Miracle-dz/UniFAR-FTUs huggingface dataset:
Automating Website Registration for Studying GDPR Compliance

Investigating how websites use sensitive user data is an active research area. However, research based on automated measurements has been limited to those websites that do not require user authentication. To overcome this limitation, we developed a crawler that automates website registrations and newsletter subscriptions and detects both security and privacy threats at scale. We demonstrate our crawler’s capabilities by running it on 660k websites. We use this to identify security and privacy threats and to contextualize them within EU laws, namely the General Data Protection Regulation and ePrivacy Directive. Our methods detect private data collection over insecure HTTP connections and web-sites sending emails with user-provided passwords. We are also the first to apply machine learning to web forms, assessing violations of marketing consent collection requirements. Overall, we find that 37.2% of websites send marketing emails without proper user consent. This is mostly caused by websites failing both to verify and store consent adequately. Additionally, 1.8% of websites share users’ email addresses with third parties without a transparent disclosure.
Are You Sure? - Multi-Modal Human Decision Uncertainty Detection in Human-Robot Interaction

In a question-and-answer setting, the respondent is often not only communicating the requested information but also indicating their confidence in the answer through various behavioral cues. Humans excel at interpreting these cues and monitoring the uncertainty of other persons. Being able to detect human uncertainty in human-robot interactions in a similar way can enable future robotic systems to better recognize uncertain and error-prone human input. Additionally, automatic human uncertainty detection can enhance the responsiveness of robots to the user in moments of uncertainty by providing help or clarification. While there is some work on uncertainty detection based on a single modality, only a few works focus on multi-modal uncertainty detection. Even fewer works explore how human uncertainty manifests through behavioral cues in human-robot interactions. In this work, we analyze occurrences of behavioral cues related to self-reported uncertainty on experimental data from 27 participants across two decision-making tasks
VU Research Portal Data Clustering by Large-Scale Adaptive Agent Systems

Finding items with speciﬁc characteristics in large distributed systems can be problematic. Directories, the most common way of enabling capability-based search in distributed systems, gather in a central location data which is often inherently decentralized. This paper considers an alternative decentralized method of enabling search, which leaves data objects in place at their natural location within a physically distributed network. This form of decentralized search is likely to gain importance as computer systems become more widely distributed and the autonomy of their components increases. Autonomy plays a key role in this development since it precludes the global use of a single comparison method for determining the similarity of objects. With this in mind, this work explores the ability of explicitly autonomous peer-to-peer agents to form themselves into groups within an overlay network, based on their locally perceived similarity, thus providing a structure that can facilitate search. We introduce a decentralized clustering procedure, designed to discover small clusters (of 500 items or less) in very large, widely distributed sets of data. This procedure is shown to scale well in the number of clusters. The paper further demonstrates that for 2D spatial data it produces clusterings that compare well to those produced by central clustering algorithms, especially for data sets that contain widely varying cluster characteristics.
Modality Translation through Conditional Encoder-Decoder

With the recent rise of multi-modal learning, many of the developed models are task-specific, and, as a consequence, lack generalizability when applied to other types of down-stream tasks. One of the representative models that overcomes this issue of generalizability is CLIP, which attacks downstream tasks using cosine similarity metric. However, CLIP has shown relatively low cosine similarity between text and image vector representations. For this reason, we aim to develop a new approach that more accurately maps the hyperplanes of text and image embeddings, and thus, achieves a high-quality text-image modality translation. To this end, we propose a new conditional encoder-decoder model that maps a latent space of one modality given another modality as a condition. We observe that our model is a general method that can be used with various latent encoders and decoders, which are not limited to multi-modal models. Experiments show that conditional encoder-decoder achieves comparable results with the previous state-of-the-art on several downstream tasks.
Human Neuroscience

and Pressley, 1999), little is known about how these processes may mediate the complementary ability to prevent successful memory. Addressing this question is thus important for a comprehensive theory of memory and its development, as well as to draw interesting connections with other domains of psychology, such as coping and emotion regulation. A growing body of research documents that with development children acquire increasingly sophisticated notions about mind control (Flavell, 1999), and about the cognitive strategies that can be used to cope with stressors. For instance, the frequency with which participants report using coping strategies capitalizing on cognitive distraction, such as diversionary thinking or attempts to forget a stressor, increases from middle childhood to adolescence (e.g., Altshuler and Ruble, 1989; Skinner and Zimmer-Gembeck, 2007). These observations suggest that the ability to exert control over memory retrieval develops during middle childhood years. However, the developmental trajectory of the capacity to actively prevent unwanted information from entering consciousness , and its effects on long-term memory are unknown. Thus, the present research offers a window into the developmental progression of the ability to regulate memory retrieval and into further examinations of its neurodevelopmental underpinnings. To examine the development of intentional memory suppression, we used a child-friendly version of the TNT paradigm (Anderson
Evaluating the Cybersecurity Robustness of Commercial LLMs against Adversarial Prompts: A PromptBench Analysis

—This study presents a comprehensive evaluation of the cybersecurity robustness of five leading Large Language Models (LLMs) - ChatGPT-4, Google Gemini, Anthropic Claude, Meta Llama, and Mistral 8x7B - against adversarial prompts using the PromptBench benchmark. Through a dual approach of quantitative and qualitative analysis, the research explores each model’s performance, resilience, and vulnerabilities. Quantitative metrics such as accuracy, precision, recall, and F1 scores offer a statistical comparison across models, while qualitative insights reveal distinct patterns of response and susceptibility to various adversarial strategies. The findings highlight significant variations in model robustness, underlining the importance of a complex approach to enhancing LLM security. This study not only sheds light on current limitations but also emphasizes the need for advancing evaluation methodologies and model development practices to mitigate potential threats and ensure the safe deployment of LLMs in sensitive and critical applications.
DigitalCommons@Kennesaw State University DigitalCommons@Kennesaw State University

: Research has shown that during the COVID-19 pandemic, approximately 20% of children and adolescents in the United States experienced mental health issues that became a signiﬁcant social concern. However, recent studies have demonstrated that the majority of adolescents maintain positive emotions despite the crisis. This cross-sectional and descriptive study delves into the emotional states of adolescents during the pandemic, considering the viewpoints of both adolescents and their parents, with a speciﬁc focus on Hispanic adolescents. Survey results revealed that most adolescents reported positive and happy moods. However, a percentage of adolescents experienced worry, signiﬁcant changes in feelings, and loneliness as a result of the physical and social isolation associated with virtual learning. Unfortunately, most surveyed Hispanic parents did not adequately recognize their adolescents’ mood changes well. This lack of awareness, caused by factors such as an insufﬁcient understanding about the importance of adolescent mental health, cultural reasons, language barriers, low education, unstable jobs, and more, could lead to missed opportunities for timely mental health interventions. This study seeks to provide a comprehensive discussion on the mental health of adolescents, while also advocating for the emotional wellbeing of Hispanic adolescents.
North Pacific Subtropical Mode Water Volume and Density Anomalous Decrease in a Recent Stable Kuroshio Extension Period from Argo Observations

North Pacific subtropical mode water (NPSTMW) is formed as the low stratification water mass in the wintertime mixed layer south of the Kuroshio Extension (KE). In a recent period of 2018-2021, the KE jet is in a persisting stable 10 dynamic state. But based on analysis of Argo observation, the mean volume of NPSTMW in ventilation region drop anomalously by ~21% during 2018-2021 relative to 2012-2015 when the KE jet is likewise stable. Moreover , the NPSTMW volume in denser density range (approximately   >25.2 kg m -3 ) starts to decrease but the volume of lighter density of the NPSTMW increases since 2018. The decreasing of the NPSTMW subduction and formation rate are associated with anomalously shallow wintertime mixed layer depth (MLD) and weak heat loss in the NPSTMW formation 15 region. The interannual variations of the NPSTMW subduction and formation reflect the variability of the overlying atmosphere which is correlated with Pacific decadal oscillation (PDO) shift in 2018-2021. When the PDO shifts from its positive to a negative phase in analysis period, the effects of local wind stress anomalies seem to play an evident role in driving the variability of NPSTMW on interannual time scales. The MLD and heat loss change during the cold season in 2018-2021 are strongly coupled with the poleward shift of the westerlies-which cause the weaker wintertime wind and the 20 easterly wind anomalies over the NPSTMW formation region. The declines of
Real-Time System Benchmarking with Embedded Linux and RT Linux on a Multi-Core Hardware Platform

To catch up with the growing trend of parallelism, this thesis work focuses on the adaption of embedded real-time systems to a multicore platform. We use the embedded system of Xilinx ZCU-102, a multicore board, as an example of an embedded system without getting deep into its architecture. First, we deal with the tasks required to be able to make an embedded system operational and discuss why they are different from those for normal computer systems. The processes it takes to make a custom operating system for the given Xilinx embedded system are examined and patching the custom operating system along with customizing it is studied. We then take a look at related work in the field of benchmarking real-time systems and embedded systems and with a good understanding of related work propose a design similar to the related work for benchmarking embedded systems. The benchmarks we use run on multiple cores and aim at challenging the Xilinx board’s capabilities of running real-time tasks when the other cores on the board are occupied with performing independent tasks. We test the designed benchmarks on different conditions under two different operating systems of RT-Linux and Embedded Linux to study the differences between them. We then note how the RT-Linux would be a real up-grade for real-time systems if multicore operations are considered. The final result we have obtained is that core idling might decrease the performance of real-time tasks and RT-Linux might experience more interrupts but it is also better at recovering from interrupts.
Historical

The objective of the study was to reconstruct the emergence, development and abandonment of the bilingual-bicultural model in Venezuelan public schools for the deaf between 1985 and 1996. Although this process has been previously addressed by some academic publications, all of them are limited to the points of view of teachers linked to the university sector. The novelty of the present article consisted in its reconstruction based on the direct testimonies of protagonists of the model who occupied different roles in it: a manager of the educational sector, a teacher, a mother of a deaf child, a deaf person who visited the school during the application of the model, and a Venezuelan Sign Language (LSV) interpreter. Accordingly, new perspectives were expected to enrich the current understanding of the model. Indeed, the analysis of the data collected in individual interviews contrasts the limited scope of the model in achieving the intended school transformations with its enormous impact on the power relations of the languages involved: within the Deaf community, LSV went from being the low variety to becoming the high variety in relation to signed Spanish. The latter implied the empowerment of the Deaf identity. That change originated in the model, but transcended it beyond its abandonment in 1996.
ANNALES DE L’INSTITUT FOURIER

— We prove a D = 1 analytic versal deformation theorem in the Heisenberg algebra. We deﬁne the spectrum of an element in the Heisenberg algebra. The quantised version of the Morse lemma already shows that the perturbation series arising in a perturbed harmonic oscillator become analytic after a formal Borel transform. Résumé. — Nous démontrons un théorème de déformation verselle analytique pour l’algèbre de Heisenberg dans le cas D = 1 . Nous déﬁnissons le spectre d’un élément dans cette algèbre. La quantiﬁcation du lemme de Morse montre que les séries perturbatives du spectre de l’oscillateur harmonique deviennent analytique après une transformation de Borel formelle.
A systematic literature review: ESG criteria implementation in the Insurance industry

Purpose: Sustainability and ESG criteria are gaining more and more relevance, and the insurance industry is playing a relevant role in the sustainability transition. Therefore, this study aims to review existing academic literature on ESG criteria in the insurance industry. Specifically, it addresses the determinants in three objectives: First, analysing the focus on sustainability considering the three dimensions of the ESG framework: environment, social and governance; the second one, focusing on the relevant topics in the insurance industry involving the ESG criteria. And finally, identifying the main gaps and point out new research lines.Design/methodology: The research was conducted through a systematic literature review considering published articles of Web of Science and Scopus.Originality/value: Although the insurance industry has a very relevant weight into the economy and the society, and it plays a key role in promoting the transition to a low-carbon economy, we noticed that there are not many scientific articles on this subject.Findings: Findings contribute to the body of literature on sustainable finance, providing a new and complete overview about how ESG criteria implementation has been approached in the insurance industry: mapping research streams, analysing the ESG approach, and identifying research gaps in this domain.Practical implications: This article wants to provide a broader and a more structured knowledge about ESG criteria implementation, and to help managers and insurance companies to move forward with sustainability strategies, and to identify the future lines of research.Social Implications: Business sustainability aims to combine market logic with social welfare logic, but we have found little activity on how insurance companies develop the social dimension within the ESG perspective, as a way to influence the community by promoting equal practices, access to education, etc.
Phenolics content and antioxidant properties of Strobilanthes crispus as affected by different extraction solvents

Strobilanthes crispus or locally known as Pecah Kaca among Malaysian is a medicinal plant that belongs to the family Acanthaceae. S. crispus is an ethnomedicinal plant with high antioxidant content and is indicated in the treatment of diabetes, cancer, and hypertension. This study was conducted to study the phenolics content and antioxidant properties of S. crispus leaf as affected by different concentrations of extraction solvents. In this study, water and various concentrations (25, 50, 75 and 100%) of methanol and acetone in water were used as extraction solvent of S. crispus dried leaves. The antioxidant properties of S. crispus were measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH) (free radical scavenging activity and ferric reducing antioxidant power (FRAP) assays. The highest polyphenols and phenolic acids content were recorded in 50% acetone extract with 10.80 and 33.86 mg GAE g − 1 DW, respectively. Meanwhile, the highest total ﬂavonoids content (4.98 mg QE g − 1 DW) was obtained in 100% acetone extract. In the antioxidant analysis, the highest DPPH free radical scavenging activity was exhibited from 75% acetone extract with 24.88 mg TE g − 1 DW and the highest FRAP value was obtained from 25% acetone extract with 47.21 mg TE g − 1 DW. In conclusion, acetone was found to be the most suitable extraction solvent for phenolics content and antioxidant properties of S. crispus leaf in this study.
in 26 Billion RDF Triples

We present SemOpenAlex , an extensive RDF knowledge graph that contains over 26 billion triples about scientiﬁc publications and their associated entities, such as authors, institutions, journals, and concepts. SemOpenAlex is licensed under CC0, providing free and open access to the data. We oﬀer the data through multiple channels, including RDF dump ﬁles, a SPARQL endpoint, and as a data source in the Linked Open Data cloud, complete with resolvable URIs and links to other data sources. Moreover, we provide embeddings for knowledge graph entities using high-performance computing. SemOpenAlex enables a broad range of use-case scenarios, such as exploratory semantic search via our website, large-scale scientiﬁc impact quantiﬁcation, and other forms of scholarly big data analytics within and across scientiﬁc disciplines. Additionally, it enables academic recommender systems, such as recommending collab-orators, publications, and venues, including explainability capabilities. Finally, SemOpenAlex can serve for RDF query optimization benchmarks, creating scholarly knowledge-guided language models, and as a hub for semantic scientiﬁc publishing.
UvA-DARE (Digital Academic Repository) Futures of the social metabolism: Degrowth, circular economy and the value of waste

Circular economy and degrowth offer two different imaginaries for a future social metabolism: both seek to downscale waste and the demand for raw materials. Yet whereas degrowth proposes a circular metabolism to reduce consumption and production, mainstream circular economy sees waste as an opportunity for sustainable growth. This paper puts these two visions of circular futures into dialog. It unpacks the institutional dimensions of these two approaches, focusing on how they produce relations with and responsibilities to the future. It argues that the extent to which circularity can deliver its promise of reduction depends on the value that is ascribed to both present and future waste. This value is defined by the institutional conditions that regulate the responsibilities, geographies and conceptions of value mobilized in dealing with waste. The paper dissects three institutional shifts necessary for a degrowth circularity: from individual consumers to collective responsibilities in waste reduction, from global regional waste markets to bio-regional waste economies and from monetary to socio-ecological value of waste.
Interfacial Form Stress in the Southern Ocean State Estimate

The wind stress that drives the Antarctic Circumpolar Current (ACC) exits the fluid via topographic form stress (TFS) at the sea floor; interfacial form stress (IFS) is thought to carry much of this momentum from source to sink. These form stresses combine to help set the strength and structure of the Southern Ocean meridional overturning circulation (MOC), a key nexus of heat and gas exchange between the deep ocean and the atmosphere. For the first time in a general circulation model, we calculate the timevarying, three-dimensional IFS field directly from zonal pressure gradients across vertical perturbations in isopycnal layer interfaces. We confirm previous findings that IFS compensates wind stress at the surface and topographic form stress at the seafloor in the Drake Passage latitudes. We find that zonal and time-mean IFS is primarily responsible for this surface wind stress compensation, with some contribution from transient eddy IFS. Mean, standing eddy, and transient eddy IFS combine to compensate topographic form stress at depth. Both standing and transient eddy IFS concentrate at stationary meanders along the ACC, and transient eddy IFS dominates standing eddy IFS in regions of high eddy kinetic energy. Finally, total IFS changes sign from balancing eastward wind stress to balancing westward topographic form stress around 28.1 kg m, close to the upper limit of Antarctic Bottom Water, indicating the role of buoyancy forcing in setting the structure of the IFS field. Plain Language Summary Winds over the Southern Ocean blow toward the east, continuously inputting eastward momentum into the ocean. This eastward momentum is balanced by the landmasses and undersea ridges that block the Antarctic Circumpolar Current (ACC)’s eastward path around Antarctica. We analyze a high-resolution model of the Southern Ocean to map interfacial form stress (IFS), the mechanism by which momentum travels from wind source to seafloor sink. We conduct this analysis in a new, unique way, by calculating the pressure exerted from one ocean layer to another for every day in the 6 year model run; this analysis shows where lighter layers are ‘‘leaning’’ against denser layers and thus transferring eastward momentum downward from lighter to denser ocean layers. We find that IFS mostly concentrates where there are large-scale meanders in the ACC, and to a lesser degree in regions where the Southern Ocean is mixed by eddies.
Diversity of Indigenous Fish Species in Ratargul Freshwater Swamp Forest, Bangladesh

Understanding the biodiversity indices provide key information for the conservation and management of natural aquatic ecosystem. The present study was conducted in the Ratargul freshwater swamp forest of Bangladesh from April to October 2016 to assess the biodiversity status of indigenous fish species. A total 62 fish species comprising 28 threatened species were recorded. Cypriniformes (37.46%) was the most dominant order while Anguiliformes (0.026%) was in lest dominant. Among the identified fish species 19.98% was recorded as threatened following IUCN. The Mean Shannon-Wiener index, Margalef richness index, Pielou‟s evenness index and Simpson dominance index were counted as 3.690±0.191, 9.497± 1.314, 0.971±0.003 and 0.982±0.003, respectively. In case of similarity percentages analysis, the highest number of similar species was found during July to August and the lowest during April to October. It may be concluded that Ratargul swamp forest is enriched with fish biodiversity.
Village housing investments of multi-locational households and their spatial and environmental impacts: Case study of Kilimanjaro region, Tanzania

v TABLE OF CONTENTS. vi LIST OF TABLES . xiv LIST OF FIGURES . xxii ABBREVIATIONS . xxviii CHAPTER ONE . 1 MOTIVATION AND THE STATEMENT OF THE PROBLEM . 1 1.