Tabor College

Este artículo explora los fundamentos con los que se estructura una de las iniciativas más renovadoras de la práctica cinematográfica joven en nuestro panorama hondureño: la Escuela de Cine en Posguerra. Esta comunidad de creadores emergentes procura la exploración y el conocimiento del lenguaje audiovisual como principal insumo para estimular la libertad de expresión a través del cine, en los estudiantes de la universidad más importante de Honduras. Reconociendo que la gran mayoría de participantes proviene de núcleos sociales modestos y de escasos recursos, les concientiza que el quehacer cinematográfico es principalmente un arte colectivo, el cual, al desarrollarse mediante el apoyo de todos los implicados, con los recursos que se cuenten y con una dosis de rebeldía, talento, disciplina y amor al arte, con él se pueden realizar obras que cuestionen la realidad y ayuden a su mejor entendimiento.

Beyond Borders is a collaborative project developed through a joint effort between education and research institutions in Tanzania, Norway, the UK, and Italy, alongside communities from Tanzania and Sinai. Launched in 2024, the initiative was spearheaded by Camilla Haule (Horizon Award, Wells Cathedral School) and brought to fruition through the coordination of Agnes Haule (Tanzania), Ladslaus Bigambo Masakula, the kindergarten teachers group (NEMCA), Margherita Paola Poto, Carolina Sarti (ECOCARE), Pietro Parola, Valentina Russo (Mucho Amor), Dana Ahmed, Claudia D'Andrea, Faezeh Karimpour, and the communities of the Verdis Vocational School in Mbeya. The project unfolded in three key phases: (1) Project inception and ideation led by Camilla Haule during the Summer Semester of 2024; (2) Development of research and teaching materials, coordinated by Carolina Sarti in the Spring Semester of 2025; (3) Implementation in the Ruvuma Region, carried out in the Summer Semester of 2025. This report describes and assesses the relevance of the activities conducted by the Beyond Borders team during the Summer Semester 2025, focusing on fieldwork in the Ruvuma Region, Tanzania, and particularly in the municipality of Songea. The Beyond Borders Initiative is part of a larger effort to foster meaningful partnerships and expand educational opportunities through direct engagement with local communities. It is also a deliverable of the SDG Ocean Action Commitment: Ocean for All: Reimagining Justice with Love and Law.

The paper proposes a hybrid wireless power transfer (WPT) system for electric vehicles (EVs) combining solar and grid power sources, simulated in MATLAB. The system utilizes an Inductively Coupled Power Transfer (ICPT) mechanism, which facilitates automatic EV charging in parking spaces. It has a two-stage switching power supply with soft-switching control to reduce losses and increase efficiency. The circuit features precisely chosen receiver and transmitter coils to produce resonance for the highest power transfer. A Neuro Fuzzy model for control is also used to ensure grid stability. The system accommodates bidirectional power transmission so that power in excess can be returned to the grid. The simulation result reveals a 70-watt maximum WPT capacity, and it proves to be efficient and reliable. This study helps in the development of sustainable and effective EV charging solutions.

Chronic Obstructive Pulmonary Disease (COPD) exacerbation is a life-threatening condition which manifests with overlapping symptoms that require early and correct differential diagnosis to ensure effective treatment. To this end, in this study, we propose a Natural Language Processing (NLP) enabled AI system to enhance COPD exacerbation identification and classification from EHRs and clinical notes. Based on large language models (LLMs) and AI based multi agent architectures, we automate data extraction and analysis of patients' data such as symptoms, patient's medical background and lifestyle factors. We perform unstructured clinical text processing for the cases of COPD exacerbation vs other respiratory conditions using multiple machine learning classifiers and NLP pipelines. It combines structured and unstructured data sources to increase the precision of conjunctive diagnostics and thus shorten the time needed for medical professionals to assess critical cases. In the study, different AI models are evaluated by random forest, logistic regression and Naïve Bayes classifiers, and results indicate that the random forest model is able to detect COPD exacerbation with the highest accuracy (80%) and F1-score (73%). This AI powered NLP system can automate the Medical History analysis and differential diagnosis process to be more efficient in diagnosis, reduce misclassification and improve patient outcomes. The model will be developed to include real-time patient monitoring and has been integrated with hospital information systems for clinical decision supports.

Kinetic studies investigate the catalytic oxidation of lactic acid in aqueous micellar sulfuric acid environment using 1,10-phenanthroline promoter. Here, lactic acid concentration is greatly exceeded with respect to chromic acid [Cr(VI)]T concentration under various temperatures. It is observed that in the absence of phenanthroline, H2CrO4 is a kinetically active species. In contrast, in the presence of [phen]T, Cr(VI)-phencomplex is proposed as an active oxidant (receiving an electron from the electron donor/Lewis base). The complex under phen pathway undergoes nucleophilic attack by the substrate, Lactic acid. It forms a Cr(VI)-phen complex through a two-electron transfer redox decomposition. Now, the complex is ready to oxidise lactic acid and convertafter reducing to Cr(III)-phen complex. Both pathways are first-order dependent on the concentration of [Lactic acid]T and [Chromic acid]T, while the phen-promoted pathway shows first-order dependence on the concentration of phen. Adding sodium dodecyl sulfate (SDS), an anionic surfactant, enhances the reaction rate in thephen-promoted pathway.

In this review, we examine the protein-protein interactions of cytosolic malate dehydrogenase (MDH), an under-studied area in cellular metabolism. We provide a comprehensive overview of MDH involvement in metabolism, especially its interactions with metabolic partners and dynamics of changing metabolism. We present an analysis of the biophysical nature of these interactions and the current methods used to study them. Our review includes an assessment of computational docking studies, which offer initial hypotheses about potential MDH interaction partners. Furthermore, we provide a summary of the sparse yet insightful experimental evidence available, establishing a foundation for future research. By integrating biophysical analysis and methodological advancements, this paper aims to illuminate the intricate network of interactions involving cytosolic MDH and their metabolic implications. This work not only contributes to our understanding of MDH's role in metabolism but also highlights the potential impact of these interactions in metabolic disorders.

A case is reported where a patient, after using a tooth whitening gel containing the active ingredient hydrogen peroxide over 2 days, found that the expected onset of postprandial gastroesophageal reflux symptoms (RS) did not occur. Oxygen in air dissolves in water contained in the gut lumen to form hydrogen peroxide, and so the role of oxygen, rather than potentially toxic hydrogen peroxide, was investigated as a treatment for RS. Air swallowing can provide oxygen to the gut lumen, and breathing exercises can supply oxygen from the blood to the gut epithelium. Air swallowing and breathing exercises (ASBE) were performed as required over 34 days, and it was found that a single ASBE session (3-8 ASBE episodes over 30 seconds) brought temporary relief from RS over 1-2 hours. Up to 3 sessions of ASBE were required and resolved RS over 74% of days, reducing the need to take antacid tablets. To understand the impact oxygen could have on RS, the oxidation potential for oxygen, calculated as mmol electrons/100 ml (2-3 breaths) of swallowed air, was calculated and compared to the reported values for the antioxidant content of various foods. It was found that 100 ml of swallowed air has the potential to oxidize 1 serving of coffee, red wine, or orange juice, known refluxogenic or trigger foods that can cause RS. Based on the finding that ASBE can reduce RS and a brief review of the role oxygen plays in digestion, a hypothetical oxygen model for digestive reflux was proposed. For the model, the reflux of digesting food to the more oxygenated esophageal regions is triggered by refluxogenic foods high in antioxidants that react with oxygen in the lumen to create an inadequate supply necessary for aerobic digestion, resulting in gastroesophageal reflux. As the ASBE did not resolve all RS, with ≈26% remaining unresolved, the oxygen supply was considered only a part of the complex digestive reflux mechanism.

COVID has caused a major outbreak in the world. It has brought about the breakdown of the economy, significant over-burden in the well-being area, a break in the schooling system and lost lives, and so forth. To ensure that the condition of the world comes to a superior spot regarding work, money and well-being, controlling the outbreak has turned into a main concern. In this paper, ARIMA time series forecasting model is utilized to predict and forecast the assessment of the spread of COVID-19 contamination in the following week. We have taken the data of COVID-19 patients of the Pune district in India. The data is visualized in a simple-to-consume and interactive format. By and large, this paper can help experts and authorities control the COVID-19 outbreak by helping them gain alertness.

The networks that are constantly a part of the Cloud infrastructure exist in the real world with different representations, further these networks exchange information with each other. Nowadays, the real-time data stored in Terabytes and Petrabytes must be processed by using an effective mechanism. The HDFS combined with Machine Learning Techniques frequently provides an intelligent technique for processing the big data. For a better understanding of the network's complex structure, the real-time structure in the networks can be represented as a community structure. However, it is necessary to detect the links in a distributed heterogeneous complex network for community detection. This research study proposes a novel algorithm for community detection by employing a genetic algorithm based K-Means Unsupervised Technique and C-Means Fuzzy Clustering. The Map Reduce framework is used to provide scalability and parallelism in the proposed work. The performance analysis metrics such as accuracy and convergence are measured. The Folkes and Mallows Coefficient with Hyperparameter Tuning is used to further assess the community development. The Fuzzy C-Means Clustering Algorithm is used to define the Objective Function. The proposed method has additionally included a Map Reduce Framework and is more efficient when compared to other existing research regarding community recognition over a Cloud Based environment, based on an experimental evaluation of five real-time datasets.

Purpose: The article aims to examine the effects of the Belt and Road Project (BRI) of China and its recent developments.
 Methodology: It does this by analyzing the effects Chinese investments have had on their largest beneficiaries. The article considers several factors such as transport, energy, and debt profiles of the countries after receiving aid under BRI.
 Findings: Through our analysis, we have found that the project is by far the most secure investment developing countries might have especially considering the diminishing aid of the USA and European countries. It is largely beneficial for both China and the beneficiaries encouraging economic growth. We have made our conclusions based on data reported through various research articles both domestic and international. These include but are not limited to papers from the SAIS-CARI website, the American Enterprise Institute (AEI), the World Bank, and the Boston University Energy Database.
 Recommendations: We recommend that in the future studies should be further conducted on the progress of BRI projects that have been started or planned in the future as well as the effects previous long-term investments are currently having on beneficiaries. Some research should also be conducted comparing the effectiveness of loans from the US and European countries when compared with Chinese counterparts