ethicalabs/Research-Intent-Collab huggingface dataset:
Supplementary Figure S1 from Blood-Based Genomic Alteration Signature for Predicting Progression-Free Survival in &lt;i&gt;De Novo&lt;/i&gt; Metastatic Hormone-Sensitive Prostate Cancer: A Real-World Study

&lt;p&gt;Figure S1. Construction of the alternative genes signature for prognostic risk prediction.&lt;/p&gt;
How participation as a right enhances realization of the rights to water and sanitation

‘User participation’ and ‘community ownership’ have been part of the lexicon of the water and sanitation sector since the adoption of the integrated water resource management approach in the 1980s. However, these terms have their origin in an era of budget cuts, and therefore participation has been invariably evaluated and justified in instrumental terms – what it can do for project outcomes such as sustainability. This article argues that participation is a right and ought to be incorporated into all stages of decision-making concerning water and sanitation. The human rights standard for participation is that it should be ‘active, free and meaningful’. This article identifies and analyses the elements of active, free, and meaningful participation, as elaborated in various international human rights documents and selected national experiences. The implications of this analysis are then considered at the various stages of decision-making: planning and formulation of policy and legal frameworks, finance and...
Digital Colonialism and the Role of Local Intermediaries: Examining Big Tech’s Impact on Data Sovereignty and Human Rights in Africa

Abstract                   This article explores digital colonialism in Africa, focusing on how Big Tech and local intermediaries perpetuate data exploitation, infrastructure dependency and algorithmic bias. Applying a Third World Approaches to International Law (TWAIL) lens, it draws parallels between historical colonialism and the modern digital economy, highlighting persistent power imbalances in data control and tech sovereignty. Multinational firms from the Global North extract and monetise African data with little benefit to local communities, reinforcing dependency. Local actors (governments, tech elites and influencers) often enable this through policy gaps and cultural alignment with Western platforms. The article examines the impact on data sovereignty, human rights and economic autonomy, including risks of surveillance and silencing local voices. It calls for policy reforms, investment in African tech ecosystems, digital literacy and robust regional regulation. Ultimately, it advocates for digital justice and self-governance to reclaim Africa’s digital future.
Having a toilet is not enough: the limitations in fulfilling the human rights to water and sanitation in a municipal school in Bahia, Brazil

This article addresses the enjoyment of the human rights to water and sanitation (HRTWS), in particular access to toilets, in a public school in Bahia, Brazil.Participant observation of the school's routine, focus groups with students in grades 8 and 9 of primary school (13 to 17 years old) and individual, semi-structured, interviews with members of school staff were applied, exploring access to water and sanitation by adolescent girls and boys.Students and school staff reported that the amount of toilets was insufficient and that their conditions were often inadequate because they were plugged or dirty. The impact on girls is greater as toilets do not offer a clean and healthy environment for menstrual hygiene management. Several elements of the normative content of the HRTWS, especially accessibility, acceptability, quality, safety and dignity, were largely not fulfilled. The study identified that, to comply with the HRTWS, it is necessary to go beyond infrastructure, as the lack of maintenance; cultural elements and student participation hinder the usage of sanitary facilities. Since schools can be privileged spaces to train critical and reflective citizens and to foster autonomy and emancipation, education oriented by human rights and citizenship is an opportunity for a more equitable society. By increasing access to social, economic and cultural rights in all phases and aspects of life, including when children and adolescents are in a school environment, people are able to enjoy better living conditions and a higher standard of health.The study raised the importance of considering each community's sociocultural aspects in analyzing access to sanitary facilities in schools, which are spaces where citizens' rights should be exercised and fulfilled.
Computing quantum phase transitions

This article first gives a concise introduction to quantum phase transitions, emphasizing similarities with and differences to classical thermal transitions. After pointing out the computational challenges posed by quantum phase transitions, a number of successful computational approaches is discussed. The focus is on classical and quantum Monte Carlo methods, with the former being based on the quantum-to classical mapping while the latter directly attack the quantum problem. These methods are illustrated by several examples of quantum phase transitions in clean and disordered systems.
Adopting Human Resource Information System (HRIS)-Enabled Government Transformation: Perspective of MBHTE Employees

MBHTE dealing with a 60 percent the number of BARMM employees requires strategic direction so that desired changes will be attained. Addressing identified issues and concerns will enable the ministry to accomplish its tasks effectively and efficiently. Recently the Ministry developed and piloted HRIS as a way of improving the reporting and monitoring of government employees through automation. The main function of these features in the dashboard application is to provide automated reports of (1) HR Management, (2) Performance Evaluation, (3) Document/Files, (4) Data Parameter, and (5) User Management. To determine the system performance of MBHTE HRIS this study used a quantitative descriptive survey to gauge the extent of the HR Information System performance of 240 respondents coming from MBHTE regional level. This paper documented that the significant difference between HR Manual System and HR Information system is very large thus the former manifested a grand mean result of 2.27 while the latter acquired a grand mean result of 4.56. Therefore, MBHTE HR Information System is high performing since it manifested a result of each indicator ranging from 4.44-to 4.65. Praying that this documentation will serve as a data reference for the proposal of a policy, training, and utilization of the MBHTE HR Information System.
Epigenetic Regulation of Telomere Chromatin Integrity in Pluripotent Embryonic Stem Cells

Telomeres are protective chromosomal structures highly conserved from primitive organisms to humans. The evolutionary conservation of telomere DNA implicates the importance of telomeric structure for basic cellular functions. Loss of telomere function causes chromosomal fusion, activation of DNA damage checkpoint responses, genome instability and impaired stem cell function. In human cells, the telomeric chromatin consists of TTAGGG repeats associated with a complex of proteins known as Shelterin. It is also organized in nucleosomes enriched with epigenetic modifications of 'closed' or 'silenced' chromatin states, including DNA hypermethylation and trimethylation of H3K9 and H4K20. These heterochromatin marks serve as a higher-order level of control of telomere length and structural integrity. Recent studies have shown that the telomere nucleosome in pluripotent embryonic stem cells is characterized by a more 'open' chromatin state that switches to become more repressive during differentiation. Conversely, the reprogramming of adult somatic cells into induced pluripotent cells results in the switch in telomeric chromatin from a repressive to a more open embryonic stem cell-like state, coupled with the restoration of telomere length. These findings indicate that telomeric chromatin is dynamic and reprogrammable, and has a fundamental role in the maintenance of embryonic stem cell pluripotency.
Potential risks and governance strategies of artificial intelligence generated content technology

Artificial intelligence generated content technology is reshaping the production and consumption patterns of digital content.The research was based on the basic concepts and technological development process of artificial intelligence generated content technology, focusing on exploring ethical risks and governance challenges such as privacy leakage, algorithm hegemony, digital divide, intellectual property protection and employment impact caused by artificial intelligence generated content.After reviewing the typical governance paths and experiences of developed countries abroad, this paper summarized and proposed measures and development suggestions for China to address the potential risks of AI generated content.One was to prioritize development and coordinate layout; Second was to strengthen the full factor investment in the research and development of artificial intelligence technology; Third was to improve the governance rule system of artificial intelligence technology; Fourth was to accelerate the research and development of artificial intelligence governance technology.
A CHAID Based Performance Prediction Model in Educational Data Mining

The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining model for students' performance so as to identify the slow learners and study the influence of the dominant factors on their academic performance. In the present investigation, a survey cum experimental methodology was adopted to generate a database and it was constructed from a primary and a secondary source. While the primary data was collected from the regular students, the secondary data was gathered from the school and office of the Chief Educational Officer (CEO). A total of 1000 datasets of the year 2006 from five different schools in three different districts of Tamilnadu were collected. The raw data was preprocessed in terms of filling up missing values, transforming values in one form into another and relevant attribute/ variable selection. As a result, we had 772 student records, which were used for CHAID prediction model construction. A set of prediction rules were extracted from CHIAD prediction model and the efficiency of the generated CHIAD prediction model was found. The accuracy of the present model was compared with other model and it has been found to be satisfactory.
Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks

Currently, the number of common benchmark datasets that researchers can use straight away for assessing data-driven deep learning approaches is very limited. Most studies provide data as configuration files. It is still up to each practitioner to follow a particular data generation method and run computationally intensive simulations to obtain usable data for model training and evaluation. In this work, we provide a collection of datasets that includes several small and medium size publicly available Water Distribution Networks (WDNs), including Anytown, Modena, Balerma, C-Town, D-Town, L-Town, Ky1, Ky6, Ky8, and Ky13. In total 1,394,400 hours of WDNs data operating under normal conditions is made available to the community.
Semantics of the Black-Box: Can Knowledge Graphs Help Make Deep Learning Systems More Interpretable and Explainable?

The recent series of innovations in deep learning (DL) have shown enormous potential to impact individuals and society, both positively and negatively. The DL models utilizing massive computing power and enormous datasets have significantly outperformed prior historical benchmarks on increasingly difficult, well-defined research tasks across technology domains such as computer vision, natural language processing, signal processing, and human-computer interactions. However, the Black-Box nature of DL models and their over-reliance on massive amounts of data condensed into labels and dense representations poses challenges for interpretability and explainability of the system. Furthermore, DLs have not yet been proven in their ability to effectively utilize relevant domain knowledge and experience critical to human understanding. This aspect is missing in early data-focused approaches and necessitated knowledge-infused learning and other strategies to incorporate computational knowledge. This article demonstrates how knowledge, provided as a knowledge graph, is incorporated into DL methods using knowledge-infused learning, which is one of the strategies. We then discuss how this makes a fundamental difference in the interpretability and explainability of current approaches, and illustrate it with examples from natural language processing for healthcare and education applications.
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice

Many currently deployed Reinforcement Learning agents work in an environment shared with humans, be them co-workers, users or clients. It is desirable that these agents adjust to people's preferences, learn faster thanks to their help, and act safely around them. We argue that most current approaches that learn from human feedback are unsafe: rewarding or punishing the agent a-posteriori cannot immediately prevent it from wrong-doing. In this paper, we extend Policy Gradient to make it robust to external directives, that would otherwise break the fundamentally on-policy nature of Policy Gradient. Our technique, Directed Policy Gradient (DPG), allows a teacher or backup policy to override the agent before it acts undesirably, while allowing the agent to leverage human advice or directives to learn faster. Our experiments demonstrate that DPG makes the agent learn much faster than reward-based approaches, while requiring an order of magnitude less advice.
THE ATACAMA COSMOLOGY TELESCOPE: A MEASUREMENT OF THE 600 &lt; ℓ &lt; 8000 COSMIC MICROWAVE BACKGROUND POWER SPECTRUM AT 148 GHz

We present a measurement of the angular power spectrum of the cosmic microwave background (CMB) radiation observed at 148 GHz. The measurement uses maps with 1.4' angular resolution made with data from the Atacama Cosmology Telescope (ACT). The observations cover 228 square degrees of the southern sky, in a 4.2-degree-wide strip centered on declination 53 degrees South. The CMB at arcminute angular scales is particularly sensitive to the Silk damping scale, to the Sunyaev-Zel'dovich (SZ) effect from galaxy clusters, and to emission by radio sources and dusty galaxies. After masking the 108 brightest point sources in our maps, we estimate the power spectrum between 600 &lt; \ell &lt; 8000 using the adaptive multi-taper method to minimize spectral leakage and maximize use of the full data set. Our absolute calibration is based on observations of Uranus. To verify the calibration and test the fidelity of our map at large angular scales, we cross-correlate the ACT map to the WMAP map and recover the WMAP power spectrum from 250 &lt; ell &lt; 1150. The power beyond the Silk damping tail of the CMB is consistent with models of the emission from point sources. We quantify the contribution of SZ clusters to the power spectrum by fitting to a model normalized at sigma8 = 0.8. We constrain the model's amplitude ASZ &lt; 1.63 (95% CL). If interpreted as a measurement of sigma8, this implies sigma8^SZ &lt; 0.86 (95% CL) given our SZ model. A fit of ACT and WMAP five-year data jointly to a 6-parameter LCDM model plus terms for point sources and the SZ effect is consistent with these results.
Palliative Care for Patients With Hematologic Malignancies in a Low-Middle Income Country: Prevalence of Symptoms and the Need for Improving Quality of Attention at the End of Life

Background:                     Palliative care (PC) for patients with malignant hematological diseases is scarcely documented, particularly in low- and middle-income countries. This study aimed to document PC provided to patients with hematologic malignancies.                                                           Methods:                     Bidirectional study conducted from July 2016 to June 2019 at the hematology and palliative care departments at a reference center in Northeast Mexico for low-income open population uninsured patients. Clinical records and electronic files of patients with malignant hematological diseases of both sexes and all ages attending an academic hematology center were reviewed. Statistical analysis was performed with the SPSS version 22 program. Acute and chronic leukemias, multiple myeloma, Hodgkin lymphoma, non-Hodgkin lymphoma, and others were included.                                                           Results:                     Five-hundred ten patients were studied, of which 148 (29%) died. Eighty-one (15.88%) patients including 31 (20.9%) who died received PC. Median age at palliative diagnosis was 42 (2-91) years. The most common symptom was pain (69.7%). The most frequent reason for palliative referral was treatment-refractory disease (39%). During the last week of life, 19 (95%) of 20 patients had blood sampling; 17 (85%) received antibiotics; 16 (80%) had a urinalysis performed; 16 (80%) received analgesia, including paracetamol (11, 35.5%) and buprenorphine (7, 22.6%); 10 (50%) received blood products; 9 (45%) were intubated; and central venous catheters were inserted in 5 (25%) patients.                                                           Conclusions:                     Palliative care was provided to a minority of patients with hematologic malignancies and considerable improvement is required in its timely use and extension.
Optical Comb Generator-based Microwave Photonic Filter Performance Improvement Using Multilayer Perceptron (MLP) Neural Network

In this paper, we proposed multilayer perceptron (MLP) neural network for improving the performance of a microwave photonic filter (MPF). Moreover, we proposed an optical comb generator to attain a central reconfigurable MPF. The frequency response of MPF varies due to some factors such as fiber length, optical carrier, and wavelength spacing. Thus, we can accurately adjust the center frequency of the MPF and its bandwidth by varying these factors, which enhances the network flexibility and very important for future optical networks. However, very difficult to determine these factors if we assign the MPF’s transmission window randomly. Thus, we apply MLP technique to learn and understand the inverse mapping between the frequency response and the MPF parameters such as length of the fiber and wavelength spacing for precise prediction of the given arbitrary frequency response. Therefore, the experimental result proves that the proposed MLP model accurately predicts the parameters of MPF such as length of the fiber and wavelength spacing.
A metagenomics analysis of rumen microbiome

Climate change and food security are significant global challenges facing society. The dairy industry is inextricably linked to these challenges as it is concerned with the economies of food production, while acknowledging that it is a major contributor to greenhouse gas production. Action by microbial communities in the rumen is responsible for efficient breakdown of plant matter for food conversion, but a by-product of this action is substantial methane production. Insight into food conversion and methane production in rumen microbiota is possible through metagenomics analysis, which is the analysis of microbial communities and their interactions with the environment. However, metagenomic analysis is hampered by the sheer volume and complexity of data that needs to be processed. This paper presents a bioinformatics pipeline and visualisation platform that facilitates deep analysis of microbial communities, under various conditions in cattle rumen, with the aim of leading to significant impact on probiotic supplement usage, methane production and feed conversion efficiency. This pipeline was developed as part of the EU H2020 MetaPlat project and will pave the way for a more optimal usage of metagenomic datasets, thus reducing the number of animals necessary to be engaged in such studies. This will ensure better and more economic animal welfare, better use of resources and lessen the impact of the dairy industry on climate change.
Comments on “Geochemistry, petrogenesis and tectonic setting of the Samothraki mafic suite, NE Greece: Trace-element, isotopic and zircon age constraints” by Nikola Koglin, Dimitrios Kostopoulos and Thomas Reischmann, Tectonophysics 473 (2009), 53–68

Abstract   The manuscript “Geochemistry, petrogenesis and tectonic setting of the Samothraki mafic suite, NE Greece: Trace-element, isotopic and zircon age constraints” presented by Koglin et al. (2009a) tries to re-interpret the Samothraki ophiolite as a non ophiolitic mafic suite, which has been generated in a propagated fore-arc rift setting. However, incomplete sampling by the authors and overinterpretation of the few data are suspicious. The geochemical and petrological similarity of the Samothraki mafic sequence with other well-known ophiolites is not acknowledged and the proposed geotectonic regime is unrealistic.
Comparative Study of Children’s Personal Data Protection Regulation on COPPA (Children’s Online Privacy Protection Act) and Children and GDPR

Background: Personal data is the most fundamental right for everyone including children. Children are the most vulnerable subjects when it comes to the processing of personal data, it is because they do not have awareness and understanding of the risks of misuse of personal data. Regulations regarding the protection of children's personal data in Indonesia are already contained in the draft of personal data protection law but with very limited guidance. Through this comparative study, researchers wanted to compare the United State's COPPA(Children's Online Privacy Protection Act) with the Children and GDPR by the United Kingdom. Both of these regulations are very detailed in regulating the protection of children's personal data. This study will provide a clearer picture of children’s privacy protection regulations so that it can be used as a reference for Indonesia's draft of personal data protection law in regard to the rights of children's privacy.  Method: This comparative research uses qualitative descriptive methods with library research and approach.  Result: There are fundamental differences regarding the form of guidance, the definition of child, the perpetrator processing of the child's personal data, and things that are included in the child's personal data.  Conclusion: The application of children's personal data protection is adjusted to the values and cultures of the country.
Best Before? Expiring Central Bank Digital Currency and Loss Recovery (Extended Abstract).

An important feature of physical cash payments is resilience, due to their independence of power outages or network coverage. Many central banks are exploring issuing digital cash substitutes with similar offline payment functionality. Such substitutes could incorporate novel features making them more desirable than physical cash. This paper considers introducing an expiry date for offline digital currency balances to automate personal loss recovery. We show this functionality could increase consumer demand for digital cash, with the time to expiration playing a key role. The optimal time to expiration should have short wait time to get lost money reimbursed but leave enough time for agents to deposit received offline balances. Setting the time to expiration a bit too long has minor impact on welfare but setting it too short dramatically reduce welfare. If the offline device provides information about past transactions to the central bank, the accuracy of loss recovery can be improved but welfare can decrease.