ethicalabs/Research-Intent-Collab huggingface dataset:
Boundary value problems for elliptic partial differential equations

This course is intended as an introduction to the analysis of elliptic partial differential equations. The objective is to provide a large overview of the different aspects of elliptic partial differential equations and their modern treatment. Besides variational and Schauder methods we study the unique continuation property and the stability for Cauchy problems. The derivation of the unique continuation property and the stability for Cauchy problems relies on a Carleman inequality. This inequality is efficient to establish three-ball type inequalities which are the main tool in the continuation argument.   We know that historically a central role in the analysis of partial differential equations is played by their fundamental solutions. We added an appendix dealing with the construction of a fundamental solution by the so-called Levi parametrix method.   We tried as much as possible to render this course self-contained. Moreover each chapter contains many exercices and problems. We have provided detailed solutions of these exercises and problems.   The most parts of this course consist in an enhanced version of courses given by the author in both undergraduate and graduate levels during several years.   Remarks and comments that can help to improve this course are welcome.
Oxidative Stress and Inflammation in COPD and Sleep Apnea and Its Comorbidities. Molecular Insights and Artificial Intelligence Approaches in Diagnosis and Prognosis

In chronic respiratory diseases (CRDs), oxidative stress and inflammation exhibit a strong pathophysiological interplay, playing essential roles in the onset and progression of these conditions and their associated comorbidities. Oxidative stress can activate inflammatory pathways, leading to sustained airway inflammation. In turn, chronic inflammation can increase the production of reactive oxygen species (ROS), thereby exacerbating oxidative stress. This vicious cycle contributes to airway remodeling, reduced lung function, and disease progression. This review emphasizes the central roles of inflammation and oxidative stress in two of the most prevalent hypoxemic conditions, chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA), as well as their involvement in the development of major comorbidities. A comprehensive understanding of these processes is crucial to developing therapeutic strategies aimed at reducing oxidative stress and inflammation for the effective management and treatment of CRDs and their comorbidities.  It also underscores the crucial role of hypoxia and its transcriptional effects, mediated by hypoxia-inducible factors (HIF), as a primary driver of disease progression through the promotion of oxidative stress and inflammation. Another key element is the rapid advancement of Artificial Intelligence (AI), which presents promising strategies to mitigate the global burden of CRDs. AI holds potential for reducing healthcare costs while improving diagnostic specificity, enabling earlier detection, and optimizing disease monitoring and management. This review explores the current landscape and future prospects of AI in transforming the diagnosis, clinical management, and prognosis of these respira-tory disorders.
Artificial intelligence in pathologic diagnosis, prognosis and prediction of prostate cancer

Histopathology, which is the gold-standard for prostate cancer diagnosis, faces significant challenges. With prostate cancer ranking among the most common cancers in the United States and worldwide, pathologists experience an increased number for prostate biopsies. At the same time, precise pathological assessment and classification are necessary for risk stratification and treatment decisions in prostate cancer care, adding to the challenge to pathologists. Recent advancement in digital pathology makes artificial intelligence and learning tools adopted in histopathology feasible. In this review, we introduce the concept of AI and its various techniques in the field of histopathology. We summarize the clinical applications of AI pathology for prostate cancer, including pathological diagnosis, grading, prognosis evaluation, and treatment options. We also discuss how AI applications can be integrated into the routine pathology workflow. With these rapid advancements, it is evident that AI applications in prostate cancer go beyond the initial goal of being tools for diagnosis and grading. Instead, pathologists can provide additional information to improve long-term patient outcomes by assessing detailed histopathologic features at pixel level using digital pathology and AI. Our review not only provides a comprehensive summary of the existing research but also offers insights for future advancements.
Thermodynamics of non-elementary chemical reaction networks

Abstract                We develop a thermodynamic framework for closed and open chemical networks applicable to non-elementary reactions that do not need to obey mass action kinetics. It only requires the knowledge of the kinetics and of the standard chemical potentials, and makes use of the topological properties of the network (conservation laws and cycles). Our approach is proven to be exact if the network results from a bigger network of elementary reactions where the fast-evolving species have been coarse grained. Our work should be particularly relevant for energetic considerations in biosystems where the characterization of the elementary dynamics is seldomly achieved.
Geophysical inversions to delineate rocks with CO$_2$ sequestration potential through carbon mineralization

In addition to reducing anthropogenic emissions of CO$_2$, it is increasingly clear we also need to remove CO$_2$ from the atmosphere in order to avoid some of the worst case scenarios for climate change. Geologic sequestration of CO$_2$ is among the most attractive approaches because of the large global capacity and long-time scales for storage. One mechanism of geologic storage is through carbon mineralization. Some mafic and ultramafic rocks contain minerals that will react with CO$_2$ in a carbonation reaction and convert it to carbonated minerals. This is effectively a permanent CO$_2$ storage mechanism. The geologic question we are faced with is then to locate, delineate and estimate the volume of potentially reactive rocks. Using a synthetic model that emulates a prospective site for carbon mineralization in British Columbia, we simulate and invert gravity and magnetic data to delineate reactive rocks. We begin by inverting each data set independently and introduce a proxy experiment to contend with the challenging problem of choosing an appropriate physical-property threshold to estimate volumes from the recovered model. We use this proxy experiment to estimate thresholds for standard, $\ell_2$ inversion of the gravity and magnetics, as well as for inversions which use sparse and compact norms. A Petrophysically and Geologically Guided Inversion (PGI) framework is used to construct quasi-geologic models from which volumes can be estimated directly. We apply the PGI framework to the magnetics and gravity data independently. The framework is also used to jointly invert these data and produce a model that is consistent with both data sets. Cumulative volume estimates with depth are informative and can help decide whether in situ or ex situ sequestration might be appropriate. Using each of the inverted models, we estimate cumulative volume of reactive rock as a function of depth.
Measuring the Consistency of Pancasila Rule of Law Implementation in Ensuring Judicial Independence in Indonesia

This study examines the consistency of the implementation of the Pancasila State of Law in guaranteeing judicial freedom in Indonesia, as stipulated in Article 1 paragraph (3) and Article 24 paragraph (1) of the 1945 Constitution. The Pancasila State of Law integrates the rule of law, protection of human rights, the principles of legality, and judicial independence with Pancasila values that are philosophical, ethical, and religious. Judicial independence, as a key pillar, requires judges to be free from external intervention to produce fair and objective decisions. However, its implementation faces challenges, such as a history of executive intervention, the quality of human resources, and corrupt practices, collusion, and nepotism. This study uses a juridical normative method, analyzes laws and regulations, legal doctrine, and judicial practices in Indonesia, and compares them with the Dutch and United States judicial systems. The results show the need for legal reconstruction through strengthening the guarantee of the position of judge, transparent recruitment, separation of powers, independent budget management, and improving the appeal and cassation mechanisms. This reform will ensure an independent, professional, and integrity judiciary, in line with the values of Pancasila.
Do Not Leave Us Out! Access to Sexual and Reproductive Health Rights for Women with Disabilities

A broad definition of disability that does not prioritise impairment as the primary cause of dysfunction is increasingly accepted in contemporary disability discourse. Disability is defined as long-term physical, mental, intellectual, or sensory impairments that, in interaction with various barriers, may impede full and effective participation in society (United Nations Convention on the Rights of Persons with Disabilities [UNCRPD], 2006). This chapter does not aim to examine access to sexual and reproductive health and rights (SRHR) for women with disabilities through a medicalised lens of disability (Riddle, 2020). Instead, it seeks to explore existing policies in Zimbabwe within the context of a society that is evolving towards greater inclusivity (Berghs et al., 2019). Access to SRHR is crucial for the empowerment of women to enable them to make informed choices regarding their personal lives.
Asymptotic behavior of sample paths for retarded stochastic differential equations without dissipativity

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Comparing Oxidation of Aluminum by Oxygen and Ozone Using Reactive Force Field Molecular Dynamics Simulations

Abstract         This work investigated the Al(100) surface oxidation simulations by O2 and O3 molecules at 400, 600, and 800 K temperatures with the Reactive Force Field (ReaxFF) method. One hundred ozone molecules and 150 oxygen molecules were placed in an empty space above the Al(100) surfaces in separate simulation boxes to compare this metal's behavior with them (gases incipient density of 0.47 g/cm3). We found further growth of the oxide layer in the case of ozone-aluminum. Subsequently, we surveyed the correlation between temperatures and the growth of alumina layers in the case of oxygen and ozone in separate sets through ReaxFF simulation to untangle the mechanism of oxidation kinetics of the Al(100) surface by ozone. Even though there are proven constraints on growing an oxide layer with ozone as well as oxygen, it’s possible to produce a thicker oxide layer at lower temperatures using ozone.
Review of Logistics Models for Perishable Goods: Comparative Analysis of Location Planning and Inventory Management under Supply Chain Disruptions

This study reviews and compares two logistics models tailored to perishable goods, focusing on the spatial and temporal dimensions of supply chain optimization. The first model proposes a population-density-based location planning framework that applies network centrality measures to determine optimal order fulfillment center locations. The second model introduces a two-warehouse inventory policy designed to handle disruption scenarios, such as lockdowns, by balancing demand variation and spoilage rates. Both models were evaluated for their methodological approaches, performance under disruption, and adaptability. The integrated review underscores the necessity of combining spatial efficiency with dynamic stock resilience to improve supply chain effectiveness for perishable goods. Findings suggest that hybrid models leveraging both geographic and temporal decision layers can significantly strengthen logistics adaptability.
From pixels to prognosis: Application and challenges of artificial intelligence in oral disease diagnosis

Background:                     Early and accurate diagnosis of oral diseases is essential for effective treatment, but traditional methods can be subjective and time-consuming. Artificial intelligence (AI) offers potential improvements. This review examines the applications and challenges of AI in oral disease diagnosis.                                                           Objective:                     The objective of this study was to comprehensively review the applications of AI and machine learning (ML) in oral disease diagnosis, focusing on algorithms, diverse applications, and challenges, particularly within the Indian healthcare context.                                                           Method:                     An electronic search was conducted using the PubMed database, focusing on peer-reviewed articles published up to February 2025, using the keywords “Artificial Intelligence,” “Machine Learning,” and “Oral Disease Diagnosis,” which resulted in 15,554, 12,661, and 6,867 items, respectively. After a thorough review, relevant data from other electronic sources were also included for additional information.                                                           Result:                     AI algorithms show potential in enhancing diagnostic accuracy and efficiency for conditions such as caries, periodontal disease, and oral cancer. Implementation challenges include data privacy, limited datasets, regulatory compliance, interpretability, clinical workflow integration, and cost, which are amplified in the diverse Indian landscape due to disparities in healthcare access, digital infrastructure, and linguistic diversity.                                                           Conclusion:                     Addressing challenges through collaboration between researchers, clinicians, policymakers, and industry is essential to responsibly harnessing AI’s transformative potential for more accurate, personalized, and accessible oral healthcare.
Retraction Notice: Efficient Multi-User Computation Offloading and Reducing Latency in Mobile-Edge Computing for IoT Applications

NOTICE OF RETRACTION FOR: Abdul-Samad, Sarmad T.; Al-Hwaidi, Osamah; and Muslem, Ali Abd Al-Rasool (2025) ``Efficient Multi-User Computation Offloading and Reducing Latency in Mobile-Edge Computing for IoT Applications,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 29. DOI: https://doi.org/10.52866/2788-7421.1298. Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/29.
Use of computer vision to detect tangles in tangled objects

Untangling of structures like ropes and wires by autonomous robots can be useful in areas such as personal robotics, industries and electrical wiring &amp; repairing by robots. This problem can be tackled by using computer vision system in robot. This paper proposes a computer vision based method for analyzing visual data acquired from camera for perceiving the overlap of wires, ropes, hoses i.e. detecting tangles. Information obtained after processing image according to the proposed method comprises of position of tangles in tangled object and which wire passes over which wire. This information can then be used to guide robot to untangle wire/s. Given an image, preprocessing is done to remove noise. Then edges of wire are detected. After that, the image is divided into smaller blocks and each block is checked for wire overlap/s and finding other relevant information. TANGLED-100 dataset was introduced, which consists of images of tangled linear deformable objects. Method discussed in here was tested on the TANGLED-100 dataset. Accuracy achieved during experiments was found to be 74.9%. Robotic simulations were carried out to demonstrate the use of the proposed method in applications of robot. Proposed method is a general method that can be used by robots working in different situations.
Price Discrimination in the Information Age: Prices, Poaching, and Privacy with Personalized Targeted Discounts

Abstract                We study list price competition when firms can individually target consumer discounts (at a cost) afterwards, and we address recent privacy regulation (like the GDPR) allowing consumers to choose whether to opt-in to targeting. Targeted consumers receive poaching and retention discount offers. Equilibrium discount offers are in mixed strategies, but only two firms vie for each contested consumer and final profits on them are Bertrand-like. When targeting is unrestricted, firm list pricing resembles monopoly. For plausible demand conditions and if targeting costs are not too low, firms and consumers are worse off with unrestricted targeting than banning it. However, targeting induces higher (lower) list prices if demand is convex (concave), and either side of the market can benefit if list prices shift enough in its favour. Given the choice, consumers opt in only when expected discounts exceed privacy costs. Under empirically plausible conditions, opt-in choice makes all consumers better off.
Inequities in access to health care by income and private insurance coverage : a longitudinal analysis

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Taking a Case to the African Court of Human and Peoples' Rights : Procedural Challenges and the Court's Role in Addressing Them

ABSTRACT The Protocol on the African Court of Human and Peoples’ Rights, adopted in 1998 and entered into force in 2004, is designed to reinforce the human rights protection that has been under the African Commission on Human and Peoples’ Rights. The provisions of the Protocol are not clearly stipulated on points that deal with the salient procedural issues. This thesis explores the challenges that the Court will encounter in applying procedural rules and its role in addressing them. Of specific interest are the questions of which parties have the right of access to the Court, the right of individuals and NGOs to take a case to court, and related admissibility procedures. Further, the jurisdiction of the Court presents the Court with problems of definition. As a result, the central idea of the thesis attempts to unearth the challenges that the Court will come across in interpreting the doubtful provisions. The thesis argues and concludes that it is possible for the Court to address these issues in a proper manner and suggests that it should be judicially active in its interpretation to safeguard the protection of human rights in Africa.
GEM-4D: Geometry-Enhanced Video World Models for Robot Manipulation

Video world models can generate realistic futures from a single instruction, but they often fail to track the same physical points consistently across time. As a result, the generated videos appear plausible, yet lack the physical grounding required for reliable action execution, such as robot manipulation. We present GEM-4D, a geometry-grounded video world model that resolves this limitation by injecting dense 4D correspondence supervision distilled from a pretrained geometry foundation model into the video generative backbone during training. This supervision enables the model to jointly capture appearance and geometric structure while retaining a single-stream architecture with no additional inference cost. We further introduce an inverse dynamics module that converts correspondence-consistent video rollouts into executable robot trajectories, enabling direct deployment in both real-world and simulated manipulation. GEM-4D achieves state-of-the-art performance on both video prediction and geometric consistency across both simulation and realistic scenarios and improves real-world manipulation success from 61% to 81%. Additional results are available at https://gem-4d.github.io/.
From Internet Access Provision to Digital Rights Activism: The History of the French Data Network

This paper chronicles the history of the French Data Network (FDN), France's first community network and first Internet access provider open to the general public, from its foundation in 1992 to the creation of the Fédération FDN in 2011. In the French context, state and public actors have been central in the development of early computer networks such as Cyclades, RENATER, and Minitel. While these actors have already received scholarly attention, very little consideration has been given to the political action of grassroots actors such as FDN, and to their role in the co-shaping of computer networks, their politics, and their users. To help remedy these gaps, the paper traces the evolution of FDN from early concern with Internet access and education to its more recent political commitments. In doing so, this paper simultaneously contributes to the development of a French national history of computer networks, to the ongoing diversification of the historiography of digital rights activism, as well as to future comparative research.
Data Linkage Graph: computation, querying and knowledge discovery of life science database networks

Summary To support the interpretation of measured molecular facts, like gene expression experiments or EST sequencing, the functional or the system biological context has to be considered. Doing so, the relationship to existing biological knowledge has to be discovered. In general, biological knowledge is worldwide represented in a network of databases. In this paper we present a method for knowledge extraction in life science databases, which prevents the scientists from screen scraping and web clicking approaches.We developed a method for extraction of knowledge networks from distributed, heterogeneous life science databases. To meet the requirement of the very large data volume, the method used is based on the concept of data linkage graphs (DLG).We present an efficient software which enables the joining of millions of data points over hundreds of databases. In order to motivate possible applications, we computed networks of protein knowledge, which interconnect metabolic, disease, enzyme and gene function data.The computed networks enabled a holistic relationship among measured experimental facts and the combined biological knowledge. This was successfully applied for a high throughput functional classification of barley EST and gene expression experiments with the perspective of an automated pipeline for the provisioning of controlled annotation of plant gene arrays and chips.Availability: The data linkage graphs (XML or TGF format), the schema integrated database schema (GML or GRAPH-ML) and the graph computation software may be downloaded from the following URL: http://pgrc.ipk-gatersleben.de/dlg/