpindi, Pakistan from Aug 2014 to Aug 2023.
Methodology: A review of 2000 patients with Chronic Empyema undergoing decortication was conducted at Thoracic surgery Department Combined Military Hospital, Rawalpindi. Biopsy specimens were obtained following decortication in individuals with persistent empyema to determine the frequency of TB in pleural peel. The patients' demographic information, medical records, and current clinical state were all gathered using a stringent data collecting process. The occurrence of TB was calculated by the examination of pleural peel biopsy specimens following decortication. The data was described utilizing descriptive statistics, encompassing measures such as medians, percentages, and means. The frequency of TB was calculated by dividing the total number of participants in the study by the number of persons who were diagnosed with tuberculosis.
Results: The majority of the patients 1296(64.8%) who had decortication for persistent empyema underwent open decortication, while 704(35.2%) underwent Video-Assisted Thoracoscopic Surgery (VATS). The most common result 955(47.75%) in the histopathological study was TB, underscoring its strong correlation with persistent empyema. Additional results included malignancy 31(1.55%), pleuritis 119(5.95%), pleural fibrosis 227(11.35%), acute and chronic inflammation 433(21.65%), and nonspecific inflammation 235(11.75%). These results highlight the frequency of TB in instances of chronic empyema.
Conclusion: This study shows a high correlation between TB (47.75%) and chronic empyema. ...
Comparison of Analgesic Efficacy of Thoracic Erector Spinae Plane Block Versus Pectoral Block in Patients Undergoing Mastectomy
Authors: Ali Aijaz , Sabir Ghulam , Iqbal Muhammad Rashid , Qureshi Kamil Hussain , Iqbal Mudassar , Mehmmod Tariq 
Published: February 2025

Objective: to assess the Analgesic efficacy of single-shot ultrasound guided Pectoral Block-II and Thoracic Erector Spine Plane Block were evaluated for postoperative pain in breast surgery.
Study Design: Quasi-experimental study.
Place and Duration of Study: Combined Military Hospital, Rawalpindi Pakistan, from Mar to Aug 2022.
Methodology: We enrolled 68 female patients in this study, who were between 25-55 years of age, booked for unilateral mastectomy and classified as American Society of Anesthesiologists I and II. They were divided randomly into two groups, where Group-M (n=34) received ultrasound guided Pectoral II Block and Group-N (n=34) received ultrasound guided Erector Spine Plane Block, with 25ml of 0.25% bupivacaine used in both groups. Pain was measured postoperatively by Visual Analog Scale for pain and 1g intravenous paracetamol was given 8 hourly with rescue pain-relieving Nalbuphine used if the score was greater than 4.
Results: Postoperatively nalbuphine consumption was found to be considerably less in patients on whom ultrasound guided Pectoral II Block was given compared to Group-N, while mean analgesia requirement was found to be 0.05±0.07882 mg/kg in Group-M compared with 0.1118±0.01 mg/kg in Group-N with p-value less than 0.007, which was statistically significant.
Conclusion: Ultrasound Guided Pectoral II Block is more significantly effective in female patients for relieving pain especially after having undergone unilateral mastectomy.
NGHIÊN CỨU HIỆU QUẢ VÀ TÍNH AN TOÀN CỦA TIÊU HUYẾT KHỐI KẾT HỢP PHẪU THUẬT XÂM LẤN TỐI THIỂU ĐIỀU TRỊ CHẢY MÁU NÃO NGUYÊN PHÁT TẠI KHOA HỒI SỨC TÍCH CỰC BỆNH VIỆN THANH NHÀN
Authors: Lê Văn Dẫn , Nguyễn Thế Anh 
Published: February 2025

Mục tiêu: Đánh giá hiệu quả và tính an toàn của dùng thuốc tiêu huyết khối kết hợp phẫu thuật xâm lấn tối thiểu trong điều trị chảy máu não nguyên phát tại khoa Hồi sức tích cực bệnh viện Thanh Nhàn từ tháng 6/2021 đến tháng 12/2024. Phương pháp: Nghiên cứu can thiệp trên35 bệnh nhân được chẩn đoán chảy máu não nguyên phát điều trị tại khoa Hồi sức tích cực Bệnh viện Thanh Nhàn từ tháng 6 năm 2021 đến tháng 12 năm 2024, các bệnh nhân được can thiệp đặt catheter dẫn lưu ổ máu tụ kết hợp thuốc tiêu sợi huyết. Kết quả: Nhóm nghiên cứu có 35 bệnh nhân, trong đó có 43% bệnh nhân nam, 57% bệnh nhân nữ, bệnh nhân trong nhóm chủ yếu có tiền sử tăng huyết áp (77%), đái tháo đường (45%), điểm Glassgow (GCS) lúc vào viện chủ yếu: 13- 15 điểm: 45,7%; 5-8: 34,3%. Bệnh nhân không thở máy lúc vào viện: 60%, bệnh nhân được can thiệp sớm dưới 12h chiếm 86%, thể tích khối máu tụ lớn nhất trước điều trị: 98±30.5, thể tích nhỏ nhất sau điều trị: 8±2.5. Tổng liều tiêu sợi huyết: 9 liều chiếm 68,6%. Mức độ hồi phục theo mRS lúc ra viện: 0-3: 31%, 4-6: 69%; 1 tháng: 0-3: 55%, 4-6: 45%; 3 tháng: 0-3: 73%, 4-6: 27%. Trong số 35 bệnh nhân nghiên cứu: 22 bệnh nhân ra viện chiếm 63%, thời gian nằm viện (ngày): 15.68±8.13. Biến chứng của dẫn lưu ổ máu tụ chủ yếu viêm phổi sau chảy máu não chiếm 28.5%, không có viêm não. Kết luận: Áp dụng dùng thuốc tiêu huyết khối kết hợp phẫu thuật xâm lấn tối thiểu trong điều trị chảy máu não nguyên phát cải thiện đáng kể kết cục thần kinh của bệnh nhân
O Sentimento de Vivência e a Sensibilidade Comunicacional: Etnografia de uma feira de Belém do Pará
Authors: Xavier Fábio Rodrigo de Moraes 
Published: February 2025

Este artigo procura o sentimento de vivência na comunicação e sua sensibilidade, que pertence à razão sensível na feira. O local fica situado na cidade de Belém, no Estado do Pará, no norte do Brasil, na Amazônia brasileira. A investigação busca movimentos na expressão da localidade. No contato entre frequentadores e na condição de existência cotidiana. Desse modo, trazemos autores como Simmel, na interação de indivíduos, além do Araújo, na ideia de afecções humanas, ainda mais, Santin no sentimento na afetação do cotidiano. Temos também, Schutz na intersubjetividade ao mundo da vida e Maffesoli na expressividade da realidade. Assim sendo, na pesquisa de campo temos a Peirano na perspectiva da etnografia como experiência. Portanto, o nosso resultado é a comunicação entre indivíduos, que estrutura a localidade no envolvimento das pessoas. Dessa maneira, possui a organização da vida na movimentação dos sujeitos no contexto da afetação cultural e social amazônica.
Efektivitas Teknik Tanam dan Jarak Tanam terhadap Pertumbuhan dan Produksi Selada Merah (Lactuca sativa var. Crispa) pada Wiremesh Tower Garden
Authors: Yulianti Anggie , Puspitawati Mutiara Dewi , Warid  
Published: February 2025

Tanaman selada merah (Lactuca sativa var. Crispa) yaitu tanaman sayuran daun yang memiliki bentuk daun keriting atau bergelombang dan berwarna hijau kemerahan. Tanaman ini banyak disukai oleh urban community di kota karena memiliki nilai gizi yang baik, mudah tumbuh, dan estetik. Keterbatasan lahan atau ruang yang dimiliki grower menjadi kendala utama dalam budidaya selada merah di kota sehingga diperlukan teknik tanam secara vertikal atau vertikultur. Teknik vertikultur yang digunakan yakni vertikultur Wiremesh Tower Garden (WTG). Tujuan penelitian adalah untuk membandingkan efektivitas pertumbuhan dan produksi selada merah pada WTG dengan budidaya konvensional di lahan. Rancangan lingkungan yang digunakan adalah Rancangan Acak Kelompok (RAK) yang terdiri atas dua faktor yaitu teknik tanam sebagai faktor pertama yang terdiri atas WTG dan konvensional/lahan terbuka. Sedangkan jarak tanam merupakan faktor kedua yang terdiri atas 10x12 cm dan 20x24 cm. Hasil penelitian ini menunjukkan teknik tanam WTG dengan rekomendasi jarak tanam 10 x 12 cm memberikan hasil tidak berbeda nyata pada tinggi tanaman, lebar daun, jumlah daun, bobot segar tajuk, bobot segar akar, bobot produksi total tanaman, bobot produksi segar tajuk dan kandungan vitamin C dibandingan teknik tanam secara konvensional atau di lahan. Penggunakan teknik tanam WTG memberikan keuntungan dengan luasan lahan yang hemat (sempit), dapat ditanam di lahan pekerasan (semen atau aspal), meberikan hasil pertumbuhan dan produksi yang sama dengan teknik tanam secara konvensional di lahan.
NSOAS24: a new global marine gravity model derived from multi-satellite sea surface slopes
Authors: Zhang Shengjun , Chen Xu , Zhou Runsheng , Jia Yongjun 
Published: February 2025

Abstract. Judging by the early release of the NSOAS22 model, there were some known issues, such as boundary connection problems in blockwise solutions and a relatively high noise level. By solving these problems, a new global marine gravity model, NSOAS24, is derived based on sea surface slopes (SSSs) from multi-satellite altimetry missions. Firstly, SSSs and along-track deflections of vertical (DOVs) are obtained by retracking, resampling, screening, differentiating, and filtering procedures on the basis of altimeter waveforms and sea surface height measurements. Secondly, DOVs with a 1′×1′ grid interval are further determined using Green's function method, which applies directional gradients to constrain the surface, least-squares fit to constrain noisy points, and tension constraints to smooth the field. Finally, the marine gravity anomaly is recovered from the gridded DOVs according to the Laplace equation. Throughout the entire processing procedure, improvements in accuracy are expected for the NSOAS24 model due to the following changes, e.g., supplementing recent mission observations and removing old mission data, optimizing the step size during Green's function method, and special handling in nearshore areas. These optimizations effectively resolved the known issues of signal aliasing and the “hollow phenomenon” in coastal zones. Typical altimetry-derived marine gravity models are the DTU series released by the Technical University of Denmark and the S&amp;S series released by the Scripps Institution of Oceanography (SIO), University of California San Diego (UCSD). Their latest models, DTU21 and SS V32.1, were used for comparison and validation. Numerical verification was conducted in three experimental areas (the Mariana Trench area, Mid-Atlantic Ridge area, and Antarctic area, representing low-, mid-, and high-latitude zones) with DTU21, SS V32.1, and shipborne data. Taking NSOAS22 for comparison, NSOAS24 showed improvements of 1.2, 0.7, and 1.0 mGal in the three test areas by validating with SS V32.1, while declines of 0.6, 0.5, and 0.3 mGal and 0.2, 0.4, and 0.3 mGal occurred in SD statistics with DTU21 and shipborne data. Finally, NSOAS24 was assessed using two sets of shipborne data (the early National Centers for Environmental Information (NCEI) dataset and the later dataset from the Japan Agency for Marine-Earth Science and Technology (JAMSTEC), the Marine Geoscience Data System (MGDS), the French Oceanographic Cruises Directory (FOCD), and the French Naval Hydrographic and Oceanographic Service (SHOM)) on a global scale. Generally, NSOAS24 (6.33 and 4.95 mGal) showed a comparable accuracy level with DTU21 (6.20 and 4.71 mGal) and SS V32.1 (6.40 and 5.53 mGal) and better accuracy than NSOAS22 (6.64 and 5.64 mGal). The new model is available at https://doi.org/10.5281/zenodo.12730119 (Zhang et al., 2024).
The MESSy DWARF (based on MESSy v2.55.2)
Authors: Kerkweg Astrid , Kirfel Timo , Do Duong H. , Griessbach Sabine , Jöckel Patrick , Taraborrelli Domenico 
Published: February 2025

Abstract. The adaptation of Earth system model (ESM) codes to modern computing architectures is challenging as ESMs consist of a multitude of different components. Historically grown and developed by scientists rather than software engineers, the codes of the individual components are often interwoven, making the optimisation of the ESMs rather challenging, if not impossible. Thus, in the last few years, the codes have become increasingly modularised, and, with that, different components are now disentangled from each other. This helps porting the code section by section to modern computing architectures, e.g. to GPUs. For more than 20 years, the modularisation has been the fundamental concept of the Modular Earth Submodel System (MESSy). It is an integrated framework providing data structures and methods to build comprehensive ESMs from individual components. Each component, e.g. a cloud microphysical scheme, dry deposition of tracer gases, or diagnostic tools, as output along satellite orbits, is coded as an individual so-called submodel. Each submodel is connected via the MESSy infrastructure with all other components, together forming a comprehensive model system. MESSy was mainly developed for research in atmospheric chemistry, and, so far, it has always been connected to a dynamical (climate or weather forecast) model, i.e. what we call a base model. The base model is a development outside the MESSy framework. Running a full dynamical model for technical tests when porting only one submodel is a tedious task and unnecessarily resource-consuming. Therefore, we developed the so-called MESSy DWARF, a simplified base model based on the MESSy infrastructure. We implemented the definition of a very simple grid, a parallelisation scheme, and a time control to replace a fully fledged base model. The MESSy DWARF serves as a valuable tool for technical applications, such as porting individual component implementations to GPUs and performance tests or as an easy test environment for process implementations. Due to the MESSy structure, the applied components can be used in a dynamical model without any changes because the interface is exactly the same. Furthermore, the MESSy DWARF is suited for scientific purposes running simplified models (with only a selection of components), e.g. a chemical box model for the analysis of chamber experiments or a trajectory box model imitating an air parcel rising slowly into the stratosphere. Column and plume models could also easily be built based on the DWARF. In this article, we introduce the technical setup of the MESSy DWARF and show four example applications: (1) a simple application using a component calculating orbital parameters, (2) a chemical kinetics model including photolysis frequency calculation, (3) an application of a chemical box model, and (4) some details on a GPU performance test of the chemical kinetics model.
Critical Analysis of the Impact of AI in Higher Education and Its Consequences on Students
Authors: Sheren Shafei  
Published: February 2025

Introduction: The introduction of Artificial Intelligence (AI) in the education sector has sparked a lot of controversy opinions regarding its effectiveness in shaping student learning process and systematic mental growth. While AI has immense potential to transform learning experiences by providing personalised learning, immediate feedback, and access to enormous information, but fears have also been aired that overreliance on artificial intelligence will stifle the problem-solving and critical thinking capabilities of students by providing pre-programmed answers instead of encouraging independent thoughts.
Objectives: The purpose of this paper is to rigorously explore the impacts of AI on higher education, with an inspection of how it impacts learning processes, intellectual growth, and the further expectations from students, academics and universities. This research aims to develop AI tools and programs through mixed approaches for the higher education environment that function as collaborative partners rather than just tools. The goal is to establish guiding principles and frameworks for a creative AI practice, incorporating computational tools, benchmarking of successful experiments, and their future applications. The current focus is on presenting early-stage research findings.
Methods: Given this research focus on impact of AI in higher education, overviewing several studies, the backgrounds, and research findings achieved through exploratory research to gain a deeper understanding of a topic, develop practical guidelines, and develop more focused research questions for future investigation.
Results: By investigating different studies, the examined strategies can be consolidated to address the promise of ethical AI implementation in education and in a manner to enhance and sustain cognitive capabilities among students and other stakeholders while offsetting risks associated with over-reliance and degrading of the human capacity.
Conclusions: By embracing AI's potential while upholding core educational values, institutions can ensure AI enhances the learning experience. Successful implementation requires a balanced approach, developing adaptable and culturally sensitive AI tools while investing in teacher training for effective human-AI collaboration. This thoughtful approach considers students' diverse backgrounds and learning preferences, along with the vital role of educators, maintaining human agency, critical thinking, and ethical considerations as central to education. AI in higher education offers significant potential benefits, but responsible integration is key to maximising its positive impact. This approach ensures AI serves educational purposes effectively.
AI-Driven Personality Development: Enhancing Emotional Intelligence and Social Skills through Machine Learning
Authors: Tejaswini Panse  
Published: February 2025

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has opened new frontiers in human personality development, particularly in enhancing emotional intelligence (EI) and social skills. Emotional intelligence, which includes self-awareness, self-regulation, empathy, and effective communication, is a crucial factor in personal and professional success. Traditional methods of personality development rely on human-led training, coaching, and therapy, but AI-powered systems now offer scalable, personalized, and data-driven alternatives. This paper explores the application of AI in personality development, emphasizing how ML techniques such as Natural Language Processing (NLP), deep learning, and reinforcement learning can facilitate emotional intelligence enhancement. Sentiment analysis software, virtual emotional coaches, chatbots, and affective computing systems—among other AI-powered tools—help people identify, understand, and control their emotions. By means of conversational agents and virtual reality simulations, AI-driven social skills training offers real-time feedback, therefore empowering users to improve their interpersonal contacts. AI-driven personality development poses ethical questions despite its transforming power including data privacy, algorithmic prejudice, and the possibility of over-reliance on AI for social contacts. Dealing with these issues calls for a well-rounded strategy combining ethical artificial intelligence models with enhanced openness, human-AI cooperation in social skill development, The research comes to the conclusion that artificial intelligence has great potential to improve communication abilities and emotional intelligence. Through responsible use of AI's powers, people may increase their self-awareness and interpersonal efficacy, therefore enhancing their social contacts and professional performance. To best maximise the advantages of AI-driven personality development, future studies should concentrate on improving AI models, reducing bias, and guaranteeing ethical deployment.