ethicalabs/Research-Intent-Collab huggingface dataset:
Distilling genomic knowledge into pathology slides for robust cancer survival prediction

Aims: To develop a robust and clinically feasible framework for cancer survival prediction using only histopathology images while leveraging transcriptomic knowledge during training.  Methods: The study proposed Adaptive Multi-modality Knowledge Distillation (AMKD), a framework designed to transfer complementary molecular-level information from transcriptomic data to pathology-based models. The AMKD framework consists of two essential elements. First, a gene-guided pathology enhancement module is designed to inject genomics-aware information from a multimodal teacher into pathology features. Second, an adaptive redundancy reduction loss is introduced to regulate knowledge distillation by accounting for prediction discrepancies between teacher and student models. This design allows the student model to retain biologically meaningful knowledge during training and remain effective with only histopathology data at inference.  Results: Comprehensive experiments on four The Cancer Genome Atlas (TCGA) cancer cohorts demonstrate that AMKD achieves state-of-the-art survival prediction performance, with an average concordance index (C-index) of 0.669, surpassing both unimodal pathology-based and fully multi-modal approaches. External validation on the independent Clinical Proteomic Tumor Analysis Consortium head and neck squamous cell carcinoma (CPTAC-HNSC) cohort further confirms the robustness and cross-dataset generalization ability of the proposed framework. Ablation studies further confirm the effectiveness of each proposed component in enhancing cross-modal knowledge transfer and improving generalization under incomplete modality scenarios.  Conclusion: The proposed AMKD framework provides a clinically practical solution for robust cancer survival analysis when transcriptomic data are unavailable. By adaptively distilling multi-modal knowledge into a pathology-based model, AMKD bridges the gap between research and clinical applicability, enabling scalable and cost-effective prognostic prediction in real-world settings.
The global modulation of cosmic rays during a quiet heliosphere: A modeling perspective

Abstract   A perspective is given of the solar modulation of galactic cosmic rays in the heliosphere during the extraordinary quiet solar minimum period from 2006 to 2009. This is done in the context of the total modulation of cosmic rays in a global heliosphere. Such an approach has become possible since the observation of galactic cosmic rays made beyond the heliopause by Voyager 1 so that together with very precise observations at higher energies at the Earth, more reliable local interstellar spectra can be established. Combined with the results from comprehensive modeling, a global view unfolds. The requirements for such an approach to the modeling of solar modulation are discussed. Computed, modulated spectra for protons and electrons are shown, for 2006–2009 together with computed radial and latitudinal gradients for protons, in comparison with observations where available. Predictions are made for the energy ranges not covered by the 2006–2009 observations. Respectively, the modulation factor for protons, electrons and positrons are given for energies as low as 5 MeV for the mentioned period. The computed electron to positron ratio is presented as applicable to solar minimum modulation conditions. The differences in the modulation of protons, electrons and positrons are illustrated for such conditions and the main contributions to this global process, including particle drifts, are discussed.
Epigenetic Regulation by Chromatin Activation Mark H3K4me3 in Primate Progenitor Cells within Adult Neurogenic Niche

Histone 3 lysine 4 trimethylation (H3K4me3) is known to be associated with transcriptionally active or poised genes and required for postnatal neurogenesis within the subventricular zone (SVZ) in the rodent model. Previous comparisons have shown significant correlation between baboon (Papio anubis) and human brain. In this study, we demonstrate that chromatin activation mark H3K4me3 is present in undifferentiated progenitor cells within the SVZ of adult baboon brain. To identify the targets and regulatory role of H3K4me3 within the baboon SVZ, we developed a technique to purify undifferentiated SVZ cells while preserving the endogenous nature without introducing culture artifact to maintain the in vivo chromatin state for genome-wide studies (ChIP-Seq and RNA-Seq). Overall, H3K4me3 is significantly enriched for genes involved in cell cycle, metabolism, protein synthesis, signaling pathways, and cancer mechanisms. Additionally, we found elevated levels of H3K4me3 in the MRI-classified SVZ-associated Glioblastoma Multiforme (GBM), which has a transcriptional profile that reflects the H3K4me3 modifications in the undifferentiated progenitor cells of the baboon SVZ. Our findings highlight the importance of H3K4me3 in coordinating distinct networks and pathways for life-long neurogenesis, and suggest that subtypes of GBM could occur, at least in part, due to aberrant H3K4me3 epigenetic regulation.
Do universities have moral duties with regard to a human right to health?

This article argues that universities have duties to negotiate contracts with the pharmaceutical industry that are favourable to the world’s poor, and to do more research into diseases which disproportionately strike the global poor. It is argued that these duties are related to human rights (in particular to a human right to health) and that they are therefore very weighty. Furthermore, these duties are in line with some of the most important things that Universities Allied for Essential Medicines (UAEM), a worldwide group of students and academics, wants universities to do. A number of objections are discussed, among other things to do with safeguarding pharmaceutical innovation, and it is argued that the aforementioned duties should, as UAEM also advocates, often be combined with efforts on the part of universities to work towards more long-term, large-scale institutional arrangements to ensure access to and availability of essential medicines for the global poor.
Knowledge discovery via multidimensional science maps: the case of the Species Problem

Science mapping (SM), the study of the organization and development of science and technology, is a rapidly developing field within information science. The volume of available data allows this methodology to empirically address such issues as the historical development of topics, discourses, fields or the entire science system. Based on the pool of related methods, we are proposing an integration of various maps to obtain a novel kind of science map we call multidimensional. The basic idea behind is to combine the most informative relations available from various maps based on different bibliometric indicators, in order to produce a rich structrue for the study of knowledge dynamics, with special emphasis on causal-historical connections. As a proof of concept, we deploy the proposed framework in an extensive case study on a historical topic from the life sciences, namely, the debate on the species concept in biosystematics.
scCluBench: Comprehensive Benchmarking of Clustering Algorithms for Single-Cell RNA Sequencing

Cell clustering is crucial for uncovering cellular heterogeneity in single-cell RNA sequencing (scRNA-seq) data by identifying cell types and marker genes. Despite its importance, benchmarks for scRNA-seq clustering methods remain fragmented, often lacking standardized protocols and failing to incorporate recent advances in artificial intelligence. To fill these gaps, we present scCluBench, a comprehensive benchmark of clustering algorithms for scRNA-seq data. First, scCluBench provides 36 scRNA-seq datasets collected from diverse public sources, covering multiple tissues, which are uniformly processed and standardized to ensure consistency for systematic evaluation and downstream analyses. To evaluate performance, we collect and reproduce a range of scRNA-seq clustering methods, including traditional, deep learning-based, graph-based, and biological foundation models. We comprehensively evaluate each method both quantitatively and qualitatively, using core performance metrics as well as visualization analyses. Furthermore, we construct representative downstream biological tasks, such as marker gene identification and cell type annotation, to further assess the practical utility. scCluBench then investigates the performance differences and applicability boundaries of various clustering models across diverse analytical tasks, systematically assessing their robustness and scalability in real-world scenarios. Overall, scCluBench offers a standardized and user-friendly benchmark for scRNA-seq clustering, with curated datasets, unified evaluation protocols, and transparent analyses, facilitating informed method selection and providing valuable insights into model generalizability and application scope.
CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks

Contrastive language-image pretraining (CLIP) links vision and language modalities into a unified embedding space, yielding the tremendous potential for vision-language (VL) tasks. While early concurrent works have begun to study this potential on a subset of tasks, important questions remain: 1) What is the benefit of CLIP on unstudied VL tasks? 2) Does CLIP provide benefit in low-shot or domain-shifted scenarios? 3) Can CLIP improve existing approaches without impacting inference or pretraining complexity? In this work, we seek to answer these questions through two key contributions. First, we introduce an evaluation protocol that includes Visual Commonsense Reasoning (VCR), Visual Entailment (SNLI-VE), and Visual Question Answering (VQA), across a variety of data availability constraints and conditions of domain shift. Second, we propose an approach, named CLIP Targeted Distillation (CLIP-TD), to intelligently distill knowledge from CLIP into existing architectures using a dynamically weighted objective applied to adaptively selected tokens per instance. Experiments demonstrate that our proposed CLIP-TD leads to exceptional gains in the low-shot (up to 51.9%) and domain-shifted (up to 71.3%) conditions of VCR, while simultaneously improving performance under standard fully-supervised conditions (up to 2%), achieving state-of-art performance on VCR compared to other single models that are pretrained with image-text data only. On SNLI-VE, CLIP-TD produces significant gains in low-shot conditions (up to 6.6%) as well as fully supervised (up to 3%). On VQA, CLIP-TD provides improvement in low-shot (up to 9%), and in fully-supervised (up to 1.3%). Finally, CLIP-TD outperforms concurrent works utilizing CLIP for finetuning, as well as baseline naive distillation approaches. Code will be made available.
Geology, ore-forming fluid and genesis of the Qiucun gold deposit: Implication for mineral exploration at Dehua prospecting region, SE China

Abstract   The Qiucun gold deposit, located in the central Fujian Province, is one of the most important gold producers at the Dehua prospecting region. The deposit is hosted in the Nanyuan Formation consisting of continental arc volcanic rocks, which belong to the Mesozoic coastal volcanic belt of south China. Gold ore bodies are controlled by a group of NE-NEE trending faults. Wall rock alteration shows that gold mineralization is closely associated with quartz (chalcedony)-illite-pyrite-calcite assemblages, in which pyrite is the dominate sulfides (>90%). Petrographic study of ore minerals shows that gold occurs as electrum grains of 2–65 μm in diameter, interstitially or in fractures within pyrite. EPMA analysis of electrum yielded compositions of 62–69 wt% Au and 28–33 wt% Ag. Fluid inclusions petrographic and microthermometric studies were carried out on auriferous quartz veins from three different elevations, i.e. 712 m, 742 m and 820 m above sea level. Two types of fluid inclusion were observed, namely two-phase liquid-rich (type I) and two-phase vapor-rich (type II) fluid inclusions. There inclusions are predominately aqueous inclusions but can sometimes contain minor CO2 and N2 as revealed by laser Raman analysis. Type I inclusions show homogenization temperatures (Th) of 181–248 °C, with salinities of 0.5–2.6 wt% NaCl equivalent. Type II inclusions display Th of 208–249 °C, with salinities of 0.5–0.9 wt% NaCl equivalent. The occurrence of platy calcite and hydrothermal breccias, together with coexisting type I and type II inclusions which shows similar homogenization temperatures but contrasting salinities, all indicate that fluid boiling is a crucial mechanism for ore deposition at the Qiucun gold deposit. Combining the geological settings, alteration, mineralization and fluid inclusion characteristics, we propose that the Qiucun gold deposit is a low-sulfidation epithermal deposit. The estimated pressure calculated by fluid inclusion boiling assemblages corresponds to a formation depth of 200 to 260 m below paleo-surface, which is slightly deeper than the current depth. Accordingly, the denudation thickness of the overlying Nanyuan volcanic rocks is supposed to be approximately 100 m since ore deposition, which is conductive to the preservation of epithermal ore deposit. It is therefore suggested that the large area of the Daiyunshan Volcanic Basin at Dehua district is of great potential for epithermal ore exploration.
PERANCANGAN APLIKASI HUMAN RESOURCE INFORMATION SYSTEM (HRIS) BERBASIS WEBSITE PADA PT. SUPER TATA RAYA STEEL

Human Resource Information System (HRIS) adalah sebuah sistem informasi yang menangani permasalahan-permasalahan yang berkenaan dengan pengelolaan sumber daya manusia pada sebuah organisasi (perusahaan). Pengelolaan data sumber daya manusia pada PT. Super Tata Raya Steel masih bersifat manual (microsoft excel) sehingga perusahaan kesulitan memperoleh informasi yang berhubungan dengan sumber daya manusia atau bisa disebut kepegawaian. Dalam pembangunan sistem HRIS ini menggunakan metode pengembang waterfall dimulai dengan proses analisis kebutuhan sistem dan dilanjutkan dengan proses perancangan sistem yang didasarkan pada hasil analisis kebutuhan. Tahap terakhir dari proses penyusunan sistem ini adalah implementasi perancangan sistem menjadi sebuah sistem baru. Dalam tugas akhir ini dapat disimpulkan bahwa sistem HRIS yang dibangun dapat membantu dalam pengolahan data kepegawaian yang berada di PT. Tata Raya Steel. Untuk menangani permasalahan  tersebut  dibuatlah  aplikasi  Human  Resources  Information  System (HRIS) yang dapat membantu bagian personalia / HRD untuk menjalankan tugasnya, mulai dari proses pendataan pegawai, pendataan devisi pegawai, pendataan jabatan pegawai, pendataan status pekerjaan pegawai, pendataan penghargaan pegawai, pendataan pelatihan pegawai, pendataan pelanggaran pegawai, penggajian pegawai, pencataan pengadaan kebutuhan perusahaan dan penilaian kinerja pegawai, serta dapat menghasilkan informasi yang dapat digunakan untuk pengambilan keputusan. Kata Kunci: Sistem informasi, sumber daya manusia, kepegawaian, aplikasi HRIS
Dispute settlement mechanism of the World Trade Organization: its importance beyond the WTO framework

The Dispute Settlement Mechanism of the World Trade Organization was recognized as one of the most successful mechanisms of settlement of inter-State disputes. Due to recent developments, however, the functioning of the WTO Appellate Body has been suspended, which could give the impression that the WTO dispute settlement mechanism might lose its importance. The present article explores the idea that the importance of the WTO mechanism goes beyond the framework of this organization. In particular, the WTO mechanism has strongly influenced the establishment of dispute settlement mechanisms in regional trade agreements. Another important area influenced by the WTO mechanism is international investment dispute settlement, which is currently undergoing a reform under the UNCITRAL initiative. One can note the influence of the WTO Mechanism on the elements of regional dispute settlement mechanisms, as well as its importance for the reform of international investment arbitration, first of all in the establishment of an appeal mechanism. The article also discusses the meaning of the WTO DSB practice for regional mechanisms and obligations of parties to regional trade agreements to take into account decisions of panels and the Appellate Body. Besides that, there are examples of the use of WTO DSB practice in the context of international investment arbitration: although this approach caused a mixed reaction of specialists, it cannot not be excluded that arbitrators dealing with investment disputes will use WTO practice in the future. Based on the results of research presented in the article, the author comes to the conclusion that, notwithstanding current difficulties, the WTO dispute settlement mechanism remains important, beyond the WTO framework and serves as a guidance for a number of other dispute settlement systems.
(Invited) Electrochemistry-based and electrochemistry-coupled characterization of lithium ion based battery materials and systems

Lithium ion batteries are ubiquitous in our everyday lives and have revolutionized portable electronics and the transportation industry. As self contained energy storage systems, lithium ion batteries often appear as black boxes. However, the chemistry inherent to their function is diverse and complicated. Examples of mechanistic insight gained from in situ and operando characterization of lithium ion batteries will be highlighted in this presentation. This will include approaches to spatially locate and resolve productive and parasitic processes in functional energy storage materials and systems, with an emphasis on electrochemistry-based and electrochemistry-coupled approaches.
Knowledge representation for natural language processing in implemented  systems

This special issue presents the state-of-the-art in implemented,  general-purpose  Natural Language Processing (NLP) systems that use nontrivial Knowledge  Representation  and Reasoning (KRR). These systems use full-scale implementations of  traditional KRR techniques as well as some newer knowledge-related processing   mechanisms that have been developed specifically to meet the needs of natural   language processing. The papers cover a wide range of natural language  inputs,  knowledge and formalisms, application domains and processing tasks, illustrating   the key role that knowledge representation plays in all types of NLP systems.
Frequency responses of age-structured populations: Pacific salmon as an example

Increasing evidence of the effects of changing climate on physical ocean conditions and long-term changes in fish populations adds to the need to understand the effects of stochastic forcing on marine populations. Cohort resonance is of particular interest because it involves selective sensitivity to specific time scales of environmental variability, including that of mean age of reproduction, and, more importantly, very low frequencies (i.e., trends). We present an age-structured model for two Pacific salmon species with environmental variability in survival rate and in individual growth rate, hence spawning age distribution. We use computed frequency response curves and analysis of the linearized dynamics to obtain two main results. First, the frequency response of the population is affected by the life history stage at which variability affects the population; varying growth rate tends to excite periodic resonance in age structure, while varying survival tends to excite low-frequency fluctuation with more effect on total population size. Second, decreasing adult survival strengthens the cohort resonance effect at all frequencies, a finding that addresses the question of how fishing and climate change will interact.
Effectiveness of implementing evidence based practices guidelines regarding blood transfusion on quality of nursing care and patients' safety in Pediatric Units

Background and objective: The new trend that widely accepted in health care institutions is to implement an evidence-based practice. Health facilities frequently integrate standards of practice that reveal current best evidence to increase patients’ outcomes and consequently decrease hospital cost. Transfusion of blood is a cornerstone in managing many critically ill children. However, nurses have a chief role in transfusing blood and their knowledge and performance are important for them to transfuse blood safely and efficiently. Aim: Evaluate the effectiveness of implementing evidence based nursing practices guidelines on quality of nursing care and patients' safety as regards blood transfusion to improve transfusion practices and ensure safety.Methods: A quasi-experimental design. Settings: This study was conducted at Pediatric Intensive Care Unit, Neonatal Intensive Care Unit, Emergency Room, Medical and Surgical Wards, Hematology/Oncology Units in Children Hospital affiliated to Ain Shams University Hospitals. Sample: A convenience sample composed of 95 pediatric nurses, whom were willingness to participate in the study and 78 children whom were receiving blood transfusion. Tools: I. A Self-Administered Questionnaire Sheet to assess nurses’ knowledge regarding blood transfusion; II. Child’s Medical Record to collect data about child’s health status; III. An Observational Competence Checklist to assess the quality of actual nurses’ practices about Blood Transfusion; and IV. Evidence Based Nursing Practices Guidelines of Blood Transfusion that was described the EBNP guidelines that provide a standardized approach for transfusion (before and after).Results: The studied nurses’ knowledge and practices regarding to blood transfusion were improved and reflected a highly significant differences before and after guidelines implementation.Conclusions: The present study concluded that studied nurses showed an improvement in their knowledge and practices regarding blood transfusion after implementation of evidence based nursing practices guidelines. Recommendation: It is essential that all nurses who administer blood transfusion for children should complete periodic in-services training programs to keep them up to date regarding to safe and efficient administration of blood transfusion.
Dominant Shuffle: A Simple Yet Powerful Data Augmentation for Time-series Prediction

Recent studies have suggested frequency-domain Data augmentation (DA) is effec tive for time series prediction. Existing frequency-domain augmentations disturb the original data with various full-spectrum noises, leading to excess domain gap between augmented and original data. Although impressive performance has been achieved in certain cases, frequency-domain DA has yet to be generalized to time series prediction datasets. In this paper, we found that frequency-domain augmentations can be significantly improved by two modifications that limit the perturbations. First, we found that limiting the perturbation to only dominant frequencies significantly outperforms full-spectrum perturbations. Dominant fre quencies represent the main periodicity and trends of the signal and are more important than other frequencies. Second, we found that simply shuffling the dominant frequency components is superior over sophisticated designed random perturbations. Shuffle rearranges the original components (magnitudes and phases) and limits the external noise. With these two modifications, we proposed dominant shuffle, a simple yet effective data augmentation for time series prediction. Our method is very simple yet powerful and can be implemented with just a few lines of code. Extensive experiments with eight datasets and six popular time series models demonstrate that our method consistently improves the baseline performance under various settings and significantly outperforms other DA methods. Code can be accessed at https://kaizhao.net/time-series.