ethicalabs/Research-Intent-Collab huggingface dataset:
Research on Digital Watermarking Technology Based on Artificial Intelligence Generated Content Model

With the rapid development of Generative Artificial Intelligence (AIGC) technology, the creation and dissemination of digital content have entered a new era. However, issues such as copyright protection, security, and traceability of these generated contents are gradually becoming prominent, and effective technological measures are still needed to address them. Digital watermarking technology, as an effective means to solve these problems, has a wide range of application prospects. This study proposes a new digital watermarking algorithm specifically targeting the characteristics of AIGC generated content, aiming to address the shortcomings of existing technologies in terms of concealment, robustness, and security. By comparing and analyzing existing technologies, improvement plans were proposed and optimized and experimentally verified. The experimental results show that the proposed algorithm can effectively improve the copyright protection capability of content while ensuring the concealment of watermarks, and has good application prospects.
Chromatic Distortion Precompensation in OFDM-Based Optical Systems Through an Integrated Silicon Photonic Neural Network

In this paper, we report an experimental demonstration of using an integrated silicon photonic neural network to overcome the chromatic distortion of direct-detection optical systems based on orthogonal frequency-division multiplexing (OFDM). The precompensation is conducted in the optical domain of a 125 km link of standard single-mode fiber (SSMF), i.e., the proposed approach enables OFDM pre-equalization directly in the optical domain instead of electronic distortion compensation that characterizes common OFDM-based systems. Thanks to the intrinsic features of the OFDM multiplexing format, and to the elimination of cyclic prefix provided by our proposal, improvements in spectral and power efficiencies can be achieved. The performance enhancements registered in the conducted experiments show that photonic integrated circuits can be embedded in future OFDM-based commercial transceivers, paving the way for new and promising architectures of intensity modulation and direct-detection optical communication systems.
Legal Vacuum in Indigenous Peoples' Legal Representation Regarding Communal Land Rights

The aim of this study is to critically examine the normative vacuum regarding the civil representation of indigenous peoples in Indonesia, with a particular focus on disputes over communal land rights The method used is a normative legal approach by examining legislative instruments, jurisprudence, and analysis of selected cases, which aims to reveal systemic weaknesses in the legal recognition of indigenous peoples' representatives in the national legal structure. The novelty lies in its direct involvement in unresolved issues regarding the legitimacy of indigenous community representation in formal judicial and administrative processes, a dimension that has often been overlooked in previous legal studies. The results of the study propose a reform agenda that includes formal legal recognition of customary leadership structures, the establishment of regulatory norms based on the principle of Free, Prior, and Informed Consent (FPIC), and the adjustment of civil law principles to better reflect the customary-based collective governance systems that exist within indigenous communities and Informed Consent/FPIC), and the adjustment of civil law principles to better reflect the collective customary-based governance system that prevails within indigenous communities. The conclusion of the research is that in order to respond to these challenges, this paper proposes a reform agenda that includes formal legal recognition of traditional leadership structures, the establishment of regulatory norms based on the principles of Free, Prior, Prior, and Informed Consent (FPIC) principles, and the adjustment of civil law principles to better reflect the collective and customary governance systems common among indigenous communities.
The Influence of Transformational Leadership and Human Resources Management on Employee Behavior with Organizational Culture as a Mediating Variable

This study examines the influence of transformational leadership and human resources management on employee behavior, with organizational culture as a mediating variable, using the concept of green school. A quantitative approach was employed, utilizing total sampling with 51 teachers and staff as respondents. The data were analyzed using Partial Least Squares (PLS). The results reveal that transformational leadership has a positive but not significant effect on employee behavior, while it has a positive and significant effect on organizational culture. Human resources management shows a positive but not significant effect on employee behavior and a positive and significant effect on organizational culture. Furthermore, organizational culture positively and significantly affects employee behavior and mediates the influence of transformational leadership and human resources management on employee behavior.
Measurement of genome-wide DNA methylation predicts survival benefits from chemotherapy in non-small cell lung cancer

Novel molecular predictive biomarkers for chemotherapy have been screened and validated in non-small cell lung cancer (NSCLC). However, there was no report on the correlation of genome-wide DNA methylation with survival benefit from chemotherapy in NSCLC.A sandwich enzyme-linked immunosorbent assay (ELISA) method was first established, optimized and validated. A total of 191 NSCLC samples were analyzed using the sandwich ELISA for the association between the relative genome-wide DNA methylation level and the survival outcomes from chemotherapy.The analytical performance of the sandwich ELISA method was satisfying and suitable for analysis. Using the sandwich ELISA method, we found that the genome-wide DNA methylation level in NSCLC cancer tissues was significantly lower than that in adjacent normal tissues, which further validated the assay. We found that there was no significant correlation between genome-wide DNA methylation level and patients' histology, stage and progression free survivals. However, in patients with high methylation level, those without chemotherapy had significantly better overall survival than those receiving chemotherapy. In patients receiving chemotherapy, those with low genome-wide DNA methylation level had significantly better overall survival than those with relatively high DNA methylation level.Genome-wide DNA hypomethylation as a sign of genomic instability may predict overall survival benefit from chemotherapy in NSCLC.
Yüksek enerji fiziği parçacık detektörlerinde silikon şerit detektörün geant4 simülasyonu ve root nesneye yönelik veri analiz yapısı = Geant4 simulation of silicon strip detector on high energy physics particle detectors and root a data analysis framework /

Bu çalışmada, Geat 4 benzetim ve ROOT programı kullanılarak silikonun Optik Geçiş Radyasyonu Detektörlerinde görüntü ekranı olarak kullanılabilirliği incelenmiştir. OTR.lar demet hatları boyunca demet profilini ölçmek için kullanılırlar. Benzetim çalışmaları materyal tipi, kalınlığı ve demet enerjisi üzerinde yapılmıştır. Gelen elektron demet enerjisi 18.5MeV ve 38.5MeV seçilmiştir. Görüntü ekranı materyali olarak 0.1.m-5.m kalıklarında alüminyum, kurşun, titanyum, bakır, gümüş, altın ve silikon kullanılmıştır. Benzerim sonuçları demet enerjisi, materyal tipi ve kalınlığına göre tablolar ve şekillerle verilmiştir. Anahtar Kelimeler: Silikon şerit detektörler, OTR görüntüleme sistemi, geant4
Using AI to generate visual art: Do individual differences in creativity predict AI-assisted art quality?

As artificial intelligence (AI) advances in the realm of generative art, a critical question emerges: does human creativity matter? That is, do more-creative people produce more-creative AI-assisted artwork? To explore this, we conducted an online, pre-registered study in which we measured individual differences in creativity through two divergent-thinking tasks: The Alternate Uses Task and the Divergent Associations Task. Separately, participants produced creative wordsets for a hypothetical AI-art generator, which we then input into DALL-E to generate images. A group of trained raters independently assessed these images for creativity. Results revealed that both DAT performance and semantic diversity of the wordsets positively associated with the creativity of the AI-assisted images, suggesting that individuals with stronger divergent-thinking skills, and those who generated more-creative wordsets, tended to inspire more-creative AI-assisted artwork. Mediation analyses supported this conclusion by demonstrating a significant pathway between individual creative ability and AI-art creativity, mediated by semantic diversity. However, while our models yielded significant results, the effect sizes were modest, suggesting that the relationship between individual creative ability and AI-assisted creative outputs is relatively small. Taken together, these results suggest that while individual creativity appears to contribute to the quality of AI-assisted artwork, its influence may be relatively limited.
A comparative study of the conventional item-based collaborative filtering and the Slope One algorithms for recommender systems

Recommender systems are an important research topic in todays society as the amount of data increases across the globe. In order for commercial systems to give their users good and personalized recommendations on what data may be of interest to them in an effective manner, such a system must be able to give recommendations quickly and scale well as data increases. The purpose of this study is to evaluate two such algorithms with this in mind.  The two different algorithm families tested are classified as item-based collaborative filtering but work very differently. It is therefore of interest to see how their complexities affect their performance, accuracy as well as scalability. The Slope One family is much simpler to implement and proves to be equally as efficient, if not even more efficient than the conventional item-based ones. Both families do require a precomputation stage before recommendations are possible to give, this is the stage where Slope One suffers in comparison to the conventional item-based one. The algorithms are tested using Lenskit, on data provided by GroupLens and their MovieLens project.
Face Validation of a Novel Robotic Surgical Simulator

To assess the face validity of Robotic Surgery Simulator (RoSS), a novel virtual reality training platform for the da Vinci Surgical System (DVSS).Urologic surgeons, fellows, and residents attending the 2009 American Urologic Association Annual Meeting in April 2009 were invited to an orientation session with RoSS. Participants completed a questionnaire after orientation and two modules.Thirty participants including 24 surgeons and fellows experienced with robotic surgery and 6 robotic surgery novices participated in the study. Eighty percent participants had at least 4 years of experience with robotic surgery and 77% had performed an average of 340 cases on the DVSS as primary console surgeons. Subjects indicated that RoSS was realistically close to the DVSS console in terms of virtual simulation and instrumentation. Fifty-two percent of subjects rated RoSS somewhat close and 45% rated RoSS very close to the DVSS console. Thirty-seven percent rated RoSS pinch device somewhat close, and 47% very close to the DVSS. With regard to movement of the arms, 43% rated it somewhat close, 40% rated it very close, and 7% felt that it was just like the DVSS. Camera movement and clutch functions were rated not close (11%), somewhat close (57%), and very close (32%) to the DVSS. Data were further analyzed in terms of surgical volume. Thirty-eight percent of subjects had also tried the Mimic dV-Trainer robotic surgery simulator.RoSS provides opportunity for robot-assisted surgical training for future error-free surgery. Further validation will be necessary to assess RoSS and the application of specific modules for robot-assisted surgical training.
Essays on corporate social responsibility reporting: enhacing transparency and communication

This PhD thesis aim to develop the integration and transparency of corporate CSR information. To achieve this goal, it takes up the study of the Triple Bottom Line because this reporting model seems appropriate for this aim. Based on it, it seeks to propose several indications to effectively articulate this report in a practical way. This thesis also tries to demonstrate the importance of the board of directors in establishing these reporting practices as it is the most powerful organism within corporations. Furthermore, it aims to indicate which characteristics of this corporate governance mechanism are more relevant in increasing transparency of CSR information.
Recent Immigrants and Public Charge: Access to Coverage and New Legal Arrivals’ Employment, Self-Employment, and Health Insurance After Medicaid Expansions and the Marketplace

This article uses data from the American Community Survey from 2009 to 2016 to identify the effect of Medicaid expansions and the creation of the ACA Insurance Market Exchange (Marketplace) on low-income recent immigrants’ employment, self-employment, and health coverage. There is increasing interest in the connection between public coverage and employment outcomes among low-income documented immigrants after the current administration proposed to include the use of Medicaid as a potential reason for denying green card and citizenship applications based on the public charge criteria. The article finds little evidence on reduction of employment among those who are eligible in nongenerous states. We find evidence of an increase in the likelihood of being self-employed in generous states that expanded Medicaid before the implementation of the Marketplace. The findings suggests that low-income immigrants are likely to be employed regardless of their years in the country and that access to public coverage only affects the likelihood of having public versus private coverage.
Conflict resolution in Bosnia and Herzegovina: Assessing root causes, limits and possibilities of liberal peace-building

Apesar de todos os recursos dedicados à reconstrução do país após a guerra, a recente reemergência de tensões na Bósnia e Herzegovina sublinham a importância de investigar de forma mais sistemática o processo de construção de paz e as suas limitações. Com o objetivo de compreender e explicar o ressurgimento das tensões, esta tese pretende avaliar o processo de manutenção da paz e reconstrução do Estado e, mais especificamente, investigar até que ponto a abordagem liberal adotada neste processo veio contribuir para fomentar as recentes tensões. A Bósnia e Herzegovina pode ser considerado um exemplo clássico do modelo liberal da construção de Estado em ação e, nesse sentido, representa um excelente caso para discutir as limitações inerentes a esta abordagem. A principal conclusão avançada pela tese é a de que, dadas as atuais ameaças da Republica Srbska em declarar independência da Bósnia e Herzegovina, se torna evidente que a abordagem liberal adotada neste contexto foi incapaz de assegurar uma paz sustentável a longo prazo.
COX’S REGRESSION MODEL FOR RELIABILITY ANALYSIS AND FAILURE TIME PREDICTION IN ENGINEERING SYSTEMS

Reliability engineering is essential for predicting failure times, optimizing maintenance strategies, and minimizing operational risks in engineering systems. Traditional models, such as Weibull and exponential distributions, provide useful insights into failure rates but struggle to incorporate multiple influencing factors. Cox’s Proportional Hazards Model offers a more flexible approach by integrating covariates such as environmental stress, operational loads, and maintenance history, without assuming a predefined failure time distribution. This study explores the application of Cox’s regression model in reliability analysis, focusing on failure time prediction and system longevity assessment under varying operational conditions. A major advantage of Cox’s model is its ability to handle censored data, a common challenge in reliability studies where some systems remain operational beyond the observation period. By employing the partial likelihood estimation method, the model quantifies the impact of various covariates on failure risks without requiring explicit assumptions about baseline hazard functions. This study utilizes a simulated dataset of 20 industrial components observed over five years to demonstrate the model’s effectiveness in predicting system failures and estimating survival probabilities. The study further evaluates parameter estimation techniques, including maximum likelihood estimation (MLE) and Type I and Type II censoring, to validate the model’s predictive power in practical reliability applications. Additionally, statistical computations confirm that the Cox model provides reliable hazard rate estimations, enabling engineers to develop predictive maintenance schedules and enhance system reliability. This research highlights the importance of survival analysis techniques in reliability engineering. Cox’s model proves to be an effective tool for identifying risk factors and optimizing failure time predictions. The methodology is applicable to diverse engineering domains, including mechanical component wear analysis, structural health monitoring, and software reliability assessment.
<i>XMM‐Newton</i>Observations of the Supernova Remnant IC 443. I. Soft X‐Ray Emission from Shocked Interstellar Medium

The shocked interstellar medium around IC443 produces strong X-ray emission in the soft energy band (E&lt;1.5 keV). We present an analysis of such emission as observed with the EPIC MOS cameras on board the XMM-Newotn observatory, with the purpose to find clear signatures of the interactions with the interstellar medium (ISM) in the X-ray band, which may complement results obtained in other wavelenghts. We found that the giant molecular cloud mapped in CO emission is located in the foreground and gives an evident signature in the absorption of X-rays. This cloud may have a torus shape and the part of torus interacting with the IC443 shock gives rise to 2MASS-K emission in the southeast. The measured density of emitting X-ray shocked plasma increases toward the northeastern limb, where the remnant is interacting with an atomic cloud. We found an excellent correlation between emission in the 0.3-0.5 keV band and bright optical/radio filament on large spatial scales. The partial shell structure seen in this band therefore traces the encounter with the atomic cloud.
An Assessment of the Application of Generative Artificial Intelligence in News Content Production at Clouds Media Group, Tanzania

Purpose: This study assessed the use of generative Artificial Intelligence (AI) in the Clouds Media Group (CMG) newsroom in Tanzania. Applying the Technology Acceptance Model (TAM), it investigated journalists' attitudes toward the usefulness and ease of use of these tools and their experiential content opportunities, providing a granular view of technology adoption in a Global South context.  Methodology: The study adopted a qualitative explanatory design to delve into the nuanced realities of the newsroom. Data was collected through semi-structured, in-depth interviews with six purposefully selected journalists, editors, and technical staff at CMG, ensuring a representation of strategic, operational, and technical perspectives. Thematic analysis, following the framework of Braun and Clarke (2006), was used to analyze the data, generating rich, context-driven insights.  Findings: CMG journalists found generative AI beneficial for improving efficiency in research, transcription, and drafting, as well as enhancing creativity in storytelling and data analysis. The tools were widely considered user-friendly, which justified their organic, bottom-up adoption. However, this adoption was hampered by significant challenges, including reliance on informal peer-to-peer training, critically inadequate infrastructure (e.g., poor internet, outdated hardware), and significant ethical issues like the provision of misinformation, inaccuracy, and the potential deskilling of employees. The absence of formal organizational AI policies was a critical gap, leading to piecemeal and uneven assimilation and creating a landscape of both opportunity and risk.  Unique Contribution to Theory, Policy, and Practice: The study confirms the primary components of the Technology Acceptance Model (TAM) in the Tanzanian context while simultaneously illustrating a significant "ease of use paradox." This paradox states that while tools may be intrinsically easy to use, their effective adoption is significantly hindered by external structural and training issues, a factor not fully accounted for in the original model. This finding suggests that Technology Adoption Models applied in the Global South need to be re-contextualized to incorporate these critical environmental variables. The report underlines the urgent necessity for drafting national AI ethics guidelines and specific media policies for Tanzania to ensure accountability, transparency, and public trust. Furthermore, it provides media houses with a comprehensive, actionable guide for the responsible incorporation of AI technologies, pivoting on the urgent need for formal training, advanced internal digital infrastructure and internal charters on AI Ethics to govern use.
The Precautionary Principle and Statistical Approaches to Uncertainty

The central challenge from the Precautionary Principle to statistical methodology is to help delineate (preferably quantitatively) the possibility that some exposure is hazardous, even in cases where this is not established beyond reasonable doubt. The classical approach to hypothesis testing is unhelpful, because lack of significance can be due either to uninformative data or to genuine lack of effect (the Type II error problem). Its inversion, bioequivalence testing, might sometimes be a model for the Precautionary Principle in its ability to "prove the null hypothesis". Current procedures for setting safe exposure levels are essentially derived from these classical statistical ideas, and we outline how uncertainties in the exposure and response measurements affect the no observed adverse effect level, the Benchmark approach and the "Hockey Stick" model. A particular problem concerns model uncertainty: usually these procedures assume that the class of models describing dose/response is known with certainty; this assumption is, however, often violated, perhaps particularly often when epidemiological data form the source of the risk assessment, and regulatory authorities have occasionally resorted to some average based on competing models. The recent methodology of the Bayesian model averaging might be a systematic version of this, but is this an arena for the Precautionary Principle to come into play?